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The Whole Is More Than the Sum of Its Parts— Or Is It? A Review of the Empirical Literature on Complementarities in Organizations
Open accessAbstract
The concept of complementarity denotes the beneficial interplay of the elements of a system where the presence of one element increases the value of others. However, the conceptual work on complementarities to date has not progressed sufficiently to constitute a theory that would offer specific predictions regarding the nature of the elements that form complementary relationships or the conditions for their emergence. To advance our understanding of complementarities, the authors provide a synoptic review of the empirical studies on this concept in leading journals in management, economics, and related disciplines over the period 1988-2008. The authors find that whether a study provides evidence of complementarities in organizations is at least partially driven by its investigative approach. On the basis of the findings, the authors argue that complementarities are most likely to materialize among multiple, heterogeneous factors in complex systems. Therefore, the absence of complementary relationships between a limited set of individual factors may not negate the possibility of complementarities, but rather point to the need for including further systems-specific factors in the analysis. The authors conclude by providing directions for future theoretical and empirical research and outlining managerial implications of the work.
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Cites
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Capturing causal complexity: Heuristics for configurational theorizing
Furnari, S., Crilly, D., Misangyi, V. F., Greckhamer, T., Fiss, P. C., & Aguilera, R. V. (2021) · Academy of Management Review · doi:10.5465/amr.2019.0298 · Cited by 861
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Metadata
- Authors
- Ennen, E., & Richter, A.
- Venue
- Journal of Management
- Publisher
- SAGE Publications
- Published
- 2009-12-28
- Volume
- 36
- Issue
- 1
- Pages
- 207-233
- ISSN
- 0149-2063 (ISSN-L)
- 1557-1211
- OpenAlex
- W1539890103
- Cited by
- 440
- References
- 140
- FWCI
- 47.21
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.