Creating Strategic Business Value from Big Data Analytics: A Research Framework

• 成果类型: Article
• 署名作者: Grover, Varun; Chiang, Roger H. L.; Liang, Ting-Peng; Zhang, Dongsong
• 署名单位: University of Arkansas System; University of Arkansas Fayetteville; University System of Ohio; University of Cincinnati; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Purdue University System; Purdue University; Chinese University of Hong Kong; City University of Hong Kong; University System of Maryland; University of Maryland Baltimore County; Jinan University
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2018.1451951
• 发表日期: 2018
• 页码: 388-423
• 关键词: information-technology; Real options; Competitive advantage; DIRECTIONS; behaviors; insights; adoption; systems; MARKET; web

摘要

Despite the publicity regarding big data and analytics (BDA), the success rate of these projects and strategic value created from them are unclear. Most literature on BDA focuses on how it can be used to enhance tactical organizational capabilities, but very few studies examine its impact on organizational value. Further, we see limited framing of how BDA can create strategic value for the organization. After all, the ultimate success of any BDA project lies in realizing strategic business value, which gives firms a competitive advantage. In this study, we describe the value proposition of BDA by delineating its components. We offer a framing of BDA value by extending existing frameworks of information technology value, then illustrate the framework through BDA applications in practice. The framework is then discussed in terms of its ability to study constructs and relationships that focus on BDA value creation and realization. We also present a problem-oriented view of the framework-where problems in BDA components can give rise to targeted research questions and areas for future study. The framing in this study could help develop a significant research agenda for BDA that can better target research and practice based on effective use of data resources.