Sheng, Jie, Amankwah-Amoah, Joseph, Wang, Xiaojun (2017) A Multidisciplinary Perspective of Big Data in Management Research. International Journal of Production Economics, 191 . pp. 97-112. ISSN 0925-5273. (doi:10.1016/j.ijpe.2017.06.006) (KAR id:61981)
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Official URL: https://doi.org/10.1016/j.ijpe.2017.06.006 |
Abstract
In recent years, big data has emerged as one of the prominent buzzwords in business and management. In spite of the mounting body of research on big data across the social science disciplines, scholars have offered little synthesis on the current state of knowledge. To take stock of academic research that contributes to the big data revolution, this paper tracks scholarly work's perspectives on big data in the management domain over the past decade. We identify key themes emerging in management studies and develop an integrated framework to link the multiple streams of research in fields of organisation, operations, marketing, information management and other relevant areas. Our analysis uncovers a growing awareness of big data's business values and managerial changes led by data-driven approach. Stemming from the review is the suggestion for research that both structured and unstructured big data should be harnessed to advance understanding of big data value in informing organisational decisions and enhancing firm competitiveness. To discover the full value, firms need to formulate and implement a data-driven strategy. In light of these, the study identifies and outlines the implications and directions for future research.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.ijpe.2017.06.006 |
Uncontrolled keywords: | Big data; Management research; Literature review |
Subjects: | H Social Sciences > H Social Sciences (General) |
Divisions: | Divisions > Kent Business School - Division > Department of Marketing, Entrepreneurship and International Business |
Depositing User: | Joseph Amankwah-Amoah |
Date Deposited: | 07 Jun 2017 17:14 UTC |
Last Modified: | 05 Nov 2024 10:56 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/61981 (The current URI for this page, for reference purposes) |
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