Online statistics:

Number of Volumes 12
Number of Issues 23
Number of Articles 213
Number of Contributors 485
Article View 201,761
PDF Download 159,204
View Per Article 947.23
PDF Download Per Article 747.44
Accepted Submissions 213
Acceptance Rate (Percent) 25
Average Accept Date (Days) 162
Number of Indexing Databases 7
Number of Reviewers 334

 

 

Journal of Industrial Engineering and Management Studies (JIEMS) is an open-access and double-blind peer-review journal devoted to publishing original research papers in the field of industrial engineering and management.

Subject areas include, but are not limited to:

  • Supply Chain Management
  • Production Management
  • Quality and Reliability Management
  • Project Scheduling and Management 

For a full list of topics, please click here.


About JIEMS:

  • Scope: Industrial Engineering and Management
  • Frequently: Semi-annual 
  • Open Access: Yes
  • Indexed and Abstracted: Yes
  • Acceptance Rate: 25%
  • Average Accept Date: 174 days
  • Average Time to First Review: 60 days
  • DOI Prefix: 10.22116/JIEMS
  • Reviewing Process Fee: No 
  • Publication Fee: Yes
  • Language: English
  • Review Policy: Double-Blind Peer Review
  • Contact Emails: jiems@icms.ac.ir & info@icms.ac.ir  

Note:

The papers with a similarity index of over 10% will be rejected. The author should use plagiarism checkers to make sure the submitted manuscript is original and satisfies the defined limit. 


CONFLICT OF INTEREST AND COPYRIGHT FORM 

PUBLICATION ETHICS AND PUBLICATION MALPRACTICE STATEMENT

Modeling the Impact of Social Media Marketing Activities on Customer Equity Using a System Dynamics Approach

Pages 1-12

https://doi.org/10.22116/jiems.2025.474741.1573

Parimah Salarmanesh, Shahram Saeidi

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.

Evaluating and Ranking of Software Companies in Adapting to IT Outsourcing Risks

Pages 13-19

https://doi.org/10.22116/jiems.2025.485146.1579

Mehdi Ajalli, Abbas Nasiri, Jafar Zarin

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.

Roadmap for Industry Transformation in the Digital Economy (Case Study of Two Industries: Insurance and Transportation)

Pages 20-29

https://doi.org/10.22116/jiems.2025.529791.1606

ali Eslamibidkoli, Hamidreza Ezzati

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.

Identifying business development challenges in knowledge-based companies (FinTech field)

Pages 30-41

https://doi.org/10.22116/jiems.2025.518843.1600

mina isazadeh, Manouchehr Ansari

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.

Optimizing Facility Breakdown in Multi-Period Routing and Location for Heterogeneous Vehicles in a Circular Supply Chain

Pages 42-58

https://doi.org/10.22116/jiems.2025.535630.1609

Ghassem Ghorbannia Ganji, Esmaeel Afzoon, Farshad Kaveh, Hamidreza Keihani, Raheleh Alamiparvin

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.

Effect of different types of failure and repair policies in determining warranty policy parameters

Pages 59-67

https://doi.org/10.22116/jiems.2025.536603.1610

Ehsan MoghimiHadji

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.

A Fuzzy – Chance Multi Objective Programming for Supply Network Multi Modal Transportation Routes

Pages 68-85

https://doi.org/10.22116/jiems.2026.555782.1621

Reza Ehtesham Rasi, Davood Ezzattalab, Sadegh Abedi

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.

A two-objective Mathematical Model for Job Scheduling on Parallel Machines and Solving by Particle Swarm Optimization

Articles in Press, Accepted Manuscript, Available Online from 01 July 2025

https://doi.org/10.22116/jiems.2025.498885.1587

Shahram Saeidi

Abstract Time is one of the most valuable assets in industry, and cost is another highly regarded factor. Optimal utilization of these resources can increase efficiency and profit. The parallel machine scheduling problem is a fundamental issue in industry and services. This research proposes a two-objective mathematical model for parallel machine scheduling. The first objective function is defined as the makespan, which is the completion time of the last job. The second objective function is defined as the maximum cost incurred by any single machine, which is a function of the sum of the processing costs of each operation and the fixed cost of purchasing and maintaining the machines. Each job consists of multiple operations, and all operations must be completed to finish the job. Additionally, it is assumed that jobs have priorities, and precedence constraints between operations must be satisfied. Due to the model's non-linearity and the problem's complexity, a metaheuristic algorithm based on the particle swarm optimization (PSO) approach is developed to solve the proposed model by aggregating the objective functions. The proposed method is simulated in MATLAB on three sample instances in small, medium, and large scales. The computational results demonstrate the robustness and efficiency of the proposed method.

Designing a Perishable Food Supply Chain Model and Analyzing the Financial Risk of Purchase and Distribution

Articles in Press, Accepted Manuscript, Available Online from 12 May 2026

https://doi.org/10.22116/jiems.2026.570876.1628

Amir Mola Yousefi, Vahid Bardaran, Kaveh Khalili-Damghani

Abstract Perishable food supply chains (PFSCs), particularly in the dairy sector, face significant challenges due to product deterioration, quality degradation, and financial risks associated with distribution delays. Despite extensive research on supply chain optimization, a critical gap remains in accurately modeling the dynamic relationship between product shelf-life and selling price—a factor that significantly impacts revenue and risk assessment in real-world operations. This study addresses this gap by developing a multi-objective optimization model for the dairy supply chain in Iran that incorporates: (1) a novel stepwise pricing mechanism based on remaining shelf-life, capturing revenue loss due to spoilage; (2) financial risk assessment of purchase and distribution operations; (3) transportation planning with vehicle routing; and (4) discount sales policies aligned with product freshness. Given the NP-Hard nature of the problem, NSGA-II and MOPSO algorithms with a modified priority-based encoding-decoding method were employed. Algorithm parameters were systematically tuned using the Taguchi method. The model was validated through a numerical example solved via the LP-metric method, followed by 15 larger test problems to evaluate algorithm performance. Comparative analysis using multiple evaluation metrics—including the number of Pareto-efficient solutions (NPF), maximum spread index (MSI), spacing metric (SM), and computational time—was conducted. The TOPSIS technique was applied to rank algorithm performance, revealing that NSGA-II (weight = 0.6945) significantly outperforms MOPSO (weight = 0.3055) across all problem sizes. The key contributions of this research include: (i) introducing a realistic stepwise pricing function linked to perishability, (ii) integrating financial risk into PFSC optimization, and (iii) providing a robust algorithmic framework for large-scale dairy supply chain problems. These findings offer practical guidance for managers seeking cost-effective, risk-aware, and quality-conscious management of perishable food supply chains.

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