Anais
Resumo do trabalho
Tecnologia da Informação · Ciências de dados e Inteligência analítica
Título
Bibliometric Mapping of Knowledge and Research Agenda on Data and Analytics in the field of Business Strategy and Information Systems Management
Palavras-chave
Data and Analytics
Bibliometric Study
Research Agenda
Agradecimento:
We thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the financial support in the development of this research.
Autores
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Mauricius Munhoz de MedeirosUNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL (UFRGS)
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Antonio Carlos Gastaud MaçadaUNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL (UFRGS)
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Andreon MagagnaUNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL (UFRGS)
Resumo
Introdução
With the proliferation of digital and analytical technologies such as Data and Analytics (D&A) and Artificial Intelligence (AI), data management has become even more crucial for guiding organizations. In the scientific literature at the intersection of business strategy and information systems management, the debate agenda on underlying issues of D&A management and capabilities is also emerging and expanding, driven by the diffusion of digital transformation. Over the last decade, publications on the topic have grown considerably, especially in the past five years.
Problema de Pesquisa e Objetivo
Despite its rapid growth and dispersion, knowledge about the role of organizational factors in value creation through big data, data analytics, or data science has received little attention in the existing literature. Moreover, there is a scarcity of studies that synthesize knowledge on the topic, and the lack of a current mapping of the field in this context hinders understanding of the existing literature and identification of research gaps. The purpose of this study is to map the state of knowledge on D&A in the research field of business strategy and information systems management.
Fundamentação Teórica
As approaches to data based value creation are still incipient or under development, conceptual works that reflect the diversity of data driven value creation strategies in organizational environments are scarce. There is a gap in understanding the business capabilities needed to create value from data. Organizing the body of scientific knowledge is an essential condition for advancing research on organizational factors of D&A and AI.
Discussão
The corpus of research on D&A in the context of management and business has been on the rise since 2012. A total of 1,229 scientific publications were analyzed - globally distributed and accumulating 42,000 citations - in leading journals in the Management Information Systems field. Four co citation clusters were identified, indicating the most influential contextual, theoretical, methodological, and thematic references. The keyword co occurrence strength analysis revealed five clusters, whose thematic examination consolidated predominant and emerging topics to shape the research agenda.
Conclusão
This bibliometric study highlights the innovative nature and high relevance of organizational research on D&A (an average of 37.21 citations per article and an H index of 98). The knowledge was organized, and the synthesis of perceived inferences enabled the systematization of a research agenda offering original questions to address theoretical gaps that may motivate future work and contribute to advancing scientific knowledge on D&A and AI in the field of business strategy and information systems management.
Contribuição / Impacto
The theoretical contributions are: (i) understanding the state of knowledge on the topic; (ii) mapping scientific production; (iii) organizing and discussing visual maps by identifying four co citation clusters that indicate the most important and influential publications, as well as five clusters in the keyword co occurrence analysis that indicate predominant themes; and (iv) proposing a research agenda. The findings can generate insights for researchers to explore gaps and for managers to guide their organizational D&A strategies and projects.
Referências Bibliográficas
Ardito, L., Scuotto, V., Del Giudice, M., & Petruzzelli, A. M. (2019). A bibliometric analysis of research on Big Data analytics for business and management. Management Decision, 57(8), 1993–2009.
Baecker, J., Weking, J., Hein, A., & Krcmar, H. (2025). Organizational data strategy: Unveiling key elements and strategic types. Journal of Information Technology, 0(0).
Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049–1064.
Baecker, J., Weking, J., Hein, A., & Krcmar, H. (2025). Organizational data strategy: Unveiling key elements and strategic types. Journal of Information Technology, 0(0).
Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049–1064.