Developing Competency Model Using Repertory Grid Technique: The Case of Spinning Master

Authors

Praveen Kumar Srivastava, Pune Institute of Business ManagementFollow
Bhavna Jaiswal, IBS HyderabadFollow

Abstract

This paper aims to develop the Competency Model using Repertory Grid Technique. 15 Spinning Master of a large textile company in India were interviewed using repertory grid technique. The study identified 9 competencies in 3 competency clusters that are Interpersonal Relationship, Operational Efficiency and Individual Traits. The study is the first attempt to develop competency model in any textile company and can be useful in implementing competency based HR practices in the organizations. The Repertory Grid Technique used in the study helps in developing competency model in a quick and comprehensive manner that may reduce the time, labor and cost involved in the same.

Keywords

Competency, Competency Model, Competency Assessment, Repertory Grid, Textile Industry, Spinning Masters, India

Author Bio(s)

Dr. Praveen Kumar Srivastava is Professor and Deputy Director, Pune Institute of Business Management, Pune. His area of expertise is Competency Based HRM. He provides training and consultancy in in the areas of Competency based HR Practices. Correspondence regarding this article can be addressed directly to: drpraveenksrivastava@gmail.com.

Dr. Bhavna Jaiswal is Assistant Professor -HR and Soft skills, IBS Hyderabad, a constituent of IFHE University Hyderabad. Her area of expertise is conflict management and behavioral assessment. She provides training and consultancy in conflict management.

Publication Date

3-26-2017

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.

DOI

10.46743/2160-3715/2017.2530

Recommended APA Citation

Srivastava, P. K., & Jaiswal, B. (2017). Developing Competency Model Using Repertory Grid Technique: The Case of Spinning Master. The Qualitative Report, 22(3), 895-914. https://doi.org/10.46743/2160-3715/2017.2530