Big data analytics capabilities: a systematic literature review and research agenda

被引:470
作者
Mikalef, Patrick [1 ]
Pappas, Ilias O. [1 ]
Krogstie, John [1 ]
Giannakos, Michail [1 ]
机构
[1] Norwegian Univ Sci & Technol, Trondheim, Norway
基金
欧盟地平线“2020”;
关键词
Big data; Dynamic capabilities; Resource-based view; Competitive performance; IT strategy; RESOURCE-BASED VIEW; DYNAMIC CAPABILITIES; COMPETITIVE ADVANTAGE; BUSINESS VALUE; FIRM PERFORMANCE; DATA SCIENCE; ORGANIZATIONAL TRANSFORMATION; MANAGEMENT; TECHNOLOGY; KNOWLEDGE;
D O I
10.1007/s10257-017-0362-y
中图分类号
F [经济];
学科分类号
02 ;
摘要
With big data growing rapidly in importance over the past few years, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. To date, emphasis has been on the technical aspects of big data, with limited attention paid to the organizational changes they entail and how they should be leveraged strategically. As with any novel technology, it is important to understand the mechanisms and processes through which big data can add business value to companies, and to have a clear picture of the different elements and their interdependencies. To this end, the present paper aims to provide a systematic literature review that can help to explain the mechanisms through which big data analytics (BDA) lead to competitive performance gains. The research framework is grounded on past empirical work on IT business value research, and builds on the resource-based view and dynamic capabilities view of the firm. By identifying the main areas of focus for BDA and explaining the mechanisms through which they should be leveraged, this paper attempts to add to literature on how big data should be examined as a source of competitive advantage. To this end, we identify gaps in the extant literature and propose six future research themes.
引用
收藏
页码:547 / 578
页数:32
相关论文
共 137 条
[1]  
Abbasi A, 2016, J ASSOC INF SYST, V17, pI
[2]   Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research [J].
Agarwal, Ritu ;
Dhar, Vasant .
INFORMATION SYSTEMS RESEARCH, 2014, 25 (03) :443-448
[3]   How to improve firm performance using big data analytics capability and business strategy alignment? [J].
Akter, Shahriar ;
Wamba, Samuel Fosso ;
Gunasekaran, Angappa ;
Dubey, Rameshwar ;
Childe, Stephen J. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2016, 182 :113-131
[4]   Big data analytics in E-commerce: a systematic review and agenda for future research [J].
Akter, Shahriar ;
Wamba, Samuel Fosso .
ELECTRONIC MARKETS, 2016, 26 (02) :173-194
[5]   STRATEGIC ASSETS AND ORGANIZATIONAL RENT [J].
AMIT, R ;
SCHOEMAKER, PJH .
STRATEGIC MANAGEMENT JOURNAL, 1993, 14 (01) :33-46
[6]  
[Anonymous], 2014, P 25 AUSTR C INF SYS
[7]   IT assets, organizational capabilities, and firm performance: How resource allocations and organizational differences explain performance variation [J].
Aral, Sinan ;
Weill, Peter .
ORGANIZATION SCIENCE, 2007, 18 (05) :763-780
[8]   Business value of in-memory technology - multiple-case study insights [J].
Baerenfaenger, Rieke ;
Otto, Boris ;
Oesterle, Hubert .
INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2014, 114 (09) :1396-1414
[9]   FIRM RESOURCES AND SUSTAINED COMPETITIVE ADVANTAGE [J].
BARNEY, J .
JOURNAL OF MANAGEMENT, 1991, 17 (01) :99-120
[10]   The Future of Resource-Based Theory: Revitalization or Decline? [J].
Barney, Jay B. ;
Ketchen, David J., Jr. ;
Wright, Mike .
JOURNAL OF MANAGEMENT, 2011, 37 (05) :1299-1315