Associations among individual cultural values, innovation effectiveness, and transformational leadership—evidence from international university students in Türkiye

Abstract

This study examines the associations among individual cultural values, innovation effectiveness, and transformational leadership among international students in higher education institutions in the Marmara Region of Türkiye. Adopting a quantitative, cross-sectional design, the study addresses the culture–leadership–innovation nexus at the individual level. While prior research has predominantly focused on innovation at the organizational level, evidence regarding individual cultural values and leadership processes remains limited, particularly in higher education and multicultural contexts. To address this gap, data were collected from 623 international students with prior internship or work experience, ensuring that leadership perceptions were grounded in real organizational settings. Cultural values were measured using Hofstede’s framework, transformational leadership through the Multifactor Leadership Questionnaire, and innovation effectiveness as a unidimensional construct. The findings indicate that individual cultural values are positively associated with innovation effectiveness. Transformational leadership was positively associated with innovation effectiveness and statistically accounted for part of the observed association between individual cultural values and innovation effectiveness. In addition, a statistically significant but limited interaction was identified, suggesting that the association between individual cultural values and innovation effectiveness varies slightly across different levels of transformational leadership. By examining innovation effectiveness at the individual level and distinguishing between the indirect statistical association and moderating role of transformational leadership, the study provides a more nuanced understanding of the culture–leadership–innovation relationship. Given the cross-sectional and single-source nature of the data, all findings should be interpreted as statistical associations rather than evidence of causal relationships.