Factors Affecting the Performance of the LARG Supply Chain Using Qualitative Methods in Poultry Farming in Gilan Province

Kaveh Kafili Kasmaei; Arshad Farahmandian; Homa Doroudi; Nabiullah Mohammadi

doi:10.61838/kman.ijimob.4.1.21

Authors

Kaveh Kafili Kasmaei PhD Student in Industrial Management, Department of Management, Zanjan Branch, Islamic Azad University, Zanjan, Iran Author https://orcid.org/0009-0008-0196-385X
Arshad Farahmandian Assistant Professor, Department of Management, Zanjan Branch, Islamic Azad University, Zanjan, Iran Corresponding Author https://orcid.org/0000-0002-2559-834X
Homa Doroudi Associate Professor, Department of Management, Zanjan Branch, Islamic Azad University, Zanjan, Iran Author https://orcid.org/0000-0003-1635-7330
Nabiullah Mohammadi Associate Professor, Department of Management, Zanjan Branch, Islamic Azad University, Zanjan, Iran Author https://orcid.org/0000-0002-0556-4951

DOI:

https://doi.org/10.61838/kman.ijimob.4.1.21

Keywords:

LARG supply chain, poultry farming, agile, lean, grounded theory

Abstract

Objective: The aim of this research is to identify the factors affecting the performance of the LARG supply chain using qualitative methods in poultry farming in Gilan Province.

Methodology: This research adopts a qualitative approach and utilizes the grounded theory method. Data were collected through semi-structured in-depth interviews. Twenty experts and specialists, including university faculty members and managers with at least 15 years of experience in management, were selected through purposive sampling and the snowball technique. The validity of this research was examined and confirmed by the interviewees and subsequently by specialized professors. To assess reliability, the test-retest method was employed. The reliability of the interviews conducted in this study was 84%, and since this value is above 60%, the reliability of the coding is confirmed. Data were analyzed using the constant comparative method in three stages: open coding, axial coding, and selective coding. The qualitative findings were analyzed using MAXQDA software, and ultimately, the paradigmatic model of the supply chain was explained.

Findings: The model's goodness-of-fit indices indicated a satisfactory fit of the data with the conceptual model, meaning that the quantitative data were in good agreement with the conceptual model of the research and supported the qualitative data.

Conclusion: The study revealed that several key factors, including customer relationship management, service delivery management, information management, employee management, financial management, capacity and resources management, pollution management, ethical management, economic factors, social factors, technological environment, political environment, and laws and policies significantly influence the supply chain performance.