Conceptualizing the data-driven mindset: An application of the mindset theory of action phases
基于行动阶段心态理论，将数据驱动心态概念化为自我效能、价值观和成本三个核心成分，并通过251份问卷数据验证这些成分对行为意图的影响，为促进数据驱动转型提供指导。
Although employees' Data-Driven Mindset (DDM) plays a key role in developing a data-driven culture and supporting data-driven transformation, research on this concept is still limited. Drawing on the mindset theory of action phases (MTAP), we address this gap by applying the expectancy-value theory to conceptualize DDM, comprising three core components: self-efficacy, values, and costs. These elements influence individuals' behavioral intention and responses. Furthermore, we establish the relationship between personal innovativeness, DDM factors, and intention. Empirical analysis (N = 251) reveals that innovativeness, although linked to the DDM composite, does not affect intention and, therefore, it is not a DDM constituent. Self-efficacy and values positively influence intention, while perceived costs negatively impact it, underscoring their role as DDM factors. This study pioneers the conceptualization of DDM through the proactive lens of MTAP, uncovering the dynamic cognitive orientations driving individuals' data-driven behaviors. We emphasize the importance of fostering a positive DDM to shape individuals' engagement in data-driven transformation by enhancing their self-efficacy and values while reducing perceived costs.