Big data and firm marketing performance: Findings from knowledge-based view

被引:72
|
作者
Gupta, Shivam [1 ]
Justy, Theo [2 ]
Kamboj, Shampy [3 ]
Kumar, Ajay [4 ]
Kristoffersen, Eivind [5 ]
机构
[1] NEOMA Business Sch, Dept Informat Syst Supply Chain & Decis Making, 59 Rue Pierre Taittinger, F-51100 Reims, France
[2] Univ Montpellier, Montpellier Management MOMA, Montpellier, France
[3] Natl Inst Technol Hamirpur, Dept Management Studies, Hamirpur, India
[4] EMLYON Business Sch, AIM Res Ctr Artificial Intelligence Value Creat, 24 Ave Guy Collongue, F-69130 Ecully, France
[5] Norwegian Univ Sci & Technol NTNU, Dept Comp Sci, Trondheim, Norway
基金
中国国家自然科学基金;
关键词
Big data analytics; Artificial intelligence; Marketing performance; Knowledge-based view; INDUSTRY; 4.0; DATA ANALYTICS; CIRCULAR ECONOMY; SUPPLY CHAIN; SYSTEMS; SUSTAINABILITY; TRANSFORMATION; EXPERIENCE; DECISIONS; IMPACT;
D O I
10.1016/j.techfore.2021.120986
中图分类号
F [经济];
学科分类号
02 ;
摘要
A universal trend in advanced manufacturing countries is defining Industry 4.0, industrialized internet and future factories as a recent wave, which may transform the production and its related services. Further, big data analytics has emerged as a game changer in the business world due to its uses for increasing accuracy in decisionmaking and enhancing performance of sustainable industry 4.0 applications. This study intends to emphasize on how to support Industry 4.0 with knowledge based view. For the same, a conceptual model is framed and presented with essential components that are required for a real world implementation. The study used qualitative analysis and was guided by a knowledge-based theoretical framework. Thematic analysis resulted in the identification of a number of emergent categories. Key findings highlight significant gaps in conventional decision-making systems and demonstrate how big data enhances firms' strategic and operational decisions as well as facilitates informational access for improved marketing performance. The resulting proposed model can provide managers with a reference point for using big data to line up firms' activities for more effective marketing efforts and presents a conceptual basis for further empirical studies in this area.
引用
收藏
页数:15
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