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Big Data Analytics and Firm Productivity

Authors:
Liang Guo
Mingtao Fu
Ruodan Lu

Keywords: big data analytics; retailing; China

Abstract:
Increasing productivity is a key task for contemporary firms. Although big data analytics has been generally viewed as an effective advanced information processing tool that enables firms to better cope with business operation, thus holding the potential to boost firm productivity, evidence to support this view is lacking in the literature. Equipped with the theory of organizational information processing and resource-based view, we hypothesize that big data analytics systems (BDAS) can help improve productivity and this contribution is influenced by the firm’s BDAS capability. These hypotheses are supported with a sample of 45 Chinese retailers over 2012-2014 using Data Envelopment Analysis and Malmquist Productivity Index. This study extends our understanding of the business value of IT by shedding light on the productivity benefit of big data investment. We also underline that for firms that have already implemented BDAS, a greater effort seems necessary to build predictive and prescriptive analytics capability.

Pages: 69 to 74

Copyright: Copyright (c) IARIA, 2016

Publication date: October 9, 2016

Published in: conference

ISSN: 2326-9383

ISBN: 978-1-61208-509-8

Location: Venice, Italy

Dates: from October 9, 2016 to October 13, 2016