Abstract
Big data technologies and analytics enable new digital services and are often associated with superior performance. However, firms investing in big data often fail to attain those advantages. To answer the questions of how and when big data pay off, marketing scholars need new theoretical approaches and empirical tools that account for the digitized world. Building on affordance theory, the authors develop a novel, conceptually rigorous, and practice-oriented framework of the impact of big data investments on service innovation and performance. Affordances represent action possibilities, namely what individuals or organizations with certain goals and capabilities can do with a technology. The authors conceptualize and operationalize three important big data marketing affordances: customer behavior pattern spotting, real-time market responsiveness, and data-driven market ambidexterity. The empirical analysis establishes construct validity and offers a preliminary nomological test of direct, indirect, and conditional effects of big data marketing affordances on perceived big data performance.
| Original language | English |
|---|---|
| Pages (from-to) | 790-810 |
| Number of pages | 21 |
| Journal | Journal of the Academy of Marketing Science |
| Volume | 49 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Jul 2021 |
Bibliographical note
Funding Information:The Authors have presented the paper to the 2019 JAMS Thought Leaders Conference connected to the Special Issue, and acknowledge the insightful comments and feedback from John Hulland and other participants. We are also indebted with all the managers who have engaged with our research, many of whom have also provided feedback on our results.
Publisher Copyright:
© 2020, The Author(s).
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
Keywords
- Affordance theory
- Big data performance
- Big data technologies and analytics
- Industry digitalization
- Marketing affordances
- Service innovation