Customer analytics and new product performance: The role of contingencies

Sena Ozdemir, Yichuan Wang, Suraksha Gupta, Vania Sena, Shijie Zhang and Minhao Zhang

Technological Forecasting and Social Change, 2024, vol. 201, issue C

Abstract: Drawing from the Knowledge Based View (KBV) of the firm and Contingency Theory, this paper examines the extent to which the relationship between Customer Analytics (CA) and new product performance is contingent on the strategic fit of CA with certain internal and external contingencies. The paper first conducts a multiple case study based on secondary data analysis. It then undertakes an empirical analysis based on a survey data of 249 high and medium tech firms based in China. We find that while some internal contingencies (such as exploitative learning strategy and market knowledge breadth) negatively moderate the effect of CA on new product performance, others (such as internal capability and knowledge integration mechanisms) mediate its effect on performance. Technological turbulence, as an external contingency, was found to reduce the positive impact of CA deployment on new product performance. This study contributed to the literature by focusing on how several internal and external contingencies of a firm may affect the relationship between CA and new product performance.

Keywords: Big Data Analytics; New product performance; Contingency Theory; Knowledge Based View; China (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:201:y:2024:i:c:s0040162524000210

DOI: 10.1016/j.techfore.2024.123225

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