International Journal of Multidisciplinary Research and Studies

Evaluating the Influence of the Work Environment on the Service Quality–Customer Retention Nexus in Ugandan Guesthouses

2026-02-05T05:35:18+00:00

The hospitality sector in developing economies relies heavily on service quality as a strategic mechanism for retaining customers. In Uganda, guesthouses play a critical role in tourism and local economic development, yet they face persistent challenges related to employee working conditions, service consistency, and customer loyalty. This study examines how the work environment shapes the relationship between service quality and customer retention in Ugandan guesthouses. Grounded in service management theory and the service–profit chain framework, the study adopts a quantitative explanatory approach. Data were collected from employees and customers of selected guesthouses in Uganda and analyzed using moderated regression techniques. The findings reveal that service quality has a significant positive effect on customer retention, and that the work environment significantly moderates this relationship. A supportive, safe, and empowering work environment strengthens employees’ service delivery, leading to enhanced customer satisfaction and repeat patronage. The study contributes to hospitality management literature by emphasizing the strategic importance of internal work conditions in sustaining customer relationships in small-scale accommodation establishments.

An Empirical Study on Energy Efficiency and Solution Effectiveness of Evolutionary Algorithms

2026-02-05T05:44:34+00:00

The rapid growth of computational intelligence and large-scale optimization has raised concerns regarding the energy consumption and environmental impact of algorithmic processes. Evolutionary Algorithms (EAs), while widely recognized for their robustness and flexibility in solving complex optimization problems, often require extensive computational resources, which directly translate into increased energy usage. This study presents an empirical comparison of several widely used evolutionary algorithms by jointly analyzing their energy consumption and the quality of solutions they produce. Through standardized experimental setups and benchmark optimization problems, the trade-offs between solution optimality and energy efficiency are investigated. Energy metrics are analyzed alongside convergence behavior and final fitness values to provide a holistic assessment of algorithmic performance. The findings highlight that energy-efficient algorithm design and implementation choices can significantly influence sustainability without severely compromising solution quality. This study contributes to the emerging field of energy-aware evolutionary computation by offering experimental evidence and practical insights for researchers and practitioners.