Thesis:

Influence of operational planning on financial performance of Airlines in Wilson airport in Kenya

This study explores the influence of operational planning decisions on the financial performance of airlines operating at Wilson Airport, Kenya. Financial performance in the aviation sector is critical for the sustainability and competitiveness of airlines, yet many struggle with high operational costs and fluctuating demand. This research examined the direct impact of four key operational planning decisions—fleet planning, aircraft route planning, crew pairing planning, and schedule development planning—on airline financial performance. The study was framed within the Resource-Based View (RBV) and Systems Theory, with the RBV emphasizing internal resource management as a source of competitive advantage, while Systems Theory underscores the interdependence of organizational components. The target population consisted of employees from eight airlines at Wilson Airport, totaling 300 employees, with a sample of 171 participants selected using purposive and random sampling methods. Data were collected through structured questionnaires and key informant interviews with eight airline managers. A pilot test was conducted with 17 respondents to ensure the reliability and validity of the research instruments, with the results confirming high reliability (Cronbach's Alpha = 0.85). Quantitative data were analyzed using descriptive and inferential statistics, including correlation and multiple regression analysis. The study found that schedule development (β = 0.491, t = 4.255, p < 0.05) and aircraft routing (β = 0.482, t = 5.309, p < 0.05) had the strongest positive impact on financial performance, followed by fleeting (β = 0.373, t = 9.325, p < 0.05) and crew pairing (β = 0.257, t = 3.337, p < 0.05). The model explained 82.6% (R² = 0.826) of the variation in financial performance. The study concludes that operational planning decisions, particularly schedule development, aircraft routing, fleeting, and crew pairing, significantly influence the financial performance of airlines. The findings highlight that optimizing these planning decisions can lead to improved profitability, cost efficiency, and revenue generation. The study emphasizes that airlines need to adopt data-driven and strategic approaches to enhance operational efficiency and financial sustainability. The study recommends that airline management focus on data-driven fleet planning, route optimization, and intelligent scheduling systems to maximize profitability. Additionally, policymakers should improve the regulatory environment by providing tax incentives, investing in aviation infrastructure, and facilitating streamlined licensing procedures to support airline efficiency. Further research should explore the role of emerging technologies, such as artificial intelligence and big data, in operational planning, and investigate best practices across different regions to enhance the global competitiveness of airlines.