تجزیه و تحلیل داده های بزرگ بدون ساختار برای بازیابی اطلاعات تدارکات الکترونیکی تجارت الکترونیک
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|82593||2018||37 صفحه PDF||سفارش دهید|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Telematics and Informatics, Volume 35, Issue 1, April 2018, Pages 237-244
The divergent evolution of e-commerce has complicated its correspondingly logistics management. However, few studies have explored e-commerce logistics business models via big data analytics. Hence, this investigation explores e-commerce logistics business models from unstructured big data. Specifically, this work develops a hybrid content analytical model to scrutinize essential knowledge of e-commerce logistics. The empirical results of the proposed model incorporate theories of resource dependence theory (RDT) and innovation diffusion theory (IDT) to generate logistical strategies. Ten critical themes of e-commerce logistics from topic mining are âSoutheast Asiaâs e-commerce logistics paymentsâ, âE-commerce order managementâ, âE-commerce logistics cloud servicesâ, âE-commerce logistics package managementâ, âEurope e-commerce trendsâ, âIndiaâs e-commerce logisticsâ, âE-commerce distribution managementâ, âTax policiesâ, âE-commerce logistics platformsâ, and âE-commerce logistics networksâ. Moreover, the fundamental rule of âcross-border e-commerce logisticsâ is uncovered by the association rules model. The proposed hybrid content analytics framework provides a research foundation for e-commerce logistics management. Furthermore, e-commerce logistics can be implemented by vital strategies: âEstablish inter-organizational and technical collaboration to create positive operations performanceâ and âComprehend law, policy, and cultural differences to customize appropriate technologies of e-commerce logisticsâ.