10.71877/ijamad.2024.8370

Designing a Model for Intelligent Management of Agri-Businesses Supply Chain

  1. PhD Student of Business Management, Faculty of Humanities, Zanjan Branch, Islamic Azad University, Zanjan, Iran
  2. Assistant professor, Department of Management, Faculty of Humanities, Zanjan Branch, Islamic Azad University, Zanjan, Iran

Received: 24-06-2023

Revised: 25-06-2023

Accepted: 29-07-2024

Published in Issue 20-12-2024

How to Cite

Asadzadeh Manjili, S., Hajaliakbari, F., & Mohammadi, N. (2024). Designing a Model for Intelligent Management of Agri-Businesses Supply Chain. International Journal of Agricultural Management and Development, 14(2), 169-186. https://doi.org/10.71877/ijamad.2024.8370

PDF views: 149

Abstract

Ensuring food safety, preventing market imbalances of supply and demand, avoiding market inflation, and improving production efficiency and productivity, along with increasing transparency and traceability in distribution networks and supply chains of active agri-businesses, particularly in the field of basic and strategic products such as rice, tea, olives, and citrus, all rely on intelligent supply chain management (SCM). Therefore, the purpose of this applied research was to present a model based on the effective factors of intelligent SCM in agri-businesses and to identify SCM strategies and effective actions. In this regard, in addition to library studies, field studies were conducted through in-depth interviews with 33 experts from both public and private sectors in Guilan, Mazandaran, and Zanjan provinces, selected through theoretical and non-probabilistic sampling. To analyze the data, qualitative data-based and coding methods were employed. The validity and reliability of the data collection tool were confirmed. The research findings identified 1,556 open codes, 75 axial codes, and 9 selective codes, which included economic and financial factors, marketing and sales, production and operations, institutional, infrastructure and logistics, communication and information, technological and innovative, climatic, environmental, biological, and political factors. The initial model based on these effective factors was designed using qualitative analysis methods and Maxqda 2020 software. After removing 29 sub-factors with a repetition rate of less than 7, the final model was presented based on 46 sub-factors. Finally, 8 supply chain strategies and 34 effective actions for successful intelligent SCM were proposed.

Keywords

  • Intelligent SCM,
  • Agri-businesses,
  • SC Strategies,
  • Effective actions