Anais
Resumo do trabalho
Tecnologia da Informação · Ciências de dados e Inteligência analítica
Título
Data Leadership Scale: Validation and Analysis of its Relationships with Project Success
Palavras-chave
data leadership
scale validation
project succes
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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Mariana Motta FleckUNIVERSIDADE 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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Mauricius Munhoz de MedeirosUNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL (UFRGS)
Resumo
Introdução
The growing demand for data-driven decision-making has expanded the need for leaders capable of translating analytical potential into strategic value. In environments marked by uncertainty and complexity, effective data use requires not only infrastructure but also leaders who foster an analytical culture, encourage collaboration, define governance, and align data with organizational objectives.
Problema de Pesquisa e Objetivo
Despite the importance of the topic, there is still a lack of validated instruments to structurally assess the different types of data leadership and their impact on data project success. This study aims to develop and validate a scale for measuring data leadership types and to analyze its relationship with project success.
Fundamentação Teórica
Leaders who can mobilize teams, make strategic decisions, and promote adaptive practices positively influence project outcomes, especially when they adjust their management style to the degree of innovation, complexity, and urgency. In this context, data leadership is considered a critical factor for project success. A recent systematic review identified four main types of data leadership: visionary, decision-maker, driving, and educator. However, there are no empirical studies that have validated and measured these constructs.
Metodologia
The instrument was built to fill this identified gap and underwent validation by seven experts, using similarity analysis and a content validity index. Empirical data were then collected from a sample of 91 respondents. The proposed data leadership scale was validated via exploratory factor analysis. Finally, the overall research model was assessed to analyze the relationship between the data leadership dimensions and project success.
Análise dos Resultados
The four-dimensional data leadership measurement scale was developed and validated through similarity analysis techniques, content validity, and exploratory factor analysis. The findings support that the driving, visionary, and educator dimensions of data leadership are positively related to project success. However, the relationship between decision-maker data leadership and project success was not supported. The final model shows strong determination, predictive relevance, and fit indicators.
Conclusão
This study fully achieved its objectives of developing and validating a scale to measure data leadership types and investigating their relationship with data project success. Based on evidence from face and content validity processes, as well as exploratory factor analysis, the research instrument was developed and validated. Thus, the first empirically validated multidimensional data leadership scale is delivered. Additionally, its relationships with project success were analyzed.
Contribuição / Impacto
This work offers an original and relevant theoretical contribution with practical impact in the field of data management and leadership. The study consolidates data leadership as a measurable, multidimensional construct, advancing beyond the fragmented literature and providing an empirical foundation for future investigations. For organizational practice, it delivers an applied instrument to diagnose leadership types and guide training and management strategies in data driven projects.
Referências Bibliográficas
Fleck, M. M., & Maçada, A. C. G. (2025). Leadership in Management Information Systems: A Systematic Review. AMCIS 2025 Proceedings.
Haude, C., Blohm, I., & Lagardère, X. (2024). How Lufthansa Shapes Data Driven Transformation Leaders. MIT Sloan Management Review.
MacKenzie, S., Podsakoff, P., & Podsakoff, N. (2011). Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques. MIS Quarterly, 35, 293–334.
Haude, C., Blohm, I., & Lagardère, X. (2024). How Lufthansa Shapes Data Driven Transformation Leaders. MIT Sloan Management Review.
MacKenzie, S., Podsakoff, P., & Podsakoff, N. (2011). Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques. MIS Quarterly, 35, 293–334.