Determinants of Bank Deposits in Ghana: A Cointegration Approcah

The study investigates the influence of selected macroeconomic and financial level variables on bank deposits in Ghana. It specifically examines the dynamic effect of deposit interest rate, inflation, monetary policy rate, growth of money supply and stock prices (All Share Index) on the level of bank deposits. The dataset for the study consisted of quarterly data spanning the years of 2000 to 2013 gathered from the Bank of Ghana (BoG) monetary time series database and the World development Indicator (WDI) database. Employing a Co-integration analysis and Fully Modified Ordinary Least Square (FMOLS), both short and long run elasticity’s of the model are estimated. The preliminary test for unit root indicated that all the variables are integrated of order one (an I (1) process) and the co-integration revealed the presence of one co-integrating equation. Empirical findings form the study indicates a significantly negative short-term impact of both inflation and growth of money supply of bank deposits in Ghana. The long-run effects of the various independent variables on bank deposit are also discussed. Some of the variables conformed to priori expectations, albeit insignificant. Appropriate measures are also recommended based on the findings thereof

Determinants of Bank Deposits in Ghana: A Cointegration Approcah

The study investigates the influence of selected macroeconomic and financial level variables on bank deposits in Ghana. It specifically examines the dynamic effect of deposit interest rate, inflation, monetary policy rate, growth of money supply and stock prices (All Share Index) on the level of bank deposits. The dataset for the study consisted of quarterly data spanning the years of 2000 to 2013 gathered from the Bank of Ghana (BoG) monetary time series database and the World development Indicator (WDI) database. Employing a Co-integration analysis and Fully Modified Ordinary Least Square (FMOLS), both short and long run elasticity’s of the model are estimated. The preliminary test for unit root indicated that all the variables are integrated of order one (an I (1) process) and the co-integration revealed the presence of one co-integrating equation. Empirical findings form the study indicates a significantly negative short-term impact of both inflation and growth of money supply of bank deposits in Ghana. The long-run effects of the various independent variables on bank deposit are also discussed. Some of the variables conformed to priori expectations, albeit insignificant. Appropriate measures are also recommended based on the findings thereof

Applying a Fuzzy Analytic Hierarchy Process to Demand Considerations of Households Opting for Mortgage Loans

The need for high economic development across the entire globe and Sub-Saharan Africa in particular has led to the awareness of the need to increase the housing base across the continent. The astronomical increase in population and urbanisation and its associated problems of accommodation call for the need to provide good housing for the people of Ghana; the provision of which could depends largely on the availability of mortgage facilities. However, obtaining the right mortgage is as crucial as obtaining the right home, yet buyers seemingly do not invest as much time and effort in a mortgage search as in house searches. It is against this backdrop that this study investigates factors considered by households before acquiring mortgage loans. A questionnaire was administered within the Accra metropolis, the area of Ghana with the most mortgage loan providers. We employed the fuzzy analytic hierarchy process (FAHP) to analyze the thought processes of households when making their decisions on acquiring a mortgage loan. The results indicated that factors considered by households when opting for a mortgage loan, ordered based on their degree of importance, were "Employment", "Housing Market Conditions", "Personal Factors", "Economic Factors", "Mortgage Lender Policy", "Housing Alternatives", "Knowledge", and "Social Factors". The weights of the first four factors were as high as 70.99% (Buckley’s method) and 69.70% (Chang’s method). These four items, have the most impact on household demand considerations when opting for a mortgage loan. If these factors are significantly improved, then, they can have a positive microeconomic impact on actual households demand for mortgage loans, in turn making the mortgage market a lucrative business

Applying a Fuzzy Analytic Hierarchy Process to Demand Considerations of Households Opting for Mortgage Loans

The need for high economic development across the entire globe and Sub-Saharan Africa in particular has led to the awareness of the need to increase the housing base across the continent. The astronomical increase in population and urbanisation and its associated problems of accommodation call for the need to provide good housing for the people of Ghana; the provision of which could depends largely on the availability of mortgage facilities. However, obtaining the right mortgage is as crucial as obtaining the right home, yet buyers seemingly do not invest as much time and effort in a mortgage search as in house searches. It is against this backdrop that this study investigates factors considered by households before acquiring mortgage loans. A questionnaire was administered within the Accra metropolis, the area of Ghana with the most mortgage loan providers. We employed the fuzzy analytic hierarchy process (FAHP) to analyze the thought processes of households when making their decisions on acquiring a mortgage loan. The results indicated that factors considered by households when opting for a mortgage loan, ordered based on their degree of importance, were "Employment", "Housing Market Conditions", "Personal Factors", "Economic Factors", "Mortgage Lender Policy", "Housing Alternatives", "Knowledge", and "Social Factors". The weights of the first four factors were as high as 70.99% (Buckley’s method) and 69.70% (Chang’s method). These four items, have the most impact on household demand considerations when opting for a mortgage loan. If these factors are significantly improved, then, they can have a positive microeconomic impact on actual households demand for mortgage loans, in turn making the mortgage market a lucrative business

Exploring the factors that enhance student–content interaction in a technology-mediated learning environment

The authors discuss the results of a study that was conducted on the factors that enhance effective interaction between students and learning contents in a technology-mediated learning environment in a higher education setting. The results revealed that effective student–content interaction is strongly enhanced by expansive learning through its five key elements; epistemic relation, contradictions, digital learning content, conglomeration of views and cognitive transformation. The intervening effect of network relations and mediating technology was also highlighted therefore, revealing the positive impact of both factors in enhancing effective student-content interaction. The empirical methods employed by the authors were focus group interview (n = 12) and questionnaire (n = 500) among students in a university. While Structural equation modelling was used to analyse the quantitative data, the focus group interviews were analysed using categories, themes and concepts. The authors present the findings and implications of the study by way of theory, practice and further research in the study

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

RecGuard: An efficient privacy preservation blockchain-based system for online social network users

Recommendation systems provide ease and convenience for users to address information overload problems while interacting with online platforms such as social media and e-commerce. However, it raises several questions about privacy, especially for users who prefer to remain anonymous, especially on online social networks (OSNs). Moreover, due to the commercialization of online users' data, some service providers sell users' data to third parties at the blind side of the users, which leads to trust issues between users and service providers. Such matters call for a system that gives online users much-needed control and autonomy of their data. With the advancement of blockchain technology, many research institutions are experimenting with decentralized technologies to resolve the OSN user dilemma of privacy intrusion against third parties and hacks. To resolve these limitations, we propose RecGuard, a privacy preservation blockchain-based network system. We developed two smart contracts, RG-SH and RG-ST, to ensure the security and privacy of user data. The RG-SH manages user data, whereas the RG-ST stores data. A graph convolutional network (GCN) was integrated with the blockchain-based system to detect malicious nodes. Finally, we implemented our framework prototype on a locally simulated network. The analysis and experiment results show that the proposed scheme demonstrates the effectiveness and privacy of users in our framework