Eli Fianu

This chapter proposes a comprehensive conceptual model that synthesizes evidence from the blockchain and pharmaceutical supply chain literature together with insights obtained from three representative blockchain implementation projects: PharmaLedger, PharmaChain, and BRUINchain. The study adopts a four-phase conceptual research methodology. The resulting model consists of a blockchain-enabled pharmaceutical supply chain architecture that integrates digital identity management, permissioned blockchain networks, smart contracts, interoperability mechanisms, distributed ledger technology, governance structures, and advanced cryptographic security. The proposed framework extends existing blockchain-pharmaceutical supply chain models by integrating technical architecture, governance mechanisms, stakeholder interactions, and operational processes into a unified conceptual representation. The chapter contributes to both theory and practice by providing researchers with a comprehensive conceptual foundation for future empirical investigations.

This study investigates how generative AI affects employee job performance in small and medium-sized enterprises (SMEs) within Ghana's education sector, using the Task-Technology Fit (TTF) framework integrated with Technology Acceptance Model 2 (TAM2). It addresses three main objectives: evaluating the fit between AI technology and employee tasks, examining how this fit and AI usage impact job performance, and exploring how perceived usefulness influences intention to use AI. A quantitative approach was used, with data from 246 SME employees in Greater Accra, analyzed through structural equation modelling. All seven proposed hypotheses were supported. Task characteristics strongly influenced task-technology fit, which positively affected both AI usage and task performance. Generative AI usage significantly improved performance, while social influence shaped perceived usefulness, which in turn influenced usage intention. The study highlights the importance of aligning AI tools with task needs and enhancing perceived usefulness to boost adoption and job performance in educational SMEs.

The study sought to investigate the service quality of chatbots on telecom service providers' websites and apps. The research model was based on an integration of the expectation confirmation model of IS, the E-S-Qual model, and the technology anxiety construct. The study used a quantitative research design. Data were collected from 263 chatbot users; however, after data cleaning, 255 responses were retained. Data analysis was done using structural equation modelling. The results show significant relationships between confirmation and perceived usefulness, as well as confirmation and satisfaction. Additionally, efficiency and privacy constructs of the E-S-Qual model have significant effects on satisfaction. Post-use confirmation, efficiency, and privacy have the most significant impacts on chatbot usage satisfaction of customers on telecom service providers' websites and apps. Technology anxiety could not significantly mediate the relationship between the E-S-Qual model constructs and post-use confirmation. Request access from your librarian to read this chapter's full text.

The study sought to examine the task-technology fit of ChatGPT for healthcare services. The research model was based on an integration of the task-technology fit (TTF) model and the technology acceptance model 2 (TAM2). The study used a quantitative research design. Data were collected from 265 health workers who have used ChatGPT in the performance of their work. Data analysis was done using structural equation modelling. Six of the seven hypotheses were accepted. The results show significant positive relationships between task characteristics and task-technology fit, task-technology fit and ChatGPT usage, ChatGPT usage and performance impacts, social influence and perceived usefulness, perceived usefulness and usage intention, as well as usage intention and ChatGPT usage. There was an insignificant positive relationship between task-technology fit and performance impacts.

The study sought to statistically compare separate sets of scores of graded essays generated from an automated essay scoring (AES) system (ChatGPT) and a human grader, and further engage stakeholders (students, lecturers, and university management) in a discussion of the results of the analysis from the perspective of fairness, bias, consistency with human grading, ethical issues, and adoption. The study adopted a sequential explanatory mixed methods design. The quantitative approach involved the collection and analysis of essay scores while the qualitative approach involved the use of interviews to ascertain stakeholder opinions of the quantitative results. The results of the quantitative study showed that the distribution of ChatGPT scores is the same across categories of age, gender, and ethnicity. Also, there was no statistically significant difference between ChatGPT scores and the scores of the human grader. The analysis of the responses from the interviews are thoroughly discussed. Request access from your librarian to read this chapter's full text.

The chapter attempts to unravel the factors that influence citizens' usage of an e-government location-based service, the Ghana Post GPS. The research model comprises a set of relationships between constructs from UTAUT (effort expectancy, performance expectancy, and social influence; age and gender as moderating variables), the model of PC utilization (complexity and affect towards use), TAM2 (output quality, intention to use, and actual usage). A quantitative research design was used for the study. The sample consisted of three hundred and thirty-seven (337) respondents. Data was analysed using PLS-SEM (partial least squares structural equation modelling) via SmartPLS 3. Twelve (12) hypotheses were tested; eight (8) were rejected while four (4) were accepted. The results are thoroughly discussed, and relevant recommendations made. Request access from your librarian to read this chapter's full text.

The study sought to investigate the determinants of MoMo fraud perception in C2C e-commerce from a trust perspective. The research model comprises a set of relationships between constructs from empirical studies. The constructs are culture (uncertainty avoidance), perceived reputation of mobile service provider, trust in C2C trader, structural assurance, perceived usefulness, and consumer fraud perception. A quantitative research design was used for the study. The sample consisted of three hundred and eighty-seven (387) respondents. Data were analysed using PLS-SEM (partial least squares structural equation modelling) via SmartPLS 3. Culture (uncertainty avoidance) was found to have a significant negative influence on consumer fraud perception. Perceived reputation of the mobile service provider was found to have an insignificant influence on consumer fraud perception. Trust in C2C trader, structural assurance, and perceived usefulness were found to have a significant positive influence on consumer fraud perception.

The study sought to determine factors that significantly influence university students’ continuance use of Zoom in blended learning arrangements in the post-Covid era. Zoom Cloud Meetings is a proprietary video teleconferencing software program developed by Zoom Video Communications. Zoom became one of the e-learning platforms that gained attention in the education sector in Ghana after the COVID-19 pandemic outbreak and has been widely used by educational institutions for online lectures. The research model comprises a set of relationships between constructs from the Information System (IS) success model (system quality, usage intention, and user satisfaction), Expectation Confirmation Model (ECM) of IS (perceived usefulness and usage continuance), and two constructs identified from empirical review (instructional quality and computer self-efficacy). Three hundred and thirty-five (335) students from selected universities in Ghana who partake in Zoom-based lectures completed an online survey via Google forms. Survey data were analysed using partial least squares structural equation modelling (PLS-SEM). Lecturers and management of universities will find the study useful for the improvement of teaching and learning via Zoom-based lectures.