{"title":"用改进的 AHP-ISM 方法创建 MaaS 就绪指数","authors":"Attila Aba, Domokos Esztergár-Kiss","doi":"10.1016/j.commtr.2024.100122","DOIUrl":null,"url":null,"abstract":"<div><p>Smart mobility solutions are trending in the mobility domain realized through pilot activities and commercial solutions, but there is a lack of a broad framework defining the readiness to introduce such mobility solutions in a specific area. In this research, smart mobility solutions are examined in the perspective of the Mobility-as-a-Service (MaaS) scheme that is an adequate representation of the maturity of a region regarding smart mobility solutions including technology, business, and coopetition aspects. These three aspects define the feature selection, whereas surveys are used to collect input data from local experts (LEs). For weighting the features, the analytic hierarchy process (AHP) is used with a modified interpretive structural modeling (ISM). With this modification, an expert-friendly process is developed without affecting the results. The elaborated MaaS readiness index (MRI) is applied to six regions with different types of mobility related pilot activities to demonstrate the MRI as a comparison tool between regions and between ex-ante and ex-post pilot activities. The developed interpretive structural modeling with Graph (ISM-G) methodology requites remarkably less work from the evaluators compared to the ISM, while no important difference appeared in the results. The MRI can support smart mobility related pilot evaluations, whereas the ISM-G can be used widely in decision-making.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":null,"pages":null},"PeriodicalIF":12.5000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424724000052/pdfft?md5=47cf8eb5c19c492c8387d92054f3fc47&pid=1-s2.0-S2772424724000052-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Creation of the MaaS readiness index with a modified AHP-ISM method\",\"authors\":\"Attila Aba, Domokos Esztergár-Kiss\",\"doi\":\"10.1016/j.commtr.2024.100122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Smart mobility solutions are trending in the mobility domain realized through pilot activities and commercial solutions, but there is a lack of a broad framework defining the readiness to introduce such mobility solutions in a specific area. In this research, smart mobility solutions are examined in the perspective of the Mobility-as-a-Service (MaaS) scheme that is an adequate representation of the maturity of a region regarding smart mobility solutions including technology, business, and coopetition aspects. These three aspects define the feature selection, whereas surveys are used to collect input data from local experts (LEs). For weighting the features, the analytic hierarchy process (AHP) is used with a modified interpretive structural modeling (ISM). With this modification, an expert-friendly process is developed without affecting the results. The elaborated MaaS readiness index (MRI) is applied to six regions with different types of mobility related pilot activities to demonstrate the MRI as a comparison tool between regions and between ex-ante and ex-post pilot activities. The developed interpretive structural modeling with Graph (ISM-G) methodology requites remarkably less work from the evaluators compared to the ISM, while no important difference appeared in the results. The MRI can support smart mobility related pilot evaluations, whereas the ISM-G can be used widely in decision-making.</p></div>\",\"PeriodicalId\":100292,\"journal\":{\"name\":\"Communications in Transportation Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":12.5000,\"publicationDate\":\"2024-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772424724000052/pdfft?md5=47cf8eb5c19c492c8387d92054f3fc47&pid=1-s2.0-S2772424724000052-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Transportation Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772424724000052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TRANSPORTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Transportation Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772424724000052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION","Score":null,"Total":0}
Creation of the MaaS readiness index with a modified AHP-ISM method
Smart mobility solutions are trending in the mobility domain realized through pilot activities and commercial solutions, but there is a lack of a broad framework defining the readiness to introduce such mobility solutions in a specific area. In this research, smart mobility solutions are examined in the perspective of the Mobility-as-a-Service (MaaS) scheme that is an adequate representation of the maturity of a region regarding smart mobility solutions including technology, business, and coopetition aspects. These three aspects define the feature selection, whereas surveys are used to collect input data from local experts (LEs). For weighting the features, the analytic hierarchy process (AHP) is used with a modified interpretive structural modeling (ISM). With this modification, an expert-friendly process is developed without affecting the results. The elaborated MaaS readiness index (MRI) is applied to six regions with different types of mobility related pilot activities to demonstrate the MRI as a comparison tool between regions and between ex-ante and ex-post pilot activities. The developed interpretive structural modeling with Graph (ISM-G) methodology requites remarkably less work from the evaluators compared to the ISM, while no important difference appeared in the results. The MRI can support smart mobility related pilot evaluations, whereas the ISM-G can be used widely in decision-making.