Journal of Industrial Engineering and Management Studies

Abstract Customer equity, the potential profit that all of the company's customers can generate throughout the business-customer relationship, is a critical business management concern for companies. In the face of intelligent customers and high market competition, the survival of any brand depends on its ability to increase the specific value of the customer, the management of customer relations, and retention. However, studying customer equity management under dynamic situations and analyzing factors affecting social media marketing has not been fully explored. A dynamic approach is presented in this manuscript to cover this gap. This research proposes a model using the system dynamics approach to analyze and predict the influence of social media marketing activities on customer equity. The model, simulated in Vensim under two possible scenarios, provides practical insights. The results show that if the policy of commercial companies leads to a decrease in customer equity, the customer's loyalty will not last for more than ten months. Conversely, increasing customer equity leads to a reliable, steady state of customer loyalty after the fourth month, demonstrating the practical implications of the research that should be noticed by the department of marketing management.

Abstract In recent decades, the effective use of information technology (IT) systems has become an integral part of industries. On the other hand, due to the benefits of these systems (cost reduction, access to the latest technology versions, monitoring and control, risk reduction, improvement of plans for future progress, and ultimately improvement of productivity), the use of IT outsourcing systems has been a special focus of these industries. However, the use of this system has always faced risks and challenges. This research aims to evaluate the key risks effective in IT outsourcing and to rank selected software companies in successful adaptation to IT outsourcing. For this purpose, the opinions of 75 experts were used to evaluate the risks and rank the companies. A binomial test (BT) approach was used to identify the final risks. The result showed that 6 risks are effective in IT outsourcing. Also, the risk assessment with a weighted average (WA) showed that technical risks are in the first importance and communicational risks are in the last importance. Ranking of companies based on the weight of risks with the Simple Additive Weighting (SAW) technique showed that the first software company was ranked first and the third company was ranked seventh. Based on the evaluations, practical suggestions were provided to companies. The proposed model of this research provides a suitable perspective for company managers in facing the risks of IT outsourcing.

Abstract With the occurrence of the Fourth Industrial Revolution worldwide, industries are facing transformation, and Iranian industries will inevitably be part of this transformation. Although some industries, such as transportation and logistics, have embraced these changes, other industries, such as insurance, have struggled to leverage the benefits of these transformations and have lagged behind. The question arises: why have some industries undergone fundamental changes under similar general condi-tions, while others have not? This research aims to provide a roadmap for fundamental changes in domestic industries by com-paring a successful industry with an unsuccessful one. Based on this, four scenarios—digital transformation, digital evolution, startup creation, and change planning—were derived from in-depth expert interviews in startup companies within these indus-tries. Through thematic analysis, a strategic framework has been proposed to determine the roadmap for industry transformation. Companies operating in various industries can utilize this practical framework to design and implement their industry trans-formation roadmap.

Abstract The aim of this study is to identify the challenges involved in the business development of knowledge-based companies active in the FinTech sector. This research is categorized as applied-developmental in terms of its purpose and employs an exploratory mixed-methods approach from a methodological perspective. In the qualitative phase, the grounded theory strategy following Strauss and Corbin’s systematic approach was used for data analysis. Data were collected through semi-structured interviews with 20 experts, including 9 university professors and 11 FinTech managers. Data analysis was conducted using MAXQDA software in three coding stages: open, axial, and selective, resulting in the identification of 625 initial codes and 99 sub-categories. In the next phase, to examine the relationships between the challenges and development strategies, Interpretive Structural Modeling (ISM) was employed. The results indicated that factors such as fostering a culture of adaptability, customer experience strategy, and the improvement of operational and sustainability infrastructures play a key driving role in the development of FinTech businesses. These findings can serve as a foundation for formulating optimal strategies to overcome development barriers in knowledge-based FinTech companies.

Abstract This study presents a novel approach to optimizing facility breakdown scenarios within a multi-period routing and location framework for a two-echelon supply chain. The increasing emphasis on sustainability and resource efficiency has led to the emergence of circular economy principles in supply chain management. We develop a comprehensive model that addresses the complexities of vehicle routing and facility location while accounting for potential disruptions caused by facility breakdowns. By integrating multi-objective optimization techniques, our model aims to optimize two objectives. The first objective is to minimize the total cost per path. The second goal is to minimize the total repair time of vehicles to visit all areas. The Epsilon Constraint (EC) method has been used to solve the proposed model to obtain non-dominate solutions. The applicability of the proposed model is shown via a numerical problem. The results obtained from solving the proposed model are compared with the routing plan. The comparisons show that the results obtained through solving the proposed model are better than the current routing programs. Based on the obtained results, the lowest allocation cost and duration of vehicle repairs have been calculated separately in each period. In the first period, the lowest and in the second period, the highest amount of cost has been calculated. In addition, in the second period, the lowest and in the third period, the maximum service time of vehicles has been determined. Through a series of simulations and case studies, we demonstrate the effectiveness of our approach in achieving optimal routing strategies and facility placements, ultimately contributing to more robust and efficient supply chain operations. The findings underscore the importance of proactive planning in mitigating the impacts of facility breakdowns, providing valuable insights for practitioners and researchers in the field of supply chain management.

Abstract Nowadays offering attractive warranty offers along with selling products become a common tool in marketing. Warranty offers make sure the customer about receiving some services in the case of product failure during its useful lifetime. On the other hand, they help manufacturers to protect their reputation in the case of product failure by providing repair services for their customers. In this study, a repairable product after initial performance test (which is known as the burn-in test) sends to the market with a non-renewable linear pro-rata warranty offer. If during burn-in test or warranty periods minor or major failure occurs, depend on the failure type, the product is repaired minimally, generally, or replaced. In this study, the cost model for these two periods is extracted and optimum values for the length of burn-in test and warranty period with the aim of minimizing average total cost from manufacturer perspective is obtained. In order to show the applicability of the proposed model, a numerical example is presented.

Abstract All Social orders depend on and advantage from the significant and important parcel of worldwide trade that it’s backed by consolidation-based transportation over brief, medium, long and interconversion separations. By consolidating the cargo of different shippers into the same stacking units for their full or fractional journeys, consolidation looks for to extend operational and financial efficiency. This paper's focus is on consolidation-based transport and the tactical planning difficulties carriers confront when creating a set of scheduled services that viably and profitably match resource allocation with expected shipping requests over a medium- to long-term timeframe. The main contribution of this research is to provide a new integrated MOFCCP model for supply chain (SC) planning that simultaneously calculates the total tardiness, minimizes the total costs including fixed and variable travelling, purchasing and waiting cost and minimizes the total risk of travel routes. This study addresses the crucial supply chain challenges of multi modal transportation routes. Global SCs encounter major difficulties when it comes to SCM due to uncertainty. In this paper, a supply chain network (SCN) is designed using a novel multi-objective optimization model that accounts for multi modal transportation routes uncertainty. Fuzzy goal programming (FGP) is used to assist businesses in making decisions and the trade-off between the costs and benefit of alternative options because of multiple competing objectives. The primary goal of designing the suggested SCN is to minimize the overall risk of multi modal transportation costs. In order to manage the uncertainty, the novel multi-objective mathematical model is subjected to fuzzy chance constrained programming (FCCP), and a case study in steel company is carried out to investigate.

Abstract Manufacturing small and medium enterprises (SMEs) in Iran play a pivotal role in employment, innovation, and industrial output. However, national financial crises, such as economic sanctions and currency devaluation, coupled with global disruptions like the COVID-19 pandemic, threaten their sustainability. This study aims to develop a comprehensive framework for the internationalization of Iranian manufacturing SMEs under crisis conditions. Employing a qualitative approach, data were collected through 20 semi-structured interviews with managers from SMEs in the automotive parts, food, industrial machinery, plastics, and pharmaceutical sectors. The analysis identified key drivers, challenges, strategies, market entry pathways, and outcomes of internationalization. Findings revealed that currency devaluation (85%), domestic market stagnation (75%), and opportunities in neighboring markets (95%) were primary drivers. Challenges included foreign currency payment issues (85%), logistical barriers (80%), and lack of awareness of international regulations (60%). SMEs adopted strategies such as flexible currency contracts (90%), barter trade (60%), cryptocurrencies (25%), and export-oriented technological advancements (55%). Market entry pathways, aligned with the Uppsala model, encompassed commercial networks (95%), local agents (95%), and international exhibitions (45%). Outcomes included sustainable growth (85%), entry into new markets (75%), and job retention (60%). The proposed Structural Interpretive Model (SIM), integrating the Uppsala model, network theory, and risk management principles, offers a practical framework validated through theoretical and practical triangulation. Recommendations include training programs, government support, and investment in digital infrastructure.

Abstract The complexity of the food supply chain is increasing and due to the elements, such as climatic and demographic changes, the management of perishable food itself contains various challenges. Despite the considerable potential of new hard and soft technologies such as Artificial Intelligence (AI) and new business models in making food supply chain circular, the adoption of these related principles is in first steps. So, transformative elements during this path should be investigated to make it possible to determine a roadmap and set strategies to do performance enhancement based on special circumstances of developing countries. For this purpose, the principles to implement CE concept considering ReSOLVE framework in developing countries are determined by literature review and finalized by asking experts opinions. After that, Pythagorean Fuzzy Decision-Making Trial and Evaluation Laboratory (PF-DEMATEL) method is applied to do ranking of these principles while considering uncertainties. It has been determined that “Regeneration” is a basilar practice since without healthy ecosystems, endeavours to optimize processes or create loops are less effective and unsustainable in the long period. “Looping” gets the second rank since it builds its fundamentals on regenerative systems to ensure that resources within ecosystems are cycled and reused, reducing waste. “Optimization” of processes and value chains gets the third rank and seeks to enhance efficiency, ensuring that resources are used as effectively as possible. “Sharing” which is about technologies related to promoting equitable access to tools and knowledge, supports regeneration, optimization, and looping by enabling more participants to implement sustainable practices. That is why it gets the fourth rank in this study. At last, “Virtualization” and “Exchange” offer tools to enhance decision-making, collaboration, and efficiency and receive the fifth and sixth ranks. However, these practices rely on a stable foundation of well-managed resources and infrastructure to maximize their potential.

Abstract Performance appraisal of sales teams plays a critical role in organizational effectiveness; however, many existing appraisal systems suffer from subjectivity, inappropriate weighting of indicators, and a lack of role-specific competency prioritization. In particular, limited empirical research has applied structured multi-criteria decision-making approaches to prioritize sales competencies across different organizational levels. To address this gap, this study develops a competency-based performance appraisal framework and empirically prioritizes sales competencies for managers and sales experts in commercial firms located in the Isfahan Science and Technology Town using the Best–Worst Method (BWM). Based on an extensive literature review and expert consultations, performance indicators were identified across four competency dimensions: technical, behavioral, core, and managerial. Expert judgments were collected from twelve experienced sales professionals through pairwise comparison questionnaires, and the BWM was employed to derive indicator weights, while the geometric mean was used to aggregate expert opinions and ensure consistency. The results reveal clear role-specific differences in competency priorities, with managerial competencies emerging as the most critical dimension for supervisors, whereas technical competencies were assigned the highest importance for sales experts, highlighting the need for differentiated performance expectations across hierarchical roles. This study contributes to the human resource management literature by providing a quantitative, role-specific, and replicable framework for competency-based sales performance appraisal and offers practical guidance for designing fair appraisal systems, aligning training and development programs with weighted competencies, and supporting data-driven human resource decisions to enhance employee performance and organizational effectiveness.

Abstract Blockchain technology offers significant potential to enhance transparency, traceability, and trust in supply chains, yet its adoption in agri-food systems remains uneven. Most studies focus on distribution and retail stages, while limited attention has been given to upstream phases—from dairy farms to processing facilities—where food safety risks, coordination failures, and information asymmetries frequently originate. This gap is particularly critical in developing economies, where regulatory instability, infrastructure limitations, and investment constraints increase uncertainty in technology adoption. Without a structured understanding of these uncertainties, blockchain initiatives risk misaligned policies and fragmented implementation. This study examines the future implementation of blockchain technology in the Iranian dairy supply chain, focusing on the production-to-processing interface. To address systemic interdependencies, the research integrates cross-impact structural analysis with scenario planning. Thirty-seven drivers were identified through literature review and expert consultation. MICMAC analysis revealed seven critical factors influencing adoption: supply chain flexibility, trust among members, governmental policies and regulations, readiness of business partners, social influence on technology acceptance, investment, and supply chain collaboration. Scenario Wizard was then used to construct internally consistent future configurations. Seven coherent scenarios were developed and grouped into desirable, intermediate, and adverse pathways. Findings show that low technological readiness and weak investment commitment act as persistent structural barriers, even when social acceptance and operational flexibility are favorable. In contrast, regulatory stability, coordinated collaboration, and strategic investment alignment significantly increase the likelihood of successful blockchain integration. This study contributes by addressing an underexplored upstream segment in a developing-country context, applying an uncertainty-based methodological framework, and demonstrating that adoption depends more on institutional alignment and organizational readiness than on technological capability alone.

Abstract In this paper, a bi-level optimization model is proposed for managing the supply chain of deteriorating products utilizing cold plasma technology. The model aims to simultaneously optimize the profitability of the manufacturer and retailer, reduce product waste, and lower carbon emissions. Cold plasma plays a pivotal role in extending product shelf life and reducing deterioration rates, which subsequently contributes to waste reduction and increased profitability. Moreover, this technology aids in minimizing greenhouse gas emissions throughout the supply chain and is considered a sustainable environmental solution. The model's results demonstrate that employing cold plasma leads to a significant reduction in waste and enhances both the manufacturer’s and retailer’s profits. The analysis further reveals that supply chain management strategies must adapt in response to varying deterioration rates. Based on these insights, companies should progressively shift towards sustainability and waste reduction, benefiting not only the environment but also their profitability. Implementing practical solutions and adopting efficient strategies can yield positive impacts on the overall profitability and efficiency of the supply chain. This paper investigates the economic and environmental aspects of employing cold plasma technology in the supply chain of deteriorating products and provides actionable recommendations for its practical implementation.