{"title":"一个地区对电子零售商的吸引力有多大？为非大都市印度引入区域电子零售采用模式","authors":"Shankhadeep Banerjee , Priya Seetharaman","doi":"10.1016/j.iimb.2022.07.004","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, we develop a basic regional e-tailing adoption model based on the “diffusion of innovations” (DOI) theory and the “ability-motivation-opportunity” (AMO) framework. We empirically test the model using ordinary least squares and Poisson regression on district-level e-tailing packages data collected from India Post. Further, we use a neural network model to classify districts into high/low e-tailing potential with 78% accuracy. Apart from its theoretical contribution, the adoption model can also be used by e-tailers to support their regional targeting decisions.</p></div>","PeriodicalId":46337,"journal":{"name":"IIMB Management Review","volume":"34 2","pages":"Pages 116-129"},"PeriodicalIF":1.7000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0970389622000490/pdfft?md5=a3acca2db48882c9a859f4821608285f&pid=1-s2.0-S0970389622000490-main.pdf","citationCount":"0","resultStr":"{\"title\":\"How attractive is a locale to e-tailers? Introducing a regional e-tailing adoption model for non-metropolitan India\",\"authors\":\"Shankhadeep Banerjee , Priya Seetharaman\",\"doi\":\"10.1016/j.iimb.2022.07.004\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, we develop a basic regional e-tailing adoption model based on the “diffusion of innovations” (DOI) theory and the “ability-motivation-opportunity” (AMO) framework. We empirically test the model using ordinary least squares and Poisson regression on district-level e-tailing packages data collected from India Post. Further, we use a neural network model to classify districts into high/low e-tailing potential with 78% accuracy. Apart from its theoretical contribution, the adoption model can also be used by e-tailers to support their regional targeting decisions.</p></div>\",\"PeriodicalId\":46337,\"journal\":{\"name\":\"IIMB Management Review\",\"volume\":\"34 2\",\"pages\":\"Pages 116-129\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0970389622000490/pdfft?md5=a3acca2db48882c9a859f4821608285f&pid=1-s2.0-S0970389622000490-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IIMB Management Review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0970389622000490\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IIMB Management Review","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0970389622000490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
How attractive is a locale to e-tailers? Introducing a regional e-tailing adoption model for non-metropolitan India
In this paper, we develop a basic regional e-tailing adoption model based on the “diffusion of innovations” (DOI) theory and the “ability-motivation-opportunity” (AMO) framework. We empirically test the model using ordinary least squares and Poisson regression on district-level e-tailing packages data collected from India Post. Further, we use a neural network model to classify districts into high/low e-tailing potential with 78% accuracy. Apart from its theoretical contribution, the adoption model can also be used by e-tailers to support their regional targeting decisions.
期刊介绍：
IIMB Management Review (IMR) is a quarterly journal brought out by the Indian Institute of Management Bangalore. Addressed to management practitioners, researchers and academics, IMR aims to engage rigorously with practices, concepts and ideas in the field of management, with an emphasis on providing managerial insights, in a reader friendly format. To this end IMR invites manuscripts that provide novel managerial insights in any of the core business functions. The manuscript should be rigorous, that is, the findings should be supported by either empirical data or a well-justified theoretical model, and well written. While these two requirements are necessary for acceptance, they do not guarantee acceptance. The sole criterion for publication is contribution to the extant management literature.Although all manuscripts are welcome, our special emphasis is on papers that focus on emerging economies throughout the world. Such papers may either improve our understanding of markets in such economies through novel analyses or build models by taking into account the special characteristics of such economies to provide guidance to managers.
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