http://ir.mu.ac.ke:8080/jspui/handle/123456789/62 2026-08-25T11:14:45Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10459 Title: Moderating Effect of Tax audit probability on the causality between taxpaying attitudes and tax compliance behavior in restaurant of Uasin Gishu County (Kenya) Authors: Kimitei, Edwin; Kiprono, Eric; Sang, Jane Abstract: We investigated the moderating influence of audit probability on the effect of taxpaying attitudes on tax compliance behaviour in restaurants in Kenya. Four linear regression models were compared. Estimations in the models suggest that taxpayers’ attitudesand audit probability have significant effects on the tax compliance of the restaurants, but the influence of external audit probability is more significant. Estimations in model where taxpaying attitudes without the moderating influence of audit probability exerted a significant effect on tax compliance by 22%, while taxpaying attitudes with the moderating influence of audit probability exerted 27%. Taxpaying attitudes with the moderating influence of the external audit probability dimension hada more significant contribution to the changes in tax compliance. The findings demonstrated that if taxpayers’ attitudes improved and audit probability was leveraged by the tax authorities, tax compliance behaviour of restaurants would be improved for restaurant owners in Kenya. 2024-04-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10458 Title: Effects of learning capabilities on supply chain performance of manufacturing firms In Nairobi, Kenya Authors: Gituiya, Ann; Kimitei, Edwin; Limo, Patrick Abstract: The main purpose of the study was establish the effects of learning capabilities on supply chain performance of manufacturing firms in Nairobi, Kenya. The study was guided by Resource Based View Theory. The study adopted explanatory research design. The study targeted a population of 750 registered manufacturing firms in Nairobi. The sample size is of the study was 261 procurement managers. The study used questionnaire as the main data collection instruments to collect primary data. Quantitative data collected using the questionnaires for all the objectives were analysed using descriptive statistics that is frequency, percentages, mean and standard deviation. Frequency tables were used to present the findings in relation to the objectives of the study. The inferential statistics used in this study were correlation and regression models. The study findings indicated that learning capabilities and supply chain performance of manufacturing firms had a positive strong and statistically significant correlation (r= 0.743; p<0.05). This implies that information sharing within departments enhances supply chain performance. The study concluded that leveraging learning capabilities, manufacturing firms can adapt to evolving market dynamics, anticipate changes in customer demands, and optimize their supply chain operations to achieve sustainable competitive advantage in the dynamic business landscape. The study recommends that manufacturing firms should ensure there exist proper company policy for sharing information within the company 2024-10-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10457 Title: Effect of supply chain digitization on firm performance in Government state corporations in Kenya Authors: Mulwa, Linet; Kimitei, Edwin; Zurah, Mohammed Abstract: Firm performance is a key determinant of business success, influencing operational efficiency, customer satisfaction, and profitability. To remain competitive and enhance performance, businesses are increasingly turning to supply chain digitalization as a strategic tool. However, past studies have not sufficiently linked supply chain digitalization with other critical business aspects. This study aimed to examine the effect of supply chain digitization on the performance of state corporations in Nairobi County, Kenya, focusing on the impact of electronic tendering, enterprise resource planning, cloud computing, and artificial intelligence on firm performance. The study was guided by the Resource-Based View Theory and the Technology Acceptance Model (TAM). An explanatory research design was used, targeting 411 state corporations registered with the Kenya National Bureau of Statistics. A sample size of 203 firms was selected through stratified and simple random sampling. Data collection was done using structured questionnaires, with a five-point Likert scale used to capture responses. Descriptive and inferential statistics were applied in data analysis. The study’s hypotheses were tested using linear regression analysis. The results revealed that electronic tendering (β=0.636, p<0.05), enterprise resource planning (β=0.178, p<0.05), cloud computing (β=0.157, p<0.05), and artificial intelligence (β=0.276, p<0.05) had a positive and significant effect on firm performance. The study concluded that digital tools such as these effectively enhance firm performance by improving operational processes, and recommended fostering long-term relationships within the supply chain to support competitiveness. 2025-10-01T00:00:00Z http://ir.mu.ac.ke:8080/jspui/handle/123456789/10456 Title: An evaluation of Kenya TVET Trainers on use of AI in instruction design and delivery Authors: Kimutai, Shadrack K; Kitonyi, Thomas; Kimitei, Edwin K Abstract: The integration of Artificial Intelligence (AI) in education is transforming traditional instructional practices, offering new opportunities for enhancing learning experiences and improving educational outcomes. This study evaluates the utilization of AI in instructional design and delivery among TVET trainers in Kenya. This study sought to evaluate the preparedness and practices of Kenya’s TVET trainers in adopting AI for instruction, through the dual lens of TAM and TPACK frameworks with the specific objectives being: to assess perceived usefulness and perceived ease of use of AI among trainers in instruction design and delivery. to evaluate the technological, pedagogical and content knowledge of trainers on AI integration in their teaching and to examine the relationship between perceived usefulness, perceived ease of use, and technological, pedagogical, and content knowledge among Kenya TVET trainers in relation to their use of AI for instruction. Through a mixed-methods approach, combining quantitative surveys and qualitative interviews with TVET trainers, the study provides insights into the perceptions, experiences, and readiness of trainers to incorporate AI technologies into their teaching practices. Findings suggest a growing interest in AI tools among TVET trainers, yet significant barriers such as lack of training, limited resources, and infrastructural challenges impede widespread adoption. The paper concludes with recommendations for policy makers and educational institutions to support the effective implementation of AI in TVET, emphasizing the need for comprehensive training programs, investment in AI infrastructure, and fostering a collaborative environment for sharing best practices. The study reveals a strong adoption of AI among younger, less-experienced TVET trainers in Kenya, with minimal gender disparity but notable urban-rural differences due to infrastructural limitations. Despite limited formal training, AI use is widespread, particularly for instructional tasks. Trainers value AI’s ability to enhance efficiency, personalization, and engagement. However, challenges include inadequate training structures and insufficient policy guidance. The study recommends integrating AI into teacher training, investing in infrastructure, promoting equity, developing clear policies, fostering partnerships, and establishing monitoring systems to ensure effective, ethical, and inclusive AI integration across the TVET sector. 2025-10-01T00:00:00Z