A study of electronic commerce adoption factors in Nigeria

Oluyinka, Solomon; Shamsuddin, Alina; Ajabe, Musibau Akintunde; Enegbuma, Wallace Imoudu

doi:10.1504/ijiscm.2013.060974

Cited by 18 publications

(12 citation statements)

References 57 publications

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“…Stata 13 and SPSS version was utilized as the statistical tools, KMO sampling adequacy of .823 achieved, and alpha equal to .849 achieved. Thus, descriptive statistics presented (Oluyinka et al, 2013;Ayodele et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Current Exercise Habits and Factors Affecting Physical Activity Participation Among University Students

Endozo¹

2019

GJHS

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BACKGROUND: Physical activities are indispensable to be healthy and away from illness. Yet, students are spending time being sedentary due to rapid technological advancement. Highly active individual requires physical activity for 3 days and must accumulate at least 1500-3000 metabolic equivalent tasks (MET)-minutes per week or more days of moderate or vigorous intensity activities. OBJECTIVE: This study aimed to analyze factors affecting physical activity participation among university learners in the Philippines. METHODS: An International Physical Activity Questionnaire answered by 470 participants and modified 4 point Likert scale questionnaires was utilized. RESULTS: There were 222 females (47%), 248 males (53 %), and p-value < 0.05 adoted to justify the significance of the factors in this study. CONCLUSION: This study justified that most of the participants cannot engaged in physical activities due to lack of time. Future research with larger sample groups to accurately identify the factors and recommend changes to enhance participation is encouraged.

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Section: Discussionmentioning

confidence: 99%

Current Exercise Habits and Factors Affecting Physical Activity Participation Among University Students

Endozo¹

2019

GJHS

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“…The principal component analysis, factor loading accomplished as all loaded at expected column, AVE above .5, composite reliability and all cronbach's alpha of 0.7, p-values of .05, achieved (Hair et al, 2012;Oluyinka et al, 2013;Ayodele et al, 2018). Bootstrapped value and partial least square multiple weights (R 2 ) to explain the variance of the model adopted as recommended (Hair et al, 2012).…”

Section: Methodsmentioning

confidence: 99%

Structural Equation Modeling of Mental Toughness Among University Learners

Endozo¹

2019

GJHS

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BACKGROUND: Mental toughness is recognized as an important component towards academic success thus making its psychological qualities determine how challenges are effectively addressed during pressurized situations. Challenges facing undergraduate learners in the context of mental toughness had been broadly investigated mostly in developed countries. Most of the studies centered on sports and descriptive findings lack critical analysis. OBJECTIVE: The main objective of the current study was to investigate the level of mental toughness of university learners and the impact on the learners' academic performance. The current study also investigated whether university learners who were reported with greater mental toughness are more likely to be academically successful than those lower in mental toughness. METHODS: This quantitative study employed SmartPls 3 software to predict the significant level of motivation, self-reliance, concentration and coping with pressure on academic performance among university learners. Two universities were considered for assessing the structural equation modeling of mental toughness. Additionally, sources of data included reviews of different books on the related topics, research studies, articles, journals, newspapers, and magazines. Substantial information has been gathered from these sources thus allowing for appropriate analysis, compilation, interpretation, and structuring of the entire study. Thus, in an attempt to isolate and categorize potential attributes of mental toughness and its impact on academic performance, the available literature reviewed. This quantitative study considered adoptable in handling bias findings. A sample size of 417 considered appropriate for a variance based structural equation modeling. A total number of 417 responses gathered from Angeles University Foundation (AUF) and Baliuag University (BU), Philippines considered for this mental toughness study. RESULTS: A total of a 75 percent from the questionnaires (477) returned from a sum 600 questionnaires distributed to specified respondents. Demographic details report that female responded with round-off 60%, this implied that female strive more in education than male. Ages 17-20 occupied 55% nursing/medicine marked around of 34% to top among the six colleges investigated in this study, next was college of business and administration marked around of 20% to take second place. This study suggested that students considered more to be medical doctors, professional nurses and business practitioners in the future rather than being professional teachers or system engineers. Reliability and validity of this study reported according to the Smart-Pls algorithm factor matrix, Cronbach's alpha, rho_A, and composite reliability all above 0.7 thresholds. Also, the average variance extracted from 0.5 achieved. The discriminant validity of this study based on Fornell-Lackner criterion, factor loading at 0.6 above and Heterotrait Monotrait Ratio quality achieved. Conclusively, all supported path coefficients significant at the p-values < 0.01. In a nutshell, partial least squares algorithm reported about a 58% variance explained from the entire structured model. CONCLUSION: The adopted factors for this structural equation modeling of mental toughness for university learners achieved fifty-eight percent variance explained in the study. Future studies can be directed towards replicating the use of this model in other locations and different analytical techniques.

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“…Relative advantage is extent condition to which innovation adoption is considered capable of providing greater benefits to organization than maintaining previous innovations [30]. Some studies have empirically identified relative advantage as a significant determinant of technology adoption [7,31]. Complexity indicators refer to conditions in which innovation adoption is considered relatively difficult or not to use [32].…”

Section: Influence Of Technology On E-commerce Adoptionmentioning

confidence: 99%

“…Indicators Descriptions References Technology: perceived behavior control, such as the cognitive skills of managers in using ecommerce technology and supporting resources is needed to exploit the potential of e-commerce technology Relative advantage the extent to which e-commerce technology is felt to provide greater benefits for SMEs than the ideas used previously [7,16,20,30,31] complexity the extent to which e-commerce technology is perceived as more difficult or too complex to be used than old ideas that have been used before [16,20,30,32] compatibility the extent to which e-commerce technology is felt in accordance with the needs, types of businesses and business processes that exist in SMEs [16,20,30,33,34] Organization: company characteristics and resources, such as the objectives of SMEs, readiness to use ecommerce technology and business size Top management support the extent to which the management of SMEs want to switch to using e-commerce and would allocate its resources to adopt ecommerce [16,23,37,48] Knowledge of information technology skills or knowledge of information technology from SME managers to be able to use e-commerce technology [16,39,40] size of organization the sufficient availability of resources owned by SMEs to adopt e-commerce technology [16,[41][42][43] Variables Indicators Descriptions References Environment: the condition of SME environment in carrying out its business processes and associated with the surrounding elements such as customers, competitors and presence of e-commerce technology service providers Competitive pressure the pressure experienced by SMEs from similar business competitors who have adopted e-commerce to gain a competitive advantage [23,45,48,49] Trading partners pressure willingness to gain trust in trading partners (buyers / customers) by providing valid product / service information and ease of product purchase transactions…”

Section: Variablesmentioning

confidence: 99%

E-Commerce Adoption in SMEs: A Literature Review

Religia¹,

Surachman²,

Rohman³

et al. 2021

Proceedings of the 1st International Conference on Economics Engineering and Social Science, InCEESS 2020, 17-18 July, Bekasi,

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Development of information technology (IT) has been driven changes in various fields, one of which is in marketing. The use of IT in marketing will not be separated from internet, where e-commerce services have now emerged that allow businesses to conduct face-to-face transactions by removing barriers related to distance in interacting with customers, so that every stakeholder will have same opportunity for promoting their products. On the other, Indonesia is country fourth largest population in the world, where 99.8 percent of its business units are small and medium enterprises (SMEs). Although the number of business units in the SMEs sector is very large, ecommerce adoption is still dominated by large business units, so research related to the adoption of e-commerce by SMEs is still very limited, especially in developing countries. This study aims to fill that research gap. In this study a TOE framework will be examined to determine the determinants of e-commerce adoption by SMEs. TOE framework considers technology, organization and environment variables to measure adoption of information technology. Analysis of TOE framework will consider empirical literature. This study also makes recommendations for future research.

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A study of electronic commerce adoption factors in Nigeria

Cited by 18 publications

References 57 publications

Current Exercise Habits and Factors Affecting Physical Activity Participation Among University Students

Current Exercise Habits and Factors Affecting Physical Activity Participation Among University Students

Structural Equation Modeling of Mental Toughness Among University Learners

E-Commerce Adoption in SMEs: A Literature Review

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