Journal of Industrial Engineering and Management Studies

Abstract In recent decades, the world has focused on a new concept that emphasizes the effective protection of the environment and careful use of natural resources; these emphases bring the goals of sustainable economic, environmental and social growth. Sustainable development (SD) means the development and progress of the current generation while preserving resources for the development of the future generation. The main purpose of this research is evaluation of key cement production industries based on SD factors with a combined approach of FAHP-FVIKOR. The statistical population includes 55 experts and specialists familiar with the concept of SD in 5 key industries of Iran's cement industry. Due to the limited community and lack of access to them, the opinions of 33people were finally used. The research method was practical in terms of its purpose, and it was a descriptive survey type using two questionnaires in terms of the data collection method. For this purpose, to evaluate the importance of three key factors in SD, FAHP (Analytic Hierarchy Process) approach was used and the weight of the factors was calculated. The results showed that the economic sustainability factor is more important than the environmental and social sustainability factors. Next, in order to evaluate the mentioned 5 industries based on SD factors, the fuzzy VIKOR (VlseKriter ijumskaOptimizacija I KompromisnoResenje) technique was used and the final ranking of the industries was extracted. The present research is the first applied research in the field of evaluating the SD factors of the country's cement industry and ranking the key cement industries with multi-criteria decision-making techniques; So that its results can be used in the evaluation of other cement production industries and related industries of the country.

Abstract This study aims to develop a comprehensive framework for integrating blockchain technology into the supply chain of Golrang Industrial Group. Employing a qualitative research approach, the study follows a data-driven theoretical methodology based on the Strauss and Corbin paradigm model. The research population consists of food industry factories affiliated with Golrang Industrial Group. Data collection was conducted through open interviews with ten industry experts and university professors, selected purposefully. The gathered data underwent analysis using the grounded theory method, comprising open coding, axial coding, and selective coding. The proposed model includes 54 indicators categorized into 19 concepts. The findings reveal that causal conditions for blockchain integration include strategic planning, blockchain structure design, inter-company collaboration, and financial infrastructure development. Industrial transformation, IoT, and artificial intelligence are key enablers, while employee training, continuous data updates, and skill-based selection of blockchain technology play essential roles in implementation. Effective background conditions involve transformational leadership, regulatory frameworks, and scaling mechanisms. The strategies identified include identity and access management, encryption, and secure data transmission. The study highlights blockchain’s potential to enhance production security, corporate transparency, product traceability, and cost efficiency in transportation and maintenance. Path coefficient analysis indicates “intervening factors” have the highest impact on “strategies” (0.819), followed by “contextual conditions” (0.625) and “strategies” on “implications” (0.570). These findings provide valuable insights into both the opportunities and challenges of blockchain implementation in supply chain management.

Abstract Maturity models mostly assess phenomena in each industry or organization and investigate the readiness to accept those phenomenon and paradigms. The Fourth Industrial Revolution has emerged and revealed as a new phenomenon in various industries, whose maturity model has garnered the attention of numerous experts and specialists. Considering that there is no such a model in the banking service supply chain, the present study sought to design a conceptual model for the maturity of Industry 4.0 with a focus on financial technologies and digital transformation. Thus, by conducting interviews with experts, including bank managers, and university professors, basic themes were extracted using a thematic analysis approach, based on which the final model was then designed, including seven organizing themes of managerial factors, infrastructure factors, information technology factors, human resource factors, cultural factors, economic factors, and business factors. The final model, which included seven sub-models, was validated using factor loading analysis, as a result, the findings of which showed that all sub-models were significant at a 95% confidence level; therefore, the designed model was valid enough in the qualitative section.

Abstract In this research, a new emerging model for the Tehran stock exchange market is considered, and a model with realistic constraints for the mentioned market is provided. Realistic constraints are incorporated in this model for applicable purposes, one of which is the transaction cost. The limited maximum number of stocks that should be invested is also considered. Additionally, constraints have been added to the classic portfolio selection model to prevent stocks from being bought in tiny quantities and avoid over-buying some stocks. The mentioned constraint can improve diversity in the selected portfolio. One of the factors considered by many financial market investors is the amount of liquidity of the stocks they have purchased. This study also considers the amount of portfolio liquidity as one of the essential objective functions affecting the selection of the portfolio. Finally, in the model presented in the present study, the investors can have a different stock portfolio according to their preferences. The proposed model is multi-objective fuzzy goal programming, which can simulate uncertainty in the Tehran stock exchange market and provide a rational framework for investors who invest in the financial markets. As the numerical instances show, the solutions when additional constraints are added to the mathematical model are close to exact results. This difference became significant when the maximum number of stocks increased. According to the results, when the number of stocks increases, GAMS software loses its functionality, and the utilization of meta-heuristics as an option is inescapable. Finally, the harmony search algorithm with added realistic constraints has provided better portfolios in such a situation. To compare the results, a genetic algorithm was used as the competing algorithm. After solving different instances and comparing the results of the algorithms, the superiority of the proposed harmony search algorithm has been proved.

Abstract Recently, there has been a notable increase in research efforts focused on achieving supply chain (SC) coordination by considering corporate social responsibility (CSR) as a crucial factor in decision-making. This study explores the coordination of a two-stage SC, including a manufacturer with CSR investment and a retailer with marketing efforts, under deterministic and stochastic with partial information demand scenarios. Furthermore, it analyzes decisions related to pricing, order quantity, CSR investment, and marketing efforts by presenting decentralized, centralized, and coordinated strategies. A comprehensive numerical analysis, involving a numerical example and a set of sensitivity analyses, is conducted to evaluate the efficacy of the proposed models. Results indicate that a two-part tariff (TPT) contract can effectively coordinate the SC and motivate the manufacturer to enhance its CSR investment, ultimately resulting in profitability equivalent to that of the centralized strategy. Moreover, the manufacturer's CSR investment and the retailer's marketing efforts contribute to increased market demand and profitability.

Abstract Wheat is one of the most essential crops and plays a critical role in global food security. Therefore, effective management across all stages of the wheat supply chain is vital. This study presents a sustainable wheat supply chain model that integrates economic, environmental, and social considerations. A mixed-integer linear programming (MILP) model is developed to minimize wheat loss and waste while optimizing key sustainability objectives. Economically, the model aims to reduce total supply chain costs, including those related to production, storage, transportation, and facility establishment. Environmentally, it seeks to reduce greenhouse gas emissions, while socially, it strives to enhance job opportunities through the development of new facilities. The model incorporates elements such as animal feed centers and facilities for waste collection, recovery, and disposal. It also accounts for losses during harvesting, transportation, and processing. The multi-objective epsilon-constraint method was employed to solve the model and analyze the impact of various parameters. Using real data from Isfahan Province, Iran, the results show that wheat waste can be reduced from 25,000 to 7,000 tons by upgrading harvesting machinery. Additionally, by reducing transportation losses to meet global standards and lowering bread waste by 1%, the province could save 15,000 tons of wheat. The model also supports the construction of one new silo and one waste collection center, which would create a considerable number of jobs. These findings highlight the role of sustainable supply chain design in mitigating food loss, improving resource efficiency, and enhancing long-term food security. The study offers valuable insights for policymakers and industry stakeholders, emphasizing the importance of integrating sustainability measures into supply chain management.

Abstract Software development projects in the banking industry face numerous challenges on the path to success due to extensive stakeholder interactions, the need for change management, and technical and managerial complexities. Previous research has shown that the success of these projects depends not only on hard factors (such as budget and scheduling) but also on soft factors (such as organizational culture, team interaction, and product quality). Accordingly, the present study aims to identify and determine the soft criteria influencing the success of such projects. This exploratory, applied, and mixed-methods study, using a descriptive-survey approach, initially identified criteria and sub-criteria through a meta-synthesis method by reviewing 30 selected articles. As a result, 51 sub-criteria, 11 key criteria, and 3 main domains were extracted and presented in the form of a theoretical model. In the next step, through interviews with experts in the banking network, the number of sub-criteria increased to 63. After screening through two rounds of Fuzzy Delphi by employees of Refah Bank, 38 sub-criteria and 11 key criteria were finalized. Then, using the Fuzzy DEMATEL technique, the influence and interdependence of the criteria were analyzed, and the causal diagram and network of relationships highlighted the central role of "product quality”. Findings showed that "product quality", characterized by factors such as reduced downtime, system security, and code quality, has the greatest influence. Following that, criteria such as project resource management, digital governance realization, proper utilization, and stakeholder satisfaction were identified as key factors. These results can assist banking project managers in improving product quality and increasing the likelihood of project success.

Abstract In today's world, supply chain discussion or performance evaluation debate is one of the most important issues in any industry. Performance evaluation refers to a set of actions and information that is implemented to increase the level of optimal use of resources and facilities in order to achieve goals in an economical manner combined with efficiency and effectiveness. Generally, the performance management system can be considered as a process of measuring, evaluating and comparing the amount and manner of achieving the desired status and, finally, improving performance. In this research, the efficiency of 7 units of the Iranian Electric Motors company is addressed using data envelopment analysis. To assess the company's efficiency, it has been used some parameters include intermediate cost, manpower costs, depreciation cost, value of outputs and value of data, and two outputs of factor productivity and competitiveness. So, using the data envelopment analysis, the efficiency of the model was obtained and the weighted criteria were calculated by the fuzzy TOPSIS multi-criteria decision-making method. Given that these supply chains are considered as the statistical society of the electromotor industry, and given that the average technical efficiency is 0.584, it can be concluded that the industry faces 0.416 technical inefficiencies, in its turn, it is a high value.

Abstract This study proposes a four-stage blood supply chain network for crisis conditions, integrating donor groups, permanent/temporary blood collection centers, regional blood centers, and hospitals. A multi-objective, multi-period integer linear programming model optimizes blood distribution using unmanned aerial vehicles (UAVs), ambulances, and vehicles to minimize total supply chain costs and maximum travel times. Computational experiments and a real-world case study in Kurdistan province, Iran, demonstrate that UAVs with higher speeds (150 km/h) reduce travel times by up to 35% and costs by 22% compared to baseline (100 km/h), while increasing UAV capacity from 1.6 kg to 2.2 kg decreases Pareto optimal solutions by 16%, indicating improved efficiency. Deploying 150 UAVs (vs. 110) shifts the Pareto front, lowering costs by 18% and maximum travel times by 1.2 hours. Sensitivity analyses reveal UAV specifications critically impact performance, with optimal blood allocation achieved when donor groups supply centralized processing. The epsilon-constraint method solves problems of varying scales, with CPLEX achieving solutions for medium instances in under 40 minutes, highlighting UAVs’ role in enhancing crisis-response blood supply chains.

Abstract Social trust is defined as an individual's reasonable opinion towards other members of society, which leads to expanding and facilitating social relations. Trust is vital as a social mechanism with diverse social, political, economic, and psychological functions. Many studies have been conducted on social trust, and several factors have been introduced. Most of these studies are primarily static and focus on the structural investigation of social trust and do not consider the inter-relation effects among essential parameters. To cover this gap, a dynamic approach is presented in this manuscript. This research identifies and models factors affecting social trust using the system dynamics approach and aims to analyze the behavioral equations of the subject under dynamic conditions which is addressed as the main contribution of this paper. For this purpose, an online questionnaire is designed, data are collected from 1238 Iranian social network users, and the cause-effect model is presented. The proposed model is simulated in Vensim under three scenarios, and the results revealed that having a 0.68% population growth rate, social trust will reach a maximum of 56% over 35 years and begin to decrease afterward. More simulations showed that a 1% population growth rate leads to a 52.5% equilibrium in the long term. Besides, a slightly higher growth rate (1.2%) does not lead to balance, and social trust will continue to experience a declining situation.

Abstract Start-up projects are increasingly gaining attention from investors and entrepreneurs due to changing paradigms, making their evaluation essential. But problem is that start-ups like any other firms have some risks that they are not familiar with. On the other hand, there is less research in literature which explore and assess start up project risks that can be considered as a gap. This research addresses a gap in the literature by comprehensively identifying, evaluating, and managing risks associated with start-up projects. Utilizing FMEA, fuzzy MCDM, and a mathematical model, the study aims to rank the risks of start-up projects and determine optimal strategies to mitigate them. Fuzzy MCDM technique in weighting part was Swara that was used for determination of measures weight and in ranking part was WASPAS that was used for ranking alternatives. The projects examined include Snapp, Tapsi, DigiKala, Aparat, CafeBazzar, and Alopeyk in Iran. The results reveal that time is the most significant risk factor, with a value of 0.53, followed by cost at 0.30 and quality at 0.17. Furthermore, the most critical risks identified include resource shortages and supply challenges, closely followed by team size, time pressures, and the business plan, with uncertainty ranking prominently as well. The final analysis provides optimal strategies focused on minimizing time and cost, emphasizing their optimization in risk response. This research can help managers to decide about project based on their risks and also start up business population can get information about probable risks of their project before and after running them.

Abstract Aim of this research is to provide a stochastic fuzzy model for scheduling and selection of project portfolio in multi model sustainable and resilience condition. In real environments projects are executed in multi modes and the aim of sustainability maximization and resilience in project portfolio are pursued. For this goal librarian studies have been done based on this, a stochastic fuzzy programming model was implemented that aim to schedule and select sustainable and resilience project in multimode situation. Model was validated and was solved in small dimension. Then it was analyzed by two algorithms NSGAII and MOPSO. Results indicate that NSGAII has better performance then MOPSO and is more efficient. The most of influencing is on current value and then sustainability and resilience and sustainability is influenced by reinvestment similarly. But influencing current value from reinvestment rate is significant. Impact of loan interest on objective function is totally descending. It means if loan interest is increased all objective function can be decreased that resilience most of others and then sustainability and finally current value is decreased. It seems this function are decreased between 17 to 23 percent in 50 percent increase of loan interest.