Predicting Credit Default among Micro Borrowers in Ghana

Microfinance institutions play a major role in economic development in many developing countries. However many of these microfinance institutions are faced with the problem of default because of the non-formal nature of the business and individuals they lend money to. This study seeks to find the determinants of credit default in microfinance institutions. With data on 2631 successful loan applicants from a microfinance institution with braches all over the country we proposed a Binary logistic regression model to predict the probability of default. We found the following variables significant in determining default: Age, Gender, Marital Status, Income Level, Residential Status, Number of Dependents, Loan Amount, and Tenure. We also found default to be more among the younger generation and in males. We however found Loan Purpose not to be significant in determining credit default. Microfinance institutions could use this model to screen prospective loan applicants in order to reduce the level of default. Keywords: Microfinance, Loan Default, Default Prediction, Logistic Regressio

Modeling the acceptance and resistance to use mobile contact tracing apps: a developing nation perspective

Purpose: This study proposes and validates an integrated theoretical model involving the theory of planned behavior (TPB), health belief model (HBM), personal norms and information privacy to understand determinants of acceptance and resistance to the use of mobile contact tracing app (MCTA) in a pandemic situation. Design/methodology/approach: This study draws on online surveys of 194 research respondents and uses partial least squares structural equation modeling (PL-SEM) to test the proposed theoretical model. Findings: The study establishes that a positive attitude towards MCTA is the most important predictor of individuals' willingness to use MCTA and resistance to use MCTA. Furthermore, barriers to taking action positively influence resistance to the use of MCTA. Personal norms negatively influence resistance to the use of MCTA. Information privacy showed a negative and positive influence on willingness to use MCTA and use the resistance of MCTA, respectively, but neither was statistically significant. The authors found no significant influence of perceived vulnerability, severity, subjective norms and perceived behavioral control on either acceptance or use resistance of MCTA. Originality/value: The study has been one of the first in the literature to propose an integrated theoretical model in the investigation of the determinants of acceptance and resistance to the use of MCTA in a single study, thereby increasing the scientific understanding of the factors that can facilitate or inhibit individuals from engaging in the use of a protection technology during a pandemic situation. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0533. © 2023, Michael Adu Kwarteng, Alex Ntsiful, Christian Nedu Osakwe and Kwame Simpe Ofori.Horizon Europe (HORIZON) [101071300]; [IGA/FaME/2023/009]; [FSR FORD 5-6/2021-23/FaME/003]; [IGA/FaME/2022/003]; [IGA/FaME/2021/003

Exploring Mobile Social Networking Sites Continuance Intention from the Perspective of Network Externalities and Mobile Value

Key shifts in the nature and characteristics of technology have led to evolutions in social media usage. For the first time in history, the internet is being accessed from more mobile devices than desktop computers. This revolution is especially felt among social networking sites, many of whom have presciently developed and released mobile applications of their platforms. Drawing from the Perceived Value Theory, Network Externalities and the Expectation Confirmation Theory of IS Continuance, we tested a model that sought to explain the effect of Network Externalities on Perceived Value and in turn Continuance Intention. Data was collected from 452 students from a university in Ghana and analyzed using the Partial Least Square approach to Structural Equation Modeling. Results from the current study showed that Referent Network Size and Perceived Complementarity had significant effects on both Utilitarian and Hedonic Value as well as Satisfaction. Hedonic Value, Utilitarian Value and Satisfaction in turn were found to be significant predictors of Continuance Intention. In all, the model accounted for 58.0% of the variance in continuance intention. The implications and limitations of the current study are discussed, and directions for future research proposed

Understanding post-adoption behaviour in the context of ride-hailing apps : the role of customer perceived value

PURPOSE : Despite the perceived role of customer value in post-adoption behaviour in the context of ride-hailing apps such as Uber, there has been limited research on the subject. This paper seeks to enrich the understanding of the relationships between customer perceived value, particularly hedonic value and economic value, customer satisfaction and continued use intentions of ride-hailing apps. DESIGN/METHODOLOGY/APPROACH : This analysis is based on field data collected from 567 users of ride-hailing apps in Ghana. Data collected from the survey were analysed using the partial least square (PLS) approach to structural equation modelling (SEM). FINDINGS : The paper provides evidence that hedonic value, as well as economic value, positively predicts customer satisfaction and continued use intentions of ride-hailing apps. Further analysis reveals customer satisfaction directly predicts continued use intentions in addition to partially mediating the influence of customer perceived value on continued use intentions of ride-hailing apps. Finally, the findings suggest that hedonic value has a stronger impact on continued use intentions than economic value, while economic value has a greater impact on satisfaction than hedonic value. ORIGINALITY/VALUE : The study contributes to post-adoption behaviour research by providing evidence on the relationships among the study constructs in a developing country context. Overall, the findings will stimulate future empirical debates on the subject and guide practitioners in decision-making concerning customers' usage of ride-hailing apps.https://www.emerald.com/insight/publication/issn/0959-3845hj2023Gordon Institute of Business Science (GIBS

Knowledge Sharing Among Academics: The Impact of Organizational Fairness, Trust, and Openness in Communications

The effective management of knowledge is both a vital strategic resource and a significant source of competitive advantage in academic settings. We explore the interrelationships among organizational justice, identification trust, openness in communication and knowledge-sharing behavior among academics. Results could be useful in designing strategies to improve knowledge sharing

Antecedents of customer switching intention in the Ghanaian telecommunications industry

The telecommunications industry continues to experience fierce competition due to the growth in subscribers and the rapid development of new technologies in the sector. With that hindsight, this study explores the dimensionality of factors that affect mobile phone subscribers' intention to switch operators. Survey data was collected from 235 mobile phone network subscribers and analyzed using the Partial Least Square Approach to Structural Equation Modelling (SEM). The SEM model was assessed based on the measurement model and the structural model. Factor Loadings, Cross Loadings, Average Variance Extracted Cronbach's alpha, and Composite reliabilities of the latent variables examined showed that the measurement model exhibited sufficient reliability, discriminant validity and convergent validity. Assessment of the Structural model shows that 77% of the variation in Satisfaction is explained by our model (R2 = 0.77). Furthermore, 18% (R2 = 0.18) of the variation in Intention to Switch was explained by the model. Stone-Geiser Q2 for the endogenous showed that the proposed Structural Equation Model exhibited sufficient predictive relevance. Conclusions were drawn with practical implications of the results also discussed. Growing Science Ltd. All rights reserved.

Antecedents of customer switching intention in the Ghanaian telecommunications industry

The telecommunications industry continues to experience fierce competition due to the growth in subscribers and the rapid development of new technologies in the sector. With that hindsight, this study explores the dimensionality of factors that affect mobile phone subscribers’ intention to switch operators. Survey data was collected from 235 mobile phone network subscribers and analyzed using the Partial Least Square Approach to Structural Equation Modelling (SEM). The SEM model was assessed based on the measurement model and the structural model. Factor Loadings, Cross Loadings, Average Variance Extracted Cronbach’s alpha, and Composite reliabilities of the latent variables examined showed that the measurement model exhibited sufficient reliability, discriminant validity and convergent validity. Assessment of the Structural model shows that 77% of the variation in Satisfaction is explained by our model (R2 = 0.77). Furthermore, 18% (R2 = 0.18) of the variation in Intention to Switch was explained by the model. Stone-Geiser Q2 for the endogenous showed that the proposed Structural Equation Model exhibited sufficient predictive relevance. Conclusions were drawn with practical implications of the results also discussed

Factors Affecting MOOC Usage by Students in Selected Ghanaian Universities

There has been widespread criticism about the rates of participation of students enrolled on MOOCs (Massive Open Online Courses), more importantly, the percentage of students who actively consume course materials from beginning to the end. The current study sought to investigate this trend by examining the factors that influence MOOC adoption and use by students in selected Ghanaian universities. The Unified Theory of Acceptance and Use of Technology (UTAUT) was extended to develop a research model. A survey was conducted with 270 questionnaires administered to students who had been assigned MOOCs; 204 questionnaires were retrieved for analysis. Findings of the study show that MOOC usage intention is influenced by computer self-efficacy, performance expectancy, and system quality. Results also showed that MOOC usage is influenced by facilitating conditions, instructional quality, and MOOC usage intention. Social influence and effort expectancy were found not to have a significant influence on MOOC usage intention. The authors conclude that universities must have structures and resources in place to promote the use of MOOCs by students. Computer skills training should also be part of the educational curriculum at all levels. MOOC designers must ensure that the MOOCs have good instructional quality by using the right pedagogical approaches and also ensure that the sites and learning materials are of good quality