How Does Strategic Fit Shape Strategy Implementation? An Examination of Acquisitions in Multi-business Firms
By Siddharth Natarajan, Prothit Sen
Citation
Natarajan, Siddharth., Sen, Prothit. (2025). How Does Strategic Fit Shape Strategy Implementation? An Examination of Acquisitions in Multi-business Firms .
Copyright
2025
Share:
Abstract
Extant literature on strategic fit is predominantly rooted in resource-based theory, providing less insight about its role in strategy implementation. We make progress by drawing on behavioral theory of the firm. We theorize that weak strategic fit promotes satisficing in strategy implementation, particularly when firms face lower risks to performance. Applying our theory to M&A implementation, we hypothesize that deal completion is swifter for non-core acquisitions versus core acquisitions. Further, we hypothesize four contingencies that shape aspiration levels in the implementation of non-core acquisitions: the relative speed of completing non-core versus core deals will be higher for: (1) diversified versus focused acquirers (2) domestic versus cross-border acquisitions (3) acquirers far away from bankruptcy versus those closer to bankruptcy, (4) acquisition of targets from the seller’s main business versus targets peripheral to the seller’s business. M&A performance, however, aligns with resource-based logics of strategic fit. These hypotheses are supported in an empirical study of 39,403 acquisitions implemented by 6,849 publicly listed acquirors over the period 2000–2020. Overall, our findings enhance understanding of how firms set aspiration levels with behavioral underpinnings in decision-making and enriches the extant narrative about resource-based strategic fit.

Prothit Sen is an Assistant Professor of Strategy at the Indian School of Business (ISB). His research interests primarily include business model innovations and the impact of such innovations on corporate strategy decisions such as strategic alliances and private equity portfolio strategies. In terms of research methodology, Professor Sen performs empirical analyses over secondary data by using a combination of predictive models that use machine learning algorithms and classical econometric techniques for making causal inferences regarding the phenomena of his interest.

Prior to completing his PhD, Professor Sen worked for several years as a consultant at Bain & Company in Gurgaon, India. His advisory experience in India spanned across manufacturing, automotive, IT services, and private equity sectors.

Prothit Sen
Prothit Sen