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Strategic Management Journal Vol. 43 No. 12 2022

Breakthrough invention and problem complexity: Evidence from a q uasi‐experiment

Yuchen Zhang1; Wei Yang2

1 The Freeman School of Business Tulane University New Orleans Louisiana USA · 2 The Department of Strategy and Entrepreneurship China Europe International Business School (CEIBS) Shanghai People's Republic of China

Abstract

Research Summary Problem formulation is central to recombinant invention, and problem complexity particularly shapes the process and outcome of knowledge recombination. However, research on the antecedents of problem complexity remains limited. This study examines how breakthrough inventions may serve as an important antecedent of the complexity of problems formulated by individual inventors. We propose that a breakthrough invention may facilitate inventors' appreciation of novel knowledge couplings and improve their overall comprehension of knowledge interdependence for problem formulation, thus increasing problem complexity. We further argue that inventors' prior search breadth and experimentation strengthen the above effect. By exploiting the unexpected victory of AlphaGo and tracking the questions posted on StackOverflow.com by developers interested in deep learning, we find empirical evidence that supports our hypotheses. Managerial Summary Because formulating complex problems may result in novel and valuable inventions, it is helpful to understand what drives inventors to formulate problems of higher complexity. In this study, we propose that breakthrough inventions can serve as an important antecedent of problem complexity. In the context of deep learning, we find that developers formulate problems of higher complexity after the unexpected victory of AlphaGo, a widely acknowledged inventive breakthrough. Further, the above effect is more pronounced when developers have broad search experience in the past or engage frequently in experimentation. The insights of this study are not only relevant to managerial practices within the dynamic field of deep learning but also generalizable to broader technological contexts with breakthrough inventions.

DOI
10.1002/smj.3431
Volume
43
Issue
12
Pages
2510-2544
Language
en
Sources
bibtex:phds-export.bib openalex crossref

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