Ozdemir, S., Wang, Y., Gupta, S. et al. (3 more authors) (2024) Customer analytics and new product performance: the role of contingencies. Technological Forecasting and Social Change, 201. 123225. ISSN 0040-1625
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.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in Technological Forecasting and Social Change is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Big Data Analytics; New Product Performance; Contingency Theory; Knowledge Based View; China |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Jan 2024 15:40 |
Last Modified: | 19 Feb 2024 09:25 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.techfore.2024.123225 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:208191 |