{"title":"基于熵-层次分析法的智能物流驾驶员评价系统设计","authors":"Xiuhui Wang, Xiaoyu Ma, Jing Fan, Qiongwei Ye","doi":"10.1109/ICSSSM.2019.8887599","DOIUrl":null,"url":null,"abstract":"Based on the analysis of current research in performance evaluation of logistics and the practical operation mode of x company, this paper integrates all the factors that may affect performance evaluation of distribution and finally selects 11 indicators to make a comprehensive performance evaluation of drivers. These indicators are classified as four dimensions: total amount of work, transportation quality, service level and execution. Entropy weight method and analytic hierarchy process (AHP) are adopted to determine the comprehensive weight of each indicator, which is also enriched by the introduction of region factor. Besides, the drivers' individual relative progress factor is added into this evaluation model to better measure their efforts. In the empirical analysis of x company, the rationality and performability of the model are tested by comparing with the previous performance evaluation result. The result showed that this improved model could fully reflect the performance of logistics drivers and make effective distinctions between them. Also, this model can provide a basis for subsequent salary assessment and task allocation priority. What's more, it has practical significance for encouraging drivers to carry out tasks obeying the algorithm instructions.","PeriodicalId":442421,"journal":{"name":"2019 16th International Conference on Service Systems and Service Management (ICSSSM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Design of Intelligent Logistics Drivers Evaluation System-Based on Entropy-AHP Method\",\"authors\":\"Xiuhui Wang, Xiaoyu Ma, Jing Fan, Qiongwei Ye\",\"doi\":\"10.1109/ICSSSM.2019.8887599\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the analysis of current research in performance evaluation of logistics and the practical operation mode of x company, this paper integrates all the factors that may affect performance evaluation of distribution and finally selects 11 indicators to make a comprehensive performance evaluation of drivers. These indicators are classified as four dimensions: total amount of work, transportation quality, service level and execution. Entropy weight method and analytic hierarchy process (AHP) are adopted to determine the comprehensive weight of each indicator, which is also enriched by the introduction of region factor. Besides, the drivers' individual relative progress factor is added into this evaluation model to better measure their efforts. In the empirical analysis of x company, the rationality and performability of the model are tested by comparing with the previous performance evaluation result. The result showed that this improved model could fully reflect the performance of logistics drivers and make effective distinctions between them. Also, this model can provide a basis for subsequent salary assessment and task allocation priority. What's more, it has practical significance for encouraging drivers to carry out tasks obeying the algorithm instructions.\",\"PeriodicalId\":442421,\"journal\":{\"name\":\"2019 16th International Conference on Service Systems and Service Management (ICSSSM)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 16th International Conference on Service Systems and Service Management (ICSSSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSSM.2019.8887599\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 16th International Conference on Service Systems and Service Management (ICSSSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2019.8887599","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of Intelligent Logistics Drivers Evaluation System-Based on Entropy-AHP Method
Based on the analysis of current research in performance evaluation of logistics and the practical operation mode of x company, this paper integrates all the factors that may affect performance evaluation of distribution and finally selects 11 indicators to make a comprehensive performance evaluation of drivers. These indicators are classified as four dimensions: total amount of work, transportation quality, service level and execution. Entropy weight method and analytic hierarchy process (AHP) are adopted to determine the comprehensive weight of each indicator, which is also enriched by the introduction of region factor. Besides, the drivers' individual relative progress factor is added into this evaluation model to better measure their efforts. In the empirical analysis of x company, the rationality and performability of the model are tested by comparing with the previous performance evaluation result. The result showed that this improved model could fully reflect the performance of logistics drivers and make effective distinctions between them. Also, this model can provide a basis for subsequent salary assessment and task allocation priority. What's more, it has practical significance for encouraging drivers to carry out tasks obeying the algorithm instructions.