Mapping the landscape of research findings: Generalization across contexts in strategic management research

• 成果类型: Article
• 署名作者: Levinthal, Daniel A.; Rosenkopf, Lori
• 署名单位: University of Pennsylvania
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.70071
• 发表日期: 2026
• 关键词: Diversification; RESOURCES; IMPACT

摘要

Research Summary: Knowledge accumulation requires that we understand whether and when relationships identified in any research setting generalize to others-that is, suggesting domains where results hold (or not). Strategy scholars carefully identify how theoretical mechanisms operate in their chosen research contexts, but attend less to whether their findings apply in other contexts. Accordingly, we recommend reframing empirical contexts, typically described in terms of nominal categories (e.g., industries, countries, or time periods), by highlighting contextual attributes of the nominal settings (e.g., industry concentration or technological modularity), which in turn reflect more abstract conceptual categories (e.g., uncertainty, interdependence, and variance) across potential research contexts. This approach can help integrate prior findings and suggest future study contexts to better enhance our understanding of the research landscape. Managerial Summary: Academic research in strategic management tends to derive findings in very specific nominal settings-particular industries, years, and regions. Since strategy practitioners operate across a wide variety of industries and regions, they need to assess whether available research findings are applicable in their own settings. We suggest that understanding whether and when research findings apply to unstudied settings can be facilitated by categorizing research settings using more abstract conceptual constructs (such as environment uncertainty, variance across firms, or interdependence between firms), rather than by the traditional emphasis on nominal settings. We discuss a variety of research setting attributes (such as industry concentration and technological modularity) that can aid the translation of extant research findings to settings where practitioners are operating.