Selecting an optimal project leader is a critical organizational process that strongly influences project performance, coordination efficiency, and overall operational outcomes. Poor selection decisions may increase delays, inefficiencies, and reduced team productivity. To address these challenges, this study applies the Weighted Aggregated Sum Product Assessment (WASPAS) method to evaluate eight project leader candidates using five leadership-related criteria: leadership ability, communication skills, professional experience, technical expertise, and problem-solving capability. All candidate scores were compiled into a decision matrix and normalized to ensure comparability across criteria. WASPAS was implemented through its dual-component structure, combining the additive Weighted Sum Model (WSM) and the multiplicative Weighted Product Model (WPM) to generate comprehensive preference values (Qi). This hybrid mechanism enables the method to capture both absolute and proportional differences in candidate competencies. The results show that WASPAS successfully ranked all candidates and identified the strongest performer, with the highest Qi value recorded at 3.00 and the lowest at 2.09, demonstrating a clear distinction in overall competency levels. The top-ranked candidate, Sintya Dwi Rachmawati, consistently scored high across all criteria, confirming the method’s capability to differentiate performance profiles effectively. These findings highlight the methodological precision of WASPAS in supporting structured leadership selection and underscore its potential to enhance fairness and analytical rigor in organizational decision-making. Overall, the study concludes that WASPAS is a reliable and practical multi-criteria decision-making technique suitable for leadership-oriented evaluations within diverse organizational contexts.
Erdiyanto et al. (Wed,) studied this question.