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Does big data mean big knowledge? Integration of big data analysis and conceptual model for social commerce research

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  • Xuemei Tian

    (Swinburne University of Technology)

  • Libo Liu

    (Swinburne University of Technology)

Abstract

The Big Data era has descended on many communities, from governments and e-commerce to health organizations. Information 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.

Suggested Citation

  • Xuemei Tian & Libo Liu, 2017. "Does big data mean big knowledge? Integration of big data analysis and conceptual model for social commerce research," Electronic Commerce Research, Springer, vol. 17(1), pages 169-183, March.
    • Handle: RePEc:spr:elcore:v:17:y:2017:i:1:d:10.1007_s10660-016-9242-7
    DOI: 10.1007/s10660-016-9242-7
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    References listed on IDEAS

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    Cited by:

    1. Jianshan Sun & Rongrong Ying & Yuanchun Jiang & Jianmin He & Zhengping Ding, 2020. "Leveraging friend and group information to improve social recommender system," Electronic Commerce Research, Springer, vol. 20(1), pages 147-172, March.
    2. Narisa Zhao & Hui Li, 2020. "How can social commerce be boosted? The impact of consumer behaviors on the information dissemination mechanism in a social commerce network," Electronic Commerce Research, Springer, vol. 20(4), pages 833-856, December.
    3. Fatao Wang & Lihui Ding & Hongxin Yu & Yuanjun Zhao, 0. "Big data analytics on enterprise credit risk evaluation of e-Business platform," Information Systems and e-Business Management, Springer, vol. 0, pages 1-40.
    4. Fatao Wang & Lihui Ding & Hongxin Yu & Yuanjun Zhao, 2020. "Big data analytics on enterprise credit risk evaluation of e-Business platform," Information Systems and e-Business Management, Springer, vol. 18(3), pages 311-350, September.
    5. Satish Kumar & Weng Marc Lim & Nitesh Pandey & J. Christopher Westland, 2021. "20 years of Electronic Commerce Research," Electronic Commerce Research, Springer, vol. 21(1), pages 1-40, March.
    6. Korayim, Diana & Chotia, Varun & Jain, Girish & Hassan, Sharfa & Paolone, Francesco, 2024. "How big data analytics can create competitive advantage in high-stake decision forecasting? The mediating role of organizational innovation," Technological Forecasting and Social Change, Elsevier, vol. 199(C).

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