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May 17, 2026Academy of Management Annals1 citations

Experimentation in Organizations: An Integrative Review

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LCLeonardo CorboUniversity of BolognaRKRiitta KatilaStanford UniversityBVBožidar VlačićUniversity of Donja Gorica

Key Points

  • This review synthesizes empirical literature on organizational experimentation, focusing on decision-making processes and learning.
  • Reviewed 177 empirical studies across multiple disciplines
  • Organized findings into problem-solving and causal inference streams
  • Developed a unifying framework based on variation-selection-retention
  • Highlighted key drivers and processes of organizational experimentation
  • Identified complementary insights between problem-solving and causal inference approaches
  • Outlined avenues for future research to enhance experimental effectiveness and learning

Abstract

Organizations have long relied on experiments to guide decision-making. Yet, a comprehensive synthesis of this rich and timely empirical literature remains lacking. In this integrative review, we identify two primary streams of research (problem-solving-based experimentation and causal inference-based experimentation), which we organize using the classic variation–selection–retention framework. The problem-solving stream emphasizes iterative experimentation, learning from failure, and navigating organizational challenges, while the causal inference stream focuses on sharp identification, structured experimental designs, and bounded experiments, each rooted in distinct disciplinary traditions. Despite the differences, these perspectives offer complementary insights into how organizations experiment, learn, and adapt. By analyzing 177 empirical studies across several disciplines and integrating these parallel streams, we develop a unifying framework that highlights the key drivers, processes, and outcomes of organizational experimentation. We conclude by outlining promising avenues for future research, including deeper retention in shaping experimental effectiveness and organizational learning, overcoming cognitive biases, expanding the scope of experiments to strategy, organizational design, and people processes, and the possibility of the two streams to cross-feed: problem-solving to generate broad hypotheses that causal inference sharpens, and causal inference experiments to trigger reframing of the problem-solving experiments.

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Cite This Study

Corbo et al. (2026) studied this question.

synapsesocial.com/papers/6a095b787880e6d24efe148ahttps://doi.org/10.5465/annals.2024.0287
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