Presenting a LARG Supply Chain Model with a Hybrid Approach in the Poultry Industry in Northern Iran

Abstract

The aim of the present study is to present a LARG supply chain model with a hybrid approach in the poultry industry in northern Iran. In terms of purpose, the present study is applied, and in terms of data nature, it was conducted using a mixed-methods approach (qualitative–quantitative). The qualitative section was carried out using a multiple fuzzy Delphi analysis approach, both deductively through a systematic review of the theoretical literature and inductively through semi-structured interviews with experts. The participants in the qualitative section included 20 university faculty members and senior managers of poultry industries, who were selected through non-probability theoretical sampling. Interpretive Structural Modeling (ISM) was used to analyze the data. The qualitative findings showed that the final indicators were classified into four main paradigms of the LARG supply chain, namely lean, agile, resilient, and green. To calculate the final weight of each indicator, the fuzzy Analytic Network Process (fuzzy ANP) method was used, and the results showed that just-in-time production, information technology, and continuous improvement obtained the highest final weights among the LARG supply chain indicators, respectively. The DEMATEL results indicate that, in the poultry industry, the lean paradigm has the highest importance with a weight of 35%, reflecting the industry’s focus on cost reduction and efficiency improvement. The agile and resilient paradigms ranked next, whereas the green paradigm has received comparatively less attention in this industry.