Mohaghar, Ali, Taghizadeh Yazdi, Mohammad Reza, Maleki, Mohammad Hasan, Mansouri, Samaneh. (1404). Designing an Agricultural Biomass Supply Chain Model Using Cross Impact Analysis. سامانه مدیریت نشریات علمی, (), -. doi: 10.22067/jstinp.2025.94846.1171
Ali Mohaghar; Mohammad Reza Taghizadeh Yazdi; Mohammad Hasan Maleki; Samaneh Mansouri. "Designing an Agricultural Biomass Supply Chain Model Using Cross Impact Analysis". سامانه مدیریت نشریات علمی, , , 1404, -. doi: 10.22067/jstinp.2025.94846.1171
Mohaghar, Ali, Taghizadeh Yazdi, Mohammad Reza, Maleki, Mohammad Hasan, Mansouri, Samaneh. (1404). 'Designing an Agricultural Biomass Supply Chain Model Using Cross Impact Analysis', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.22067/jstinp.2025.94846.1171
Mohaghar, Ali, Taghizadeh Yazdi, Mohammad Reza, Maleki, Mohammad Hasan, Mansouri, Samaneh. Designing an Agricultural Biomass Supply Chain Model Using Cross Impact Analysis. سامانه مدیریت نشریات علمی, 1404; (): -. doi: 10.22067/jstinp.2025.94846.1171
Designing an Agricultural Biomass Supply Chain Model Using Cross Impact Analysis
1Industrial management Department, Faculty of Management, University of Tehran, Tehran, Iran.
2Department of Operations Management and Decision Sciences, Faculty of Industrial and Technology Management, University of Tehran, Tehran, Iran
3Department of Management, Faculty of Economic and Administrative Sciences, University of Qom, Qom, Iran
4Department of Industrial Management, Kish Campus, University of Tehran, Kish, Iran
چکیده
Objective: The present study aimed to identify and analyze the factors affecting the biomass supply chain in the agricultural sector.
Method: The present study is quantitative in terms of methodology and is a survey study in terms of data collection. The theoretical population of the study was managers and consultants active in the biomass sector in the agricultural sector. Sampling was done by judgment and the sample size was 10 people. The research questionnaires were: a screening questionnaire and an impact analysis questionnaire. The fuzzy Delphi method was used to evaluate and analyze the screening questionnaires, and the Cross Impact Analysis method was used to analyze the impact assessment questionnaires.
Findings: The present study was conducted in three stages. In the first step, 34 key factors affecting the agricultural biomass supply chain were extracted through literature review and expert interviews. In the next step, these factors were screened using the fuzzy Delphi method. Eight factors had a desirable diffuzzified number and were selected for impact analysis. The screened factors were evaluated using the interaction analysis method. The most important impact factors were: demand for biofuels and renewable energy, transportation infrastructure, biomass processing technologies, and integrated supply chain management.
Results: Practical suggestions were developed based on the most important influencing factors and focus group interviews. To improve the agricultural biomass supply chain in Iran, experts recommend that the government increase demand for biofuels by providing financial incentives, reducing taxes, and enacting supportive laws. In addition, investing in the development of transportation infrastructure, improving biomass processing technologies, and utilizing digital systems and artificial intelligence in supply chain management can help increase productivity and reduce costs. Implementing these solutions, along with strengthening cooperation between farmers, industries, and government institutions, will lead to sustainable development of the sector.