An evaluation of personnel performance in port logistics industry using hybrid multi criteria decision making methods / Muhamad Safuan Shamshol Bahri

Every area of logistics, particularly maritime logistics, is expanding not only in a given country but worldwide. This indicates the demand for competent, imaginative, and capable people to join the workforce. The demand for talents and labour to serve the maritime logistics business, particularly i...

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Bibliographic Details
Main Author: Shamshol Bahri, Muhamad Safuan
Format: Thesis
Language:English
Published: 2022
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Online Access:https://ir.uitm.edu.my/id/eprint/66931/1/66931.pdf
https://ir.uitm.edu.my/id/eprint/66931/
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Summary:Every area of logistics, particularly maritime logistics, is expanding not only in a given country but worldwide. This indicates the demand for competent, imaginative, and capable people to join the workforce. The demand for talents and labour to serve the maritime logistics business, particularly in port operations, is growing as the industry expands globally. To do so, professional competency in terms of manpower and skills must be developed effectively. Furthermore, considering the current pandemic COVID-19 situation, a capable professional in port management is crucial for reviving the business after it has been harmed, as well as maintaining its long-term growth and viability. As a result, a good business performance measurement system is a very powerful instrument for engaging and monitoring a company's employees. Despite the fact that there is a lot of interest and research into developing performance assessment models, finding a well-designed system is rare. This study explores the criteria for needed talent in view of port logistics experts using of multicriteria decision making (MCDM) approaches which is analytical hierarchy process (AHP), technique for order of preference by similarity to ideal solution (TOPSIS) and preference ranking organization system method for enrichment evaluation (PROMETHEE). The objective of this study is to identify the important criteria for personnel performance evaluation in port marine logistics industry. The three (3) approaches are selected based on its ability to consider many criteria simultaneously as well as considering the subjective judgement of importance by the participating experts. For second objective, in order to determine the performance evaluation framework for personnel performance evaluation, the study uses a tri-level hierarchical criteria structure, with three (3) criteria at the first level, six (6) sub-elements at the second level, and 18 sub-elements at the third level (three for each sub-element of the second level). AHP method is used to calculate the weightage of the criteria where the highest weightage is Work Attitude (0.560) followed by Job Performance (0.298) and Work Ability (0.120). Work Attitude scored more than 50% of weightage compared to Job Performance and Work Ability. For last objective, in order to identify the suitable hybrid MCDM approaches for personnel performance evaluation in port marine logistics industry, the weightage from AHP is used to rank the personnel by using three (3) different of MCDM approaches which are AHP, TOPSIS and PROMETHEE. Based on the results, it shows that AHP is the best MCDM method to rank the personnel in port industry by getting the highest Kendall’s Tau coefficient with 0.619 coefficient compared to TOPSIS and PROMETHEE with 0.524 and 0.429 respectively. The same calculation method of Kendall’s Tau rank correlation is used to reconfirm that the proposed weightage of the criteria agrees with the actual evaluation from Sabah Port Sdn Bhd. The results of Kendall’s Tau coefficient are 0.490 which means the variables are correlated. As conclusion, experts in the port logistics industry agreed that AHP application for performance appraisal at the industry is a success, increasing the process accuracy and fairness. It is recommended for researchers to have respondents from more diverse fields in marine logistics such as shipping lines, forwarding and supply chain. By having a diverse range of respondents and experts, the sensitivity of the data is more accurate.