Big Data Analytics and Firm Performance: A Systematic Review

被引：57

作者：

Maroufkhani, Parisa ^{[1
]}

Wagner, Ralf ^{[2
]}

Ismail, Wan Khairuzzaman Wan ^{[3
]}

Baroto, Mas Bambang ^{[1
]}

Nourani, Mohammad ^{[4
]}

机构：

[1] Univ Teknol Malaysia, Azman Hashim Int Business Sch, Kuala Lumpur 54100, Malaysia

[2] Univ Kassel, DMCC, D-34125 Kassel, Germany

[3] Sulaiman AlRajhi Coll, Sulaiman AlRajhi Sch Business, Al Bukayriyah 51941, Saudi Arabia

[4] Univ Sains Malaysia, Sch Management, George Town 11800, Malaysia

来源：

INFORMATION | 2019年 / 10卷 / 07期

关键词：

big data analytics; business analytics; firm performance; technology adoption; systematic review; BUSINESS ANALYTICS; MANAGEMENT; ADOPTION; STRATEGY; AGILITY; IMPACT; MODEL;

D O I：

10.3390/info10070226

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The literature on big data analytics and firm performance is still fragmented and lacking in attempts to integrate the current studies' results. This study aims to provide a systematic review of contributions related to big data analytics and firm performance. The authors assess papers listed in the Web of Science index. This study identifies the factors that may influence the adoption of big data analytics in various parts of an organization and categorizes the diverse types of performance that big data analytics can address. Directions for future research are developed from the results. This systematic review proposes to create avenues for both conceptual and empirical research streams by emphasizing the importance of big data analytics in improving firm performance. In addition, this review offers both scholars and practitioners an increased understanding of the link between big data analytics and firm performance.

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