A model for supply chain risk management and operational performance in the food retail industry in Zimbabwe

Abstract

The importance of the food retail industry and its role in stimulating economic growth and ensuring food availability as the final actor in the food supply chain in many countries is well documented in literature. This stands true in the case of Zimbabwe, where the industry has grown tremendously to become a significant contributor to the gross domestic product through employment creation, tax contributions and infrastructural development. Despite these contributions, the industry faces challenges in the form of supply chain risks. This is primarily due to the nature of the retail supply chain in Zimbabwe where over two-thirds of the products sold are imported. This forms the basis of this study which seeks to understand how supply chain risk management in food retail firms impacts on firm operational performance. Thus, this study aimed to investigate the relationships between supply chain risk management and operational performance in the food retail industry in Harare, Zimbabwe. To achieve the study’s aim, several variables were considered; namely, supply chain risk management, supply chain risk information sharing, and supply chain risk analysis and assessment, supply chain risk-sharing mechanisms and operational performance. The study followed a quantitative research approach based on a positivist paradigm. A total of 264 food retail firm owners, managers and professional employees who possess knowledge on supply chain risk management in Harare were selected using a non-probability, purposive sampling technique. Data were then collected using a close-ended survey questionnaire which was developed using adapted measurement scales. The collected data were analysed using the Statistical Packages for Social Sciences (SPSS version 25.0) and the Analysis of Moment Structures (AMOS version 25.0) statistical software. The applied data analysis techniques included descriptive statistics and inferential statistics. Inferential statistics used two approaches, namely, Exploratory Factor Analysis (EFA) and Structural Equation Modelling (SEM). The EFA tested for the factor structure of the collected data, whereas SEM tested for both psychometric properties of measurement scales and the relationships in the proposed hypotheses. The results of the study showed that supply chain risk management has a direct and significant relationship with both supply chain risk information sharing and supply chain risk analysis and assessment. Supply chain risk analysis and assessment yielded a positive and significant relationship with supply chain risk-sharing mechanisms. The relationship between supply chain risk analysis and assessment and supply chain risk-sharing mechanisms was significant but weak. Supply chain risk-sharing mechanisms had a strong and positive relationship with operational performance. There was, however, no significant direct relationship between supply chain risk management and operational performance. Insights gained from this study have merit from both theoretical and practical perspectives. Theoretically, the study provides an understanding of some driving factors to supply chain risk management, supply chain risk-sharing information sharing, supply chain risk analysis and assessment, supply chain risk-sharing mechanisms and operational performance within the food retail industry in Zimbabwe. Since there is limited evidence of similar previous studies in Zimbabwean food retail firms, the results are an essential addition to the existing body of literature within the area of supply chain management and supply chain risk management in the context of a developing country. From a management perspective, the study suggests specific recommendations that should be implemented for the optimisation of all five constructs.