A Decision-Making Framework for Enhancing Quality Performance through Quality Management Practices and Organizational Culture in Food Manufacturing

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DOI:

https://doi.org/10.31181/dmame7220241364

Keywords:

Decision-Making Framework, Quality Management Practices, Organizational Culture, Quality Performance, Food Manufacturing Industry

Abstract

This research presents a decision-making framework that merges quality management (QM) practices with organisational culture (OC) to improve quality performance (QP) in the food manufacturing industry. It explores how various types of OC impact the implementation of both core and infrastructure QM practices and how these relationships influence overall QP. Data were gathered using a structured questionnaire, which was distributed to a random sample of food manufacturing firms in Palestine. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to analyse the data and test the proposed relationships. The Competing Values Framework (CVF) was utilised to assess organisational culture. The findings indicate that market and clan cultures significantly foster the adoption of core and infrastructure QM practices, respectively, while hierarchical culture plays a role in enhancing supplier involvement and information quality. Both core and infrastructure QM practices were found to have a positive impact on QP, with clan culture acting as a significant moderator between infrastructure practices and performance. This study provides an empirically supported model that connects culture-driven quality management with decision-making strategies for performance improvement, offering practical insights for managers in food manufacturing, especially within developing economies.

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Published

2024-12-30

How to Cite

Yahya Saleh, Nabila Abuengelah, Ramiz Assaf, Abdalmuttaleb Al-Sartawi, & Mohammad Kanan. (2024). A Decision-Making Framework for Enhancing Quality Performance through Quality Management Practices and Organizational Culture in Food Manufacturing. Decision Making: Applications in Management and Engineering, 7(2), 658–677. https://doi.org/10.31181/dmame7220241364