This paper explores how strategic management practices determine the performance of organizations at Jomo Kenyatta International Airport (JKIA), in particular, goal setting and resource management. JKIA, being a large regional aviation center, is in a challenging and competitive environment, where resource leveraging and strategic focus are critical to the success of its operations. The use of the goal-setting theory and the resource-based view underpinned the study with the descriptive research design and gathered quantitative information, including 91 employees operating in major aviation institutions in JKIA, namely the Kenya Airports Authority, Kenya Civil Aviation Authority, Kenya Airways, and the Kenya Bureau of Standards. The data were studied with the help of descriptive statistics, correlation, and regression methods. The outcome is that participatory goal setting is a significant approach in improving performance in an organization through the promotion of clarity, coordination, and motivation of the employees. Resource management was also established to be a good predictor of performance, especially by means of good allocation of financial, human, and technological resources. The two variables used together accounted for a significant percentage of performance variation at JKIA. The research suggests the institutionalization of participatory goal-setting frameworks, the reinforcement of resource optimization strategies, such as digital investment and staff capacity building. Future studies ought to take into consideration more of the moderating variables which include leadership style and innovation capability

This study's main objective was to examine the relationship between various leadership styles and employee productivity at Kenya's Rural Electrification and Renewable Energy Corporation (REREC). The research intended to evaluate the effect of transformational leadership styles on employee output at REREC, utilizing four leadership approaches: situational, participative, transformational, and transactional leadership. The research was structured around three theories: the path-goal theory, situational leadership as proposed by Hersey and Blanchard, and Keller's ARCS model of motivation. A descriptive survey methodology was employed. The study involved 199 participants from the Finance, Human Resources, Operations, Technical Services, Planning, and Procurement divisions at REREC's headquarters in Nairobi County, as well as interviews with six top managers from these divisions. A census sampling approach was used to select all 199 respondents. Both closed- and open-ended surveys were utilized, and SPSS version 26 software was used for quantitative analysis. The investigation determined that transformational leadership exhibited the highest positive correlation with employee performance (r = 0.75) and was the most significant predictor (β = 0.45, p < 0.01). Participative (r = 0.72) and situational (r = 0.70) leadership styles also demonstrated strong positive impacts on performance. Transactional leadership had a moderate correlation (r = 0.68) and was effective in structured environments but less impactful for driving long-term innovation and satisfaction. The study concluded that integrating multiple leadership approaches tailored to organizational contexts is crucial for maximizing employee performance. Transformational leadership, fostering motivation and engagement, emerged as the most effective style at REREC. Recommendations included implementing leadership development programs, enhancing employee engagement strategies, adopting data-driven leadership approaches, and continuously adapting leadership models to align with evolving workplace trends.

Universities are key sources of knowledge and serve as important channels for disseminating information through teaching, training, research, and community engagement. To remain competitive and fulfill their mission and vision, universities need to adopt enabling technologies such as cloud computing. This study aimed to examine how cloud-computing services influence organizational performance, focusing on private universities, with a case study of the Management University of Africa (MUA). The specific objective in the research is to assess the effect of cloud services adoption, the influence of cost efficiency. The research utilized the Resource-Based View (RBV) theory. Descriptive statistics were used to explore the relationships among cloud service adoption and organizational performance, while inferential statistics were applied to draw conclusions and generalizations. The results revealed that both cloud service adoption and cost efficiency had a strong positive influence on performance, with correlation coefficients of 0.929 and 0.934, respectively. The overall model explained approximately 89% of the variation in performance, underscoring cloud computing and cost management as critical drivers of success. The study concludes that private universities can significantly enhance their performance by effectively leveraging cloud services and managing costs efficiently, while also optimizing the use of time, personnel, and other resources. Recommendations include improving system integration, involving more staff in budgeting processes, and using data-driven approaches for decision-making. Future research should expand the scope to include more universities and consider qualitative methods such as interviews or focus groups for deeper insights.

Public procurement has attracted a lot of scholarly work in the recent past and particularly after the covid 19 pandemic. Majority of the firms in the hospitality sector suffered a lot of losses following the lockdowns and lack of customer contact during and after the pandemic. To date most of the hospitality firms are still faced with a lot of challenges following stringent rules and regulations put in place following the effect of covid 19 pandemic. This calls for further studies to fill the theoretical and practical gaps that exists in the literature. The purpose of this study therefore was to assess the effect of public procurement practices adopted after the pandemic on performance of firms in the hospitality industry in Kenya with a focus on selected hostels in Narok County. Institutional theory and resourcebased view underpinned the study. A descriptive survey design was used for the investigation. The study targeted a population of 30 Managers and over 950 staff in the hotel industry in Narok Town. Data was collected from the management and suppliers of the chosen hotels using a structured questionnaire. To evaluate the validity and reliability of the research tools, a pilot study was conducted. Both descriptive and inferential analyses were used to examine the data. The frequency, percentage, averages, and variances were calculated for descriptive statistics. Data analysis was done with the help of SPSS version 28 and MS Excel software. The study established that supplier diversity had a significant effect on performance of hospitality firms in Narok County. The study concluded that procurement practices adopted by firms in the hospitality sector had a statistically significant effect on the performance of the Hospitality sector. The study concluded that to enhance performance, hospitality companies should implement the most effective supplier diversification initiatives. Further research ought to be done to examine how firms in other sectors of the economy have dealt with post-COVID-19 challenges and the effect it has had on performance.

This research paper examines how Artificial Intelligence (AI) can be used to improve the organisational development of the Tanzania Breweries Limited (TBL) production in Tanzania. The study particularly looks at the role of technology, organisation, and environment in the adoption of AI and the resulting effects on the efficiency of operations, working capacity, and the resulting innovation. The research is based on the Technology-Organisation-Environment (TOE) framework, which makes it a welldeveloped theoretical foundation to comprehend the use of AI in the manufacturing setting. The quantitative research design was used, and the goal was 450 employees working in the TBL production departments. The sample size was calculated using the Yamane formula, and primary data were collected using structured questionnaires. The collected data were also compared through the summated index, descriptive statistics, and hypothesis tests to assess the association between variables and find out the mediating value of AI adoption. The results indicate that AI is significantly adopted in response to technological readiness, such as system maturity, compatibility, and ease of use. The environmental factors, including regulatory compliance, competition in the market, and industry support, have a moderate impact on the adoption decisions, whereas the type of organisational factors, including leadership support, workforce skills, culture of innovation, and resource allocation, have a critical effect on the adoption decisions. The adoption of AI is a mediating variable which converts the elements of readiness into quantifiable operational efficiency, capacity of the workforce, and improved innovation outcomes. The research arrives at the conclusion that successful AI implementation is a multi-faceted process that involves investments in technologies, the ability of organisations to develop, and adaptability to environmental factors. The findings are relevant to the theory due to their support of the TOE framework in the Tanzanian manufacturing environment and practical information to practitioners who want to use AI to improve their operations and strategies. The policy implication is clarity of the regulations, industry-supportive programs, and easy access to technical expertise to make AI adoption easy. Lastly, the paper gives future research for studies such as longitudinal studies on the long-term effects of AI and investigations into newer technologies like the IoT and machine learning in improving organisational development.