Big Data is Power: Business Value from a Process Oriented Analytics Capability

被引:4
作者
van de Wetering, Rogier [1 ]
Mikalef, Patrick [2 ]
Krogstie, John [2 ]
机构
[1] Open Univ Netherlands, Fac Management Sci & Technol, Valkenburgerweg 177, NL-6419 AT Heerlen, Netherlands
[2] Norwegian Univ Sci & Technol, Dept Comp Sci, Sem Saelandsvei 9, N-7491 Trondheim, Norway
来源
BUSINESS INFORMATION SYSTEMS WORKSHOPS (BIS 2018) | 2019年 / 339卷
基金
欧盟地平线“2020”;
关键词
Big data; Big data analytics capabilities; Qualitative coding; Resource-based view (RBV); Process stages; FIRM PERFORMANCE; STRATEGY; MANAGEMENT; RESOURCES; ASSETS;
D O I
10.1007/978-3-030-04849-5_41
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Big data analytics (BDA) has the potential to provide firms with competitive benefits. Despite its massive potential, the conditions and required complementary resources and capabilities through which firms can gain business value, are by no means clear. Firms cannot ignore the influx of data, mostly unstructured, and will need to invest in BDA increasingly. By doing so, they will have to, e.g., necessitate new specialist competencies, privacy, and regulatory issues as well as other structural and cost considerations. Past research contributions argued for the development of idiosyncratic and difficult to imitate firm capabilities. This study builds upon resources synchronization theories and examines the process to obtain business value from BDA. In this study, we use data from 27 cases studies from different types of industries. Through the coding analyses of interview transcripts, we identify the contingent resources that drive, moderate and condition the value of a BDA capability throughout different phases of adoption. Our results contribute to a better understanding of the importance of BDA resources and the process and working mechanisms through which to leverage them toward business value. We conclude that our synthesized configurational model for BDA capabilities is a useful basis for future research.
引用
收藏
页码:468 / 480
页数:13
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