Prioritizing Sales Competencies Using the Best–Worst Method: Evidence from Firms in the Isfahan Science and Technology Town

Document Type : Original Article

Author

Department of Industrial Engineering, Isfahan University of Technology, Isfahan, Iran.

10.22116/jiems.2026.564889.1627
Abstract
Performance appraisal of sales teams plays a critical role in organizational effectiveness; however, many existing appraisal systems suffer from subjectivity, inappropriate weighting of indicators, and a lack of role-specific competency prioritization. In particular, limited empirical research has applied structured multi-criteria decision-making approaches to prioritize sales competencies across different organizational levels. To address this gap, this study develops a competency-based performance appraisal framework and empirically prioritizes sales competencies for managers and sales experts in commercial firms located in the Isfahan Science and Technology Town using the Best–Worst Method (BWM). Based on an extensive literature review and expert consultations, performance indicators were identified across four competency dimensions: technical, behavioral, core, and managerial. Expert judgments were collected from twelve experienced sales professionals through pairwise comparison questionnaires, and the BWM was employed to derive indicator weights, while the geometric mean was used to aggregate expert opinions and ensure consistency. The results reveal clear role-specific differences in competency priorities, with managerial competencies emerging as the most critical dimension for supervisors, whereas technical competencies were assigned the highest importance for sales experts, highlighting the need for differentiated performance expectations across hierarchical roles. This study contributes to the human resource management literature by providing a quantitative, role-specific, and replicable framework for competency-based sales performance appraisal and offers practical guidance for designing fair appraisal systems, aligning training and development programs with weighted competencies, and supporting data-driven human resource decisions to enhance employee performance and organizational effectiveness.

Keywords


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