Different Approaches for Performance Appraisal and Bonus Calculation: The Case of Truck Drivers

Journal Title: Journal of Intelligent Management Decision - Year 2022, Vol 1, Issue 2

Abstract

Market changes last years have led to an additional understanding of people importance as the main resources of companies. Truck drivers are one of the occupations with the greatest shortage. More attention is being paid to ways of retaining employees. One of the most important measures is bonus or reward. There is a lack of models in the literature and it is exactly the main motive of this research. Proposed models create a basis for future theoretical research, but also for practical applications. The main assumption is that models must provide a fair way to earn bonuses in a "healthy environment". Two models are proposed. The first model for distribution company with a heterogeneous fleet of vehicles with less capacity. The second model refers to homogenous heavy truck fleet. In the first case, several criteria are used: distance (kilometers) driven, number of tours/rides, number of unloading stops and number of pallets. The second model is based on fuel consumption, distance driven, vehicle maintenance, driver experience (years in the company) and overall dispatcher score. The results show the convenience of applying the proposed models. Certain differences were also identified in the observed models. It can be concluded that there is no universal model for performance appraisal and bonus calculation. Ideas for overcoming and improving models are also proposed. Described models in original or adapted form can be applied to evaluate the performance of drivers in a wide variety of transport systems.

Authors and Affiliations

Milan Andrejić

Keywords

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  • EP ID EP752341
  • DOI https://doi.org/10.56578/jimd010203
  • Views 36
  • Downloads 0

How To Cite

Milan Andrejić (2022). Different Approaches for Performance Appraisal and Bonus Calculation: The Case of Truck Drivers. Journal of Intelligent Management Decision, 1(2), -. https://europub.co.uk./articles/-A-752341