{"title":"Barrier assessment of EV business model innovation in China: An MCDM-based FMEA","authors":"Yixi Xue, Jiachen Zhang, Yi Zhang, Xiaoyu Yu","doi":"10.1016/j.trd.2024.104404","DOIUrl":null,"url":null,"abstract":"<div><p>Business model innovation is imperative for electric vehicles (EVs) firms to maintain a competitive edge and the transition towards transportation electrification. However, numerous socio-technical barriers are likely to impede this innovation process. This study aims to assess the risks of various barriers through a novel fuzzy multiple-criteria decision-making (MCDM)-based failure mode and effects analysis (FMEA) model. To accomplish this, a panel of experts was convened to identify potential barriers, prioritizing risk criteria by interval-valued intuitionistic fuzzy sets (IVIFSs) and analytic hierarchy process, and utilizing the IVIF-improved grey relational projection for evaluating and ranking barriers. The model underscores the importance of considering the unique characteristics of EV business model innovation, and a hierarchical system of risk criteria for evaluating barriers is formulated based on the traditional risk factors of FMEA. The findings corroborate that ‘blocked network nodes’, ‘unprofitable revenue models’, and ‘inadequate market segmentation’ are the foremost barriers in China.</p></div>","PeriodicalId":23277,"journal":{"name":"Transportation Research Part D-transport and Environment","volume":"136 ","pages":"Article 104404"},"PeriodicalIF":7.3000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part D-transport and Environment","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1361920924003614","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Business model innovation is imperative for electric vehicles (EVs) firms to maintain a competitive edge and the transition towards transportation electrification. However, numerous socio-technical barriers are likely to impede this innovation process. This study aims to assess the risks of various barriers through a novel fuzzy multiple-criteria decision-making (MCDM)-based failure mode and effects analysis (FMEA) model. To accomplish this, a panel of experts was convened to identify potential barriers, prioritizing risk criteria by interval-valued intuitionistic fuzzy sets (IVIFSs) and analytic hierarchy process, and utilizing the IVIF-improved grey relational projection for evaluating and ranking barriers. The model underscores the importance of considering the unique characteristics of EV business model innovation, and a hierarchical system of risk criteria for evaluating barriers is formulated based on the traditional risk factors of FMEA. The findings corroborate that ‘blocked network nodes’, ‘unprofitable revenue models’, and ‘inadequate market segmentation’ are the foremost barriers in China.
期刊介绍:
Transportation Research Part D: Transport and Environment focuses on original research exploring the environmental impacts of transportation, policy responses to these impacts, and their implications for transportation system design, planning, and management. The journal comprehensively covers the interaction between transportation and the environment, ranging from local effects on specific geographical areas to global implications such as natural resource depletion and atmospheric pollution.
We welcome research papers across all transportation modes, including maritime, air, and land transportation, assessing their environmental impacts broadly. Papers addressing both mobile aspects and transportation infrastructure are considered. The journal prioritizes empirical findings and policy responses of regulatory, planning, technical, or fiscal nature. Articles are policy-driven, accessible, and applicable to readers from diverse disciplines, emphasizing relevance and practicality. We encourage interdisciplinary submissions and welcome contributions from economically developing and advanced countries alike, reflecting our international orientation.