<![CDATA[Purpose - This study aims to examine the influence of workforce diversity and employee commitment on innovation performance at Injourney Destination Management (IDM), a state-owned tourism enterprise in Indonesia. The research addresses how variations in demographic attributes and levels of commitment among employees contribute to innovation outcomes within the organization. Design/methodology/approach - A quantitative research method with a causal-descriptive design was applied. Data were collected through structured questionnaires distributed to 154 employees and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. Validity and reliability were tested through AVE, CR, and Cronbach's Alpha. Hypotheses were assessed using t-statistics and p-values. Originality - The novelty of this study lies in its integrated assessment of workforce diversity and employee commitment as combined predictors of innovation performance in a government-owned tourism organization. Such an approach remains relatively underexplored in the context of Indonesia’s public sector tourism industry. Findings and Discussion - The results show that both workforce diversity and employee commitment significantly and positively influence innovation performance. Workforce diversity, particularly across gender, age, ethnicity, and education, was found to foster creative outputs. Meanwhile, affective and normative aspects of commitment played a key role in strengthening employee contributions to innovation. The R² value of 0.404 and Q² value of 0.357 indicate a moderate to strong explanatory and predictive relevance of the model. Conclusion - This study concludes that diversity in the workplace and strong employee commitment are critical drivers of innovation performance. The findings underscore the need for inclusive HR practices and emotional engagement strategies to optimize innovation, especially within public-sector tourism enterprises. Future research is encouraged to explore alternative constructs and employ longitudinal methods for broader generalization. ]]>
