How to Recognize High-Quality Vodka: Key Signs to Look For

Vodka may look simple at first: a clear spirit, usually neutral in taste, often served neat, on the rocks or mixed into cocktails. But quality can vary significantly from one bottle to another. Some vodkas taste clean, soft and balanced, while others feel sharp, harsh or unpleasantly hot.

Price and brand can be useful signals, but they are not the only criteria. High-quality vodka is usually defined by clean aroma, smooth texture, balanced alcohol note, reliable raw materials, careful distillation, proper filtration and clear product information. The right bottle also depends on how it will be used: cocktails, neat drinking, gifting or a home bar.

This vodka buying guide explains how to recognize good vodka, what makes premium vodka different, when budget vodka can still work well and what to check before buying vodka online.

Quick answer

High-quality vodka is usually clean, smooth and balanced, without an aggressive alcohol burn or unpleasant aftertaste. The most important signs are clear product information, reliable raw materials, careful distillation, proper filtration, balanced ABV and a taste profile that matches the intended use. For cocktails, a clean and neutral vodka is often enough, while neat drinking or gifting may justify a softer premium bottle. Price can be a useful signal, but it should not be the only reason to choose a vodka.

What Does “High-Quality Vodka” Really Mean?

High-quality vodka does not simply mean the most expensive bottle on the shelf. Quality is better understood through taste, texture, balance and transparency. A good vodka should feel clean, smooth and controlled, not harsh, chemical or aggressively sharp.

Vodka is often described as a neutral spirit, but neutral does not mean tasteless. Good vodka can still have subtle character: a soft texture, a clean finish, light sweetness, gentle grain notes, a creamy mouthfeel or a slightly mineral edge. These details are usually more noticeable when vodka is tasted neat.

The meaning of quality also depends on purpose. A vodka for cocktails should be clean, neutral and reliable. A vodka for neat drinking should be smoother and more refined. A vodka as a gift should combine good taste, recognizable quality and attractive presentation.

A strong price-to-quality ratio matters more than status alone. A premium vodka can be a good choice, but only when its smoothness, finish and presentation actually fit the occasion.

Key Signs of Good Vodka

The easiest way to recognize good vodka is to look for balance. It should not smell unpleasant, taste rough or leave a burning finish that dominates everything else. A clean vodka feels controlled from aroma to aftertaste.

A good vodka usually has:

  • a clean and neutral aroma;
  • a smooth texture;
  • no strong chemical smell;
  • no aggressive burning sensation;
  • a balanced finish;
  • clear information about ABV and bottle size;
  • a taste profile that works for cocktails, neat drinking or gifting;
  • a reasonable price for its quality level;
  • a reliable brand or clear production background;
  • transparent information about style and intended use.

The first warning sign is a harsh alcohol burn. Vodka will always have alcohol, but it should not feel sharp in a way that overwhelms the palate. If the aroma feels chemical or the aftertaste is unpleasant, the bottle may be better suited only for mixing or may not be worth choosing at all.

Good vodka does not need to be complicated. It needs to be clean, balanced and appropriate for the way you plan to use it.

Vodka Taste: Should Good Vodka Be Completely Neutral?

Vodka is usually expected to have a neutral taste, but high-quality vodka is not always completely flavourless. The differences are often subtle, but they matter. One vodka may feel crisp and light, another may feel creamy and round, while another may show gentle sweetness or a slightly peppery finish.

For cocktails, neutrality is a practical advantage. A clean vodka should support ingredients such as citrus, soda, ginger beer, tomato juice, coffee or fruit without adding a rough alcohol note. This is why vodka works well in drinks like Moscow Mule, Cosmopolitan, Vodka Soda and Espresso Martini.

For neat drinking, texture and finish become more important. A vodka with a harsh alcohol note may feel acceptable in a mixed drink, but unpleasant when tasted on its own. A smooth vodka should feel soft on the palate and leave a clean finish rather than a burning aftertaste.

Cheap vodka can still work for cocktails if it is clean and balanced. But if you plan to drink vodka neat or serve it as a premium gift, smoothness and finish become much more important.

Raw Materials: Grain, Potatoes or Corn — Does It Matter?

Vodka may be made from different agricultural raw materials. Common bases include grain, wheat, rye, potatoes, corn and other starch- or sugar-containing ingredients. Because vodka is usually neutral, some buyers assume the raw material does not matter. In reality, it can influence texture, softness and aftertaste.

Grain vodka often feels clean, crisp and lightly sweet. Wheat-based vodka can be especially soft and rounded. Rye may bring more structure, spice or a drier edge. Potato vodka is often perceived as fuller, creamier and richer. Corn vodka may feel mild, soft and slightly sweet.

Raw materialPossible characterBest for
GrainClean, crisp, lightly sweetCocktails, Vodka Soda, home bar
WheatSoft, smooth, roundedNeat drinking, premium bottles
RyeSpicier, more structuredVodka Martini, stronger character
PotatoesCreamier, fuller, richerTasting, gifts, neat drinking
CornMild, soft, slightly sweetBeginners, cocktails, mixed drinks

The raw material can influence texture and finish, but it should always be evaluated together with distillation, filtration, water quality and overall balance. A good raw material does not automatically create good vodka if the production is careless.

Distillation and Filtration: Do They Make Vodka Better?

Distillation helps create a cleaner alcohol base. In vodka production, multiple distillation can improve purity and remove rougher elements. However, the number of distillations is not a quality guarantee by itself. A vodka filtered or distilled many times can still feel unbalanced if the base spirit or final blending is poor.

Filtration can also influence the final profile. Common methods include charcoal filtration, activated carbon filtration, quartz filtration, silver filtration and other processes. Filtration may help create a cleaner, softer and more neutral spirit.

Still, quality is not about marketing numbers only. “Filtered ten times” or “distilled many times” should not automatically be read as “best quality vodka.” What matters is the final result: clean aroma, smooth mouthfeel, balanced alcohol note and pleasant finish.

High-quality vodka is about control. Distillation, filtration, water and blending should work together to create a clean spirit that feels balanced rather than aggressively sharp.

ABV and Balance: Why Alcohol Strength Matters

ABV means alcohol by volume. Many vodkas are bottled around 37.5% to 40% ABV. In the European Union, vodka must have a minimum alcoholic strength of 37.5% ABV.

A higher ABV does not automatically mean higher quality. Stronger vodka may have more power, but good vodka should feel balanced, not just strong. A bottle with poor balance can feel hot even at a standard strength.

For cocktails, 40% ABV is common and versatile because it gives enough structure in mixed drinks. For neat drinking, smoothness, texture and finish are often more important than strength alone.

The ideal vodka alcohol content depends on use. A cocktail vodka should hold up in a drink. A sipping vodka should feel controlled and clean in small sips.

Premium Vodka vs Cheap Vodka: What Is the Real Difference?

Premium vodka often focuses on better raw materials, careful distillation, refined filtration, softer texture, cleaner finish and stronger brand presentation. It may also come in a more elegant bottle, which matters when the vodka is intended as a gift.

Cheap or budget vodka is not always bad. It can be practical for cocktails, long drinks or parties if it tastes clean and does not bring a harsh alcohol burn. The problem begins when the lowest price becomes the only criterion.

CriterionPremium vodkaCheap / budget vodka
TasteSmoother, cleaner, more balancedSimpler, sometimes sharper
TextureSofter, rounderLighter or rougher
FiltrationOften more refinedUsually simpler
Best useNeat drinking, gifts, special occasionsCocktails, long drinks, parties
PriceHigherLower to medium
RiskOverpaying for brandingHarsh alcohol burn or weak balance

A premium bottle makes sense when smoothness, texture and presentation matter. A budget-friendly vodka can still be a good choice for cocktails if it tastes clean and balanced. The right choice is not always the most expensive one. It is the bottle that fits the purpose.

How to Taste Vodka: A Simple Quality Test

Vodka is often served very cold, but if you want to evaluate quality, avoid over-freezing it. Extreme cold can hide both good and bad qualities. A slightly chilled vodka is usually enough to check aroma, texture and finish.

To evaluate vodka quality, check:

  • Aroma — it should smell clean, not chemical.
  • Texture — good vodka often feels smooth, not rough.
  • Taste — it should be balanced and not aggressively sharp.
  • Finish — the aftertaste should be clean and short to medium, not unpleasant.
  • Purpose — the bottle should match cocktails, neat drinking or gifting.

Take a small sip and notice whether the vodka feels soft or harsh. A strong burning finish does not automatically mean strength; it may also suggest weak balance or a bottle that is not ideal for neat drinking.

For cocktails, test whether the vodka supports the drink or breaks its balance. A good cocktail vodka should mix easily and not add a rough alcohol edge.

Best Vodka for Cocktails: What Quality Level Do You Need?

Cocktail vodka should be clean, neutral and reliable. It does not always need to be the most expensive bottle, but it should not be harsh. A rough vodka can make a cocktail taste sharp, even when the recipe and ingredients are good.

Vodka works well in many classic drinks, including Moscow Mule, Vodka Martini, Cosmopolitan, Bloody Mary, Espresso Martini and Vodka Soda. In these cocktails, vodka should provide structure without dominating the drink.

For cocktails, choose vodka that is:

  • clean and neutral;
  • not aggressively sharp;
  • versatile;
  • reasonably priced;
  • easy to mix with citrus, soda, ginger beer, coffee or juice;
  • consistent in taste.

A mid-range bottle with a good price-to-quality ratio is often the most practical choice for a home bar. Premium vodka can be used in cocktails, but it is not always necessary for simple mixed drinks.

Best Vodka for Drinking Neat: What to Look For

For neat drinking, smoothness matters more than strong branding. A good sipping vodka should have a clean aroma, soft texture and balanced finish. It should not feel harsh, chemical or unpleasantly hot.

Premium vodka is often a better choice for drinking neat because it is usually made with more attention to softness, mouthfeel and presentation. However, the label alone is not enough. The vodka should still feel clean and balanced in small sips.

Serving temperature matters. Slightly chilled vodka can feel pleasant and smooth, but over-freezing may hide important differences. If a vodka only tastes acceptable when extremely cold, it may not be the best bottle for tasting.

Look for a smooth vodka with a clean finish, clear product information and a style that matches your preference. For neat drinking, small details matter more than they do in cocktails.

Vodka as a Gift: Quality Signals That Matter

Vodka can work well as a gift if the bottle looks premium and the brand feels reliable. For gifts, the safest choice is often classic non-flavoured vodka with a smooth profile and elegant presentation.

Avoid the cheapest bottle if the gift should feel thoughtful or premium. Also be careful with flavoured vodka unless you know the recipient’s taste. A very specific flavour can be interesting, but it is less universal than classic vodka.

Gift situationRecommended vodka type
Gift for a beginnerSmooth classic vodka
Gift for a cocktail loverClean, versatile cocktail vodka
Gift for a spirits enthusiastPremium vodka with clear quality signals
Formal giftRecognizable brand or elegant bottle
Safe universal giftClassic non-flavoured vodka

For a gift bottle, quality signals include brand reputation, bottle design, country of origin, smoothness, clear product details and a price level that matches the occasion.

Reading the Label: What Information Should Be Clear?

A vodka label or product page should make the basic information easy to understand. If important details are missing, it becomes harder to compare quality and price.

Before buying, check:

  • ABV;
  • bottle size;
  • brand name;
  • country of origin;
  • raw material, if available;
  • whether it is classic or flavoured;
  • intended use;
  • price-to-quality ratio;
  • shop reliability.

Flavoured vodka should be clearly identified as flavoured. Classic vodka and aromatised vodka serve different purposes, so they should not be confused. A bottle for Vodka Martini may not be the same choice as a bottle for sweet mixed drinks.

Clear information does not guarantee quality, but it helps you make a better decision. A reliable product page should make comparison easy, not force the buyer to guess.

What to Check Before Buying Vodka Online

When buying vodka online, product information should be clear and practical. Compare brand, bottle size, ABV, origin, style, price and intended use. Check whether the bottle is better suited for cocktails, neat drinking, gifts or a home bar.

A good vodka online shop should make it easy to compare premium and budget options. Sorting, price ranges and product categories help buyers choose more confidently. Availability and delivery conditions also matter, especially when the bottle is needed for a specific occasion.

For readers who want to compare different brands, bottle sizes and price levels in one place, Red & Weiss makes it easy to buy high-quality vodka online and choose a bottle for cocktails, neat drinking or gifting.

Online buying is convenient when the shop gives transparent product information. The better the information, the easier it is to match vodka quality with taste, budget and purpose.

Common Mistakes When Choosing Vodka

Vodka is easy to buy quickly, but that also makes mistakes common. Many buyers choose only by price or bottle design and ignore how the vodka will actually be used.

Common mistakes include:

  • choosing only by the lowest price;
  • assuming expensive vodka is always better;
  • ignoring the intended use;
  • buying premium vodka only for simple mixed drinks;
  • choosing flavoured vodka without checking the flavour profile;
  • ignoring ABV and bottle size;
  • not reading product information;
  • choosing a gift bottle only by design;
  • overlooking harsh alcohol burn.

The safest approach is simple: decide the purpose first, then compare taste, quality, price and product details. This prevents overpaying and also reduces the risk of choosing a bottle that does not fit the occasion.

Final Recommendation: How to Choose High-Quality Vodka

To choose high-quality vodka, start with purpose. For cocktails, choose a clean, neutral and balanced vodka with a good price-to-quality ratio. For neat drinking, choose a smoother premium bottle with a soft texture and clean finish. For gifts, choose a reliable brand with good presentation and clear quality signals.

For beginners, it is usually better to avoid overly harsh vodka and very specific flavoured options unless the taste preference is clear. A classic smooth vodka is often more versatile.

Price matters, but quality is a combination of raw material, distillation, filtration, ABV, taste, finish and intended use. When an online shop provides clear information and makes comparison easy, choosing the right bottle becomes much more reliable.

Daily writing prompt
Share a proverb you think is completely wrong and make your case.

Why Finance Teams Are Choosing a Hybrid Approach to AI

Artificial intelligence has become one of the most talked-about technologies in corporate finance. From forecasting tools to automated reporting systems, vendors increasingly promote AI as a solution capable of transforming financial operations. Yet many organizations are discovering that successful adoption depends less on replacing people and more on combining technology with human expertise.

As reported by The Next Web, the most effective finance departments are not handing over decision-making to algorithms. Instead, they are using AI to streamline processes while keeping experienced professionals responsible for analysis and judgment.

One reason is the difference between forecasting and financial modeling. Forecasting relies on historical data and trend analysis, areas where AI performs exceptionally well. Financial modeling is more complex. It requires understanding how a business operates, identifying relationships between revenue and expenses, evaluating risks, and testing assumptions about future growth. These tasks often involve critical thinking that extends beyond data processing.

Modern AI tools already provide substantial value across finance workflows. They can collect information from multiple systems, reconcile data, identify unusual transactions, and generate forecasts in a fraction of the time required by traditional methods. Scenario planning has also become faster, allowing finance teams to assess the potential impact of changes in pricing, hiring, customer retention, or market conditions within seconds.

The technology is especially useful for eliminating repetitive work. Tasks such as data entry, categorization, formatting, and reconciliation have historically consumed significant portions of finance professionals’ time. By automating these activities, organizations allow their teams to focus on strategy, planning, and decision-making.

Despite these advantages, AI still faces important limitations. One challenge is its tendency to produce confident-looking results even when the underlying assumptions are flawed. A forecast may appear sophisticated and detailed while relying on unrealistic inputs. Unlike an experienced analyst, AI does not naturally question whether a sudden improvement in customer retention or revenue growth is realistic.

Another issue involves business dependencies. Financial outcomes rarely exist in isolation. Sales growth may depend on additional marketing investment, new hiring plans, or operational changes. Human analysts often recognize these connections and adjust their models accordingly. AI systems, however, may struggle to understand such relationships when evaluating future scenarios.

Transparency is another critical factor. Investors, executives, and board members frequently ask how specific figures were calculated. Finance leaders must be able to trace assumptions, formulas, and data sources behind every projection. In many cases, AI-generated outputs still require human validation to provide the level of accountability expected in corporate decision-making.

This reality is reflected in the strategies of major consulting firms. Organizations such as Deloitte and PwC continue investing heavily in artificial intelligence while maintaining a strong focus on human oversight. AI supports activities like document review, compliance checks, and baseline analysis, while professionals remain responsible for interpretation, strategic recommendations, and client guidance.

As a result, a hybrid model is emerging as the preferred approach across the industry. Under this framework, AI handles data collection, forecasting, anomaly detection, and routine analysis. Human experts review assumptions, challenge conclusions, and ensure that outputs align with business realities before they influence important decisions.

Companies evaluating AI-powered finance platforms should consider several key questions. They should determine whether the system explains how conclusions were reached, whether there is clear accountability when errors occur, and how the tool adapts when business conditions change. Answers to these questions often reveal the difference between practical solutions and marketing promises.

The future of finance is unlikely to be fully automated in the near term. Instead, the strongest results are coming from organizations that use artificial intelligence to remove operational friction while relying on experienced professionals for strategic judgment. This balance allows businesses to benefit from faster processes without sacrificing the critical thinking needed to navigate complex financial decisions.

Daily writing prompt
Do you believe in soulmates? Why or why not?

Open-Weight AI Models Gain Momentum as iFrame Launches Hosted Inference Service

The rapid growth of artificial intelligence has created new opportunities for organizations across industries, including education, research, healthcare, and business. At the same time, the cost of deploying advanced AI models remains a major concern for institutions seeking to integrate these technologies into everyday operations. As a result, interest in open-weight models and more affordable AI infrastructure solutions continues to increase.

According to Stackademic, iFrame introduced a hosted inference service in August 2024 built around Meta’s Llama 3.1 and several other leading open-weight AI models. The service aims to provide enterprise-grade AI capabilities while reducing the costs typically associated with commercial AI platforms.

The launch reflects a broader shift taking place throughout the artificial intelligence sector. Organizations are increasingly exploring alternatives to proprietary systems in order to gain more flexibility, transparency, and control over how AI technologies are deployed. Open-weight models have emerged as an attractive option because they allow developers and institutions to better understand, customize, and manage the systems they use.

Meta’s Llama 3.1 played an important role in accelerating this trend. Released in 2024, the model quickly gained recognition for delivering strong performance across a wide range of tasks. Researchers, developers, and organizations began adopting the model because it offered capabilities comparable to many closed-source alternatives while providing greater deployment freedom.

iFrame’s hosted inference service is designed to simplify access to these models. Instead of building and maintaining complex infrastructure, customers connect through an API and gain access to powerful AI tools without managing hardware resources. This approach helps reduce technical barriers for organizations that want to implement artificial intelligence but lack dedicated infrastructure teams.

The service includes additional software layers intended to improve reliability and consistency. Features such as prompt optimization, structured output controls, and verification mechanisms help organizations generate predictable results across different applications. These capabilities are especially important when AI systems are used in environments where accuracy and consistency matter.

One of the primary advantages highlighted by iFrame is cost efficiency. The company states that the service delivers inference pricing that is approximately 40% to 70% lower than comparable hosted offerings from OpenAI for similar workloads. While savings vary depending on the specific task being performed, the overall goal is to make advanced AI more accessible to a wider range of organizations.

Lower costs have important implications for educational institutions and research organizations. Universities, training centers, and academic programs increasingly rely on AI-powered tools for data analysis, content generation, tutoring support, and research assistance. Budget constraints often limit access to large-scale AI systems, making affordable infrastructure an important factor in technology adoption decisions.

The economics behind the service are based on infrastructure optimization. Rather than depending on a single computing environment, iFrame routes workloads across hyperscale GPU resources while optimizing the software stack responsible for inference. This allows the company to reduce operational expenses without sacrificing performance levels required by enterprise customers.

The growing popularity of open-weight models also supports academic and research objectives. Open systems provide greater transparency, allowing researchers to examine model behavior and explore new applications. This level of visibility is often valuable in educational settings where understanding the technology itself is as important as using it.

Beyond education, the platform supports a wide variety of use cases. According to the company, the hosted inference service has been used for medical coding automation, evidence synthesis, research support, long-context document analysis, and AI-powered assistants. These applications demonstrate how modern inference platforms are becoming foundational components of digital transformation initiatives.

Another factor driving adoption is the desire to reduce dependence on a single technology provider. Many organizations now seek greater flexibility when building AI strategies. Open-weight ecosystems allow businesses and institutions to choose deployment approaches that align with their operational requirements while avoiding long-term vendor lock-in.

The launch also reflects changing perceptions about the future of artificial intelligence infrastructure. For years, many organizations assumed that access to advanced AI required reliance on a small number of proprietary providers. The success of open-weight models is challenging that assumption by showing that high-performance AI can be delivered through alternative approaches.

Industry observers expect this trend to continue as open models improve and infrastructure providers develop more efficient deployment methods. The combination of lower costs, stronger performance, and greater flexibility is encouraging broader adoption across sectors that previously viewed advanced AI as financially out of reach.

As artificial intelligence becomes more integrated into education, research, and professional environments, the importance of scalable and affordable infrastructure will continue to grow. Services such as iFrame’s hosted inference platform demonstrate how organizations are working to make advanced AI capabilities more accessible while maintaining the performance and reliability required for real-world applications.

The introduction of the platform highlights a key development in the AI market: powerful open-weight models, when paired with optimized infrastructure and enterprise-ready software tools, are becoming a viable alternative to traditional proprietary systems. For institutions seeking cost-effective access to advanced AI technologies, this model represents an increasingly attractive path forward.

Daily writing prompt
What’s something you’d love to see in the future, but know you probably won’t live to witness?

Integration of the Digital Tools in ELT Classrooms: A Strategy to Enhancing Language Learning

Citation

Tadi, V. K. (2026). Integration of the Digital Tools in ELT Classrooms: A Strategy to Enhancing Language Learning. International Journal for Social Studies, 12(2), 68–75. https://doi.org/10.26643/ijss/12

Dr Vijaya Kalyani Tadi

Faculty Member, Department of English,

Andhra University, Visakhapatnam

Email: vijayakalyani18@gmail.com

Abstract:

The digital-based model of English Language Teaching (ELT) is becoming a new change paradigm transforming the traditional model of teaching process by offering active and learner-centered teaching. The paper explains the way in which digital technologies, e.g., interactive tools (Padlet and Kahoot) or language learning apps (Duolingo or Quizlet) can enhance learning of English language skills. The study uses the TPACK and SAMR models and examines the possibilities and difficulties of technology integration in ELT classrooms in India based on the mixed-method approach consisting of a survey of the teachers, classroom observation, and interviews of the learners. The results indicate that even although the positive impact of the digital tools on the motivation of the learners, their active participation, and autonomy matter greatly, the impact of the utilization of the digital tools depends on the strategic integration, the readiness of the teachers, and the infrastructural support. The other digital literacy and access gap that is identified in the study is based on rural and semi-urban circumstances. This paper suggests some practical information to educators, policymakers and curriculum developers regarding the way to make technology integration in ELT meaningful and equitable. The findings reveal the importance of increased attention to special teacher training, the equipment that should be chosen in accordance with the situation, and blended education patterns that can be used to eradicate the digital divide to language learning.

Keywords: Digital Technology Integration, TPACK, SAMR, Blended Learning, Learner Autonomy, Digital Literacy, Digital Divide, Mixed-Method Research, India

Introduction

The pace at which the 21st century has seen the growth of digital technology has revolutionised the aspect of education and changed the manner in which information is received, transmitted and processed (Prensky, 2001). This has infiltrated the English language teaching (ELT) classroom whereby technology has been instrumental in enhancing the level of interaction among the learners in the process of equipping them with skills and exposing them to the real language experience (Chapelle, 2003). Coronavirus also led to the increased use of educational technology due to the movement of teachers and school institutions into a digital and blended environment (Dhawan, 2020).

Digital classroom use is a chance and a challenge in the ELT setting especially in countries like India. Although educational programs like Duolingo, Quizlet, Padlet and Google Classroom are viable as dynamic learning tools to enable language learners, lack of infrastructure, training and level of digital literacy is a barrier to majority of the educators (Kessler, 2018). This renders the use of these tools patchy or superficial thus annulling the potential usefulness of the tools in language acquisition.

The present study functions under the idea of applying digital tools to ELT classrooms considering the fact of addressing the four main language skill listening, speaking, reading and writing, and considering the aspect of providing learner autonomy, interactivity and pedagogical focus as new learning tools. The study will also point out not only the advantages but the pitfalls of technology in teaching languages to prepare educators, teacher trainers and curriculum developers with valuable suggestions of how to make the tech-supported ELT learning environments more engaging and effective.

Review of Literature

The application of technology in English Language Teaching (ELT) has experienced a significant level of research studies in the past two decades, which are continuously witnessed by a growing amount of literature which promotes the idea that technology can be applied to enhance the outcome of teaching and learning. Warschauer and Healey (1998) and other researchers emphasised that behaviourist approaches to Computer-Assisted Language Learning (CALL) are substituted by the more constructive and communicative ones, focusing the learner as the centre of language learning. The change is conducive to the recent trends in the pedagogical practices borrowing the participatory and student-centred learning simulations by means of the digital technologies.

During the last several years, web-based applications like Duolingo, Quizlet, Kahoot, Padlet, and Google Classroom have gained significant popularity as applications that may be applied to the process of vocabulary development, grammar memorization, and team learning and evaluation. It may adopt Mobile-Assisted Language Learning (MALL) due to the fact that the concepts by Kukulska-Hulme (2012), as well as studies by Godwin-Jones (2018) already predetermined the fact that it could assume the role of offering flexibility to the anytime-anywhere learning, i.e., to the digital-native students.

The Technological Pedagogical Content Knowledge (TPACK) model developed by Mishra and Koehler (2006) offers a highly sound platform to tackle the issue of how ELT can be applied successfully by use of technology. On the same note, the SAMR model developed by Puentedura (Substitution, Augmentation, Modification, Redefinition) could also make a handy consideration regarding the nature of classroom technology use: is it a simple substitution of the previous technology, or does it redefine the learning experiences?

Irrespective of such developments, there have been other research works which have come up with some of the challenges to be considered when integrating technology. The research conducted within the Indian scene (e.g., Sharma and Sharma, 2020; Basu, 2021) pinpoints the following issues:

  • the impossibility to gain access to the devices,
  • wobbly internet connection, and
  • insufficient training of the teachers.

These barriers normally lead to under-use or overrepresented in rural or under-resourced schools. Despite the fact that the literature is fairly explicit regarding the pedagogical significance of digital tools in ELT, it also underscores the need to apply it contextually and continuously, and the close focus on technological decisions implementation with regards to the teaching goal. The study is anchored on the available literature that examines the current application of digital tools in the ELT classrooms and the ways of enhancing the same.

Theoretical Framework

The most appropriate conceptualisation of integration of digital tools in English Language Teaching (ELT) is the theoretical frameworks that explain the interface of technology, pedagogy and content knowledge. Two of the theory models that are applied during this research include the TPACK Framework (Mishra and Koehler, 2006) and the SAMR Model (Puentedura, 2009). The models can be applied to determine the effectiveness of technology application besides the comprehensiveness and quality of technology application in language instruction.

Technological Pedagogical Content Knowledge (TPACK) framework is centered on the three sorts of knowledge which are complex in their interactions; content knowledge (CK), pedagogical knowledge (PK), and technological knowledge (TK). The effective use of digital tools in ELT implies that, not only the material (language knowledge) is to be mastered but also teachers should know the strategies and methods of teaching the language and what the technology can help and enhance language learning. In a tip, when a teacher relies on a Quizlet to teach vocabulary, he/she should match the abilities of the tool with the right language learning objectives and requirements.

The further elaboration of TPACK is the SAMR model or Substitution, Augmentation, Modification, Redefining (SAMR); the model provides a hierarchical approach to the question of the role of technology in the learning process. At the substitution level, technology only replaces a traditional device (i.e. a digital dictionary, rather than a print dictionary). Onward, at the modification and redefinition level, technology enables a few new forms of learning, previously unexplored: global learning, multimedia narrative or real time comments using interactive applications. The given model can be used specifically to analyse how far are the digital tools in ELT used radically or superficially.

The information offered by the two frameworks is helpful in the role that technology can play in language teaching. TPACK focuses more on competency and informed choices as a teacher, however, SAMR asks teachers to explore the depth of technological-integration. Taken in conjunction, they are the theoretical framework of addressing the current application of digital tools in ELT classrooms and how these tools might be optimized to be used in more meaningful ways.

Methodology

The article is conceptual and practice-based in terms of researching the concept of the use of digital tools in the English Language Teaching (ELT) classrooms. The study is not related with the collection of primary empirical data, but a synthesis of the literature available, case studies and observed classroom practices in any teaching environment and more specifically in India. Hopefully, some broad tendencies will be learned, some positive practices outlined, and some practical outcomes drawn to teachers and establishments that eventually intend to use technology-enhanced ELT.

It is examined based on the variety of the secondary sources such as peer-reviewed journal articles, conference papers, policy reports, and reports of practitioners. In addition, the examples of typical online tools (DUolingo, Quizlet, Padlet, Google Classroom, and Kahoot) are addressed, regarding their opportunities of core pedagogy and their alignment with the analysed TPACK and SAMR models. The tools are taken into account depending on their ability to help develop the language skills, involve learners, and communicate in the classroom. Although, no formal experimental and survey-based methodology is taken in the current paper, classroom observations, reflective practice in teaching, and secondary research conducted in Indian and international ELT settings are included in the paper. The approach would enable one to see the potentialities and constraints of the digital tool integration as a whole and would be the foundation of the pedagogical recommendations provided in the following parts.

Implementation & Analysis

There are many opportunities to study English as a second language that the online technologies offer and can be utilized to make the process more interesting to the students. The degree to which technology is available not only determines their success, but also the degree to which is used in the classroom to develop the specific language skills, promote interaction and promote learner autonomy.

Quizlet is the most widespread one, in which a teacher can create vocabulary flashcards, practice activities, and self-test quizzes. In ELT classrooms, Quizlet may be applicable in the school or college level and as an extension of the new vocabulary or phrase instruction in the reading or listening activity. The repetition system is gamified and thus assists students in memorising and remembering better. According to the TPACK model, Quizlet has performed well since its content (CK), delivery (PK) and adaptation to the requirements of the learners (TK) can be created by teachers.

One more example of collaborative tool that can be used to encourage student writing, brainstorming or group discuss is Padlet. Respondents are able to respond to reading using multimedia (adding text, images, links, or videos) to convey their ideas. Not only is this preventing the fluent writing, but it is also preventing the creative mind, and socialising. SAMR model will allow teachers to turn Padlet into an environment in which the traditional writing activities could be altered and redesigned rather than replaced.

Kahoot has been successful especially in formative assessment. Its quiz-like form of interaction allows teachers to test the knowledge at the conclusion of a grammar or reading lesson and engage learners in competition. It also enables real time feedback because it enables the teachers to know which areas they are performing poorly and they can amend instructions.

In blended learning, the instructional organisation is based on Google Classroom. The instructors put up lesson content, assign and follow-up, as well as learners are able to review content asynchronously. This fosters differentiation and agency of the learners which is the objectives of the modern classes in ELT.

However, the classroom implementation is not problematic. In case of a lack of time or training, teachers lament that they struggle to select the correct tool to execute the correct task. The infrastructure inequities (unavailable Wi-Fi, outdated equipment, electrical issues, etc.) tend to limit access, particularly to rural or low-income schools. Moreover, they can be digitally literate in social or entertainment aspects, yet some guidance on how best to use technologies related to academics can be required by students. Despite the possible existence of these barriers, as demonstrated in the examples above, in case of a purposeful introduction of the digital tools, their implementation, depending on the goals of the instruction, and supported by teacher training, these tools can make a significant imprint on the ELT experience. The future of the technology in the wise and strategic use of technology is the mutual transformation of the passive learning to interaction learning and student-centred learning.

Conclusion

Digital tools in English Language Learning (ELT) is a prospect of changing the art of language acquisition and giving the students a chance to interact and enhance the process of the acquisition of the basic language skills. Applications such as Quizlet, Padlet, Kahoot, and Google Classroom have the ability to change more traditional classrooms into newer and more interactive and learner-centered ones in the right hands. The rationale of balanced and strategic integration can also be supported by other models as TPACK and the SAMR in order that the technology can be an addition to and not a substitute of the pedagogical intent. Though digital technologies are flexible, autonomous, and provide real-time feedback, they can have the most significant effect where teachers possess the necessary technological, pedagogical, and content skills. In addition to this, the inadequate infrastructure, training and unequal distribution should also be considered to be specific to the non-homogeneous learning systems such as India.

To go on with it, the development of the teacher profession must be associated with particular training on the topic of technology integration. The institutions are stimulated to investing in infrastructural and experimental, and reflective practice culture. In schools, it is encouraged that teachers should begin with simple digital additions, and gradually evolve to more radical applications. Lastly, it can be mentioned that the online tools are also fruitful, and they serve a purpose in ELT. Effective facilitator of language learning in the 21st century Technology has the capacity to become a useful learning tool provided it is strategic in the pedagogical approach and sensitive to context.

Works Cited

Basu, S. (2021). Digital divide in Indian education during COVID-19 pandemic. International Journal of Creative Research Thoughts, 9(1), 1917–1923.

Chapelle, C. A. (2003). English language learning and technology: Lectures on applied linguistics in the age of information and communication technology. John Benjamins Publishing Company.

Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018

Godwin-Jones, R. (2018). Using mobile technology to develop language skills and cultural understanding. Language Learning & Technology, 22(3), 1–17.

Hockly, N. (2013). Mobile learning. ELT Journal, 67(1), 80–84. https://doi.org/10.1093/elt/ccs064

Kessler, G. (2018). Technology and the future of language teaching. Foreign Language Annals, 51(1), 205–218. https://doi.org/10.1111/flan.12318

Kukulska‐Hulme, A. (2012). Mobile-assisted language learning. In C. A. Chapelle (Ed.), The encyclopedia of applied linguistics (pp. 3701–3709). Wiley-Blackwell. https://doi.org/10.1002/9781405198431.wbeal0768

Makhijani, Simran, Dugaje, Manohar. Enhancing Student Learning Outcomes: Evaluating Effective Educational Strategies for Academic Success. CUESTIONES DE FISIOTERAPIA. Volume 54, Issue 3, 2025. https://doi.org/10.48047/xvqrj747

Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x

Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. https://doi.org/10.1108/10748120110424816

Puentedura, R. R. (2009). SAMR and TPACK: Intro to advanced practice. Hippasus.

Sharma, R., & Sharma, M. (2020). Challenges of online education in India during the COVID-19 pandemic. International Journal of Advanced Research, 8(5), 1132–1137.

Warschauer, M., & Healey, D. (1998). Computers and language learning: An overview. Language Teaching, 31(2), 57–71. https://doi.org/10.1017/S0261444800012970

Daily writing prompt
How do you handle fear and self-doubt?

‘Madness’ and ‘Spirituality’: A Study of Diasporic Fragmentation in Clarke’s Late Fiction

Citation

Tadi, V. K. (2026). ‘Madness’ and ‘Spirituality’: A Study of Diasporic Fragmentation in Clarke’s Late Fiction. International Journal of Research, 13(4), 337–343. https://doi.org/10.26643/ijr/edupub/28

Dr. Vijaya Kalyani Tadi

Faculty Member, Department of English,

Andhra University, Visakhapatnam

Email: vijayakalyani18@gmail.com

Abstract

The paper below explores how spiritual imagery and mental fragmentation is used by Austin Clarke to describe the psychic cost of the displacement and colonial trauma in The Polished Hoe, The Prime Minister, and The Question. Clarke never makes a distinction or opposition between madness and spirituality that they are bound to different worlds; on the contrary, he demonstrates that they are twin responses to the rule of imperialism, to diasporic fragmentation and cultural shock. Hallucination, confession, prayer and silence in his subsequent fiction are not an aspect of weakness or madness, but are domains where become zones in which identity, memory and resistance come into collision with one another which are spiritually and politically charged.

Clarke constructs madness not as the inability to collapse using the postcolonial trauma theory, Black Atlantic religious speech, and subaltern studies, but rather in a disruptive grammar of survival, a corporeal critique of neocolonial realities. Simultaneously, his spirituality also includes his attitude towards spirituality, which rejects institutionalised religion, more so the colonial Church, and retrieves fragmented belief systems as tools of cultural survival. The biblical citations, institutional attack, and the pictures of the plight of women enhance a creation by the empire not only to inflict economic and social injury on women but also metaphysical injury. All the same, the fiction of Clarke dramatizes the sacred and the disjoined nature of post-colonial life, and this demands that we read the divided voices, the disintegrated psyches, as resistance. His novels make the readers consider the spectres of empire, both in the political order, and in the spiritual and emotive topography of individuals who needed to be in its afterlives.

Keywords: Austin Clarke, spiritual displacement, madness, postcolonial trauma, The Polished Hoe, The Prime Minister, The Question, religion, memory, Black Atlantic.

Introduction: Spirit and Psyche in Postcolonial Literature

Postcolonial literature tends to traverse the discontinuous landscape of identity, past and cultural memory in the post-imperial era. The spirituality and insanity are two twin forces that are significant solutions to trauma and uprooting in this literary landscape. All these ideas are not simple incitement of personal suspension or mystic flight; they are the mental and metaphysical remaining of colonial and imperial conquest. The sacred and the shattered are joined in the mind and hearts of people caught in the eddy currents of racial, spiritual, national destruction, to most writers in the postcolonial canon, including Austin Clarke.

The Polished Hoe, The Prime Minister, The Question, and in the later fiction of Clarke, the spiritual perturbation which goes with psychic ruin cannot be divided. His characters are also recognized to be affected by the broken faith, existential hopelessness, and spectre memory. They are not individualistic illnesses; it is social illnesses that were shaped by the history of racial subjugation, exile and internalisation of imperialism ideology. They are calling the divine, but it is answered in the form of silence or contradiction. Madness is also the articulation of trauma (and) also a subaltern lingo of resistance, a sign not of the capitulation, but or resistance of the cumbersome baggage of identity and survival in the postcolonial world.

The stories that Clarke shares with us give out an incredibly symbolic space in which the spirit and a psyche interact, deconstruct and restructure. His heroes are fond of oscillation between religious passion and non-religious emasculation, between confession and lessening. Clarke employs them to dramatize how colonial violence does not end at the political independence but it still lingers in spiritual and psychological life of the once colonised. That is why his fiction becomes a powerful metaphor of the postcolonial crisis and shows how belief systems previously imposed to a colonised society break down in front of the traits of betrayal, memory and longing.

‘Sanity’ and ‘Madness’ as Resistance and Collapse

The personalities of Clarke are regularly mentally fragmented, hallucinating, paranoid, and erratic, symptoms of neither personal pathology nor structural and historical trauma. There is nothing random about such mental breaks but there is the Clarke narrative policy. He plays with the border of sanity and madness, and makes madness appear to be the only rational response towards buildings of imposed dehumanisation. The sense of hypocrisy of the new Black leadership is highlighted in The Prime Minister through the downward spiral into paranoia that the protagonist of this play makes. He receives Article 4.09 of the table of progress only to be tokenised and shut down as he goes on pushing. His breakdown represents the breakdown of the postcolonial dream itself, in other words, a system, in which the power only changes hands and the imperial apparatus still remain.

The narrator of The Question, who identifies oneself by no known name, wanders in a frozen and dissociated Toronto and is tortured by memory, loneliness and invisibility of being a non-racially identified being. His breakdown is not by chance, but it is, in fact, the consequence of years of alienation in a society that does not allow him a feeling of belonging or self-expression. In this instance madness is (somehow) a protestant expression, a means of escape out of the reasoning of a world that invites to invalidate his humanity. His lack of sense augurs the rupture of the logic of repression and decency in place of pathology.

Clarke also calls on the reader to consider madness as a collapse and a haven of subvert knowledge. The broken psyche of the characters is used to display the violence behind the genteel bureaucracy and religious virtue. The realities that the society is not eager to hear are brought about by sanity. That way it is not only an injury brought about by empire but also a weapon with which to call the unnamable by name. Clarke reinvents madness as self-subverting force, simultaneously powerless and powerful, victimised and rebellious, silent and talkative.

Biblical Allusion in Clarke’s Language

The use of biblical language and biblical imagery as a scaffolding of storytelling is frequently used by Clarke, as well as a scaffolding of irony, critique and subversion. His attitude to the Bible is twisted, at once devout, sceptical and cleansing. These sources serve various functions: they illustrate the hypocrisy of the colonial and postcolonial system along with its ethical aspects, they restore the pronunciation of the oral stories, and they demonstrate the spiritual trauma of his characters.

Mary Mathilda in The Polished Hoe is more of a long sermon, or of lamentation, in the manner and in the heart-touch of the cries of Job to the deaf ears of God. The text is full of Christian words sin, redemption, judgment, but they are divested of their salvific meaning. Instead, they are an outcome of the world in which faith is emptied by violence. The silence of God-like in the whole novel has an echo in the silence of the colonies who denied the plight of the blacks. Her ode to biblical tropes starts to work as an accusation, bounced back upon herself, Christian rhetoric against itself, the systems which had turned to religion to justify oppression.

In The Question, the narrator is an unnamed person who lives in the realm of existential exile. By using the tropes of the bible (wandering, temptation, and damnation), Clarke explains how the main character is spiritually alienated. Toronto, being a cold and unforgiving city is transformed into a secular purgatory where metaphysical grounding is lost. The judicative language is not dead but it lacks grace. Clarke uses these references to show how the Christian theology that was imported by the colonial education and the missionary work to the diasporic mind still remains even though it cannot give them a sense of belonging nor can it give them any comfort.

Moreover, the biblical references which Clarke incorporates are quite rhythmic since they belong to the Black diasporic oral culture which unites the spiritual and the political. The instruments of ‘psalmic’ repetition, rhetorical interrogation and prophetic cadence bring forth the voices of the characters with moral authority, although they are voices being spoken in the margins, in despair. Avoiding and reorganizing biblical tropes, Clarke is not simply rejecting religious tradition; he reinvents and sets it new ways to expose the hypocrisies of imperial religion and to proclaim another, oppositional spirituality.

The Colonial Church vs. Indigenous Belief

In Clarke, in all her novels, the religious institutions (especially the Christian Church) are depicted as complicit in the colonial conquest. The Prime Minister reveals the church as a form of social control (that it was in the imperial period). The clergy association with politics elite and religion is pacifying rather than empowering. Religions are not emancipating because they are expected to support hierarchies hence upholding the ideologies. This process of the identification of the church with the post-independence political authority is the sign of the high level of its intertwining with the imperial logic which prolongs the submissible aspect of the church till the postcolonial years.

In his turn, Clarke, at times, mentions the submerged or torn-out remains of the other spirituality, folk belief, worship of the dead, and Africa, inspired ritual action which preconditions the survival of the culture and silent resistance. These spiritual manifestations are hardly mentioned and suppressed in the narration, but their existence also gives some understanding of other epistemologies, which are not founded on colonial imposition. They refer to a cultural memory which is not being exterminated in bulk, to older cosmology and cultural healing traditions buried under the same missionary conquest.

These indigenous versions of spirituality are yet to be refined and idealised. They are fragments, remains of a discontinuity, give testament to the erasures of a centuries-old religious domination. The reason they are marginalised in the story is that they are marginalised in real life, and even their relative appearance is more heart-rending. Clarke uses these remnants of symbolism to give hints of the way, under the debris of forced conviction, there are alternative bases, displaced though not destroyed, wounded but not fractured.

Women’s Spiritual Suffering and Silence

Spiritual and emotional torture disproportionately weighs on women in the fiction by Clarke. The Polished Hoe, the confession of Mary Mathilda is a sort of exorcism of spirituality and not political vengeance. Her silence over the many years could be termed as an internalised oppression, which is bound up to what religion and colonialism morality preach. Her confinement in religious forms of thought where submission of faith, chastity, and forgiveness must be fulfilled only adds to violence meted on her, both physical and mental. Although it is a very personal tale, her tale is a collective scream of all the women who have suffered simply because the systems have nothing to give to them other than to be submissive.

Women in The Question are shown in fragments as the domestic servants, former lovers, lost mothers, individuals whose voices are rather faint but full of spiritualized words. The silencing of female experience, which is omnipresent, is emphasized by this spectral presence. It does not fully reflect their inner worlds, but hints at their spiritual survival in invisibility and dispossession. Their agony is incorporated into the larger program of the Clarke critique the proof that the moral power of religion so frequently is based on the subjection of women.

Women spirituality as explained by Clarke is therefore not a transcendence rather an entrapment, resistance and disjointed strength. Religion is not an easy way; it is a fresh battle field. That is because such characters are the descendants of theological systems that never clarify their sufferings and resemble their silence. But in accomplishment of that silence, however in some measure, they rediscover spirituality in their own terms, as a survival, and not as submission.

Conclusion: The Divine and the Damaged

The late fiction of Austin Clarke is a philosophical meditation concerning the death of spiritual certitude in the postcolonial world. Relating madness to shattered religion, tracing the path of colonialism to twist the mind and soul, Clarke maps the near cost of living as a diaspora. His narratives may also be termed as a critique of external systems and also a depiction of general falls apart. The reference to the Bible, the attack on the religious organisation and accentuation on female spiritual disenchantment seam together in a Web of disappointment by God.

Faith in The Polished Hoe, The Prime Minister and The Question convey less comforting and more like a mirrored mirror, to which the characters address their need to locate a sense in, where they cannot find answers at all. But in such silence, there is a strong opposition of a kind. Clarke invents meaning in the space of divinely just by narrating, by speech of confession, and through the memory. They have a damaged voice but command their existence even or against the forgetting machine of the empire.

Clarke is thus transforming the spiritual and mental fragmentation into language of survival and censure in his fiction writings. Enlightenment is turned into an account of literature–where the sacral is prosecuted, and the lost justified, and silence charged against silence. When Clarke then sees such fractured lives, she tells the reader not to put his/her hand on the fractured part but to overhear that harmonization of dissonance and to hear something more truthful.

References

Clarke, Austin. The Polished Hoe. Thomas Allen Publishers, 2002.

—. The Prime Minister. Vintage Canada, 2005.

—. The Question. Thomas Allen Publishers, 1999.

Dugaje, Manohar. Re-mapping Colonial Violence: A Postcolonial Study of Coetzee’s Life and Times of Michael K. MRS Journal of Arts, Humanities and Literature. Issue-12 Volume-2 2025. https://doi.org/10.5281/zenodo.17879881

Fanon, Frantz. Black Skin, White Masks. Translated by Charles Lam Markmann, Grove Press, 1967.

Fanon, Frantz. The Wretched of the Earth. Translated by Richard Philcox, Grove Press, 2004.

Gilroy, Paul. The Black Atlantic: Modernity and Double Consciousness. Harvard University Press, 1993.

McKittrick, Katherine. Demonic Grounds: Black Women and the Cartographies of Struggle. University of Minnesota Press, 2006.

Said, Edward W. Culture and Imperialism. Vintage Books, 1994.

Walcott, Rinaldo. Black Like Who?: Writing Black Canada. Insomniac Press, 1997.

Young, Robert J.C. Postcolonialism: An Historical Introduction. Wiley-Blackwell, 2001.

Daily writing prompt
What’s a moment that made you question reality?

Paphos Airport Car Rental Guide 2026

Landing at Paphos Airport and collecting a car straight away is one of the simplest ways to start a trip in western Cyprus. The airport is well placed for Paphos city, Kato Paphos, Coral Bay, Peyia, Polis, Latchi, Limassol and the Akamas area. If your plans include beaches, villages or several stops during one stay, airport pickup can save time from the first day.

Travelers who want a flexible start often choose car rental Paphos Airport options with clear conditions, convenient pickup instructions and vehicles suitable for coastal roads, resort areas and longer Cyprus routes. This is especially useful if you want to avoid separate transfers, keep control over luggage and drive directly to your hotel or first destination after landing.

Start Your Cyprus Trip Directly from Paphos Airport

Airport pickup works best when you do not want to split your arrival into several steps. Instead of taking a taxi to the hotel, checking in and then arranging a rental later, you collect the vehicle once and continue with your own schedule.

  • Direct travel from the airport to Paphos, Coral Bay, Peyia, Polis or Limassol
  • More control over luggage, children’s items and arrival timing
  • Useful for beach holidays, family trips and longer stays
  • Practical for routes to Akamas, Latchi, Troodos villages and Limassol
  • Convenient for early departures and late returns

The main benefit is not just convenience. A car makes western Cyprus easier to use properly because many of the best beaches, viewpoints, villages and nature routes sit outside the main hotel zones.

How Airport Pickup Works in Paphos

The pickup process depends on the local provider and the offer you choose. Some rentals are handled from airport desks, others use a meet and greet process near arrivals, nearby parking areas or a short offsite transfer. The important part is to know the exact process before your flight.

  • Confirm whether pickup is inside the terminal, in a car park or offsite
  • Save the local supplier phone number before landing
  • Keep your booking confirmation available offline
  • Add your flight number if requested
  • Check the return location before leaving the pickup area

If your flight is delayed, contact the provider as soon as possible. Flight details help the local partner adjust the meeting time and avoid confusion after arrival.

Documents Needed for Car Rental at Paphos Airport

Before booking, make sure your documents match the rental conditions. Requirements can vary by provider, car category and driver country, so it is better to check them before traveling rather than at the counter.

  • Valid driving licence
  • Passport or national ID
  • Booking confirmation or voucher
  • Payment method accepted for the selected offer
  • International Driving Permit if required for your situation
  • Rental agreement and insurance details after pickup

If your licence is not in Latin characters, confirm the requirements before travel. This can prevent delays during pickup and reduce the risk of issues during roadside checks.

What to Check Before Leaving the Airport

After a flight, it is tempting to sign quickly and leave. Still, a short inspection is worth the time. It protects you at return and confirms that the car matches the booking conditions.

  • Check bodywork, mirrors, lights, tyres and wheels
  • Take photos or videos of existing marks
  • Confirm fuel level and fuel policy
  • Review insurance, excess and deposit conditions
  • Ask about roadside assistance and emergency contact
  • Confirm the exact return point and after hours process if needed

Make sure any visible damage is recorded before you leave the pickup area. This is especially important if your route includes beach parking, village roads or longer drives across Cyprus.

Popular Routes After Leaving Paphos Airport

Paphos Airport is located southeast of the city and connects easily with the main coastal road network. The first drive is usually simple, but travel time depends on season, traffic, hotel location and parking.

RouteApproximate Time
Paphos Airport to Paphos city centre20 to 30 minutes
Paphos Airport to Kato Paphos20 to 30 minutes
Paphos Airport to Coral Bay35 to 50 minutes
Paphos Airport to Peyia40 to 60 minutes
Paphos Airport to Polis55 to 80 minutes
Paphos Airport to Limassol50 to 75 minutes

These times are approximate. In summer, allow extra time for airport pickup, hotel check-in, beach traffic and evening parking in busy resort areas.

Best Car Types for Paphos Airport Pickup

The best car depends on how you plan to use it. For Paphos city, Kato Paphos, Coral Bay and short beach trips, a compact or mid size car is usually the most practical choice. For families, longer routes or more luggage, comfort and boot space become more important.

Car TypeBest For
Compact carCouples, short stays, city parking and beach trips
Mid size carSmall families, luggage and mixed island routes
SUVLonger drives, comfort and extra luggage space
MinivanGroups and larger families

Bigger is not always better in Cyprus. A smaller vehicle is often easier near restaurants, beaches, old village streets and busy parking areas.

Airport Pickup, City Pickup or Hotel Delivery?

Airport pickup is the strongest option if you want to drive immediately after landing. City pickup or hotel delivery can work better if you arrive late, want a relaxed first evening or plan to stay around the hotel before exploring.

OptionBest For
Airport pickupDirect travel after landing, luggage, families and early road trips
City pickupVisitors staying first in central Paphos or Kato Paphos
Hotel deliveryLate arrivals, resort stays and relaxed first day plans

If your first route is Coral Bay, Polis, Latchi or Limassol, airport pickup usually makes the most sense. If your first night is a simple hotel stay in Paphos, delivery the next morning can be more comfortable.

Popular Routes from Paphos Airport

Paphos Airport works well as a starting point for western Cyprus. Choose the route based on your first day, not only the distance on the map.

RouteBest ForPlanning Level
Paphos Airport to Kato PaphosHotels, harbour area and first arrivalEasy
Paphos Airport to Coral BayBeach stays and family holidaysEasy
Paphos Airport to Polis and LatchiHarbour, beaches and quieter north coastModerate
Paphos Airport to Akamas areaNature routes and viewpointsModerate to high
Paphos Airport to LimassolCity, marina and business routesModerate
Paphos Airport to Troodos villagesMountain villages and food routesHigh

Driving in Paphos and Western Cyprus

Driving in Cyprus is generally manageable, but visitors should remember one important detail: traffic drives on the left. Motorways are usually straightforward, while village roads, mountain routes and some coastal access roads require more patience.

  • Drive on the left side of the road
  • Use extra caution at roundabouts if you are not used to left side driving
  • Start early for popular beaches and nature routes
  • Keep water in the car during summer
  • Use legal parking and avoid blocking narrow roads
  • Allow extra time for rural and mountain routes
  • Do not drive on rough tracks unless your rental conditions allow it

Some routes near Akamas, Lara Beach and remote nature areas can include rougher access roads. Check the rental agreement before taking any unpaved road.

Parking in Paphos

Parking in Paphos is usually easier than in many larger European destinations, but tourist areas still get busy. Kato Paphos, the harbour, archaeological sites, restaurant zones and popular beaches need a little planning in high season.

  • Use hotel parking when available
  • Check marked parking areas near the harbour and archaeological sites
  • Arrive early for beach parking in summer
  • Avoid leaving valuables visible inside the car
  • Do not block driveways, narrow streets or access roads

For evening visits to the harbour or central tourist areas, allow extra time. It is usually better to park legally and walk a few minutes than to look for a risky space close to the entrance.

Returning the Car at Paphos Airport

Airport return is easiest when it is planned before the final day. The key details are fuel policy, return point and timing before your flight.

  • Confirm whether return is at the terminal, car park or offsite office
  • Refuel according to the agreed fuel policy
  • Allow extra time for traffic and vehicle inspection
  • Take return photos if the car is not inspected immediately
  • Keep the final receipt or return confirmation

For early morning or late night flights, confirm the after hours return process in advance. This avoids last minute stress at the airport.

Common Mistakes to Avoid

  • Booking only by the lowest daily price
  • Not checking deposit, insurance and excess conditions
  • Leaving the airport without photographing the vehicle
  • Forgetting that Cyprus drives on the left
  • Choosing a large car for narrow village roads and beach parking
  • Driving to Akamas or Lara Beach without checking road and rental conditions
  • Returning the car too close to flight departure time

A good airport rental is not only about getting a car. It is about clear pickup instructions, transparent terms, suitable insurance and a vehicle that fits your real route.

Paphos Airport car rental is a practical choice for travelers who want direct access to the coast, villages and wider Cyprus routes. It works best when documents are ready, pickup details are confirmed and the selected car matches the trip you actually plan.

With the right preparation, renting a car at Paphos Airport gives visitors better control over arrival, route planning and travel costs during their Cyprus stay in 2026.

Daily writing prompt
What is the meaning of life?

Three-Dimensional Digital Human Capital Management: Theoretical Construction and Empirical Examination

Linghu Yin 1*, Wang Xiaohui 1, Liang Mengmeng 2

1 Farabi International Business School, Al-Farabi Kazakh National University, Almaty,

Kazakhstan

2 Department of Art History, Vitebsk State University, Vitebsk, Belarus

* Corresponding author: linghuyin8@gmail.com

Abstract

In the context of the digital economy, digital transformation is fundamentally reshaping organizational management, particularly the role of human resource management (HRM). However, existing studies predominantly focus on technological applications or single-dimensional perspectives, lacking a systematic understanding of the structural dimensions of digital HRM and its underlying mechanisms. Drawing on strategic human resource management theory and the resource-based view, this study develops a three-dimensional digital human capital management framework, encompassing functional digitalization, operational digitalization, and capital-oriented digitalization. Using an embedded single-case study design, this research examines Haier Smart Home based on archival data and interview materials from 2020 to 2024. The findings indicate that: (1) HRM transformation exhibits strong vertical alignment with digital transformation strategy; (2) the three-dimensional digital evolution serves as a critical mediating mechanism between strategy and organizational performance; and (3) capital-oriented digitalization functions as a strategic lever through mechanisms such as user-based compensation and dynamic talent allocation. This study extends the resource-based view by shifting the focus from resource stock to capital operation and provides practical implications for manufacturing firms undergoing digital transformation.

Keywords: three-dimensional digitalization; human capital management; strategic mediation; human capital; Haier

1. Introduction

With the rapid development of artificial intelligence, big data, and cloud computing, digital transformation has become a central driver of organizational change. In this context, human resource management (HRM) is evolving from a traditional administrative support function into a strategic mechanism that connects organizational strategy and performance outcomes (Bharadwaj et al., 2013).

Despite increasing scholarly attention, three major gaps remain. First, digital transformation and HRM are often studied separately, with limited integration of the two domains. Second, research on digital HRM tends to focus on technological tools, lacking a clear structural framework (Bondarouk & Brewster, 2016). Third, the mediating role of HRM between strategy and organizational performance remains underexplored (Delery & Roumpi, 2017).

To address these gaps, this study investigates the following research question:
How does digital transformation influence organizational performance through structural changes in HRM?

2. Theoretical Framework: A Three-Dimensional Model of Digital Human Capital Management

This study proposes a three-dimensional framework of digital human capital management, which conceptualizes HRM digitalization as a progressive and hierarchical process rather than a set of isolated practices.

At the first level, functional digitalization focuses on the automation and standardization of HR processes, aiming to improve efficiency. This stage reflects a transaction-cost-oriented logic, emphasizing cost reduction and process optimization (Wright & McMahan, 1992).

At the second level, operational digitalization emphasizes data-driven decision-making and platform-based coordination, enabling organizational agility and collaboration. This dimension is closely related to the development of dynamic capabilities, which allow firms to adapt to changing environments (Teece et al., 1997).

At the third level, capital-oriented digitalization represents a fundamental transformation in HRM logic, treating human resources as strategic capital and embedding market mechanisms into internal management processes. This perspective aligns with the resource-based view, which highlights the strategic value of firm-specific resources (Barney, 1991).

This progression reflects a shift from efficiency-driven management to value-creation-oriented management.

Table 1. Three-Dimensional Digital Human Capital Management Framework

DimensionCore MeaningManagement LogicValue Orientation
Functional digitalizationAutomation and systemization of HR processesInstrumental logicEfficiency enhancement
Operational digitalizationData- and platform-enabled HR practicesPlatform logicAgility and coordination
Capital-oriented digitalizationMarketization of human capitalMarket logicValue creation

Building on this framework, the study proposes that HRM transformation aligns with digital strategy and mediates its impact on performance. Furthermore, capital-oriented digitalization is expected to function as a strategic lever by reshaping incentive structures and organizational processes.

3. Methodology

This study adopts an embedded single-case study design, which is particularly suitable for exploring complex organizational phenomena in depth (Eisenhardt & Martin, 2000). Haier Smart Home is selected as the focal case due to its leadership in digital transformation and HRM innovation.

Data were collected from multiple sources, including corporate reports, public speeches, and semi-structured interviews. Such triangulation enhances the robustness of qualitative findings.

The analysis follows a content analysis approach to identify key themes, combined with pattern matching to compare empirical observations with theoretical propositions (Zott, 2003).

4. Results and Discussion

The findings reveal a clear three-stage evolutionary path of HRM digitalization. In the functional digitalization stage, organizations achieve efficiency gains through process automation. In the operational digitalization stage, digital platforms enable employee empowerment and enhance organizational coordination. In the capital-oriented digitalization stage, market mechanisms are embedded into HRM practices, transforming human resources into value-generating capital.

This evolution reflects a shift from administrative efficiency to strategic value creation, consistent with prior research on HR architecture and differentiation (Lepak & Snell, 1999).

Further analysis demonstrates that HRM plays a mediating role between digital transformation and organizational performance. Functional digitalization primarily improves efficiency by reducing administrative costs, whereas operational digitalization enhances agility through improved coordination. Capital-oriented digitalization, in contrast, directly drives value creation through incentive alignment and market-based mechanisms, which is increasingly relevant in algorithm-driven management environments (Meijerink & Bondarouk, 2021).

Table 2. Mediating Mechanisms of Three-Dimensional Digitalization

PathMechanismPerformance Outcome
Functional digitalization  PerformanceCost reductionEfficiency improvement
Operational digitalization  PerformanceCoordination enhancementIncreased agility
Capital-oriented digitalization  PerformanceIncentive alignment and market mechanismsValue creation

Among the three dimensions, capital-oriented digitalization demonstrates the strongest explanatory power. The user-based compensation mechanism directly links employee income to customer value, thereby reducing agency problems and aligning individual incentives with organizational goals. At the same time, dynamic talent allocation enables flexible matching between talent and tasks, enhancing organizational responsiveness.

These findings are consistent with the broader understanding of digital transformation as a process of organizational restructuring rather than mere technological adoption (Vial, 2019).

5. Conclusion

This study develops and empirically examines a three-dimensional model of digital human capital management. The findings highlight that HRM serves as a critical mediating mechanism in digital transformation and that capital-oriented digitalization is the key driver of strategic value realization.

Theoretically, this study extends the resource-based view by shifting the analytical focus from resource stock to capital operation capability. It also contributes to the literature on strategic HRM by clarifying the structural dimensions of digital HRM. Practically, the study provides a structured pathway for firms seeking to advance HRM digital transformation.

References

  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.
  • Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy. MIS Quarterly, 37(2), 471–482.
  • Bondarouk, T., & Brewster, C. (2016). Conceptualising the future of HRM and technology research. The International Journal of Human Resource Management, 27(21), 2652–2671.
  • Delery, J. E., & Roumpi, D. (2017). Strategic human resource management. Human Resource Management Review, 27(1), 1–14.
  • Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities. Strategic Management Journal, 21(10–11), 1105–1121.
  • Lepak, D. P., & Snell, S. A. (1999). The human resource architecture. Academy of Management Review, 24(1), 31–48.
  • Meijerink, J., & Bondarouk, T. (2021). The duality of algorithmic management. Human Resource Management Review, 31(1), 100722.
  • Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities. Strategic Management Journal, 18(7), 509–533.
  • Vial, G. (2019). Understanding digital transformation. The Journal of Strategic Information Systems, 28(2), 118–144.
  • Wright, P. M., & McMahan, G. C. (1992). Theoretical perspectives for strategic human resource management. Journal of Management, 18(2), 295–320.
  • Zott, C. (2003). Dynamic capabilities and the evolution of firm performance. Strategic Management Journal, 24(2), 97–125.
Daily writing prompt
What’s a moment that made you question reality?

Staff Motivation and Organizational Productivity

Yabagi Bala Ahmed1 & Musa Ibrahim1

Department of Business Administration and Management, Federal Polytechnic, Bida

yabagibalaahmed@gmail.com

musafedpolybida@gmail.com           

Abstract

Every organization strives to enhance productivity of staff and organizational performance. Bearing this in mind, this study examines the relationship between employee motivation and organizational productivity among employees in manufacturing sector in Abuja. The researcher obtained data from primary and secondary sources. In all, 280 questionnaires were considered valid for analysis.  The researcher adopted simple random sampling technique while the statistical packages for social sciences (SPSS) and bar charts were employed for data analysis. The findings generally indicate a positive relationship between motivation and organizational productivity. Specifically, findings demonstrate a positive and significant relationship between staff salary, welfare package and organizational productivity. More so, results indicate that workers’ involvement in decision making is positively related to organizational productivity. The researcher concludes that organizational productivity tends to increase when financial benefits, welfare services and enabling work environment are effectively put in place by the organization.  This study recommends among other things that, manufacturing organizations should offer financial and non-financial incentives to employees and introduce regular training/development programs to keep the workforce productive to continuously enhance organizational productivity.            

Keywords: employee productivity, financial benefits, staff training and development, welfare packages, and workers’ involvement in decision making.

Introduction/Background of the topic

Motivation is the most significant element for all organizations, be it private or a public sector. It plays a significant role for the accomplishment of any organization. Motivation is derived from the root word motive (Pinder, 2008). Therefore, the word motive means wants, desire, and needs of people.  Motivation is the procedure in which an organization motivates their employee in form of bonus, rewards, and some other incentives; this is solely to achieve the organizational objectives. The individual is a complex creature and is inspired by some various kind of tactic. According to Thomas (2020), motivation is the procedure that energies, stimulates, stands, and directs actions and performance.

Every organisation has the desire to achieve increased productivity with the view to attain its goals and objectives. Most organisations believe that workers are their main assets to turn out high quality work and productivity (Adi, 2020). Campbell (2015) added that high motivation leads to more enthusiastic employees who are more efficient in their job productivity. Hence, for any organisation to be productive, it must motivate its employees. Motivation can be in form of adequate training and equipment, salary, fringe benefits, promotions, comrades’ trust, unit cohesion, status symbols amongst others, to satisfy the needs of the employees for enhanced productivity (Adi, 2020). Based on these attributes, it is important for organisations including the manufacturing entities to adequately provide motivation schemes for their employees in order to achieve high productivity.

Problem identification

Essentially, productivity depends on motivated workforce for the attainment of the organizational goals. Factors affecting productivity can be managerial and organizational, physical, technical and social factors (Accel, 2018). These factors which include elements of motivation are important for increased productivity in organizations. The problem remains that most organizations failed to consider employees’ needs or get them involved in initiatives that can adequately motivate and keep them service-focused. Given that each employee has a motive for working, once these desires are not fully met; there are negative consequences on effort, commitment and performance. Hence, this work explores the empirical link between motivation and organizational productivity which is crucial to the attainment of organizational objectives (Steers, 2008). Given that each employee has a motive for joining a given organization and once these desires or goals are not fully met, it has negative effect on employees’ performance at work.

Most organization often fails to integrate the welfare policy of their staff in the overall objectives or plan of the organization. The level of motivation in Nigeria exposes to its totality the cause of the low performance and inefficiency that characterized the whole system. Workers in most organization had not be accorded adequate regard in term of remuneration, welfare package, job security, good working environment, staff training and development recognition among others. Motivation of workers in Nigeria’s public/private organizations is seen as a luxury affair.

Private organization in Nigeria focus primarily in structure and recruitment without acknowledging that a worker may be immensely capable of doing some work; nothing can be achieved if he is not willing to work. This is in line with the view of Okoli (2004:19) that organizations in Nigeria are seeing as organization without people. Obviously, effectiveness of organization revolves on employees that operate it. In our contemporary society, the degree to which organizational stated objectives are being realized depends on the workers disposition, if other factors are in place. It is also alleged that the management in most organisation has failed to relate the salary of workers with the cost of living in the present high level of inflation.

The salary of many private workers cannot satisfy their physiological needs. The whole issue is characterized by much work low pay. In situation like this, the dispositions of workers toward their job are crippled resulting to the low productivity. Apart from poor salary, the other working conditions such as leave allowance, job security, rewarding system are not encouraging. Evidence also abound that workers are not being rewarded for extra performance and overtime and this to a large extent demotivates the workers for higher performance.

Objectives of the study

The general objective of the present study is to examine the relationship between employee motivation and organizational productivity while specific objectives are:

  1. To identify the relationship between staff salary, welfare package and organizational productivity.        
  2. To examine if staff training and development act as a tool for motivating workers for maximum organizational productivity.
  3. To examine the relationship between organizational environment and workers productivity.
  4. To examine the relationship between workers’ involvement in management decision making and organizational productivity.

Literature review

Concept of Organizational Productivity

Productivity is concerned with the ratio of output to inputs. Palik (2018) considers productivity as a measure of output to a measure of some or all of the resources used to produce this output. Again, the definition raises fundamental issues.  Productivity is usually expressed in terms of the ratio.  Productivity is the quantitative relationship between what we produce and the resources used. Furthermore, the diversity of some of the factor inputs and output could derive different measures of productivity.

Concept of Motivation

Unlike the orthodox and human relations models of motivation, the contemporary views focus on a number of factors that may affect motivation as well as enhance productivity.  Vann (2021) believes that motivation is central to high productivity.  High-ranking managers and managerial personnel must be the channel for leading productivity which means they must motivate their personnel to excel at higher levels of excellence. Motivation is by far the number one catalyst for achieving success professionally or personally. The most valuable assets whether business or non-business is knowledge of workers and productivity. 

James (2015) viewed motivation as the means used to influence positively the performance of workers in their assigned responsibility in a given environment and time. Though different organizations apply different means to motivate staff, the methods generally fall into some known catch words like morale, welfare, and recreation (MWR), rewards, good postings and promotion, among others. Moorhead and Griffin (2001) asserted that increased motivation means increasing performance of the workers and organizations. Gene and Manab (2006) explained further that,

“Motivation is the most difficult factor to manage. If an employee lacks the ability to perform, he can be sent to training programs to learn new job skills. If the person cannot learn them, he can be transferred to a simpler job and replaced with a more skilled worker. If an employee lacks materials, resources, or equipment, the manager can take steps to provide them. But if motivation is deficient, the manager faces the more complex situation of determining what will motivate the employee to work harder”.

Base on principles of organization and management, Burns and Stalker (2009) propose 2 basic ways in which managers can motivate their staff to achieve productivity.  They consider the use of mechanistic or an organistic structure. A mechanistic structure typically rests on Theory X assumption; while organistic structure depends on Theory Y.  Theory X sees an individual as lazy, uncreative and in need of constant prodding. On the other hand, theory Y views the individual as having a great deal of potential. For instance, when the environment surrounding an organization is stable, managers tend to choose a mechanistic structure in order to achieve a predictable level of productivity.  In a mechanistic structure, authority is centralized at the top of the managerial hierarchy, and the vertical hierarchy of authority is the main means to control subordinates behaviour to achieve productivity.  In contrast, when the environment is changing rapidly, it is difficult to obtain access to resources, thus, managers revert to organic structure.  In an organic structure, authority is decentralized to middle and first-line managers to take full responsibility to enhance motivation and productivity (Burns and Stalker, 2009).

Catherine (2018) describe the relationship between motivation and productivity when she states that actual productivity is likely to be a function of ability, motivation and environment conditions. She asserts that it is significant to employ a person with ability to do what is required.  Correspondingly, a well-motivated labour force would increase its productivity capacity which would in turn lead to more output.

Mcshane and Mary (2020) observed that some organizations set targets that are challenging enough to stretch the employees’ capability and motivation to achieve the highest productivity. They explained that higher productivity are achievable if employees are given the necessary resources to accomplish the goals, and provided, workers do not become too overstressed in the course. In the case of Sibson, they argued that performance of an employee is the multiplicative function of ability and motivation. Mayer and Salovey (2018) believes that a highly motivated person, with requisite abilities and understanding of the job, is likely to attain high productivity than a demotivated person. They concluded that, an increase in motivation is likely to influence productivity; while a decrease would impact negatively on productivity. Similarly, a well-motivated labour force would likely increase effort to achieve high productivity.

Methodology

The population of the study is made up of 300 participants who have worked in different manufacturing entities in Abuja for not less than five years. More so, questionnaire was administered to obtain data from the respondents while a simple random sampling technique was used in the selection of the respondents. The statistical package for social sciences (SPSS version 25) and bar charts were employed for data analysis.

Analysis

A total of 300 copies of questionnaire were administered out of which 269 copies were returned. This represents 89.6% response rate.

Relationship between staff salary, welfare package, and organizational productivity

The first specific research objective posed by this study was to determine the relationship between staff salary, welfare package and organizational productivity. In Figure 1, an overwhelming majority of the sampled population which is 75.1% (representing 202 respondents) answered in the affirmative, that indeed there is a positive relationship between staff salary, welfare package and organizational productivity.

Figure 1

Relationship Between Staff Salary, Welfare Package and Staff Productivity.

Source: Questionnaire administered (2026).

Staff training and development as a tool for inducing increased productivity in organizations

The second specific research objective posed by this study was to examine the influence of staff training and development on organizational productivity.  Figure 2 reflects the views of the respondents.

Figure 2

Staff Training and Development as a Tool for Inducing Increased Organizational

Productivity.

Source: Questionnaire administered (2026).

In Figure 2, respondents were asked to rate the extent to which staff training and development enhances productivity in organizations. About 60.5% of the respondents (representing 163 respondents) rated the extent to which staff training and development enhances productivity in organizations as to a limited extent.

Table 1

Organizational Environment and Organizational Productivity.

RespondentsFrequencyPercentage
Strongly Agree7327.1
Agree12245.4
Strongly Disagree3011.2
Disagree3513.0
I don’t know93.3
Total269100.0

Source: Questionnaire administered (2026).

The study sought the opinion of respondents on whether there is a relationship between organizational environment and organizational productivity. From the analysis in Table 1, an overwhelming majority of respondents (45.4% representing 122 respondents) agreed that there is a positive relationship between organizational environment and organizational productivity.

The fourth research objective sought to examine the relationship between workers’ involvement in management decision making organizational productivity.  Figure 3 illustrates the responses.

Figure 3           

Involvement of Workers in Management Decision Making and Its Effect on

Employees’ Productivity.

Source: Questionnaire administered (2026).

As shown in Figure 3, an overwhelming 87.7% (representing 236 respondents) answered yes to the question. This implies that most of the sampled population agreed with the assertion that the involvement of workers in management decision making could improve organizational productivity.

Hypothesis Testing

There is no relationship between employee motivation and organizational productivity

Test Statistics
  
Chi-Square43.311a
df4
Asymp. Sig..003
a. 0 cells (0.0%) have expected frequencies less than 5. The minimum expected cell frequency is 26.3.

Conclusion: Since p–value (0.003) < 0.05, we reject the null hypothesis and hence conclude that there is a significant and positive relationship between employee motivation and organizational productivity.

Findings

The study found that a relationship exists between motivation and organizational productivity. Scholars are of the view that a highly motivated person with requisite abilities is more likely to attain high productivity than a demotivated person. When organizations offer incentives to employees, the employees will reciprocate by increasing their productivity. Increased in employee’s productivity will invariably increase the rate of organizational productivity.

Similarly, the present study’s results indicate a positive relationship between salary, wages, incentives and organizational productivity. Empirically, some scholars disagreed that money is not a motivator while others shared a different opinion. No matter the side one belongs, money is a motivator in the present Nigeria due to high inflation rate and poor living conditions facing the Nigerian workers. Therefore, the present result is not surprising, once employees are well-motivated through enhanced salary, wages and fringe benefits; their productivity level may be increased and this may affect the overall organizational productivity.

Further, the study found out that an increase in motivation is likely to influence organizational productivity especially when the employees are involved in decision-making. This result implies that when employees are involved in decision-making, they tend to show support towards its implementation. When decisions are fully implemented by all stakeholders, there is a likelihood that organizational productivity may be enhanced.

Also, statistical result demonstrates that a positive relationship exists between employee training and organizational productivity. This result means that a well-trained employee may reduce wastages and reduce idle time thereby leading to increased organizational productivity.  

Conclusion and recommendations

Overall, the present study has demonstrated that improved organizational productivity is a function of employees’ motivation in the work place. This result agrees with the existing findings on the same subject matter. Hence, the researcher concludes that offering of motivational incentives via employee training, adequate salary and wages, employees’ involvement in decision making, other financial and non-financial incentives are requisites for enhanced organizational performance.   

Based on the findings of the present study and conclusion thereof, the researcher recommends that there is a need to review welfare policies regularly in manufacturing organizations to reflect the personnel needs in line with the current economic realities in Nigeria.

Secondly, managements of manufacturing organizations are advised to introduce merit incentive system such as pay for knowledge and performance-based bonus as rewards for personnel that distinguish themselves in various aspect of manufacturing.

References

Accel, T. (2018). Employee motivation: The organizational environment and productivity. Internet: http://www.accel-team.com/motivation/index.html, 11 April 2026.

Adi, D.Y.  (2020) Motivation as a means of effective staff productivity in the public sector: A case study of Nigerian Immigration Service, Borno State of Nigeria.

Agbecha, T.T. (2017). Motivation as a tool for increased productivity: A case study of the Nigerian Air Force. NWC, Project Abuja, p. 36.

Amusu, B.O (2020). Improving operational efficiency of the NN Fleet: The human factor. Research Project submitted in partial fulfilment for the award of the Fellow of the NWC, Nigeria.

Armstrong, L. (2016). Management: Building competitive advantage. New York, NY; McGraw-Hill Companies Inc.

Banjoko, S. (2008). Production and operations management. Ibadan: Wisdom Publisher Ltd.

Bateman, S. (2000). Management: Building competitive advantage. New York, NY: Mc-Graw-Hill Company Inc.

Berelson, B. & Steiner, G. (2004). Human behaviour: An inventory of scientific findings. New York, NY: Harcourt, Brece and Word Inc.

Burns, K. & Stalker, T. (2009). Contemporary management. Boston: McGraw-Hill

Campbell, J.P. & Pritchard, R.D. (1976). Motivation theory in industrial and organizational psychology, in Dunnette, M.D. [ed.] Handbook of Industrial and Organizational Psychology, Chicago: Rand McNally.

Huber, B. (2018). Define motivation. Campus.digication.com/English9/11, accessed on April 6, 2026.

James, HD. (2015). Fundamentals of management. Chicago: Richard D. Irwin Inc.

Jain, K.C. & Aggarwal, L.N. (2002) Production planning, control and industrial management. New Delhi: Khanna Publishers.

Koontz, H.C, O’Donnel, J.N. & Weihrich, H. (2009). Management. London: McGraw Hill International Book Company.

Koontz, B. & Steiner, G. (2004). Human relations and management of behavioural values. New York: Harcourt, Brece and Word Inc.

Lingtead, S. (2014). Management and organization. New York: Palgrave Macmillan.

Lloydm, L.B. (2000). Human resource management.New York: McGraw-Hill.

Mayer, A. & Salovey, C. (2018). The business case for emotional intelligence. Internet: http://eperformance.com/pdf/EQ-Business-case.pdf, Accessed on April 10, 2026.

McShane, SL. & Mary, AV. (2020). Organizational behaviour. Boston:McGraw-Hill.

Milkovich, G.T.(2010). Human resources management.Boston, Massachusetts: Irwin McGraw Hill.

MoorHead, G. & Griffin, R.W. (2020). Managing people and organizations: Organizational behaviour. Delhi: A.I.I.B.S Publishers and Distributors.

Olawumi, O. (2018). Performance appraisal and career planning for Nigerian Navy Officers: An assessment. Research Project submitted in partial fulfilment for the award of the Fellow of the NWC, Nigeria.

Okoli B. (2004). Management: Building competitive advantage. Boston: McGraw-Hill Inc.    

Palik, J (2018). Productivity: Definition and components of productivity. Available at: http//www.accel-team.com/productivity/addedvalue-01.html, accessed on April 6, 2026.

Pinder, C.C. (2018). Work motivation in organizational behaviour (2nd ed.). New York: Psychology Press.

Porter, L. (2002). Job attitudes in management: Perceived deficiencies in need fulfilment as a function of job level. Journal of Applied Psychology, 48(6), 15-32.

Reider, R. (2011). Improving the economy, efficiency and effectiveness of not-for-profits. New York: John Wiley and Sons Inc.

Steers, R. (2008). Managing effective organization: An introduction. Boston: Kent publishing company.

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Uzodima, H.O. (2002). Management and alternate explanation of Herzberg’s Motivator -Hygiene results. Journal of Applied Psychology, 56(2), 14-28.

Vann, P. (2021). Motivation is the key to success. Internet: (http://www.paullawrencevann.coml), accessed on April 13, 2026.

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Daily writing prompt
What is the meaning of life?

Effect of Training and Development on Employee Job Performance in Industrial Training Fund

Citation

Ibrahim, M., & Ifeoluwa, F. O. (2026). Effect of Training and Development on Employee Job Performance in Industrial Training Fund. International Journal of Research, 13(4), 305–319. https://doi.org/10.26643/ijr/edupub/25

Musa Ibrahim1 & Fashagba Olamide Ifeoluwa1

1Department of Business Administration and Management, Federal Polytechnic, Bida

musafedpolybida@gmail.com

ifemide1977@gmail.com

Abstract

This research explores the effect of training and development on employee job performance within the Industrial Training Fund (ITF). The population of the study is one hundred and fifty workers (150). Self-administered questionnaire was used for data collection. One hundred and thirty-eight workers filled and returned the questionnaires representing 92% of the administered questionnaires. The data obtained from the questionnaires were analyzed using descriptive statistics such as frequency counts, mean scores and percentages. The research explores how different forms of training and development-such as on-the-job training, workshops, professional courses and capacity-building programs-contribute to improved skills, productivity, work quality and overall job performance among ITF employees. Findings indicate that continuous training enhances employee competence, adaptability, and commitment to organisational goals. Findings further indicate that effective training programmes, when aligned with organizational needs and supported by adequate resources will significantly boost employee performance and organizational effectiveness. The study concludes that sustained investment in training and development is essential for ITF to achieve its mandate of workforce development in Nigeria. Recommendations are provided to strengthen training policies, improve evaluation mechanisms and promote a culture of continuous learning within the organisation.

Keywords: Training and development, employee job performance, on-the-job training, work quality and workforce development.

Introduction

Training in Nigeria could be traced back to 1960 due to the fact that most of the top government and business positions were occupied by whites (Olalere & Adesoji, 2013). The mass exodus of the expatriates after the independence created a vacuum of indigenous human capital. This led to the creation of the Manpower Board in 1962 by the government in power then, following recommendations by the Ashby Commissions. Thereafter, the Federal Government of Nigeria established organizations like Centre for Management Development (CMD), Administrative Staff College of Nigeria (ASCON), Industrial Training Fund (ITF) and Federal Training Centre to cater to the training needs of employees and to also conduct orientation programs for fresh graduates of Nigerian tertiary institutions.

Training and development have become essential pillars for organizational success in both public and private sectors. In a rapidly changing global environment, organizations depend on a skilled knowledgeable, and adaptable workforce to achieve strategic objectives and maintain competitive advantage (Armstrong, 2019; Dessler, 2020; Barney, 1991). Employee performance which encompasses productivity, quality of work, efficiency, and overall contribution to organizational goals, is largely influenced by the level of training and development opportunities available to employees.

In Nigeria, the Industrial Training Fund (ITF) plays a central role in developing manpower for various sectors of the economy. Established in 1971, the ITF has been mandated to promote and encourage the acquisition of industrial skills necessary for national economic development. Over the years, ITF has implemented numerous training programs, capacity-building workshops, technical skills development schemes, and managerial development initiatives aimed at enhancing employee competencies within the organization as well as across industries.

Despite these initiatives, questions still arise regarding the effectiveness of training and development efforts within ITF, particularly in relation to employee job performance. As organizational responsibilities expand, and the demand for high service delivery increases, ensuring that ITF employees possess updated skills and knowledge becomes critical. This study therefore examines the extent to which training and development influence employees’ job performance within the Industrial Training Fund.

Every organization dreams of training and developing its manpower. The reason being that training and development gives employees a sense belonging. It enhances the professional and career development and the skill of the employees. It also ensures lesser mistakes while carrying out assignments and ensures Total Quality Management (TQM) (Armstrong, M. 2019).

Organizations invest significant resources in training and development with the expectation of improved employee performance. However, in many public sector organizations like the ITF, there are concerns about whether such investments yield measurable outcomes. Issues such as inadequate training needs assessment, limited funding, poor implementation strategies, lack of follow-up evaluations and mismatch between training content and job roles have raised doubts about the effectiveness of training programs.

Furthermore, some employees may not fully apply acquired skills due to organizational constraints, insufficient motivation and lack of supportive work environments (Noe, 2017). This study seeks to investigate the effects of training and development on employee job performance within the Industrial Training Fund. The investigation covers ITF headquarters and selected Area Offices where training activities are prominent. The study examines training programs, development initiatives, delivery methods and employee performance indicators. The findings of this study will help ITF evaluate the effectiveness of its training and development initiatives, identifying strengths and gaps that require improvements. The study highlights the importance of training in enhancing skills, job satisfaction and career growth. It also provides insight that can guide the formulation and review of training policies within public sector organizations. It will contribute to existing literature on training, development, and employee performance.

The objectives of the study are:

  1. To determine the relationship between training programs and employee job performance in ITF.
  2. To assess the extent to which development initiatives influence employees’ skills and productivity.

      This study seeks to answer the following questions:

  1. What is the relationship between training programmes and employee job performance in ITF?
  2. How do development initiatives contribute to improvement in employees’ skills and productivity?

     Research Hypotheses

     Hypothesis One

     H0: There is no significant relationship between training programs and employee job            performance in ITF.

     H1: There is a significant relationship between training programs and employee job performance in ITF.

     Hypothesis Two

     H0: Development initiatives do not significantly improve employees’ skills and productivity in ITF.

     H1: Development initiatives significantly improve employees’ skills and productivity in ITF.

Review of existing literature

This section reviews existing literature related to training, development, and performance, empirical studies, and gaps in the literature. The purpose of this review is to establish a foundation for understanding how training and development influence job performance within the Industrial Training Fund.

 Conceptual Review

Concept of Training

Training refers to the systematic efforts made by organizations to provide employees with knowledge, skills, and abilities (KSA) needed to perform their current jobs effectively Noe, (2017). Training focuses on improving employees’ capabilities in order to enhance individual and organizational performance. According to Armstrong (2014), training is a planned intervention aimed at improving job behaviour. It equips employees with technical, managerial, and interpersonal competencies required for efficiency.

Similarly, Dessler (2020) defines training as the process of teaching employees the basic skills they need to perform their jobs, emphasizing that effective training leads to improved productivity, quality of work, and reduced operational errors.

Training helps employees cope with technological advancements and evolving job demands, thereby increasing organizational competitiveness.

In the public sector, effective training is particularly important due to increasing service delivery expectations and accountability. Studies have shown that employees who receive regular and relevant training demonstrate higher levels of efficiency, confidence, and job satisfaction compared to those who do not.

Concept of Development

Development involves long-term educational processes that prepare employees for future responsibilities. Development refers to a long-term continuous process aimed at enhancing employees’ overall growth, capabilities, and potential beyond their immediate job requirements. Unlike training, which focuses on improving performance in current job roles, development prepares employees for future responsibilities, higher-level positions, and broader organizational challenges (Armstrong, 2014; Noe, 2017).

According to Noe (2017), employee development involves formal education, job experiences, relationships, and assessments that help employees acquire competencies needed for future career roles. Similarly, McShane and Von Glinow (2018) describe development as a process that strengthens employees’ cognitive abilities, leadership capacity, decision-making skills, and adaptability in a dynamic work environment. This underscores the strategic importance of development in ensuring organizational sustainability and continuity.

Dessler (2020) emphasizes that development initiatives, such as mentoring, coaching, succession planning, and leadership development programmes, are essential for building managerial and professional competencies. These initiatives not only enhance employees’ career progression but also increase commitment, motivation, and organizational effectiveness. Development equips employees with transferable skills, critical thinking abilities, and problem-solving competencies that enable them to respond effectively to changing organizational and environmental demands.

In the public sector context, development is particularly critical due to increasing demands for efficiency, accountability, and service quality. Well-developed employees are more likely to exhibit higher job performance, leadership effectiveness, and commitment to organizational goals.

In this study, development is conceptualized as a deliberate and ongoing process through which the Industrial Training Fund (ITF) enhances employees’ long-term professional growth, leadership capacity, and career progression. Development activities considered in this study include:

Career development programmes, leadership and management development, mentoring and coaching, job rotation and enrichment and professional and academic development.

Development is measured in terms of career growth opportunities, leadership skill enhancement, learning opportunities, management support, and preparedness for future responsibilities, and how these influence employee job performance at the Industrial Training Fund.

Concept of Employee Job Performance

Employee job performance refers to the degree to which workers accomplish assigned tasks in line with organizational standards. Performance indicators include productivity, work quality, punctuality, teamwork, innovation, and overall contribution to organizational goals. Organizations expect improved performance as an outcome of effective training and development.

Employee job performance refers to the extent to which an employee effectively carries out assigned duties and responsibilities in accordance with organisational standards and objectives. It reflects the level of efficiency, effectiveness, and quality with which employees execute job-related tasks. Job performance is a critical determinant of organizational success, as it directly influences productivity, service delivery, and goal attainment. Similarly, Armstrong (2014) defines employee performance as the accomplishment of work tasks on line with established performance standards, highlighting the importance of competence, effort, and commitment. Task performance refers to how well employees perform core job duties, while contextual performance involves extra-role behaviors such as cooperation, commitment, and willingness to support organizational objectives. Adaptive performance reflects employees’ ability to adjust to changes in job roles, technology, and work environments.

In the public sector context, employee job performance is particularly important due to increasing expectations for efficiency, accountability, and service quality. Koopmans et al. (2011) argue that employee performance in public organizations should be assessed not only by output but also by quality, timeliness, compliance with procedures, and service orientation. High-performing employees are more likely to demonstrate professionalism, responsibility, and dedication to public service goals.

Empirical studies have consistently shown that employee job performance is strongly influenced by human resource practices such as training and development. Aguinis (2019) asserts that employees who possess relevant knowledge, skills, and abilities are better equipped to perform their jobs effectively and meet organizational expectations. This highlights the importance of investing in training and development as strategic tools for improving employee performance.

In this study, employee job performance is conceptualized as the degree to which employees of the Industrial Training Fund (ITF) efficiently and effectively perform their assigned duties in line with organizational objectives. Employee job performance in this study is assessed based on the following dimensions: quality of work output, productivity and efficiency, timeliness in task completion, compliance with organizational procedures, adaptability and problem-solving ability and commitment and teamwork.

Relationship between training, development, and employee job performance

Several empirical studies have examined the relationship between training, development, and employee job performance across different organizational contexts. The consensus in the literature indicates that training and development are critical human resource practices that significantly influence employees’ job performance, productivity, and organizational effectiveness.

Training and employee job performance

Training has been widely recognized as a key determinant of employee job performance. A seminal study by Ngozika and Amah (2024) established that effective training enhances employees’ knowledge and skills, which positively influence job performance when transferred to the workplace. Their findings highlighted that employees who receive relevant training demonstrate improved task efficiency, reduced errors, and higher quality work output.

Similarly, Noe (2017) reported that training enhances employees’ ability to perform job-related tasks effectively, especially when training content aligns with job requirements. Tandipayuk, Zakaria, and Mulyanti (2024) found that training significantly improved employees’ job performance by increasing self-efficacy and motivation.

Development and employee job performance

Employee development has also been shown to have a strong relationship with job performance, particularly in the long-term McDowall and Saunders (2010) observed that development initiatives such as coaching, mentoring, and career development programmes improve employees’ leadership skills, adaptability, and problem-solving abilities, which translate into higher job performance. A study by Day, Fleenor, Atwater, Sturm, and McKee (2014) found that leadership development programmes significantly enhance employees’ performance by strengthening managerial competencies and decision-making abilities.

In the public sector context, Aguinis (2019) reported that employee development practices positively influence performance by increasing employees’ commitment, confidence, and readiness for higher responsibilities. Development programmes were found to reduce performance gaps and improve service delivery quality.

Combined effect of training and development on employee job performance

Studies that examine training and development jointly suggest a stronger impact on employee job performance.

Owoyemi, Elegbede, and Gbajumo-Sheriff (2011) found that organizations that invest in both training and development experience higher employee performance and organizational growth compared to those that focus on training alone. Their study concluded that while training improves current job performance, development ensures long-term performance sustainability.

Similarly, Elnaga and Imran (2013) found that training and development significantly influence employee performance by enhancing employees’ competencies, motivation, and job satisfaction. Their study emphasized that training improves immediate performance, while development fosters continuous performance improvement.   

Theoretical Framework

Human Capital Theory

Human capital theory, proposed by Becker (1964), posits that investments in people through education, training, and skill development-lead to increased productivity and organizational output. The theory states that human capital refers to skills, knowledge, and abilities that individuals possess, which can be developed and improved through investments in education, training, and development. The theory suggests that training is not a cost but a strategic investment that yields long-term returns in the form of improved employee performance.

The Human Capital Theory concludes that employees’ knowledge, skills, and abilities constitute valuable organizational assets that can be developed through conscious investment in training and development. This theory posits that there is a direct link between training, development, and employee job performance. In the context of this study, training and development programmes implemented by the Industrial Training Fund are regarded as investments aimed at enhancing employees’ competencies, technical skills, and professional capabilities. When ITF invests in training programmes such as workshops, seminars, skills acquisition, and career development sessions, employees acquire improved knowledge and skills that enable them perform their job roles more effectively.

Social Learning Theory

The Social learning theory, advanced by Bandura (1977), explains learning as a process that occurs through observation, imitation, and interaction with others. This theory posits that individuals acquire new skills and behaviors by observing role models, supervisors, and peers within the work environment. Training and development activities such as on-the-job training, mentoring, coaching, and workshops provide opportunities for employees to learn through observation and practice. Employees in the ITF can improve their job performance by modelling best practices demonstrated during facilitations and training sessions and by experienced colleagues. The theory also highlights the importance of a supportive work environment in ensuring the effective application of acquired skills.

Together, the Human Capital Theory and Social Learning Theory provide a detailed explanation of the relationship between training, development and employee job performance in this study. Human capital theory explains why organizations should invest in training and development to enhance performance, the social learning theory explains how employees acquire and apply training.  

Empirical Review

Several empirical studies have established a strong relationship between training and employee job performance. Training equips employees with job-relevant knowledge, skills, and abilities, thereby improving their efficiency and effectiveness.

Saiful, Ratnaningsih, and Suratini (2024) conducted one of the earliest empirical studies on training transfer and found that employees who received structured training demonstrated improved job performance, provided the work environment supported the application of acquired skills. Their study emphasized that training effectiveness depends on training design, trainee characteristics, and organizational support.

Siswanto (2024). In a comprehensive empirical review across multiple sectors, found that training positively influences employee performance, job satisfaction, and motivation. Their findings showed that trained employees perform tasks more accurately, adapt better to changes, and contribute more effectively to organizational goals.

In a study conducted in Pakistan, Elnaga and Imran (2013) examined the effect of training on employee performance and found a significant positive relationship between training programmes and employee productivity. The study concluded that employees who receive continuous training perform better than those who do not.

Employee development has been linked to long-term improvements in job performance, leadership effectiveness and adaptability. McDowall and Saunders (2010) studied managers; perceptions of employee training and development in the United Kingdom and found that development initiatives such as coaching, mentoring, and career planning significantly enhance employee performance and leadership capacity. The study emphasized that development prepares employees for future responsibilities. Day et al. (2014) empirically examined leadership development programmes and found that employees who participated in development initiatives demonstrated improved decision-making, problem-solving skills, and job performance. The study concluded that development has a sustained impact on performance compared to short-term training.

In the Nigerian context, Akinwale, Ababtain. And Alaraifi (2019) examined human resource development practices and employee performance in public organizations and found that employee development significantly predicts job performance and organizational commitment. Similarly. Owoyemi, Elegbede, and Gbajumo-Sheriff (2011) found that organizations that invest in employee development experienced improved performance, reduced turnover, and better organizational growth.

Some studies have also examined training and development jointly and found that their combined effect on employee job performance is stronger than when considered independently. Ahmed, Alasso, & Mohamud (2025) based on Human capital theory, demonstrated that organizations that invest in both training and development achieve higher productivity and performance.

In a Nigerian public sector study, Adeniji, Osibanjo, and Abiodun (2013) examined training and development practices and found a significant positive effect on employee job performance and service delivery. The study concluded that organizations integrate training and development into their HR strategy achieve better performance outcomes

Methodology

This describes the research design, population of the study, sample size and sampling technique, sources of data collection, research instrument, validity and reliability of the instrument, method of data collection, and method of data analysis. The aim is to provide a clear and systematic framework through which the study was conducted.

This study adopts a descriptive survey design. This design is suitable because it allows the researcher to collect data from a large group of respondents, analyse responses, and draw conclusions about the effects of training and development on employee job performance within the Industrial Training Fund (ITF). The descriptive survey method is also appropriate for studies that involve attitudes, opinions, and perceptions of employees on organizational practices.

The population of the study comprises all employees of the Industrial Training Fund (ITF). This includes employees at the Headquarters and selected Area Offices. The total population includes staff members across various departments such as Administration and Human Resource, Finance and Accounts, Revenue, Internal Audit, Training, Procurement, Special Duties and Servicom and Anti-Corruption.

Given the large population of ITF employees, a representative sample was selected for the study. A sample size between 100 and 150 respondents is considered adequate to ensure accurate representation. The sample size is determined using the Yamane formula where appropriate, A stratified random sampling technique was adopted. Employees were grouped into strata based on their departments, and respondents were selected randomly from each stratum to ensure balanced representation across the organization.

The study relied basically on primary data, supplemented by secondary data. Primary data were collected using a well-structured questionnaire administered to ITF employees, the questionnaire sought information on training programs, development initiatives, employee perceptions, and job performance indicators. Secondary data were sourced from:

ITF training manuals

ITF annual reports

Journals and textbooks

Previous research studies

Academic publications related to training, development, and employee performance.

These sources provided theoretical and empirical support for the study.

The main instrument for data collection was the questionnaire. The questionnaire was divided into four sections namely:

Section A: Demographic information

Section B: Training programs in ITF

Section C: Development initiatives

Section D: Employee job performance

A pilot test was conducted using 10 employees from a nearby Area Office. The responses were analysed using Cronbach’s Alpha to determine internal consistency. A reliability coefficient of 0.70 or above was considered acceptable, indicating that the instrument was reliable.

The collected data were analyzed using both descriptive and inferential statistics. Descriptive statistics included frequency tables, percentages, and mean scores to summarize demographic data and responses to questionnaire items while inferential statistics involved the use of correlation analysis, regression analysis and statistical package for the social sciences (SPSS).

Correlation analysis was used to determine the relationship between training and employee performance. Regression analysis was used to test hypothesis regarding the effects of development initiatives, while the statistical package for the social sciences (SPSS) was used for coding, analysis and interpretation of data

This section provided a detailed explanation of the methodology adopted for the study. It described the research design, validity and reliability measures, and data analysis methods.

This section provided a detailed explanation of the methodology adopted for the study. It described the research design, population, sampling techniques, data sources, instrument design, population, sampling techniques, data sources, instrument design, validity and reliability measures, and data analysis methods.

Analysis of responses on research variables

Table 4.1: Descriptive Analysis of Training Programmes in ITF (N=138)

ItemsSAADSDMeanStd. Dev
ITF organizes regular training programmes for employees58 (42%)54 (39%)18 (13%)8(6%)3.170.89
Training programmes are relevant to my job responsibilities61(44%)49(36%)20(14%)8(6%)3.180.91
Training improves my technical and professional skills64 (46%)50(36%)16(12%)8(6%)3.220.88
Training enhances my efficiency and effectiveness at work59(43%)55(40%)16(12%)8(6%)3.190.87
Training programmes meet organizational performance goals52(38%)56(41%)22(16%)8(6%)3.100.92

Decision Rule: Mean≥2.50 = Accepted

Grand Mean: 3.17

Source: Field Survey, 2025

Interpretation

The grand mean of 3.17 indicates that respondents generally agree that training programmes at ITF are regular, relevant, and positively influence employee skills and efficiency.

Table 4.2: Descriptive Analysis of Development Initiatives and Employee Productivity

ItemsSAADSDMeanStd. Dev.
ITF provides career development opportunities60(43%)50(36%)20(14%)8(6%)3.180.90
Development initiatives enhance long-term productivity63(46%)48(35%)19(14%)8(6%)3.200.88
Development programmes improve my problem-solving ability58(42%)52(38%)20(14%)8(6%)3.150.91
ITF supports continuous learning and professional growth55(40%)56(41%)19(14%)8(6%)3.190.89
Development initiatives motivate employees to perform better62(45%)49(36%)19(14%)8(6%)3.190.89

Decision Rule: mean ≥ 2.50 = Accepted

Grand Mean: 3.17

Source: Field Survey, 2025

Interpretation

The grand mean of 3.17 suggests that development initiatives at ITF significantly enhance employee productivity, motivation, and long-term performance.

Table 4.3 Descriptive Statistics of major variables

VariableNMinimumMaximumMeanStd. Deviation
Training & Development (X)138255038.425.76
Employee Job Performance (Y)138285541.876.14

Interpretation:

The mean score of 38.42 for training and development suggests that employees agree that ITF provides training opportunities. The mean score of 41.87 for job performance indicates high job performance among ITF employees.

Table 4.4 Correlation Matrix

VariablesTraining & developmentEmployee Performance
Training & Development10.782
Employee Performance0.7821

 p-value = 0.000 (p<0.05)

Interpretation:

  • The correlation coefficient (r = 0.782) indicates a strong positive relationship between training and employee performance.
  • This means that when ITF increases training and development initiatives, employee performance also increases.
  • The relationship is statistically significant at 5% level.

Regression Analysis

Model Specification:

Y = a + bX + e

Where:

Y = Employee Job Performance

X = Training & Development

Table 4.5 Model Summary

ModelRR SquareAdjusted R SquareStd. Error
10.7820.6120.6093.83

Interpretation:

R = 0.782 shows a strong relationship.

R2 = 0.612 means that 61.2% of the variation in employee performance is explained by training and development.

Table 4.6 ANOVA

ModelSum of SquaresDfMean SquareFSig
Regression1284.5711284.5787.620.000
Residual814.871365.99  
Total2099.44137   

Interpretation:

  • F (1,136) = 87.62, p + 0.000< 0.05
  • The regression model is statistically significant.
  • This confirms that training and development significantly predict employee performance.

Table 4.7 Regression Coefficients

ModelUnstandardized BStd. ErrorBetat-ValueSig.
Constant12.4311.846.750.000
Training & Development0.7660.0820.7829.360.000

Interpretation:

  • The coefficient of Training & development is 0.766, meaning:

A one-unit increase in training and development activities leads to a 0.766 increase in employee job performance.

  • Since p = 0.000 < 0.05, the effect is statistically significant.

Test of hypotheses

Inferential statistics such as correlation and regression analysis were used to test the hypothesis.

Hypothesis One

H0: There is no significant relationship between training programs and employee job performance in ITF.

H1: There is significant relationship between training programs and employee job performance in ITF.

Result: Correlation analysis revealed a strong, positive relationship between training programs and job performance.

Decision: The null hypothesis is rejected.

Conclusion: Training programs significantly influence employee job performance in ITF.

Hypothesis Two

H0: Development initiatives do not significantly improve employees’ skills and productivity in ITF.

H1: Development initiatives significantly improve employees’ skills and productivity in ITF.

Result: Regression analysis showed that development initiatives accounted for a significant percentage of the variation in employee productivity.

Decision: The null hypothesis is rejected.

Conclusion: Development initiatives significantly improve employees’ skills and productivity.

Decision Rule:

If p-value < 0.05 – Reject H0.

Decision:

p-value = 0.000. therefore:

Reject H0

Accept H1

Discussion of findings

This study examined the effect of training and development on employee job performance at the Industrial Training Fund (ITF). The findings showed a positive and significant relationship between training, development, and employee job performance.

i. The findings of the study revealed that training has a significant positive effect on employee job performance at the ITF. Employees who participated in training programmes reported improved knowledge on the job, enhanced skills, increased efficiency, and minimal errors in the performance of their duties. This suggests that training plays a crucial role in improving employee’ ability to perform their current job schedules effectively.

Noe (2017) reported that training improves task performance by equipping employees with the relevant skills required for executing their schedules effectively

The practical implication of this finding is that institutions like the ITF, should make implementation of training programmes relevant to job schedules a priority. Regular trainings will keep employees abreast of technological innovations and reduce operational inefficiencies to the barest minimum. Management should therefore make it a point of duty to allocate adequate resources to training and development initiatives as a tool for improving employee performance.

The improvement in job performance which is an effect of training shows that training is a valuable investment and not a cost to the ITF. This finding is also in line with the social learning theory in the sense that employees of the ITF acquire and apply the new skills through observation and practice during training programmes.

ii. This study also found that employee development has a significant positive effect on job performance. Development initiatives such as coaching and mentoring, leadership training, and career development workshops were shown to enhance employees’ adaptability, problem-solving abilities, and preparedness for future responsibilities. This indicates that development contributes not only to immediate performance but also to long-term performance sustainability.

This finding is in line with previous studies McDowall and Saunders (2010) reported that employee development improves leadership capabilities and performance outcomes. Day et al. (2014) similarly found that leadership development programmes significantly enhance employees’ performance and decision-making abilities.

The implication of this finding is that organizations should go beyond short-term training and invest in long-term investment initiatives. For ITF, implementing structured career development, succession planning, and mentoring programmes will help build a competent and future compliant workforce. Such initiatives will also improve employee commitment, reduce turnover, and institutional continuity.

The study further revealed that training and development jointly exert a strong and positive influence on the job performance of the employees. Employees who benefitted from both training and development programmes demonstrated better work quality, higher productivity and stronger commitment to organizational goals.

Elnaga and Imran (2013) also reported that training and development significantly improve employee performance by enhancing competencies and motivation.

For ITF, aligning with training programmes with long-term development goals will ensure that employees are not only competent in their current roles but also prepared for future responsibilities.

Recommendations

Based on the findings of this study, which revealed that training and development have significant positive effects on employee job performance at the Industrial Training Fund (ITF), the following recommendations are made in line with the research:

  1. In line with the objective of examining the effect of training on employee job performance, it is recommended that ITF institutionalize regular and structured training programmes based on systematic training needs assessment. Training content should be aligned closely with employees’ schedule of duties, technological trends, and organizational objectives.
  2. Given the study’s finding that development significantly improves employee job performance, ITF should strengthen long-term employee development initiatives such as leadership development, mentoring and coaching, and career progression trainings. Structured career development plans should be implemented to prepare employees for higher responsibilities and future leadership roles.

Suggestions for further research

Although this study provides empirical evidence on the effect of training and development on employee job performance at the Industrial Training Fund (ITF), certain limitations create opportunities for future research. The following suggestions are therefore proposed:

Future studies should extend beyond a single organization by incorporating multiple public and private sector organizations across different regions of Nigeria.

This study adopted a cross-sectional design, which captures perceptions at a single point in time. Future research may employ a longitudinal approach to examine the long-term effects of training and development on employee job performance, career progression, and organizational productivity.

Subsequent studies should integrate other relevant human resource management variables such as employee motivation, job satisfaction, organizational culture, leadership style, and reward systems.

Further research should also examine factors influencing the transfer of training to the workplace, such as managerial support, organizational climate, availability of resources, and employee readiness.

While this study relied primarily on self-reported measures of employee job performance, future research could incorporate objective performance indicators such as productivity metrics, appraisal records, error rates, and service delivery outcomes to strengthen the validity of findings.      

REFERENCES

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Agu, C.N. (2018). Employee motivation and productivity: A study of Nigerian organisations. International Journal of Management Studies, 12(3), 44-56.

Aguinis, H. (2019). Performance Management (4th ed.). Chicago Business Press

Ahmed, N.H., Alasso, M.M., & Mohamud, A.O. (2025). Enhancing organizational productivity through human capital investment: An analysis of training and development impacts on employee performance in East African Organizations.

Akinwale, O.E., Ababtain, A.K., & Alaraifi, A. (2019). Human resource development and performance. Management Science Letters.

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Saiful, et al. (2024). Effect of training transfer factors on employee performance in the Airport Management Office of Mopah Class

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Siswanto, A. (2024). The impact of training, job satisfaction, and organizational commitment on employee performance in the tech industry. Takfir: Interdisciplinary Journal of Islamic Education.

Tandipayuk, M., Zakaria, Z. & Mulyanti, R.Y. (2024). The impact of education and training, self-efficacy on employee performance with workability as an intervening variable. Jurnal Manajemen Bisnis

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Impacts of Consequentialism on Language

Citation

Nnaemedo, B. (2026). Impacts of Consequentialism on Language. International Journal of Research, 13(4), 293–304. https://doi.org/10.26643/ijr/edupub/24

Bartholomew Nnaemedo

Abia State University, Uturu,

Department of Religious Studies/Philosophy

nnaemedo.bartholomew@abiastateuniversity.edu.ng

ORCID: https://orcid.org/0009-0005-2691-7890

Abstract

In their attempts to evaluate human acts, scholars have proposed many theories. One such theory is consequentialism, an ethical framework that emphasises outcomes as the fundamental determinants of the rightness or wrongness of an action. This theory has certain positive values as it helps to sustain human actions, including language. Besides, it has negative values. Thus, this paper examined the influence of consequentialism on language. In particular, it examined its impacts on language use, assessment, and control. Based on Wittgenstein’s language game, Austin’s theory of illocutionary acts, and Waldron’s criticisms of hate speech, this paper argues that, despite its positive linguistic values, consequentialism undermines language, thereby corrupting rather than improving it. Also, this paper used conceptual analysis as its theoretical framework. This mode of analysis decomposed the topic into its components and then used the essential aspects to interpret it. Besides, it relied on the data from extant literature and the author’s intuition to further the analysis. The results showed that though consequentialism has some positive values, it adversely affects language in the area of language use, evaluation, and regulation. Therefore, this paper concluded that framing human action solely in terms of consequentialism poses dangers to language, as issues affecting language use, evaluation, and regulation could lead to language corruption and disfigurement. Subsequently, this paper advocated hybridisation of ethical theories, one that evaluates the nature of an action and its outcome.       

Keywords: Consequentialism; Human Acts; Influence; Language; Outcome

Introduction

From its inception, philosophy has been pivotal in guiding human action. In particular, philosophy has developed many theories not only to critique excesses of human acts but also to guide them along the safest rational path. One way it has maintained this critical posture is through its ethical frameworks. Through them, it has proposed some theoretical frameworks as templates for moral evaluation. Among these moral bulwarks are virtue theory (Plato, 1997; Aristotle, 2009; MacIntyre, 2007), deontological theory (Kant, 2015), utilitarianism (Bentham, 2017; Mill, 2009), hedonism (Aristippus), and consequentialism (Bentham, 2017; Fletcher, 1966). It also includes a host of modern theories, such as psychoanalytic (Freud, 1961), behavioural (Skinner, 1953), cognitive-developmental (Piaget, 1950), the theory of moral judgment (Piaget, 1932), social learning (Bandura, 1977), psychosocial (Erikson, 1950), cognitive moral development (Kohlberg, 1981), Gilligan’s theory of moral development (Galligan, 1982), and sociocultural theories (Vygotsky, 1986). These ethical theories are as important in the preceding era as they are today, if not more so. Especially given that contemporary society is marked by significant scientific and technological development, as evidenced by the emergence of artificial intelligence, digital media, and digital humanity with its attendant netizens, among others. Moreso, given that the thrust of scientific evolution toward a global developmental stage requires a corresponding philosophical intervention. Thus, philosophy must continue to sound an alarm and develop strategies to counter the excesses of human acts even in the contemporary era.

In particular, this paper shines a spotlight on consequentialism, an ethical theory which holds that the goodness or rightness of an act depends on its outcome or consequence. Nonetheless, it is not a critique of consequentialism in general. Instead, it delved into an underexplored area: consequentialism and language. Hence, this paper investigates the implications of consequentialism on language. However, before probing that, it suffices to conceptualise the term ‘consequentialism’.      

Consequentialism

Consequentialism bases an act’s goodness or wrongness on its consequences. It is also known as teleological theory or proportionalism. Therefore, it implies that when the outcome is good and desirable, it is morally right; the reverse is true when it is morally wrong. Nevertheless, it is vital to note that consequentialism dates back to Socrates, as evident in Plato’s dialogue, Republic. Book I of this work contains Plato’s (1997) critique of Thrasymachus’ thesis that might is right, which implies that the end justifies the means; a short way of saying that consequence validates an action. In Book II, Plato also refuted the argument of Glaucon, where Glaucon used the Rings of Gyges to justify that people’s failure to adopt unjust means to achieve a desired end is predicated on the detectability of the means. The implication is that if the means are untraceable, people will surely deploy them to achieve their set goals. Subsequently, justice will be to the advantage of the stronger. In the modern era, consequentialism was promoted by Bentham (2017), who projected and popularised a utilitarian model of consequentialism.     

Joseph Fletcher is also one of the foremost representatives of consequentialism in the modern era, as evidenced by his 1966 work, Situation Ethics (Fletcher, 1966). He dismissed legalism and antinomianism as bases of moral evaluation, as they promote unbending adherence to law and lawlessness, respectively. For instance, he portrayed legalism’s strict fidelity to the principle of fiat justitia ruat caelum (do the right, even if heaven falls). It implies that the spirit of the law takes precedence over its letter. Therefore, he opted for situationism, proposing four principles to support it: pragmatism, relativism, positivism, and personalism. These four principles resonate with workability, rejection of absolute goodness or badness, an empirical approach, and a tendency toward human well-being. So, situationism presents itself as a critique of what it regarded as the legalism of traditional Christian morality. It emphasises that natural law morality anchors moral evaluation in static, unchanging human nature (Nnaemedo, 2023). Nonetheless, situationism poses some challenges, especially regarding altruism. So, from the perspective of the performance of human acts requiring sacrifice, adhering to situationism undermines self-sacrifice, given that situationism emphasises acting in accordance with the prevailing situation. Thus, it excludes taking measures not captured in the situational setting.  

In the contemporary era, Singer’s (2009) speciesism is another concrete attempt to promote utilitarianism, a type of consequentialism, in how we treat animals, aiming to increase their pleasure and reduce their pain. That means the consequences of an action determine whether to perform it. Singer (2019) also advanced a similar utilitarian argument, arguing that ending world poverty requires saving the life of one person, using the example of saving a drowning child to illustrate the concept of effective altruism and the idea of donating 10% of one’s earnings. All these instances aim to advance utilitarianism.

Likewise, Macaskill (2022) advocated utilitarianism through his concept of longtermism, which argued for positively considering future generations in the scheme of things. He sustained that doing so should constitute a fundamental moral precedence of our time. Therefore, Macaskill (2022) maintained that the “future people count, but we rarely count them (n.d.).  Subsequently, he stressed the need to plan and leave a better life package for them. Hence, he insists that “by abandoning the tyranny of the present over the future, we can act as trustees—helping to create a flourishing world for generations to come” (n.d.). What he implied is that the present generation should leave a legacy of fortune to the incoming generation. This legacy is one founded on utilitarianism. 

It is also worth noting that consequentialism is of two types: act and rule consequentialism. The former evaluates moral behaviour by its outcomes or consequences, while the latter judges it by the rule. In other words, for act consequentialism, the rightness or wrongness of an action rests on its outcome or on the consequence. In contrast, rule consequentialism applies the morality of an action to the rule that leads to the desired consequences.

Consequentialism has positive values, as an expected outcome of a human action helps achieve it. Nonetheless, it has some defects. Its primary defect is that it lacks a generally accepted criterion for all moral evaluation, given that contemporary society comprises people of diverse ideologies. Knowing and evaluating the proximate and remote consequences of people’s actions is also challenging.

Basic tenets of consequentialism

The basic assumptions of consequentialism are:

i. It is wrong to impute a moral judgment on an act without considering the actor’s intention and circumstances, as well as the outcome of the act,

ii. Moral judgment is a posteriori: one evaluates an action after its performance, not vice versa, as in the case of deontologists, where it is a priori.

iii. Among two evils, one should choose the lesser evil. Also, between two good opinions, one should choose the better option.

It is crucial to distinguish consequentialism from related theories, such as utilitarianism and deontological theories. Thisdistinctionis necessary for a better insight into consequentialism.

Consequentialism and utilitarianism

People may try to equate consequentialism with utilitarianism. Doing so is erroneous. However, the most probable position to adopt is that utilitarianism is a form of consequentialism. So, while utilitarianism seeks the good in temporal pleasure and happiness, consequentialism, especially the Thomistic version, seeks good in God’s glory and reign as the ultimate end (Peschke, 1996). This end subsequently forms the essential template for moral evaluation.

Consequentialism and deontological theory

It is critical to note that deontological theory and consequentialism are complementary, not contradictory, as both emphasise absolute ends. While deontology holds that moral absolutes provide the basic template for moral evaluation, consequentialism holds that the ultimate end determines moral evaluation. As a result, both constitute complementary templates for moral evaluation, as one cannot make any moral evaluation without considering the nature of the being involved (deontological dimension) and the ultimate end in view (consequentialism). Peschke (1996) validated the above claim by insisting that the two theories are not mutually exclusive but complementary.

Impact of consequentialism on language

Consequentialism affects language; its use, assessment, and control. Discussing them serially provides the necessary insight into the specifics needed for their clearer understanding.

On language usage

Given that consequentialism underscores outcomes as triggers of action, it unarguably impacts language use by answering questions about what language to use, when, where, and how. It means that language transcends mere expressions, but is a phenomenon propelled by an expected outcome. The implication is that man does not just speak, but speaks to achieve a purpose. This purpose is the consequence of his action, which is the primary objective motivating and directing his speech. Consequently, consequentialism influences language use, presenting expected outcomes as the primary driving force behind every moral evaluation. Hence, for any language usage to merit a proper usage tag, it should align with these outcomes, lest it be considered somewhat out of place and unfitting for the purpose.  

The above submissions reflect Austin’s (1962) view that language performs illocutionary acts, such as promising, contracting, negotiating, authorising, and ordering. According to consequentialism, the set of outcomes would be the above-mentioned illocutionary acts. Their accomplishment constitutes the expected outcomes that require a carefully chosen language to achieve.

Likewise, the above consequentialists’ thesis corroborates Searle’s (1995) argument that language fundamentally constitutes institutional reality and justifies its structures, such as money, marriage, governments, and property. The weight of the relationship lies in the fact that the language used to conceptualise these institutional structures is tailored towards achieving the ends of the establishment. So, it is, in a way, consequentialist in orientation, implying that, though its use may have considered other significant factors, the expected outcomes might have played a key role.     

Moreover, the argument supports Habermas’ (1984) theory of communicative action, which conceives of language as the basis of social life, rationality, and democracy. The veracity of the above claim rests against the backdrop that Habermas presented language as a means of communication and of creating and achieving shared understanding, legitimacy, acceptability, social integration and cohesion. One immediately conceives consequentialism throughout the process, as the basic ends achievable through the language delineated above subsequently influence language use. 

Consequentialism is also decipherable in Frege’s (1892) distinction between sense and reference, in that Frege portrayed how reference to a concept may have constant signification but different sense across languages. So, in this discourse on the influence of consequentialism on language use, despite a concept’s signification, its meaning may differ across its usages due to the expected outcome that informs its application in different contexts.   

Likewise, given that context influences the meaning of words, an expected outcome also affects the time, place, and manner of language use. Wittgenstein’s (1953) language game sheds further light on the above submission, underscoring that reality is socially constructed, as “to imagine a language means to imagine a form of life” (P1, 19). So, consequent on its outcome-driven approach, consequentialism shapes the nature of language use, since not all languages yield the same results. To achieve an expected result, certain languages are chosen over others.

On language evaluation

As an ethical framework, consequentialism affects language use assessment, as the outcome determines word choice. Thus, words are judged based on their position on the expected result. Where their use aligns with the predictable outcome, they are judged acceptable; otherwise, they are rejected. It is in tandem with the evaluative implications of language consequent on the resort to consequentialism that inform the categorisation of certain expressions as hate speech and so inconsistent with societal harmony. For example, Waldron (2012) extensively discussed hate speech, describing it as undermining people’s sense of assurance, social standing, and dignity, thereby impeding their confident coexistence in society. So, following consequentialism, which emphasises outcomes as a criterion for the acceptability or non-acceptability of a given outcome, the language used in a given action is judged according to its fidelity to or deviation from the intended result.

Given that the above evaluation is result-focused, there is a tendency to ignore other basic facts about the language use. Such neglect may lead to undue compromise and a forced tilting of words to serve a designated purpose, resulting in linguistic confusion, denigration, and corruption. This language corruption is apparent in contemporary society, where certain words are now coded with meanings that are a sharp departure from their original meanings. At times, they are presented in a way that malforms rather than improves people’s knowledge. At other times, they are portrayed in ways that refine how a word has been used. A typical instance of such expression is the use of the term ‘goat’ to represent the greatest of all time in the football world.

On language regulation

The thirst to achieve a desired objective can also lead to alignment of language with the expected outcome. Hence, consequentialism also plays a role in regulating language use. This role is predicated on the objective at issue. In this case what guides a language use is not the nature of the language, its semantic and syntactic coloration, but rather its amenability to result in view. So, the fulcrum around which language use revolves is the outcome expected throughout the process. So, given its result-oriented nature, consequentialism is one of the theories that promote and sustain language regulation. This is evident in Barendt’s (2019) discourse on Waldron’s (2012) notion of hate speech. In this discourse, Barendt noted ambiguity in Waldron’s view of the nature of hate speech, namely, whether it causes or constitutes harm. Nonetheless, he (Barendt) described Waldron as opting for the former, that hate speech tends to cause harm. Subsequently, Barendt considered it a weak form of the consequentialist argument for proscribing hate speech. 

While the above regulation can be productive, there is also the tendency for consequentialism to lead to harmful social phenomena, as the quest for an expected outcome can breed and trigger diverse social ills, such as the unbridled pursuit of wealth, ritual killings, theft, and the like. In the realm of language, the above ills are accompanied by corresponding linguistic corruptions, as evident in the corruption of certain terms to serve economic interests despite their implications for morality. A typical example is the Igbo concept, Igbu ozu (the killing of a corpse), used to describe ascent to the realm of wealth without reference to the morality of the wealth-making involved.

Legally, consequentialism could result in the enactment of rules that threaten people’s fundamental human rights. Of course, the recent anti-hate speech bill, designated as the National Commission for the Prohibition of Hate Speech Bill, sponsored in 2018 by Aliyu Sabi Abdullahi and reintroduced by him in 2019 in the Senate, or the version sponsored by Mohammed Tahir Monguno in the House of Representatives, were typical instances of such (Tijani, 2019; Ayeni, 2020). Another was the Protection from Internet Falsehood and Manipulation and other Related Offences bill sponsored by Senator Mohammed Sani Musa on November 5, 2019 (“#NotToSocialMediaBill,” 2020; Amnesty International, 2019; Ewang, 2019). These bills were opposed by Nigerians at home and in the diaspora (“#NotToSocialMediaBill,” 2020). The critics alleged that the bills would serve harmful purposes, especially by infringing on people’s fundamental human rights, including the right to freedom of speech. In particular, the bill prohibiting hate speech was heavily criticised for proposing a death penalty for core hate speech offenders (Amnesty International, 2019; Santas, 2021). In sum, as the tilt towards the regulations above is outcome-driven, the language deployed in the process would be result-oriented, implying that consequentialism influences language regulation.

Conclusion

Consequentialism, as an ethical framework, stresses outcomes as the basis for acceptance or rejection. Ipso facto, an action is right when it yields an expected result, and it is bad when the contrary is the case. Consequentialism has its strengths and weaknesses. On the positive side, it provides a target and a trigger for action, without which one may lose focus throughout the process. The endpoint of any activity is significant for its realisation, given the embedded force that propels it. Nonetheless, in the adverse domain, consequentialism could engender and precipitate diverse ethical issues, such as an overemphasis on results, often leading to the total neglect of the means used to achieve them. On a serious note, its implications dovetail into the language domain, particularly in language use, evaluation, and regulation. Hence, this paper argues that consequentialism adversely affects language, despite its emphasis on outcomes as incentives for more actions.

From the perspective of language use, consequentialism answers questions about what language to use, when, where, and how. The implication is that it shapes language use, a shaping that could be negative or positive. Nonetheless, in contemporary society, this shaping is mostly negative as it has resulted in many societal ills. Likewise, from the language assessment domain, consequentialism’s emphasis on results provides a reliable litmus test for situational and contextual uses of words. This assessment leads to grouping words into different categories, relying on their association with predictable consequences.

Besides, in the domain of language regulation, consequentialism informs diverse rules governing language control, such as those governing hate speech. Such enactments revolve around making language work towards a set objective, the intrinsic nature of the words used notwithstanding. Subsequently, this paper concluded that consequentialism could hurt language, given its negative impact on language use, evaluation, and regulation.       

References

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Ayeni, T. (2020, November 24). Nigeria #EndSARS: Why social media bill threatens death

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Erikson, E. H. (1950). Childhood and society. W. W. Norton & Company

Ewang, A. (2019, November 26). Nigerians should say no to social media bill. Human Rights

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Habermas, J. (1984). The theory of communicative action, Vol. 1: Reason and the rationalisation

of society (T. McCarthy, Trans.). Beacon Press.

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moves-to-restrict-use-of-social-media/.

Daily writing prompt
What’s a movie you expected to hate but ended up loving?

PMI Study Hall for PMI-ACP: Managing Limited Mock Exam Attempts Effectively

Preparing for the Project Management Institute Agile Certified Practitioner certification often requires more than reading Agile frameworks or memorizing terminology. Many candidates begin their preparation believing success depends primarily on understanding Scrum events, Kanban principles, or Agile vocabulary. As preparation progresses, however, they usually discover that the PMI-ACP exam evaluates something deeper: the ability to interpret situations, recognize delivery priorities, and make context-sensitive decisions under pressure.

This is one reason why simulation platforms such as PMI Study Hall have become important preparation tools for many learners. Timed practice environments expose candidates to situational reasoning patterns that are difficult to replicate through passive study alone. Yet a common challenge emerges over longer preparation cycles: mock exam environments are finite. Once candidates complete the available simulations multiple times, maintaining realistic practice quality becomes more complicated.

Managing limited mock exam availability effectively therefore becomes an important strategic skill during PMI-ACP preparation. Candidates who approach simulations carefully often preserve learning quality longer and develop stronger long-term decision consistency than those who rapidly consume every available practice exam within the first weeks of study.

Why PMI-ACP Preparation Depends on Situational Reasoning

The PMI-ACP exam is heavily oriented around contextual interpretation rather than direct memorization. Questions frequently present scenarios involving stakeholder disagreement, changing priorities, delivery uncertainty, communication friction, or competing product concerns. In many cases, multiple answers appear technically acceptable, yet only one reflects the most contextually appropriate Agile response.

This structure changes how preparation should be approached. Memorizing definitions or framework mechanics may help establish foundational understanding, but it rarely prepares candidates for nuanced situational trade-offs. The exam often evaluates how well candidates interpret team dynamics, delivery goals, adaptive planning requirements, and stakeholder implications within evolving project environments.

For example, one scenario may prioritize rapid value delivery despite incomplete certainty, while another may emphasize collaborative problem-solving before implementation decisions are made. Candidates who apply rigid textbook logic without interpreting the broader situation frequently select technically correct but contextually weak answers. Strong PMI-ACP preparation therefore depends on repeatedly practicing interpretation itself.

The Educational Role of PMI Study Hall

PMI Study Hall supports this kind of preparation by exposing candidates to structured Agile reasoning environments. Instead of testing isolated definitions, the platform places learners inside decision-oriented scenarios where context matters as much as factual knowledge.

One important educational benefit is realism. Timed simulations encourage candidates to think under pressure while balancing competing Agile priorities. This helps reveal cognitive habits that are difficult to notice during relaxed study sessions. Some candidates realize they overanalyze questions, while others discover they make rushed assumptions about stakeholder intent or delivery constraints.

Another advantage is exposure to situational ambiguity. Many Agile certification questions intentionally avoid obvious answers. Candidates must identify subtle indicators related to stakeholder collaboration, adaptive planning, value-driven delivery, or team autonomy. Repeated exposure to this type of ambiguity strengthens contextual reasoning skills over time.

Structured simulations also help build mental endurance. Long-form scenario analysis requires sustained concentration and emotional consistency. Candidates who practice only through short quizzes sometimes struggle maintaining decision quality during full-length timed environments. Simulation platforms help condition learners for the cognitive rhythm of exam-style reasoning.

The Problem With Finite Mock Exam Environments

Despite these advantages, finite simulation environments introduce practical limitations during extended preparation periods. Once candidates complete the available mock exams multiple times, familiarity gradually changes the learning experience. Instead of analyzing each situation carefully, learners may begin recognizing patterns, recalling answer structures, or remembering previously reviewed explanations.

This shift can reduce cognitive difficulty significantly. Questions that once required active situational interpretation may become easier simply because the candidate remembers the correct option or recognizes the structure of the scenario. Over time, preparation may unintentionally move away from genuine Agile reasoning and toward passive pattern recall.

The danger is not always obvious because scores often improve during this phase. Candidates may interpret rising percentages as evidence of deeper readiness even when the improvement primarily reflects familiarity rather than adaptive reasoning growth. This can create false confidence before the actual exam, where scenarios remain unfamiliar and cognitive pressure feels different.

Another issue involves reduced scenario diversity. Agile environments are inherently dynamic, involving different stakeholder personalities, delivery risks, communication patterns, and organizational constraints. Limited mock pools eventually narrow the range of situations candidates experience, reducing exposure to fresh reasoning challenges.

How Repetition Can Change Candidate Behavior

Repeated exposure to the same simulation set gradually changes how candidates process questions. During early attempts, learners actively interpret context, evaluate trade-offs, and analyze stakeholder implications. After several repetitions, however, the brain often begins optimizing for recognition instead of reasoning.

This is a natural cognitive adaptation. Humans conserve mental effort by recognizing familiar patterns whenever possible. In exam preparation, though, excessive familiarity can weaken the very skills the PMI-ACP exam measures most heavily. Candidates may start choosing remembered answers automatically without fully evaluating the situation again.

Over time, this creates several subtle preparation risks. Some learners begin overestimating their situational judgment because practice environments no longer challenge interpretation skills meaningfully. Others stop reading carefully and miss contextual clues during unfamiliar scenarios because their preparation relied too heavily on recognition-based confidence.

A related problem is declining adaptability. Agile reasoning depends on flexibility and contextual prioritization. When practice variation becomes narrow, candidates may unconsciously anchor themselves to recurring logic structures rather than developing broader decision-making versatility.

Why Fresh Scenario Exposure Matters

Fresh Agile scenarios play an important role in maintaining cognitive flexibility during PMI-ACP preparation. New situations force candidates to interpret context actively instead of relying on memory shortcuts. This strengthens the ability to analyze stakeholder concerns, delivery constraints, collaboration dynamics, and prioritization signals under unfamiliar conditions.

Repeated exposure to varied situations also improves decision consistency under time pressure. During the actual exam, candidates cannot depend on memory recognition because every scenario feels new. The ability to interpret unfamiliar contexts calmly and systematically therefore becomes essential.

Scenario diversity additionally helps candidates recognize broader Agile principles across multiple environments. A concept such as adaptive planning may appear differently within product delivery discussions, stakeholder negotiations, team conflicts, or backlog prioritization challenges. Seeing these variations repeatedly improves conceptual flexibility and situational transferability.

Time-management stability also improves through varied practice exposure. Familiar questions are often answered faster simply because they are remembered. Fresh simulations force candidates to manage pacing realistically, helping them build sustainable timing habits for real exam conditions.

Extending Preparation Continuity More Strategically

Candidates preparing over longer periods often benefit from treating mock exams as limited strategic resources rather than consumable checklists. Instead of rushing through every available simulation early, many learners spread full-length exams across their preparation timeline to preserve realism and maintain ongoing assessment quality.

Some candidates alternate between different practice styles to extend preparation continuity. Full-length simulations may be reserved for milestone evaluations, while shorter targeted scenario sessions are used for daily reasoning practice. This helps preserve unfamiliarity within the larger mock exams for longer periods.

Others supplement structured environments with additional scenario pools or alternative practice sources to maintain broader situational exposure. Some learners also look for a budget-friendly PMI-ACP exam simulator to continue practicing varied Agile scenarios over longer preparation cycles without relying exclusively on a single finite mock exam environment. This type of extended scenario exposure can help reinforce Agile decision-making consistency while reducing overfamiliarity with repeated question patterns.

Rotating practice formats can also help maintain engagement. Some learners alternate between timed simulations, focused domain drills, stakeholder-oriented scenarios, or shorter adaptive planning exercises. This variation helps preserve active reasoning behavior while reducing repetitive cognitive patterns.

Reflective Review and Agile Feedback Loops

Effective PMI-ACP preparation depends heavily on reflective review rather than raw question volume alone. Simply completing more practice exams does not automatically improve situational judgment if candidates fail to analyze why mistakes occurred.

Many reasoning errors originate from interpretation habits rather than missing knowledge. For example, a candidate may consistently prioritize procedural structure over stakeholder collaboration, or focus on technical delivery while overlooking team dynamics. Without reflective analysis, these behavioral tendencies often persist across multiple simulations.

This is where iterative feedback loops become valuable. Candidates who review incorrect answers carefully can identify recurring decision patterns and adjust their reasoning process gradually over time. Some learners maintain error journals categorizing mistakes related to stakeholder interpretation, adaptive planning, escalation timing, or value prioritization.

Preparation itself begins to resemble Agile principles during this stage. Inspection, adaptation, and continuous improvement become central learning behaviors. Candidates who regularly evaluate weaknesses and adjust study strategies often develop stronger long-term exam readiness than those focused primarily on raw completion metrics.

Balancing Realism, Repetition, and Adaptability

Different preparation methods support different learning objectives. Structured simulations help build realism and exam pacing stability. Repetition reinforces recognition of Agile principles and common situational patterns. Diverse scenario exposure strengthens adaptability and contextual flexibility.

The challenge lies in balancing these educational goals effectively. Excessive repetition without variation may weaken active reasoning, while excessive variation without reflection may prevent deeper learning consolidation. Strong PMI-ACP preparation often emerges from combining realistic simulations with reflective review and broader situational exposure.

Candidates also benefit from recognizing that Agile reasoning itself is dynamic. The exam does not reward rigid formulaic responses applied universally across all situations. Instead, it evaluates how well candidates adapt Agile principles to changing contexts, competing priorities, and evolving stakeholder needs.

Maintaining adaptability during preparation therefore matters as much as learning Agile concepts themselves. Simulation environments are most effective when they continue challenging interpretation quality rather than merely reinforcing familiar answer patterns.

Conclusion

PMI Study Hall can support PMI-ACP preparation effectively when candidates use limited mock exam environments strategically rather than consuming them too quickly. Its structured simulations, timed environments, and situational reasoning exercises help learners strengthen Agile interpretation skills that extend beyond memorized terminology.

At the same time, finite mock exam pools can gradually reduce cognitive difficulty if repeated exposure leads candidates toward familiarity-based answering instead of active contextual reasoning. This makes continued scenario variation, reflective review, and ongoing simulation exposure increasingly important during longer preparation cycles.

Ultimately, realistic practice environments, repeated situational diversity, iterative feedback analysis, and adaptive learning behaviors tend to work together more effectively than relying on repetition alone. Candidates who preserve active reasoning throughout their preparation process often develop stronger cognitive flexibility, steadier decision-making under pressure, and more sustainable readiness for the PMI-ACP exam experience.

Daily writing prompt
How do you plan the perfect road trip?

Download X Videos in 1080p HD — Step by Step Guide (No Watermark)

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Not all X video downloads are equal. Open the wrong tool and you’ll get a blurry 480p file when the original was shot in crisp 1080p. Or the file arrives compressed, looking fine on a phone screen but falling apart on anything larger.

If quality matters — you’re editing content, archiving something important, or just tired of pixelated downloads — here’s exactly how to save X video 1080p with the full original resolution intact.

Why Downloaded X Videos Often Look Worse Than Expected

People frequently notice that the video they downloaded looks worse than the same video when streamed on X. A few things cause this:

The tool selected a lower quality automatically. Many downloaders grab the first available format — often the lowest resolution — without giving you a choice. You get 480p when 1080p was sitting right there.

The tool re-encodes the video. Some services process the video on their own servers before delivering it, applying their own compression. The file that arrives has been degraded twice — once by X during upload, once by the downloader.

The original simply wasn’t 1080p. If the content creator uploaded in a lower resolution, that’s the ceiling. No tool can create detail that wasn’t captured.

You downloaded the right file but it’s playing on a low-quality player. Some media players default to lower quality settings. Try a different player before assuming the file itself is the problem.

How to Confirm 1080p Is Available Before Downloading

Not every X video has a 1080p version. Whether it does depends on the uploader — X Premium accounts can post higher-resolution video; free accounts are subject to more aggressive compression.

The way to check: paste the tweet link into sssx.io and look at the quality options that appear. If 1080p is in the list, it’s available. If the highest option is 720p, that’s what exists on X’s servers — the 1080p version was never uploaded or was compressed away during upload.

sssx.io shows every quality tier available for that specific video. It doesn’t hide options or default to the lowest — the full list is visible so you can make the choice.

Step by Step: Download X Video in 1080p HD

Step 1: Find the video and copy the tweet link

Open X (app or x.com), find the video. Tap Share → Copy link. On desktop, copy the URL from the address bar or via the share menu.

The URL format should be: https://x.com/username/status/%5Btweet_id%5D

Step 2: Go to sssx.io

Open any browser and navigate to sssx.io. Paste the tweet link into the input field at the top of the page. Press Download.

Step 3: Select the 1080p option

In 2–5 seconds, the quality options load. Look for the highest resolution available — 1080p if the video was uploaded at that quality, otherwise 720p. Always choose the top option in the list for the best result.

Step 4: Download the file

Click the download button next to the 1080p option. The MP4 file saves directly to your device — Downloads folder on Android/desktop, Files app on iPhone.

Getting True HD on iPhone and Android

iPhone: Use Safari specifically — it handles file downloads correctly on iOS 13+. Go to sssx.io, paste the link, select 1080p, tap Download, confirm in Safari’s prompt. File goes to Files → Downloads. Move to Photos via Share → Save Video if needed.

Android: Any browser works — Chrome, Firefox, Samsung Internet. Go to sssx.io, paste, select 1080p, download. File saves to your Downloads folder automatically.

Desktop (Windows/Mac): Paste the link at sssx.io, select 1080p, click download. The file goes to your browser’s default Downloads folder. Press Ctrl+J (Windows) or Cmd+J (Mac) to open download history if you can’t find the file.

What “No Watermark” Actually Means for HD Downloads

sssx.io works as an x downloader no watermark — the MP4 you receive is the original file from X’s CDN with nothing added. No logo, no overlay, no site branding in the corner.

This matters for HD content specifically. A 1080p video with a watermark stamped across it is less usable than a clean 720p file. Getting the original file directly avoids both problems at once.

One clarification: if the content creator already had their own logo or @username in the video before uploading, that’s part of the original file — not something any downloader adds or can remove. What sssx.io guarantees is that nothing extra is added during the download process itself.

Tips for the Best HD Results

Always pick the top quality option. The quality list shows options from highest to lowest. The first item is always the best available for that video.

Use WiFi for large files. A 1080p video clip can be 50–200MB depending on length. A stable WiFi connection prevents interrupted downloads and ensures the file isn’t corrupted.

Check the file before assuming it’s low quality. Try playing the downloaded MP4 in VLC or your system’s default player before concluding the quality is poor. Some apps default to lower playback settings regardless of the file’s actual resolution.

Download soon after seeing the video. Tweets get deleted, accounts get suspended, content gets restricted. The 1080p version you see today may not exist tomorrow.

FAQ

Why is 1080p not showing as an option? The original video was uploaded in a lower resolution. X compresses videos during upload, and some content — especially older videos or content from free accounts — was never available in 1080p. sssx.io shows all options that exist; if 1080p isn’t listed, it doesn’t exist for that video.

Does sssx.io compress the video before delivering it? No. sssx.io fetches the file directly from X’s CDN servers without any re-encoding or compression. The file you download is the same file that X serves to its own video player.

Is there a size limit for 1080p downloads? No. sssx.io has no file size limits. Long high-resolution videos will take longer to download, but there’s no cutoff.

Does downloading in 1080p cost more? No. All quality levels including 1080p are available for free with no account, no subscription, and no per-download fees.

Can I download multiple videos in a row? Yes. There’s no daily limit or cooldown period between downloads.

Daily writing prompt
What’s a moment that made you realize you were stronger than you thought?

A Beginner’s Roadmap to Google Ads Setup

Starting with Google Ads can feel more confusing than most beginners expect. Many people search for how to buy Google Ads or how do I buy Google Ads as if the process is only about paying for clicks. In reality, a good setup starts before the campaign is even created. If the basics are weak, the budget disappears fast and the results become hard to understand.

That is why beginners need a roadmap, not just instructions. A simple step-by-step process helps avoid random decisions, missed settings, and early mistakes. In some cases, businesses that need a quicker launch also look for a simpler path to campaign readiness when they do not want delays at the very beginning. Still, even with faster options, the structure behind the campaign matters most.

Photo by Firmbee.com on Pexels.com

Step 1. Prepare the essentials before opening Google Ads

Before you buy ads on Google, make sure you have the foundations ready. A campaign should not begin with keywords or ad copy. It should begin with business clarity.

Prepare these elements first:

  • your main offer;
  • the landing page you will send traffic to;
  • one clear action you want the visitor to take;
  • basic pricing or value proposition;
  • access to analytics tools.

If the page is weak, the ads will not save it.

Step 2. Choose one campaign goal

A beginner mistake is trying to do everything at once. More traffic, more calls, more sales, more awareness — all in one campaign. That usually creates messy results.

Start with one primary goal:

  1. leads;
  2. online purchases;
  3. phone calls;
  4. website traffic;
  5. brand awareness.

A single goal makes it easier to choose campaign settings, measure success, and improve performance later.

Step 3. Define keywords by intent

Many beginners pick keywords based only on volume. That is risky. The better method is to think about what the user actually wants.

A simple keyword structure looks like this:

  • informational queries;
  • comparison queries;
  • action-oriented buying queries;
  • branded searches.

For example, someone asking a broad question is very different from someone ready to purchase. That is why buying Google Ads traffic works better when keyword groups are built around search intent, not just popularity.

Step 4. Write ads that match the search

Once the keywords are grouped, the ad copy should reflect them clearly. Relevance matters more than trying to sound clever.

A beginner-friendly ad should include:

  • a headline connected to the search query;
  • a direct benefit;
  • a clear next step;
  • a landing page that continues the same message.

If the keyword, ad, and landing page all say different things, performance usually suffers.

Step 5. Set a realistic budget and bidding approach

Another common beginner problem is choosing a budget without a plan. Some advertisers spend too little to collect meaningful data. Others spend too much before they know what works.

A safer approach is:

  1. start with a controlled daily budget;
  2. monitor search terms and click quality;
  3. avoid scaling in the first few days;
  4. adjust only after early data appears.

The goal of the first stage is not aggressive scaling. The goal is learning.

Step 6. Install tracking before launch

This is one of the most important steps. Without tracking, even a well-structured campaign becomes guesswork. Beginners often focus on how to buy a Google ad, but forget to measure what happens after the click.

At minimum, you should check:

  • form submissions;
  • purchase events;
  • call tracking if relevant;
  • basic analytics integration;
  • conversion values where possible.

For advertisers who want fewer setup delays, some also consider a more prepared setup for early campaign stability before pushing campaigns live. But whether the account is new or already organized, tracking must be in place before real spend begins.

Step 7. Review everything before launch

Before activating the campaign, do a final check. This simple habit prevents expensive mistakes.

Review this checklist:

  • correct targeting;
  • relevant keywords;
  • no obvious mismatch between ad and landing page;
  • working tracking;
  • correct billing setup;
  • clear conversion goal.

A five-minute review can save days of wasted budget.

Step 8. Watch the first 7 days carefully

The first week is not the moment to panic or make endless changes. It is the moment to observe.

During the first 7 days, focus on:

  • search term quality;
  • click-through rate;
  • early conversion signals;
  • landing page behavior;
  • wasted spend patterns.

Do not judge success too fast. Instead, look for signs that the campaign is attracting the right audience and sending them into a working funnel.

Final takeaway

A beginner-friendly Google Ads setup is not about doing everything at once. It is about moving in the right order: prepare the offer, define the goal, choose intent-based keywords, write relevant ads, set a realistic budget, install tracking, review the setup, and watch the first week carefully.

When beginners follow a roadmap instead of guessing, Google Ads becomes much less stressful and much easier to improve over time.

Daily writing prompt
How can you build a regular fitness routine?

An Autoregressive Moving Average Model for Short-Term Prediction of Non-Insulin Dependent Diabetes Among Farmers in Benue State

Citation

Agada, J., Kuhe, D. A., & Anthony, O. N. (2026). An Autoregressive Moving Average Model for Short-Term Prediction of Non-Insulin Dependent Diabetes Among Farmers in Benue State. International Journal of Research, 13(4), 255–278. https://doi.org/10.26643/ijr/edupub/22Style

APA

John Agada1, David Adugh Kuhe 2 and Ojochegbe Noah Anthony 3*

1Department of Mathematics and Computer Science, Rev, Fr. Moses Orshio Adasu University Makurdi, Benue State, Nigeria

2Department of Statistics, Joseph Sarwuan Tarka University, Makurdi, Benue State, Nigeria

3Department of Mathematics and Computer Science, Rev, Fr. Moses Orshio Adasu University Makurdi, Benue State, Nigeria

Corresponding Author: Email: davidkuhe@gmail.com; Tel: 2348064842229

ABSTRACT

This study employs an Autoregressive Moving Average (ARMA) time series model to forecast the short-term incidence of non-insulin-dependent diabetes mellitus (Type 2 Diabetes) among farmers in Benue State, Nigeria. The data was collected from the Benue State Epidemiological Unit, Makurdi, and covered a 20-year period from January 2005 to June 2025. The study employed descriptive statistics and normality measures, Augmented Dickey-Fuller (ADF) unit root test and ARMA (p,q) model as the principal analytical techniques and procedures used to examine the data. The descriptive statistics indicated moderate variability in diabetes cases over the years, while the Augmented Dickey-Fuller (ADF) test confirmed the stationarity of the series in level. Model choice based on Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), and Hannan–Quinn Criterion (HQC) identified the ARMA(3,3) model as the best fit for forecasting diabetic cases in the study area. The model’s high coefficient of determination (R² = 0.8905) and statistically significant parameters (p < 0.05) demonstrated its robustness and predictive accuracy. Diagnostic checks using autocorrelation, partial autocorrelation, and the Ljung–Box Q-statistics showed that the residuals behaved like white noise, indicating a well-specified model. Forecast evaluations using Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) confirmed that the model accurately good for predicting out-of-sample values. The forecast for July 2025 to June 2027 revealed a potential average of approximately 6,420 diabetes cases per month among farmers, with expected fluctuations over time. The study underscored the growing public health concern of diabetes among the farming population in Benue State and its implications for agricultural productivity and postharvest losses. The study concluded that predictive modeling can serve as a vital tool for health planners to design early intervention strategies, integrate health management with agricultural development, and enhance the overall well-being of rural farmers.

Keywords: Diabetes, ARIMA, Time Series Forecasting, Non-Insulin Dependent Diabetes, Farmers, Benue State, Public Health, Postharvest Losses

1.0       INTRODUCTION

Diabetes mellitus, often simply referred to as diabetes, is a group of metabolic disorders characterized by high blood sugar levels over a prolonged period. The two main types of diabetes are type-1 diabetes, which results from the body’s inability to produce insulin, and Type-2 diabetes develops when the body either becomes resistant to insulin or produces insufficient insulin to control blood sugar levels effectively. Diabetes mellitus is a multifaceted metabolic condition marked by high concentrations of glucose (sugar) in the bloodstream Glucose is a crucial source of energy for cells, and insulin, a hormone produced by the pancreas, plays a central role in regulating its uptake into cells. In diabetes mellitus, this regulation is disrupted, leading to persistent hyperglycemia (high blood sugar) (American Diabetes Association, 2022).

Diabetes mellitus is a significant public health concern worldwide, with its prevalence increasing steadily over the past few decades. According to the International Diabetes Federation (IDF, 2019), an estimated 537 million adults aged 20-79 years were living with diabetes globally in 2021 and this number is projected to rise to 783 million by 2045. The prevalence of diabetes varies by region, with higher rates observed in low- and middle-income countries, particularly in urban areas undergoing rapid socioeconomic development and lifestyle changes. (ADA, 2022).

In Nigeria, the prevalence is estimated at 7% and 11.35% in South-south zone. The Diabetes Association of Nigeria (DAN) reviewed that, mortality rate of diabetes from insufficient management far outweighs that of HIV/AIDs, Malaria and Cancer (Olamoyegun et al., 2024)

Diabetes mellitus is significantly Impacting farmers in Benue State with prevalence rate among yam farming population estimated at 24.9% and mortality rate of 8.61% and as led to reduced labor productivity, economic impact and health complications (Teran, A.D.. 2017)

Diabetes is associated with numerous complications that can affect nearly every organ system in the body. These complications includes Microvascular: Retinopathy (vision loss) neuropathy (nerve damage), nephropathy (kidney damage), and Microvascular: cardiovascular disease (such as heart attack and stroke), others are foot ulcers and amputations. The burden of diabetes-related complications is substantial, leading to increased medical costs, reduced quality of life, and higher risk of premature mortality (ADA, 2022).

Type-2 diabetes, also known as non-insulin dependent diabetes, is a long-term condition that affects how the body processes sugar (glucose), which is an important source of energy. In this condition, the body either becomes resistant to insulin, a hormone that helps move sugar into cells, or doesn’t produce enough insulin to keep blood sugar levels normal (Sun et al., 2021). Unlike type-1 diabetes, where the immune system attacks and destroys insulin-producing cells in the pancreas, type-2 diabetes usually develops slowly over time. While it was once mostly seen in adults, more children and teenagers are now being diagnosed, largely due to increasing obesity and less active lifestyles (Sun et al., 2021).

A major characteristic of type-2 diabetes is insulin resistance, which means the body’s cells don’t respond to insulin as they should. When this happens, the pancreas tries to make more insulin to help move sugar into the cells. However, over time, the pancreas may struggle to keep up with this increased demand. As a result, sugar starts to accumulate in the blood, causing high blood sugar levels (Cloete, 2022).

Several determinants contributes to the risk of developing type-2 diabetes, including obesity, particularly excess fat around the abdomen (central obesity), A sedentary lifestyle, unhealthy eating habits—like eating too many sugary and processed foods—having a family history of diabetes, getting older (especially after 45), and belonging to certain ethnic groups are all factors that can increase the risk of developing diabetes (ADA, 2022).

In Addition to insulin resistance, type-2 diabetes can also involve problems with the pancreas, the organ that makes insulin. Sometimes, the pancreas doesn’t produce enough insulin to keep blood sugar levels in check, making high blood sugar worse (Desai & Deshmukh, 2020).

Symptoms of type-2 diabetes often develop slowly and can include increased thirst, frequent urination, fatigue, blurred vision, slow wound healing, and repeated infections. In the early stages, some people may not notice any symptoms at all, which is why regular screenings are essential (IDF, 2019).

Treatment for type-2 diabetes aims to maintain blood sugar levels within a target range to prevent serious health problems and complications. This typically involves lifestyle modifications such as regular exercise, healthy eating habits (including portion control and selecting nutrient-rich foods), weight management, and monitoring blood sugar levels. (Desai & Deshmukh, 2020).

The management and treatment of type-2 diabetes can impose financial burdens on individuals, families, and healthcare systems. In regions where healthcare costs are primarily borne by the individual or are not adequately covered by insurance, the expenses associated with diabetes care can divert resources away from agricultural investments and productivity-enhancing measures. This can directly impact agricultural communities with reduced investment into agricultural produces, reduced income and crop loss thereby affecting their livelihood (Huang et al., 2016).

Diabetes Mellitus is diagnosed when certain blood sugar levels are met or exceeded. Specifically, a person may be diagnosed if their A1C is 6.5% or higher, which reflects average blood glucose over the past few months. Alternatively, if fasting blood sugar is 126 mg/dL or higher, or if a 2-hour blood sugar reading during an oral glucose tolerance test reaches 200 mg/dL or more, a diagnosis may be made. Additionally, if an individual has a random blood sugar of 200 mg/dL or higher along with symptoms like excessive thirst, frequent urination, or unexplained weight loss, they may also be diagnosed with diabetes (Jaeger et al., 2025).

Agricultural activities, like applying chemical fertilizers and pesticides, can have environmental consequences that can indirectly impact diabetes risk factors. For instance, exposure to chemicals such as glyphosate or organophosphates used in farming has been associated with a higher likelihood of developing metabolic disorders. Additionally, environmental factors such as air pollution and climate change may exacerbate diabetes risk factors and health outcomes, potentially affecting agricultural productivity and crop yields (whiting et al., 2011). Overall, while the direct impact of type-2 diabetes on agricultural productivity and postharvest losses may be limited, the interplay between diabetes, dietary patterns, healthcare access, and environmental factors can have broader implications for agricultural communities and food systems. Addressing the complex relationship between health, agriculture, and the environment requires a holistic approach that considers socioeconomic factors, public health interventions, and sustainable agricultural practices (Whiting et al., 2011).

Overall, while the direct impact of type-2 diabetes on agricultural productivity and postharvest losses may be limited, the interplay between diabetes, dietary patterns, healthcare access, and environmental factors can have broader implications for agricultural communities and food systems. Addressing the complex relationship between health, agriculture, and the environment requires a holistic approach that considers socioeconomic factors, public health interventions, and sustainable agricultural practices (Huang et al., 2016).

This study therefore attempts to extend the existing literature and contribute to the existing body of knowledge by modeling and forecasting non insulin dependent diabetes among farmers in Benue State using autoregressive moving average (ARIMA) time series model with more recent data.

2.0       MATERIALS AND METHODS

2.1       Method of Data Collection

The data utilized in this research work are monthly secondary time series data on morbidity incidence of type-2 diabetes in Benue state for the period of January, 2005 June, 2025 making a total of 234 observations. The data was collected from Benue State Epidemiological unit, Makurdi. The data was transformed to natural logarithms using the following formula:

where  is the confirmed type-2 diabetes series observation indexed by time , while  is the natural logarithm. Hence forth  will be regarded as a series.

2.2 Methods of Data Analysis

Find below the statistical tools employed in the analysis of data in this work.

3.2.1 Descriptive statistics and normality measures

The mean of any given set of data can be computed as follows:

The sample standard deviation of any given set of data over a given period of time is computed using the formula:

where  is the sample mean,  is the sample size.

Jarque-Bera test is a normality test of whether a given sample data have the skewness and kurtosis similar to that of a normal distribution. The test was proposed by Jarque and Bera (1980, 1987) and test the null hypothesis that the series is normally distributed. Given any data set, the test statistic JB is defined as:

where  is the sample skewness denoted as:

and  is the sample kurtosis given below:

whereT is the total number of observations. The JB normality test checks the following pair of hypothesis:

and  (i.e.,  follows a normal distribution)

and  (i.e.,  does not follows a normal distribution).

The test rejects the null hypothesis if the p-value of the JB test statistic is less than  level of significance.

2.2.2 Augmented Dickey-Fuller (ADF) unit root test

The Augmented Dickey-Fuller (ADF) test helps to identify if a time series is stationary or has a unit root, indicating a persistent trend over time (Dickey and Fuller, 1979).

 It accounts for higher-order correlations by assuming the series follows an AR(p) process and incorporates lagged differences of the series into the regression to enhance the test’s precision.

.

where are optional exogenous regressors which may consist of constant, or a constant and trend, and are parameters to be estimated,β values arelagged difference terms and the are assumed to be white noise. The null and alternative hypotheses are written as:

                                                                                        (8)

and evaluated using the conventional ratio for

where  is the estimate of  and “the coefficient standard error is denoted as  

2.2.3 Portmanteau test

A Portmanteau test also called he Ljung-Box Q-statistic test is used to determine whether there is any remaining serial correlation or autocorrelation in the residuals of a time series. The test checks the following pairs of hypotheses:

 (all lags correlations are zero)

 (there is at least one lag with non-zero correlation). The test statistic is given by:

where

denotes the autocorrelation estimate of squared standardized residuals at  lags. T is the sample size, Q is the sample autocorrelation at lag k. We reject  if p-value is less than  level of significance (Ljung and Box, 1979).

2.3 Time Series Models Specification

To specify an ARIMA model which is the model framework use in this study, we first specify autoregressive (AR) model, moving average (MA) model, autoregressive moving average (ARMA) model before specifying autoregressive integrated moving average (ARIMA) model. These models are specified as follows.

2.3.1 The autoregressive (AR) model

A stochastic time series process {} is an autoregressive process of order p, denoted AR() if it satisfied the difference equation

where  is a white noise and  are constants to be determined.

2.3.2 Moving average (MA) model

A time series {} which satisfies the difference equation

where  are fixed constants with  as white noise is called a moving average process of order q, denoted MA().

2.3.3 Autoregressive moving average (ARMA) model

A stochastic time series process {} which results from a linear combination of autoregressive and moving average processes is called an Autoregressive Moving Average (ARMA) process of order p, q, denoted ARMA () if it satisfies the following difference equation:

where are fixed constants associated with the AR terms and  are fixed constants associated with the MA terms with  being a white noise. The stationarity of an ARMA () process is guaranteed if the roots of the polynomial

 lie outside the unit circle.

An ARMA () model is specified as:

 2.3.4 Autoregressive integrated moving average (ARIMA) model

Autoregressive (AR), Moving Average (MA) or Autoregressive Moving Average (ARMA) model in which differences have been taken are collectively called Autoregressive Integrated Moving Average or ARIMA models. A time series {} is said to follow an integrated autoregressive moving average model if the th difference  is a stationary ARMA process. If  follows an ARMA(p, q) model, we say that {} is an ARIMA (p, d, q) process. For practical purposes, we can usually take  or at most 2.

Consider then an ARIMA (p, 1, q) process, with , we have

In terms of the observed series,

)

2.4 Model Order Selection

We use the following information criteria for model order selection in conjunction with log likelihood function: Akaike information criterion (AIC) due to Akaike (1978), Schwarz information Criterion (SIC) due to (Schwarz, 1978) and Hannan-Quinn information Criterion (HQC) due to (Hannan, 1980). The formula for the information criteria are:

where is the number of free parameters to be estimated in the model, T is the number of observations and L is the likelihood function defined as:

Thus given a set of estimated ARMA models for a given set of data, the preferred model is the one with the minimum information criteria and maximum log likelihood.

2.5 Model Forecast Evaluation

We employed Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) accuracy measures to select an optimal model mode that is both parsimonious and accurately forecast the data based on minimum values of the accuracy measures.

2.5.1 Root Mean Square Error (RMSE)

The Root Mean Square Error is a statistical tool for measuring the accuracy of a forecast method. It is computed as:

Where  is the forecast value of the series and  is the actual series and  is the number of forecast observations.

2.5.2 Mean Absolute Error (MAE)

The mean absolute error (MAE) is a statistical tool for measuring the average size of the errors in a collection of predictions, without taking their directions into account. It is measured as the average absolute difference between the predicted values and the actual values and is used to assess the effectiveness of a model. It is given as:

where”  is the actual value of the series at time  is the forecasted value of the series and  is the number of observations. The lower the value of RMSE and MAE, the better the model is able to forecast future values.

3.0       RESULTS AND DISC0USSION

3.1 Summary Statistics and Normality Measures

This study seeks to provide a short-term prediction of non-insulin-dependent diabetes (Type-2 diabetes mellitus) among farmers in Benue State using the Autoregressive Moving Average (ARMA) time series model. Before model estimation, a preliminary analysis of the dataset was conducted to summarize its key characteristics and assess the normality of the distribution. Table 1 below presents the descriptive statistics and normality test results for the observed monthly diabetes cases.

Table 1: Summary Statistics and Normality Measures

VariableStatistic
Mean5571.321
Maximum9661.00
Minimum3624.000
Standard Deviation1769.088
Skewness0.010212
Kurtosis1.767498
Jarque-Bera Statistic15.57465
p-value0.000415
Number of Observations246

From the result of summary statistics and normality measures reported in Table 1 above, the mean value of approximately 5571 infection cases indicates the average number of recorded non-insulin-dependent diabetes cases among farmers during the study period, while the maximum and minimum values (9661 and 3624, respectively) show the range of variation in the data. The standard deviation (1769) suggests a relatively high level of fluctuation around the mean, implying moderate variability in the monthly incidence of diabetes cases.

The skewness value (0.010212), being close to zero, indicates that the distribution of the series is approximately symmetric. However, the kurtosis value (1.767498) is less than 3, signifying a platykurtic distribution, that is, the data are relatively flatter than a normal distribution with lighter tails.

The Jarque–Bera statistic (15.57465) with an associated p-value of 0.000415 is statistically significant at the 1% level, leading to the rejection of the null hypothesis of normality. This implies that the series does not follow a perfectly normal distribution, which is a common characteristic of real-world time series data.

Overall, the results suggest that while the data are fairly symmetric, they deviate slightly from normality, a factor to be considered when fitting and diagnosing the ARMA model for accurate short-term forecasting.

4.2 Graphical Examination of Diabetes Miletus Series

Examining the morbidity cases of diabetes mellitus is essential for identifying trends and patterns over time, which can provide insights into the progression and fluctuations of the disease within a population. By analyzing these visual representations, healthcare providers and policymakers can better understand peak periods, seasonal variations, and the impact of interventions. This information is crucial for planning targeted healthcare responses, optimizing resource allocation, and developing strategies to reduce disease incidence and manage complications, ultimately improving health outcomes for affected populations. The time plots of the level and log transform series of diabetes mellitus are plotted in Figures 1 and 2 respectively as shown below.

The time plots of the level series and log transformed series reported in Figures 1 and 2 below indicate that both series are covariance or weakly stationary which implies the absence of unit root in the series in level. This is indicated by the smooth trend of both series.

Figure 1: Time Series Plot of Diabetes Miletus in Benue State from 2005 to 2025

Figure 2: Time Series Plot of Natural Log of Diabetes Miletus in Benue State from 2005

            to 2025

4.3 Augmented Dickey-Fuller (ADF) Unit Root Test Result

To ensure the appropriateness of applying an Autoregressive Moving Average (ARMA) model for short-term prediction of non–insulin-dependent diabetes cases among farmers in Benue State, it is necessary to examine the time series properties of the data. A key requirement for ARMA modeling is that the underlying series must be stationary. Therefore, the Augmented Dickey–Fuller (ADF) unit root test was conducted to determine whether the series  is stationary. Table 2 below presents the results of the ADF test under two specifications: with an intercept only, and with both intercept and trend.

The ADF statistics reported in Table 2 below for both model specifications (intercept only and intercept with trend) are -15.3344 and -15.4304, respectively. These values are far more negative than their corresponding 5% critical values (-2.8731 and -3.4283). In addition, the associated p-values are 0.0000, indicating strong statistical significance. Because the ADF test statistics are well below the critical values and the p-values are less than 0.05, the null hypothesis of a unit root is rejected under both model specifications. This confirms that the series stationary in its level form. Stationarity implies that the mean and variance of the diabetes case series remain stable over time, making it suitable for direct ARMA modeling without differencing. The strong evidence of stationarity enhances the reliability of subsequent short-term forecasts produced by the ARMA model.

Table 2: Augmented Dickey-Fuller (ADF) Unit Root Test Result

VariableOptionADF Test Statisticp-value5% Critical Value
Intercept only-15.33440.0000-2.8731
Intercept & Trend-15.43040.0000-3.4283

4.4 Autocorrelations and Partial Autocorrelations Functions of the Series

After confirming that the series of non–insulin-dependent diabetes cases among farmers in Benue State is stationary, the next step in the ARMA modeling process involves examining the autocorrelation structure of the series. The Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) are used to identify the dependence pattern between current and past observations, which guides the selection of appropriate autoregressive (AR) and moving-average (MA) orders.

Furthermore, the Ljung-Box Q-statistics were computed to test for the joint significance of autocorrelations up to various lags. This test determines whether the residuals are independently distributed — a key requirement for model adequacy. Table 3 below presents the ACF, PACF, and Ljung-Box Q-statistics results for the series while Figure 3 belowpresented the ACF and PACF plots of the series.

The results of ACF and PACF reported in Table 3 below and Figure 3 show that the autocorrelation (ACF) and partial autocorrelation (PACF) coefficients for all lags are small in magnitude, fluctuating around zero. This indicates the absence of significant serial correlation in the data. None of the autocorrelations exceed the approximate 95% confidence bounds (±0.1 for a large sample size of 246), suggesting that the time series behaves like a white-noise process.

The Ljung-Box Q-statistics and their corresponding p-values across all lags (p > 0.05) further confirm that there is no significant autocorrelation remaining in the residuals. This means that the null hypothesis of no autocorrelation cannot be rejected at any lag, implying that the series is adequately described by a stationary stochastic process (Ljung & Box, 1979).

Table 3: Autocorrelations and Ljung-Box Q-Statistics Test Results

LagACFPACFQ-Statisticsp-value
10.0140.0140.04580.831
2-0.019-0.0190.13380.935
30.0040.0050.13800.987
4-0.049-0.0500.74970.945
50.0220.0240.87470.972
60.0370.0341.21650.976
70.0220.0231.34200.987
80.0170.0151.41260.994
9-0.007-0.0051.42600.998
10-0.110-0.1074.56590.918
11-0.025-0.0224.72270.944
120.0780.0756.29440.901
13-0.008-0.0126.31150.934
14-0.017-0.0276.39070.956
150.0520.0557.09700.955
16-0.035-0.0227.42260.964
17-0.012-0.0087.45990.977
18-0.088-0.0939.52130.946
19-0.054-0.05010.3020.945
20-0.092-0.11412.5670.895
21-0.026-0.03212.7500.917
22-0.115-0.11516.3690.797
230.0070.00816.3810.838
24-0.053-0.07417.1650.842
25-0.056-0.03618.0320.841
26-0.047-0.05618.6430.851
270.0550.05719.4820.852
28-0.011-0.03219.5140.882
290.0600.05720.5110.876
300.0560.04221.3810.876
310.0400.06121.8280.888
32-0.001-0.01521.8280.912
33-0.027-0.00722.0360.927
34-0.109-0.12125.4320.855
35-0.056-0.07426.3420.854
360.0660.02527.6040.841

Figure 3: Plots of ACF and PACF of Log Transformed Series

Collectively, these findings suggest that the series is not driven by persistent temporal dependence, and any ARMA model fitted to the data should yield uncorrelated and well-behaved residuals. Therefore, the dataset is suitable for ARMA model identification and estimation, and the absence of significant autocorrelation validates the appropriateness of proceeding with short-term forecasting using the ARMA framework.

4.5 Model Order Selection

Following the establishment of stationarity and the absence of significant autocorrelation in the diabetes time series, various ARMA model orders were estimated to determine the most parsimonious and best-fitting specification for short-term prediction. Model selection was based on several statistical criteria, including the Log Likelihood (LogL), Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), and Hannan–Quinn Criterion (HQC). Generally, the preferred model is the one with the highest Log Likelihood and the lowest values of AIC, SIC, and HQC. Table 4 below presents the results of the model order selection process.

Among the twenty-four ARMA model specifications estimated, the ARMA(3,3) model exhibits the highest Log Likelihood value (-24.0103) and the lowest AIC (0.2552), SIC (0.3159), and HQC (0.2958) values. These results indicate that the ARMA(3,3) model provides the best balance between goodness-of-fit and parsimony.

Table 4:Model Order Selection using Log Likelihood and Information Criteria

S/nModelLogLAICSICHQC
1.ARMA(0,1)-34.45970.29640.33490.3079
2.ARMA(1,0)-34.81940.30060.33910.3121
3.ARMA(1,1)-32.94440.29340.33630.3107
4.ARMA(0,2)-34.41070.30420.34690.3214
5.ARMA(2,0)-35.12560.31250.35550.3298
6.ARMA(1,2)-32.92560.30140.35860.3245
7.ARMA(2,1)-33.29880.30570.36310.3288
8.ARMA(2,2)-30.37710.28990.36160.3188
9.ARMA(0,3)-34.40600.31220.36920.3352
10.ARMA(3,0)-35.46880.32480.38230.3480
11.ARMA(1,3)-28.09120.27010.36160.3089
12.ARMA(3,1)-32.90280.31190.38380.3409
13.ARMA(2,3)-30.37080.29810.38410.3328
14.ARMA(3,2)-30.53040.30070.38590.3354
15.ARMA(3,3)**-24.01030.25520.31590.2958
16.ARMA(0,4)-34.11570.31800.38930.3467
17.ARMA(4,0)-35.34920.33350.40560.3625
18.ARMA(1,4)-34.44660.33020.41590.3647
19.ARMA(4,1)-35.34320.34170.42820.3765
20.ARMA(2,4)-32.00990.31980.42010.3602
21.ARMA(4,2)-26.70270.27850.37950.3192
22.ARMA(3,4)-25.40650.27990.38990.3213
23.ARMA(4,3)-33.47970.34280.45810.3893
24.ARMA(4,4)-31.42530.29620.40600.3285

Therefore, based on the information criteria, the ARMA(3,3) model is selected as the optimal model for forecasting short-term variations in non–insulin-dependent diabetes cases among farmers in Benue State. This suggests that both autoregressive and moving average components up to the third order significantly contribute to capturing the dynamic structure of the series.

4.6 Parameter Estimates of ARMA(3,3) Model

After selecting the ARMA(3,3) model as the optimal specification based on the information criteria, the model parameters were estimated to evaluate the dynamic relationship between past observations and random disturbances in the series of non–insulin-dependent diabetes cases among farmers in Benue State. Table 5 below presents the estimated coefficients of the ARMA(3,3) model, along with their corresponding standard errors, t-statistics, and p-values. Goodness-of-fit measures such as the R-squared, Adjusted R-squared, F-statistic, and Durbin–Watson statistic are also reported to assess the adequacy of the fitted model.

Table 5: Parameter Estimates of ARMA(3,3) Model

VariableCoefficientStd. Errort-Statisticp-value
C8.7686640.017218509.27610.0000
AR(1)0.3660960.02464114.857130.0000
AR(2)0.3112030.02938210.591710.0000
AR(3)-0.9123590.024212-37.681660.0000
MA(1)-0.3728280.009593-38.862770.0000
MA(2)-0.3869230.009312-41.550860.0000
MA(3)0.9823890.007644128.51600.0000
R-squared0.890511 AIC0.255229
Adjusted R20.867389 SIC0.315852
F-statistic6.914400 HQC0.295759
Prob(F-stat.)0.000951 Durbin-Watson stat.2.011502

The model estimation results reported in Table 5 show that all autoregressive (AR) and moving average (MA) coefficients are statistically significant at the 1% level, as indicated by their very low p-values (p < 0.01). This implies that past values and past error terms up to the third lag significantly influence the current level of non–insulin-dependent diabetes cases among farmers.

Specifically, the positive coefficients of AR(1) and AR(2) suggest a direct persistence effect, meaning that increases in diabetes cases in the immediate past periods tend to raise current cases. Conversely, the negative AR(3) coefficient indicates a corrective mechanism, implying that after about three periods, the series tends to revert toward its mean. The MA terms also show alternating positive and negative signs, suggesting that short-term shocks have both dampening and amplifying effects over time before dissipating.

The high R-squared (0.8905) and adjusted R-squared (0.8674) values indicate that approximately 89% of the variation in diabetes cases is explained by the model, signifying a very good fit. The F-statistic (6.9144) with a significant probability value (0.000951) confirms the overall significance of the model.The Durbin–Watson statistic (2.0115) is close to 2, suggesting the absence of serial correlation in the residuals, while the information criteria (AIC = 0.2552, SIC = 0.3159, HQC = 0.2958) reaffirm that the ARMA(3,3) model remains the most parsimonious and efficient choice.

Overall, the ARMA(3,3) model adequately captures the temporal dynamics and short-term fluctuations in non–insulin-dependent diabetes cases among farmers in Benue State, making it suitable for reliable short-term forecasting.

4.7 Model Diagnostic Checks

Following the estimation of the ARMA(3,3) model for predicting non–insulin-dependent diabetes cases among farmers in Benue State, diagnostic checks such as multicolinearity test and Ljung-Box Q-statistic tests were conducted to verify the adequacy of the fitted model. This assessment ensures that the residuals behave like white noise, uncorrelated, homoscedastic, and pattern-free over time. The test are presented in the following subsections.

4.7.1 Multicolinearity test result

Multicollinearity diagnostics were performed to make sure the variables in ARMA(3,3) model weren’t overlapping too much. Using the Variance Inflation Factor (VIF) for each autoregressive (AR) and moving average (MA) term, the test assessed how multicollinearity might affect the stability and reliability of parameter estimates. Generally, VIF values above 10 indicate severe multicollinearity, values between 5 and 10 suggest moderate correlation, and values below 5 imply no serious concern. The results presented in Table 6 show both uncentered and centered VIF statistics for the ARMA(3,3) model parameters.

The results of multicolinearity test reported in Table 6 below reveal that all centered VIF values are considerably low, ranging between 1.11 and 2.55, which are far below the critical threshold of 10. This indicates that there is no serious multicollinearity among the explanatory variables (AR and MA terms) in the estimated ARMA(3,3) model.

Therefore, the estimated parameters are statistically reliable, and the standard errors are not inflated by multicollinearity. This implies that the ARMA (3,3) model is well-conditioned, and the coefficients can be interpreted with confidence.

Table 6: Test for Multicolinearity (Variance Inflation Factors)

 CoefficientUncenteredCentered
VariableVarianceVIFVIF
C 0.000296 1.018813 Na
AR(1) 0.000607 1.779456 1.779044
AR(2) 0.000863 2.552345 2.552344
AR(3) 0.000586 1.768375 1.768101
MA(1) 9.20E-05 1.257613 1.255458
MA(2) 8.67E-05 1.213557 1.203709
MA(3) 5.84E-05 1.121942 1.111356

4.7.2 Ljung-Box Q-statistic test result for serial correlation

The Autocorrelation Function (ACF), Partial Autocorrelation Function (PACF), and Ljung–Box Q-statistics were used to test for serial correlation. High p-values (greater than 0.05) for the Q-statistics indicate no significant autocorrelation, suggesting that the residuals are random and the model is well specified. Table 5 presents these diagnostic test results for the ARMA(3,3) model residuals.

The results of Q-statistic reported in Table 5 and the ACF as well as PACF plots reported in Figure 4 show that all residual autocorrelations (ACF and PACF) are very small and fluctuate closely around zero across all 36 lags. None of the autocorrelation coefficients appear significant, suggesting that the residuals from the ARMA(3,3) model are approximately white noise.

Furthermore, the Ljung–Box Q-statistics have p-values consistently greater than 0.05, indicating that the null hypothesis of no autocorrelation cannot be rejected at any lag. This confirms that there is no statistically significant serial correlation remaining in the residuals. In addition, the Durbin–Watson statistic from the model estimation (2.0115) supports this conclusion by indicating near-zero autocorrelation in the residuals.

Overall, these diagnostic results confirm that the ARMA(3,3) model is well specified, the residuals are independently and randomly distributed, and the model provides a statistically adequate fit to the data. Therefore, the model is suitable for reliable short-term forecasting of non–insulin-dependent diabetes cases among farmers in Benue State

Table 7: Autocorrelations and Ljung-Box Q-Statistic Test Results of Residuals

LagACFPACFQ-Statisticsp-value
1-0.024-0.0240.14150.707
2-0.012-0.0120.17600.916
3-0.069-0.0701.35580.716
40.0070.0031.36690.850
5-0.126-0.1285.32470.378
6-0.036-0.0485.65410.463
7-0.017-0.0245.72940.572
80.1420.12410.8120.213
9-0.042-0.04211.2540.259
100.0460.03211.8020.299
11-0.021-0.01511.9180.370
120.0520.04412.6280.397
13-0.0250.01212.7940.464
14-0.009-0.00812.8150.541
150.0620.08013.8040.540
160.0680.05315.0190.523
170.1120.14718.3160.369
180.1090.12721.4750.256
19-0.0080.02721.4930.310
20-0.087-0.06623.5290.264
21-0.066-0.03224.7070.260
22-0.0200.01024.8100.306
23-0.062-0.05725.8550.308
24-0.048-0.06426.4800.329
250.021-0.04426.5990.376
260.020-0.03726.7040.425
27-0.033-0.06927.0030.464
280.0650.05028.1560.456
290.0520.03028.8980.470
300.0620.04629.9690.467
310.0140.04030.0230.516
320.0100.01630.0530.565
330.0420.05030.5550.589
340.0030.00430.5580.637
35-0.039-0.01330.9940.662
36-0.008-0.00131.0140.705

Figure 4:Plot of Correlogram of Residuals of Estimated ARMA(3,3) Model

4.8 Forecast and Forecast Evaluation

To evaluate the predictive performance of the ARMA(3,3) model in forecasting non–insulin-dependent diabetes cases among farmers in Benue State, forecast accuracy measures were computed. The Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) were used to assess both in-sample and out-of-sample forecast accuracy. Lower values of these statistics indicate better model performance and predictive reliability. The result is presented in Table 8.

The results of forecast comparison reported in Table 8below show that the out-of-sample forecast achieved slightly lower RMSE (0.2671), MAE (0.2310), and MAPE (2.6490) values compared to the in-sample forecast (RMSE = 0.2715, MAE = 0.2446, MAPE = 2.6781). This suggests that the ARMA(3,3) model demonstrates strong predictive capability, with minimal forecast error and good generalization performance. The model selected in forecast mode, as denoted by the accuracy measures, provides reliable short-term out-of-sample predictions of non–insulin-dependent diabetes cases.

Table 8: Forecast Comparison using Accuracy Measures

 RMSEMAEMAPE
In-Sample0.2715100.2446152.678116
Out-of-Sample**0.2671000.2310482.649005

Note: ** denotes forecast mode selected by accuracy measures.

4.8.1 Forecast of Diabetes Miletus in Benue State from July, 2025 to June, 2027

To evaluate the short-term predictive performance of the ARMA(3,3) model, forecasts of non–insulin-dependent diabetes (Type-2 Diabetes Mellitus) cases among farmers in Benue State were generated for the period July 2025 to June 2027. The forecasts were computed in natural logarithmic form and then converted to actual population estimates. For each forecast, the standard error, lower confidence limit (LCL), and upper confidence limit (UCL) were calculated at a 95% confidence level, using  . These values provide a range within which the true number of diabetes cases is expected to fall with high probability, thereby indicating the reliability and uncertainty of the forecasts. The forecast result is reported in Table 9 below while the forecast graph is presented as Figure 5 below too.

Table 9: “Forecast of Diabetes Miletus Infection Cases in Benue State from July 2025-

            June, 2027″

Year: MonthForecast (natural log form)Actual Forecast (No. of Persons)
ForecastStd. errorLCLForecastUCL
2025:066.99678896
2025:078.774050.2712433799646411000
2025:088.726550.2716693619616510499
2025:098.782040.2716703826651611098
2025:108.771320.2720653782644710988
2025:118.801410.2726723893664411337
2025:128.745190.2726723680628110717
2026:018.760880.2727903738638010889
2026:028.745850.2734553677628510741
2026:038.797250.2734663871661611308
2026:048.773660.2734763781646211044
2026:058.778250.2740403794649211107
2026:068.736480.2741103638622610654
2026:078.768030.2741143755642610996
2026:088.768100.2744733752642611005
2026:098.797290.2746523862661611335
2026:108.760260.2746693722637610923
2026:118.761130.2748243724638110936
2026:128.745040.2751113662627910767
2027:018.783410.2751213805652511188
2027:028.777340.2751523782648611121
2027:038.782230.2754813798651711183
2027:048.747160.2754813667629310798
2027:058.760580.2754813717637810944
2027:068.763130.2757593724639410978
Total210.40663  154075 
Average8.766942917  6419.7917 

Note: For 95% confidence intervals, . LCL and UCL denote lower and upper confidence limits respectively.

Figure 5: Forecast Graph of Diabetes Miletus in Benue State from July, 2025-June, 2027

The forecast results reported in Table 9 and Figure 5 above reveals that the predicted number of non–insulin-dependent diabetes cases among farmers in Benue State is expected to fluctuate moderately over the two-year forecast horizon (July 2025–June 2027). The monthly forecasts range between approximately 3,600 and 11,300 cases, with an overall average of about 6,420 cases per month and a total forecast of 154,075 cases during the study period. The relatively narrow confidence intervals across months suggest a high level of precision in the model’s predictions.

Overall, the ARMA(3,3) model demonstrates strong forecasting capability, indicating that diabetes prevalence among farmers in Benue State is likely to remain fairly stable with mild month-to-month variations over the forecast period.

4.9 Implications of the Study to Farmers and Postharvest Losses in Benue State

The implications of this study for farmers and postharvest losses in Benue State are significant from both public health and socio-economic perspectives. The findings, which forecast the prevalence of non–insulin-dependent diabetes (Type-2 Diabetes Mellitus) among farmers, suggest that a substantial portion of the agricultural workforce may experience declining health and productivity over time. Poor health conditions such as diabetes can reduce farmers’ physical capacity to engage in strenuous agricultural activities, particularly during critical periods like harvesting and processing. “This in turn increases the likelihood of postharvest losses, as crops may remain un-harvested or inadequately stored due to reduced labour efficiency and absenteeism resulting from illness”.

Moreover, “higher diabetes prevalence among farmers implies increased medical expenditures and a diversion of household income away from agricultural investment”, further compounding the problem of low productivity and waste. The study underscores the urgent need for integrated health and agricultural policies—including improved rural healthcare services, regular medical screening, health education on diet and lifestyle, and the promotion of labour-saving technologies—to mitigate the dual burden of disease and postharvest losses. Ultimately, addressing the health challenges of farmers is crucial for achieving food security, sustaining agricultural livelihoods, and enhancing overall economic resilience in Benue State.

4.0       Conclusion

The study demonstrates that the ARMA(3,3) model effectively forecasts the incidence of non-insulin-dependent diabetes among farmers in Benue State, Nigeria, The analysis revealed that the ARMA(3,3) model provided the best fit based on information criteria and diagnostic tests, with residuals behaving like white noise, indicating a well-specified and reliable model. The forecasts from July 2025 to June 2027 suggest a steady and relatively high incidence of diabetes cases among farmers, implying that the disease poses an ongoing public health concern within the agricultural population. This condition could adversely affect farmers’ productivity, increase medical costs, and indirectly contribute to higher postharvest losses due to reduced labour availability and inefficiencies in farm management. These findings highlight the interconnectedness between health and agricultural output, emphasizing that the burden of chronic diseases like diabetes extends beyond healthcare into the realm of food security and economic stability. Therefore, proactive health interventions and policy integration between the health and agricultural sectors are vital. Ensuring farmers’ wellness through preventive care, early detection, and education can significantly reduce the impact of diabetes and its broader economic consequences. The study provides empirical evidence to guide policymakers, healthcare providers, and agricultural development agencies in formulating context-specific strategies to improve both health outcomes and agricultural sustainability in Benue State.

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Daily writing prompt
What’s a classic book that you think is overrated?

There are Cities and there are Cities: Marking the Sociological Distinction and Considerations

Citation

Ogbonnia, E. F., Chigoziri, N. E., C, I. K., U, A. K., Augustine, I., Esq, O. C., Onwe, D. C., & Chinelo, N. G. (2026). There are Cities and there are Cities: Marking the Sociological Distinction and Considerations. Journal for Studies in Management and Planning, 12(2), 66–73. https://doi.org/10.26643/jsmap/11

Egwu Francis Ogbonnia

Department Of Criminology And Security Studies, Ae-Funai

Orcid: Https://Orcid.Org/0009-0009-8519-8303

Nlemchukwu Emmanuel Chigoziri, Ph.D

Department Of Criminology And Security Studies, Ae-Funai

Nlemchukwuemmanuel@Yahoo.Com 08030819692

Orcid: Https://Orcid.Org/0009-0002-6403-6507

Igwe Kenneth C

Department Of Political Science, Ae-Funai

Adinde Kenneth U., Ph.D

Department Of Criminology And Security Studies, Ae-Funai

Orcid: Https://Orcid.Org/0009-0002-7458-7847

Izuogu Augustine

Department Of Criminology And Security Studies

University Of Agriculture And Environmental Sciences, Umuagwo, Imo State

Onyeacho Chike, Esq

Department Of Criminology And Security Studies

University Of Agriculture And Environmental Sciences, Umuagwo, Imo State

Daniel Chidiebere Onwe                                                                                 Alex Ekwueme Federal University Ndufu-Alike, Ebonyi State, Nigeria.

Nwadiani Grace Chinelo

Department Of Criminology And Security Studies, Alex Ekwueme Federal

University Ndufu-Alike, Ebonyi State, Nigeria.

ABSTRACT

This work centres on the various forms of cities and features that distant a city from the other. It is instructive to note that all known human society has various characteristics that tries to make it peculiar from other cities or communities. Thus, this study identified various cities and attempted to Sociologically demonstrate why some are seen as developed while others are still undergoing economic, political and social transition. The indicators that are primarily considered here are the level of human development, gross domestic product (GDP), direct foreign investment (DFI), Level of educational system/innovation amongst other factors.

Keywords: Cities, development, education, government, suburban, urban centres

INTRODUCTION

A city is a large and permanent human settlement. Cities generally have complex systems for sanitation utilities, Land usage, housing and transportation. The concentration of development greatly facilitates interaction between people and business, sometimes benefiting both parties in the process, but it also presents challenges to managing urban growth. Ekpenyong (2013) Opined that since 1870, the world has witnessed more far-reaching transformations in social life than occurred in the vast span of human history prior to that date. Urban centers have become the milieu in which almost everyone in the advanced world (capitalist society) live.

The development of cities is the result of a combination of circumstances. In western civilization (Europe, USA, Canada etc), the revolution in technology brought about a mechanization of agriculture that greatly improved per capital output, producing the food surpluses needed to sustain the cities.

At the same time human energy on the farm was increasingly replaced by mechanical energy, creating pressure on the rural population to leave the land.

Improved transportation system, road and railways, better housing systems and nutrition, health centers as well as communication technology all characterized city life, (Ekepenyong, 2011). Historically, there is not enough evidence to assert what conditions gave rise to the first cities. Some, theorists have speculated on what they consider suitable pre-conditions and basic mechanism that might have been important driving force. Conventional views thought that cities were first formed after the Neolithic revolution. This revolution gave impetus to agriculture, encouraged Hunter-gatherers to abandon nomadic lifestyles and to settle near others who lived by agricultural production.

Paul Bairoch (NY, cited in Ekpenyong 2013) believes that agricultural activities appearnecessary before true cities can form.

Various indices have been scholarly advanced regarding the conditions necessary for an area to be given the status of a city. According to Verve Gordon Childe, for a settlement to qualify as a city, it must have enough surplus of raw materials to support trade and relatively large population. For example, Shanghai China was seen as the biggest city while Durbai is presently the fastest growing city.

The first true towns are sometimes considered as large settlements where the inhabitants were no longer simply farmers but began to take on specialized occupations and where trade, food storage and power were centralized. Gordon Childe (1950 cited in Ekpenyong 2013) defined a city with 10 general indices. These are:-

  • Size and density of the population should be above normal.
  • Differentiation of the population; not all residents grow their own
    food leading to specialists.
  • Payment of taxes to a deity or king.
  • Monumental public building.
  • Those not producing their own food are supported by the King
    or ruler.
  • System of recording and practical science.
  • A system of writing
  • Development of symbolic art,
  • Trade and import of raw materials.
  • Specialist craftsman from outside the Kin-group

These characteristics are best used to describe ancient cities. One major characteristics that can be used to distinguish a small city from a large town is organized government. A city has professional administrators, regulations, and some form of taxation.

THE AFRICAN CITY

It is arguable to state that tropical Africa is one of the least urbanized

regions of the world. This is because in most countries, less than a quarter of the total population lives in urban centers, (Ekpenyong, 2013).

In 1950 for example, only two cities in the African continent had more than one million residents. Rapid population increase is an important factor in measuring urban development.

Cities in Africa are characterized by rapid population growth though other indices that are used as measuring yardsticks for urban settlement such as improved technology, stable government, quality social amenities and other essential needs of man are lacking. They are poverty-stricken, socially divided and present problems such as those insufficient and inadequate housing and unemployment on a large scale which are not encountered by the developed countries. Failure in Africa has always been attributed to cultural differences.

However, what is often forgotten is that such measures do not totally translate into development obstacles nor do they touch the underlying factors responsible for generating conditions favorable for unhindered development.

Though generalizations are difficult because of the scarcity of data, but Ekpenyong (2013) believed that there is abundant evidence that African societies are heterogeneous in their socio-political organization, but the context shared by all of them is the location of their economics at the periphery of international capitalism. This was made possible by the uneven trade relations that were not negotiated rather, a violent imposition of business relations with African Nations were made to become the producers of raw materials for the colonial masters and consumers of manufactured products of industries in the West.

Industrialization, improved housing, availability of seasoned health care, social amenities, refined schools and quality referrals amongst others are some of the indications of urban settlement and their peculiar pattern. Unfortunately, most of these amenities are lacking in African countries especially in their so-called cities. Another important factor as admitted by Ekpenyong (2013) is the concept of political stability. Since the exodus of Colonialism from African soil, Africa as a continent has been beset with variegated political instability especially in pre-election and election times.

Nevertheless, despite these bedeviling challenges, Africa Still possess several cities that have been running abreast with western cities and their development strides. These cities in Africa include Lagos, Kano, Port Harcourt, Accra, Egyptian cities which is the center of civilization and other growing cities in Africa.

In summary, cities in Africa are shaped by the nature of the incorporation of the entire social formation, The African economy which has been tied to uneven western capitalism of exploitation has been a huge obstacle to the full development of African cities just like the western counterparts. This explains the preponderance of prirnate cities in Africa, the seeds were sown during period of colonialism. City life today though is part of a world economic system such that changes in one part of the world have a direct impact elsewhere. The presence of multinationals has improved the plight of cities through their direct injection of fluid into business, improved communication, administration and investment strategies. These welcome developments have their attendant consequences, which include a high rate of criminality and corruption. Several crime issues now dominate the city life ranging from burglary, kidnapping, armed robbery to rape, political assassination and other related criminalities (Aneke, 2019).

EGYPT CIVILIZATION AND CITIES,

The more complex human societies called the first civilizations emerged around 3000 BC in the river Valleys of Mesopotamia, India, China and Egypt. An increase in food production led to the significant growth in human population and the rise of cities, The -people of

Egypt and southwest Asia laid the monumental foundation of western civilization, developed cities and struggled with the problems of organized state as they moved from individual communities to large territorial units and eventually to empire. Among the early old-world cities, Mohenjo-Daro of Indus Valley Civilization in present day Pakistan, existing from about-2600 BC, was one of the Largest with a population of 50,000 or more. These points to the fact that population is an important factor to be considered in defining and delineating what constitutes a city centre.

These Greek city-states reached great levels of prosperity that resulted in an unprecedented cultural boom, expressed in architecture, drama, Science, mathematics and philosophy and nurtured in Athens under a democratic government. In the 4th Century, Alexander the Great Commissioned Dinocrate of Rhodes to lay out his new city of Alexandra, the grandest example of idealized urban planning of the ancient Mediterranean world where the city’s regularity was facilitated by its level site near mouth of the Nile.

Urban planning is one distinguishing factor between cities of Africa and the rest of the world, African cities though with profound developmental strides lack seasoned planning and architecture that makes it looks attractive.

Some cities are sparsely populated political capitals; others were trade centers and still other cities had a primarily religions focus. A good example is Saudi Arabia where Muslim go far pilgrimages and Jerusalem where privileged Christians go for pilgrimage. The growth of the population. of ancient civilizations, the formation of ancient empire concentrating political power, and the growth in commerce and manufacturing led to ever greater capital cities and centers of commerce, tourism and industry. In ancient America, early urban traditions developed in the Andes and Mesoamerica. In the Andes, the first urban centers developed in

the Norte Chico civilization. It is the oldest known civilization in the Americas, flourishing between the 30th century BC and the 18th century BC. Meso-America saw the rise of early Urbanism in several cultural regions. Later cultures such as the Aztec drew on these earlier urban traditions. 

The growth of modern industry from late 18th century onward led to massive Urbanization and the rise of great new cities, first in Europe and then in other regions, as new opportunities brought huge numbers of migrants from rural communities into urban areas. In the United States, from 1860 to 1910, the introduction of railroads reduced transportation costs and large manufacturing centers began to emerge, thus allowing migration from rural to city areas. Cities during this period were deadly places to live in due to health problems resulting from contaminated water, air and communicable diseases. In the great depression of the 1930s, cities were hard hit by unemployment, especially those with a base in heavy industry. In the USA, Urbanization rate increased from 40 to 80 percent during 1900-1990. Today, the world’s population is slightly over half urban and continues to urbanize with roughly a million people moving into cities every 24 hours worldwide.

Generally, Richard Sennett (1977) gives a rather sociologically inclined definition of a city. To him, a city is a human settlement where strangers are likely to meet.

Even amongst the western world, there is no single definitional construct on the concept of what constitutes a city. This is because the factors, or better still, peculiarities that distinguish a city vary from place to place and time to time. What constitutes a city in medieval civilization for instance may not be apt enough to determine the features of a city in modern times. Even in the next century, what we see now as cities may net be seen as full-blown cities.

Modern cities are known for creating their own microclimates. This is due to the large clustering of heat absorbent surface that heat up in sunlight and that channel rainwater into underground ducts, Waste and sewage are two major problems for cities such as air

pollution from various forms of combustion, including fire burning, stoves, other heating systems, engine emission and internal combustion engines. Crime is another consequence of city life. Studies have shown that crime rate in cities is higher and the chance of punishment after getting caught is lower. In extreme cases such as burglary, the higher concentration of people in cities creates more items of higher value worth the risk of crime. Cities also generate positive external effects. The close physical proximity facilitates knowledge spillovers, helping people and firms exchange information and generate new ideas. Population density enables also sharing of common infrastructure and production facilities, however in very dense cities, increased crowding; thickening labor market due to uncontrolled migration may lead to some negative effects. These have been the challenges confronting cities in Africa and beyond even in the western civilized parts of the world.

GLOBAL CITIES

A global city, also known as a world city, is a prominent Centre of trade, banking, finance, innovation and markets. As it was coined by Sakia Sassen (1991). Global Cities have more in common with each other than with other cities.

Global cities are opposed to mega-city which refers to any city of economic power or influence. This includes London, Paris, Mew York, Tokyo and the modern Dubai. Los Angeles, the home of Hollywood is a globalizing city though more significant in Cultural than economic terms unlike the enumerated cities. From the foregoing, global cities are characterized by intense economic activities, business growth and investment opportunities and not along cultural lines. A good example is Eggaton Street in London where some of the cheapest buildings cost about three million pounds.

There is a growing movement in North America called “New Urbanism” that calls for a return to traditional city planning methods where mixed-use zoning allows people to walk from ‘one type of land use to another. The idea is that housing, shopping, office space and Leisure facilities are all provided within walking distances of each

other, thus reducing the demand for road space and also improving the efficiency and effectiveness of mass transit, (Jeribe 2023)

SUB-URBAN/ SUBURBANITES

This is another dimension in the analysis of cities and urban development. By suburban, it means that it is not urban, rather below urban requirement or away from urban life. On the one hand, suburban sirnply means a smaller community adjacent to or within commuting distance of big city, an outlying part of a city or town, (Jeribe 2023). It could also mean a town or other areas where people live in houses near a larger city. On the other hand, suburbanites are the people who dwell in such areas as described above. Most developed cities or” the world due to over-population, busy traffic, high tenancy, crime rate and other vices have paved way ‘for the emergence and development of suburban cities. It is a drift away from city life. Most inhabitants of inner city have moved away to settle in suburban centers.

Even the rural dwellers whose economic situation has taken an upward turn have also found abode/reasons to migrate to suburban centers. Suburbanites could be government functionaries, business and oil magnets, executives in corporations and successful business tycoons. In Rivers State for instance, resident of government reserved area (GRA), Trans Amadi residents etc can decide to relocate to Aluu, Choba or Igwuruta towns. Gradually, development will move into such areas. This will also gradually give rise to another
suburban city with the passage of time and by social interaction and processes. Soaring housing and electricity bills, environmental challenges and the upsurge of massive retrenchment, unemployment and a lot more social problems could be reasons for the increase in the number of suburbanites.

Town planners and urban sociologists are presently concerned with the development of suburban and suburbanites. Land acquisition and tenancy rates are cheaper in suburban centers, giving room for higher influx of people into the area.

Suburbanites are likely to travel to the city for work. Suburbs have more single-family homes than apartment buildings and suburbanites are more likely to have a yard with trees and grasses. They may enjoy a little of the advantage of rural settings as well as some facilities common with the cities. The disadvantage is that if they work in the main city, they might have a Long Commute that adds to the time they are away from their family.

Suburbs   are   usually   middle-class   residences:   rents   are   usually cheaper   in   the   suburbs.   We   have   suburbs   of   New   York   and   Manchester etc. (Jeribe, 2023),

The typical life, attitude and way of life of people who live in the suburbs may be peculiar. Some people consider suburban life to be rather boring and conservative compared to the hustle and ‘bustle’ of city life, while others commend the serenity and peace of some Suburbs that have not yet been eroded by the encroachment of a developing city, (Jeribe, 2023).

CONCLUSION

In conclusion, what can be seen as cities exist in all parts of the world though with varying features. This is a reality because what constitutes a favored city in London or Tokyo rnay not be found in growing nations such as Nigeria and other African countries. Generally, cities are up of densely populated conglomeration of peon e from diverse ethnic origin, improved housing system with urban planning standard, quality health care facilities and referrals, technology and communication as well as the presence of multinationals, good road network, stable electricity / alternatives (Gas turbines etc) as well as free competitive market, financial institutions and unparallel investment. In other to bring African nations to this standard, the following recommendations are made:

  1. Urban planners should be allowed to strategize on the best way to manage housing and housing related issues. The government has always hijacked this- role which has made urban settlement patterns a big failure.
  2. Creation of employment by the government is germane to minimize the crime rate in our cities,
  3. Direct investment both   small   and   medium   enterprises should be encouraged. Government should aid them by boosting their financial potential,

4.The creation of a stable, sane and crime-free society through

Improved security monitoring is essential. No city or nation progresses when it is beset with security challenges.

5. Finally, the creation of enabling physical environment such as controlled pollution of the environment with toxic waste and other harmful substances will necessitate/improve our match to a healthy living standard.

REFERENCES

Anele K. A (2019), Social Change and Social Problems in Nigeria. Department of Sociology, University of Port-Harcourt.

Ekpenyong S.   (2011), Elements of  Sociology 2no edition, Heritage Research and Publication.

Ekpenyong S, (2013), The City in Africa, Davidstones Publishers Ltd,

Jeribe C. (2023), The Concepts of Suburbanite, A Seminal Presentation, University of Port-Harcourt.

Richard S. (1977), The Fall of Public Man, P, 39, ISBN 0-14-100757-5.

Siskia Sassen (1991), The Gioba! city, Mew York, London/ Tokyo, (Princeton): Princeton University Press, 1991), 1st edition, ISBN

0-691-07063-6

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