Clustering Innovation Behaviors Using Machine Learning: Roles of Future Time Perspective and Proactive Motivation - Solberg, Henrik; Sánchez Romero, Laura; Moreau, Julien (International Journal of Innovation Management and Organizational Behavior (IJIMOB), 2026)
Objective: This study aimed to identify distinct profiles of employee innovation behaviors using unsupervised machine learning and to evaluate the predictive roles of future time perspective and proactive motivation in determining membership within these empirically derived behavioral clusters. Methods and Materials: A quantitative, cross-sectional design was utilized to collect data from a purposive sample of professionals employed in various knowledge-intensive sectors across Spain. Participants completed validated self-report questionnaires assessing three core dimensions of innovation behavior (idea generation, idea promotion, and idea realization), alongside measures of future time perspective and proactive motivation. The analytical framework employed a K-means clustering algorithm to partition the multidimensional innovation scores into distinct profiles, followed by multinomial logistic regression models to evaluate the predictive capacity of the psychological variables in determining cluster categorization. Findings: The K-means clustering analysis ( ) successfully identified three distinct behavioral profiles: “Passive Innovators” ( , ), “Moderate Innovators” ( , ), and “High Innovators” ( , ). The multinomial logistic regression model demonstrated robust predictive power (Nagelkerke ). A one-unit increase in future time perspective significantly increased the odds of an individual belonging to the High Innovators cluster rather than the Passive Innovators cluster ( , ). Furthermore, proactive motivation emerged as an exceptionally strong differentiator; a one-unit increase in proactive motivation drastically elevated the likelihood of being classified as a High Innovator compared to the passive reference group ( , ). Conclusion: Fostering a future-oriented mindset and cultivating intrinsic proactive motivation are critical psychological catalysts for transforming passive employees into highly engaged innovators capable of driving ideas from initial conception to full realization.