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Development of conceptual model for social commerce research through integration with big data analysis
conference contribution
posted on 2016-01-01, 00:00 authored by X Tian, L Liu, Kristijan MirkovskiKristijan Mirkovski, M LiInformation systems designers face great opportunities and challenges in developing a holistic big data research approach for the new analytics savvy generation. In addition business intelligence is largely utilized in the business community and thus can leverage the opportunities from the abundant data and domain-specific analytics in many critical areas. The aim of this paper is to assess the relevance of these trends in the current business context through evidence-based documentation of current and emerging applications as well as their wider business implications. In this paper, we use BigML to examine how the two social information channels (i.e., friends-based opinion leaders-based social information) influence consumer purchase decisions on social commerce sites. We undertake an empirical study in which we integrate a framework and a theoretical model for big data analysis. We conduct an empirical study to demonstrate that big data analytics can be successfully combined with a theoretical model to produce more robust and effective consumer purchase decisions. The results offer important and interesting insights into IS research and practice.
History
Event
Pacific Asia Conference on Information Systems. Conference (2016 : Chiayi, Taiwan)Pagination
1 - 10Publisher
Association for Information SystemsLocation
Chiayi, TaiwanPlace of publication
Atlanta, Ga.Start date
2016-06-27End date
2016-07-01ISBN-13
9789860491029Language
engPublication classification
E1.1 Full written paper - refereed; E Conference publicationTitle of proceedings
PACIS 2016 : Proceedings of the 20th Pacific Asia Conference on Information SystemsUsage metrics
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