{"title":"走向众包交付商业模式的分类","authors":"Georgiana Ciobotaru, S. Chankov","doi":"10.1108/IJPDLM-10-2019-0326","DOIUrl":null,"url":null,"abstract":"PurposeThe paper aims to develop (1) a comprehensive framework for classifying crowdshipping business models and (2) a taxonomy of currently implemented crowdshipping business models.Design/methodology/approachThe business models of 105 companies offering crowdsourced delivery services are analysed. Cluster analysis and principal component analysis are applied to develop a business model taxonomy.FindingsA detailed crowdsourced delivery business model framework with 74 features is developed. Based on it, six distinct clusters of crowdshipping business models are identified. One cluster stands out as the most appealing to customers based on social media metrics, indicating which type of crowdshipping business models is the most successful.Research limitations/implicationsDetailed investigations of each of the six clusters and of recent crowdshipping business model developments are needed in further research in order to enhance the derived taxonomy.Practical implicationsThis paper serves as a best-practices guide for both start-ups and global logistics operators for establishing or further developing their crowdsourced delivery business models.Originality/valueThis paper provides a holistic understanding of the business models applied in the crowdshipping industry and is a valuable contribution to the yet small amount of studies in the crowd logistics field.","PeriodicalId":14251,"journal":{"name":"International Journal of Physical Distribution & Logistics Management","volume":" ","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Towards a taxonomy of crowdsourced delivery business models\",\"authors\":\"Georgiana Ciobotaru, S. Chankov\",\"doi\":\"10.1108/IJPDLM-10-2019-0326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PurposeThe paper aims to develop (1) a comprehensive framework for classifying crowdshipping business models and (2) a taxonomy of currently implemented crowdshipping business models.Design/methodology/approachThe business models of 105 companies offering crowdsourced delivery services are analysed. Cluster analysis and principal component analysis are applied to develop a business model taxonomy.FindingsA detailed crowdsourced delivery business model framework with 74 features is developed. Based on it, six distinct clusters of crowdshipping business models are identified. One cluster stands out as the most appealing to customers based on social media metrics, indicating which type of crowdshipping business models is the most successful.Research limitations/implicationsDetailed investigations of each of the six clusters and of recent crowdshipping business model developments are needed in further research in order to enhance the derived taxonomy.Practical implicationsThis paper serves as a best-practices guide for both start-ups and global logistics operators for establishing or further developing their crowdsourced delivery business models.Originality/valueThis paper provides a holistic understanding of the business models applied in the crowdshipping industry and is a valuable contribution to the yet small amount of studies in the crowd logistics field.\",\"PeriodicalId\":14251,\"journal\":{\"name\":\"International Journal of Physical Distribution & Logistics Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2021-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Physical Distribution & Logistics Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1108/IJPDLM-10-2019-0326\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Physical Distribution & Logistics Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/IJPDLM-10-2019-0326","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
Towards a taxonomy of crowdsourced delivery business models
PurposeThe paper aims to develop (1) a comprehensive framework for classifying crowdshipping business models and (2) a taxonomy of currently implemented crowdshipping business models.Design/methodology/approachThe business models of 105 companies offering crowdsourced delivery services are analysed. Cluster analysis and principal component analysis are applied to develop a business model taxonomy.FindingsA detailed crowdsourced delivery business model framework with 74 features is developed. Based on it, six distinct clusters of crowdshipping business models are identified. One cluster stands out as the most appealing to customers based on social media metrics, indicating which type of crowdshipping business models is the most successful.Research limitations/implicationsDetailed investigations of each of the six clusters and of recent crowdshipping business model developments are needed in further research in order to enhance the derived taxonomy.Practical implicationsThis paper serves as a best-practices guide for both start-ups and global logistics operators for establishing or further developing their crowdsourced delivery business models.Originality/valueThis paper provides a holistic understanding of the business models applied in the crowdshipping industry and is a valuable contribution to the yet small amount of studies in the crowd logistics field.
期刊介绍:
IJPDLM seeks strategically focused, theoretically grounded, empirical and conceptual, quantitative and qualitative, rigorous and relevant, original research studies in logistics, physical distribution and supply chain management operations and associated strategic issues. Quantitatively oriented mathematical and modelling research papers are not suitable for IJPDLM. Desired topics include, but are not limited to: Customer service strategy Omni-channel and multi-channel distribution innovations Order processing and inventory management Implementation of supply chain processes Information and communication technology Sourcing and procurement Risk management and security Personnel recruitment and training Sustainability and environmental Collaboration and integration Global supply chain management and network complexity Information and knowledge management Legal, financial and public policy Retailing, channels and business-to-business management Organizational and human resource development Logistics and SCM education.