Nurturing a Data‐Driven Mindset for Data‐Driven Transformation: A Conceptualization and Research Framework

ABSTRACT Despite the importance of individuals' data‐driven mindset (DDM) in the digital transformation triggered by analytics and artificial intelligence (AI) in organizations, research on this concept remains scant. This study addresses this gap by conceptualizing DDM and shedding light on its antecedents and outcomes. Based on the mindset theory of action phases, we employ the expectancy‐value theory to conceptualize DDM and propose its sub‐constructs, comprising expectancy beliefs, values, and costs that drive individuals' behavioral intentions and responses. Accordingly, we further explore how individuals' analytics knowledge relates to DDM, influencing their commitment to data‐driven approaches and, subsequently, decision quality. By providing a conceptualization and definition of DDM, this study holds original value and enriches the literature on human mindsets. This work also contributes to the digital transformation literature by elucidating the antecedents and outcome variables of DDM. It offers actionable insights into the mechanism enabling organizations to shape their employees' DDM, consequently facilitating data‐driven practices and decision‐making performance.

Authors

Institutions

Publication Details

Journal
Strategic Change
Published
2025-05-29
DOI
https://doi.org/10.1002/jsc.2678
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.57
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nurturing a Data‐Driven Mindset for Data‐Driven Transformation: A Conceptualization and Research Framework

Marjaana Gunkel, Valerio Veglio, Minh-Tay Huynh
2 citations
Strategic Change
Big Data and Business Intelligence
4.57
article

Nurturing a Data‐Driven Mindset for Data‐Driven Transformation: A Conceptualization and Research Framework

Marjaana Gunkel, Valerio Veglio, Minh-Tay Huynh
article en
2 citations

Abstract

ABSTRACT Despite the importance of individuals' data‐driven mindset (DDM) in the digital transformation triggered by analytics and artificial intelligence (AI) in organizations, research on this concept remains scant. This study addresses this gap by conceptualizing DDM and shedding light on its antecedents and outcomes. Based on the mindset theory of action phases, we employ the expectancy‐value theory to conceptualize DDM and propose its sub‐constructs, comprising expectancy beliefs, values, and costs that drive individuals' behavioral intentions and responses. Accordingly, we further explore how individuals' analytics knowledge relates to DDM, influencing their commitment to data‐driven approaches and, subsequently, decision quality. By providing a conceptualization and definition of DDM, this study holds original value and enriches the literature on human mindsets. This work also contributes to the digital transformation literature by elucidating the antecedents and outcome variables of DDM. It offers actionable insights into the mechanism enabling organizations to shape their employees' DDM, consequently facilitating data‐driven practices and decision‐making performance.

Strategic Change
Free University of Bozen-Bolzano (IT), University of Pavia (IT)
Openalex Percentile: Top 6%
Big Data and Business Intelligence
4.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.