A LINEAR PROGRAMMING APPROACH TO ANALYZE MUSCULOSKELETAL DISORDER RISK FACTORS IN HAZELNUT HARVESTING WORKERS

Abstract

Harvesting hazelnuts is a labor-intensive agricultural activity crucial for sustaining the global nut industry. Despite its significance, this activity poses a potential risk to workers’ musculoskeletal health due to the demanding nature of the work. This study proposes a linear programming approach to analyze risk factors associated with work-related musculoskeletal disorders among hazelnut harvesting workers. The initial phase of the study includes the identification of key risk factors through a literature review, field observations, and expert consultations. An expert team is formed to evaluate these factors from both academic and producer perspectives. The selection of the experts is done by considering their experience, educational background, knowledge, and publications relevant to the research topic. To determine the importance of the factors, the LP-GW-AHP method (a linear programming method to generate weights in the analytic hierarchy process) is employed. Once the pairwise comparison matrix is established, a mathematical model is created to obtain optimal weights. Additionally, a comparative analysis is conducted to support the validity of the model results. According to the results, harvest area, repetitive movements, and prolonged standing are the top three most important factors. Furthermore, the least important factors are determined to be experience, vibration, and mental and occupational stress. This study presents its novelty by formulating the evaluation of musculoskeletal disorder risk factors as a linear programming-driven multicriteria decision-making problem and applying the LP-GW-AHP method to the problem.