Dynamic capabilities, such as agility and innovation, are essential for an organization to be competitive, resilient, and adapt to rapidly evolving market dynamics. However, although an abundance of bibliometric studies are available in the literature related to organizational agility, a significant gap exists in the understanding of agility in combination with innovation, as both are key concepts to survive in a highly competitive, volatile, and evolving market. This research gap arises due to limited studies, a lack of explicit mapping of their relationships, and challenges in articulating their dynamic bibliometric profiles. Also, some studies are limited to specific times that are no longer relevant due to advancements in technology and the rapidly evolving market dynamics.
This bibliometric study includes 982 articles after careful screening and scanning of titles and abstracts of the studies relevant to agility and innovation published between 1996 and early August 2025. Using VOSviewer software, we explore the publication trend, citation impacts, and co-citation networks, identifying key authors, top journals, and pertinent research clusters related to agility and innovation.
Using VOSviewer software, we explore the publication trend, citation impacts, and co-citation networks, identifying key authors, top journals, and pertinent research clusters related to agility and innovation. Based on these results, we propose a theoretical model relating agility and innovation, and identify gaps and tensions that can orient future research on the topic.
While bibliometric analysis offers a powerful lens to map the intellectual foundations, thematic evolution, and collaborative networks of a research field, it also presents inherent limitations that should be acknowledged. Results are influenced by the scope and indexing policies of the selected databases, which may underrepresent non-indexed, regional, or non-English publications. Citation counts measure influence rather than methodological rigor and may be shaped by disciplinary norms, self-citation patterns, and network effects. Time-lag bias can further disadvantage recently published studies, underestimating the relevance of emerging topics. Moreover, keyword-based analyses depend on the accuracy and consistency of author-supplied metadata; variations in terminology and the use of synonyms can fragment related themes and distort thematic mapping. Methodological choices—such as software selection, parameter thresholds, and clustering algorithms—also affect outcomes, potentially leading to different network structures and thematic categorizations. The quantitative nature of bibliometric analysis privileges descriptive mapping over explanatory depth, making it essential to complement such approaches with qualitative or content-based analyses for richer interpretation. Historical bias can result in older, highly cited works overshadowing recent yet impactful contributions, while interpreting co-occurrence and co-citation patterns requires strong domain expertise to avoid oversimplification. For these reasons, bibliometric findings should be interpreted as one perspective among multiple methodological approaches, ensuring a balanced and contextually grounded understanding of the research landscape.
Teece’s work on dynamic capabilities continues to serve as the most influential theoretical anchor across all clusters, effectively bridging strategic and operational perspectives. In parallel, Gunasekaran’s operations-oriented contributions remain highly impactful, though they are now increasingly connected to research on digital transformation. Methodological scholars such as Hair, Ringle, and Sarstedt have become pivotal in this evolution, providing the statistical and analytical tools necessary for large-scale, multi-construct empirical studies. Over time, these developments have facilitated the transition from isolated thematic silos to a more interconnected research network, driven by the imperative to address complex, interdisciplinary challenges such as sustainability and digital disruption.
