A BWM-TOPSIS Linear Programming Model for Evaluating the Performance of Health-Promoting Hospitals with McKinsey 7s Framework in Organizational Management

Amin Lawong; Arpakorn Kejornrak; Nuchsara Kriengkorakot; Preecha Kriengkorakot

doi:10.59796/jcst.V14N2.2024.23

Authors

Amin Lawong Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani, 34190, Thailand
Arpakorn Kejornrak Health Consumer Protection and Pharmacy Department, Maha Sarakham Provincial Health Office, Maha Sarakham, 44000, Thailand
Nuchsara Kriengkorakot Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani, 34190, Thailand
Preecha Kriengkorakot Faculty of Engineering, Ubon Ratchathani University, Ubon Ratchathani, 34190, Thailand

DOI:

https://doi.org/10.59796/jcst.V14N2.2024.23

Keywords:

Health promoting hospital, Best-Worst Method, BWM, TOPSIS linear programming model, McKinsey 7s framework

Abstract

This research addresses the critical aspect of evaluating operational performance in health promotion hospitals, which play a vital role in providing medical services to local communities. The research proposes an integrated method for performance assessment, utilizing the Best-Worst Method (BWM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) linear programming model. Taking the case of health promotion hospitals in Maha Sarakham province, Thailand, and considering the McKinsey 7s framework's seven criteria, BWM is employed to determine the criteria weights. Subsequently, the TOPSIS linear programming model selects the ideal health promotion hospital based on these weights. The BWM analysis reveals criteria weights in the following order: system, staff, skill, style, structure, strategy, and shared value. The TOPSIS linear programming model identifies SH12 as the top-performing health promotion hospital with a closeness coefficient value of 0.8821. Additionally, a Spearman's rank correlation test validates this proposed method against the original TOPSIS approach, yielding a correlation value of 1.0. These findings provide valuable guidance for organizations, particularly in shaping strategic policies and resource allocation within medical service units, medical equipment, and personnel management in organizational settings. This study offers that the proposed method is simpler and will aid in the ongoing analysis of strengths and weaknesses in the improvement of organizations and development, helping organizations adapt to changes.

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