Organizational Ambidexterity and Digital Transformation: Literature Review with Empirical and Conceptual Insights

Abstract

Although digital transformation (DT) and organizational ambidexterity (OA) have been studied extensively, few reviews synthesize research at their intersection. Existing reviews tend to emphasize themes and findings while giving less attention to the theoretical frameworks, contexts, study types, and methods needed for robust conclusions. This study addresses that gap by examining how DT and OA interact to support innovation and performance. It offers a systematic overview of publication trends, geographical contexts, theoretical lenses, study types, methods, and findings through a content analysis of 43 peer-reviewed articles retrieved from the Web of Science database.The results show growing academic interest in the intersection of DT and OA. The dominant theoretical lenses are organizational ambidexterity, dynamic capabilities, the resource-based view, paradox theory, and absorptive capacity. Empirical research is concentrated in the Asia-Pacific and European regions and frequently examines regulated sectors or cross-industry samples. Quantitative designs are most common, followed by qualitative and mixed-method designs; frequently used methods include structural equation modeling, fuzzy-set qualitative comparative analysis, panel-data analysis, and case studies. The synthesis indicates a reciprocal relationship: DT can enable exploration and exploitation, whereas OA can help organizations translate digital initiatives into innovation, resilience, sustainability, and performance. An analysis of 43 studies reveals growing academic interest in both areas. The most common theoretical lenses include OA, Dynamic Capabilities, the Resource-Based View, Paradox Theory, and Absorptive Capacity. Research contexts are concentrated in the Asia-Pacific and European regions, with particular attention to regulated sectors and cross-industry settings. Empirical studies are predominantly quantitative, complemented by qualitative and mixed-method designs, and employ techniques such as SEM, fsQCA, panel data analysis, and case studies. Findings highlight a bi-directional relationship between OA and DT, shaped by context and research models.