supply chain management
shahryar marzban; Morteza Shafiee; Mohammad Reza Mozaffari
Abstract
There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, ...
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There is a growing concern about the social and environmental impact of the food supply chain, and the food industry faces numerous challenges. This has created significant pressure from various stakeholders to enhance the sustainable performance of the life cycle of perishable products. In this study, we aim to assess the sustainability of the supply chain for perishable products in the food industry. After examining both external and internal factors and identifying a research gap, the structure of the present study involves a four-stage supply chain. Input and output variables were selected based on perishable products and the three dimensions of sustainability. To achieve this goal, we conducted field and library studies to identify and extract relevant input, output, and intermediary indicators for evaluating the relative efficiency of supply chains in various sectors. Subsequently, we examined the supply chain's efficiency and ranked the efficient units. Given the primary focus on perishable materials, our study involved 18 dairy and meat factories in Fars province as the statistical population. We utilized WinQSB software to analyze network downtime and to model and solve the data. The results highlight that the most significant challenges faced by the companies are in the supply sector. Based on these findings, we provide recommendations for companies to enhance their performance.IntroductionIn the food industry, there are numerous inventory systems that deal with perishable items, which have a limited shelf life. These perishable items encompass a wide range of products, including food, fruits, and medicine. Given the extensive use of these products, it is crucial to model perishable products within a supply chain context. Furthermore, reviewing the contracts and regulations among the supply chain members is of great importance for decision-making in interactive conditions. This study aims to determine the most effective ordering policies at different levels of the perishable food supply chain. The goal is to maximize the overall profit of the chain while minimizing social and environmental negative impacts. Our supply chain consists of four levels, including suppliers, manufacturers, distributors, and retailers. We have thoroughly investigated the dimensions of sustainable development, ultimately leading to an assessment of the overall performance of the chain. The primary research question we seek to answer is: 'How does the performance of the perishable product supply chain align with a sustainable development approach?MethodologyIn this section, we employed the network data overlay analysis model to assess the performance of the research supply chain and determine the efficiency of the research units, with a particular focus on perishable products. Conventional Data Envelopment Analysis (DEA) models typically overlook the steps and internal processes within Decision-Making Units (DMUs). These conventional DEA models treat each company as a DMU and limit their calculations to initial inputs and final outputs. Given that DEA has been increasingly used in recent years for buyer-seller relationships, production-distribution processes, and performance evaluations in supply chains, and recognizing that a supply chain is a unique decision-making unit with not only input and output indicators but also intermediary indicators that flow from one stage to the next, traditional data envelopment analysis models may fall short in accurately and comprehensively evaluating supply chain performance due to the network or multi-stage nature of the supply chain. Hence, this study adopts the NDEA model with a fresh approach, calculating efficiency based on sustainability indicators related to perishable products in 18 manufacturing supply chains of dairy, meat, and protein products. Conducting an in-depth study to identify the significant parameters in the research field is a prerequisite for any applied research. To this end, we conducted extensive field and library research to investigate variables and indicators across various supply chain activities. This allowed us to identify and extract meaningful input, output, and intermediate indicators for evaluating supply chain performance in the supplier's sector. After reviewing existing literature, we identified 51 specific indicators that play a crucial role in the research.ResultsAccording to research findings, it is shown that the average efficiency of the supply chain for the production and distribution of perishable products in the financial year studied by the research was 0.9634% in the suppliers' sector. This average was 0.9899 in the producers' sector, 0.9903 in the distributors' sector, and 0.9707 in the retailers' sector. Therefore, the average efficiency indicates that the most significant inefficiency problems of the studied companies are related to the supplier sector. Furthermore, the overall average efficiency is 0.9950. According to the results obtained from the Anderson-Piterson Method for Employer Units Ranking, DMU3's Supply Chain demonstrates strong efficiency, and the supply chains of DMU7, DMU2, and DMU4 followed in the subsequent rankings. All supply chains were rated based on efficiency.ConclusionAmong the supply chains of the 18 companies studied in the research that deal with perishable products, the supplier process exhibits lower efficiency scores compared to the production, distribution, and sales processes. Consequently, it is recommended that inefficient companies at each stage take action to identify the factors causing inefficiency in the production, distribution, and sale processes of perishable products. This can be achieved by modeling the performance of efficient companies, with the goal of improving the efficiency at each stage and overall efficiency. Based on the model and research results, the following topics are suggested for future research: Given that most of the inefficiency is associated with the first stage of the model, it is advisable to pay greater attention to the supply of raw materials and transportation, or to select different input indicators. The supply of raw materials for factories emerged as one of the major challenges in this research, highlighting the inefficiency at the first stage. It is recommended that separate modeling be conducted to address the supply of raw materials in the food industry. The highest inefficiency in the fourth stage of the model is attributed to the limited consideration of the social dimension in sustainable development. For future research, it is suggested to focus more on social dimension indicators, such as satisfaction, motivation, empowerment, respect, mutual trust, social commitment, and the creation of suitable working conditions, as well as workers' health and safety. Regarding the inefficiency in the second stage (manufacturers), future research could explore strategies to enhance the freshness of raw materials and the shelf life of perishable products. For the inefficiency in the third stage (distributors), future research should concentrate on modeling and designing innovative distribution systems and routing for perishable products.
production and operations management
yousef shamsi; houshang ta; soleiman Iranzadeh
Abstract
The purpose of this article is to develop a model of manufacturing flexibility in the food industry. The present research is a mixed qualitative and quantitative research method. In qualitative research, the Grounded theory method is a tool for building a conceptual model of manufacturing flexibility. ...
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The purpose of this article is to develop a model of manufacturing flexibility in the food industry. The present research is a mixed qualitative and quantitative research method. In qualitative research, the Grounded theory method is a tool for building a conceptual model of manufacturing flexibility. The statistical sample of this section includes 20 experts familiar with the subject of manufacturing flexibility. The sampling method in the qualitative section is the Snowball Sampling method. The method of data collection in this part of the interview is semi-structured. The method of data analysis in the qualitative part is a three-step process of open, axial and selective coding. The results of this section show the model of manufacturing flexibility paradigm. The data collection tool in the quantitative part is a researcher-made questionnaire based on sub-categories and concepts obtained from the qualitative stage. The method of data analysis in this section is confirmatory factor analysis and structural equation modeling. The statistical sample in this section is 201 managers of food industry companies in East Azerbaijan province. The results show that environmental dynamics, increasing competitiveness and access to new markets are among the reasons for the need for manufacturing flexibility, in which automation and timely production are considered as industry strategies to achieve manufacturing flexibility; These factors have a direct effect on increasing organizational performance and customer satisfaction as a consequence of flexibility. The results also show that intervenors such as managerial factors, financial capability, etc. can influence strategies.
supply chain management
Abolfazl Kazai; amir mohammad khani; soraya birami
Abstract
As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research ...
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As an important dimension of company performance, the impact of supply chain quality management (SCQM) on innovation performance has not been studied in internal studies. In addition, internal research into the capabilities of SCQM, a key driver for SCQM, has been very limited. To fill this research gap, this paper examines how SCQM capabilities and SCQM performance can influence firm innovation and operational performance, and how they interact with each other. For this purpose, the information of managers and experts active in the food industry in Golestan province was collected and analyzed through a questionnaire. Research findings show that SCQM practices have a positive effect on SCQM capabilities. Another result is that SCQM methods do not have a positive effect on the operational performance of food industries in Golestan province. This finding is significantly different from some previous studies. We also found that SCQM capabilities do not have a positive effect on innovation performance.
