Industrial management
Mohsen Keramatpanah; Mohammad Taghi Taghavifard; Maghsoud Amiri; Mehdi Mehdi Shamizanjani
Abstract
With the expansion of digital technologies and fundamental changes in the financial services ecosystem, the banking industry is facing new challenges on the path toward sustainable development. In this regard, the present study aims to propose a model for achieving sustainability in digital banking within ...
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With the expansion of digital technologies and fundamental changes in the financial services ecosystem, the banking industry is facing new challenges on the path toward sustainable development. In this regard, the present study aims to propose a model for achieving sustainability in digital banking within Iran’s private banking sector. To this end, key variables were initially identified through a review of the relevant literature and subsequently validated using the fuzzy Delphi method with input from subject matter experts. To analyze the relationships among the variables and determine their systemic structure, Interpretive Structural Modeling (ISM) was employed. Subsequently, a comprehensive digital banking sustainability model was developed and simulated using a system dynamics approach and related software tools. The results of the model analysis indicate that the development of technological infrastructure, enhancement of information security, improvement of customer experience, effective collaboration with regulatory bodies, and standardization of digital processes are key drivers in realizing sustainability in digital banking. Scenario analysis further reveals that simultaneous improvement of these components, by reinforcing positive feedback loops, can lead to sustainable growth and lasting competitive advantage for private banks. In this context, attention to sustainability requirements in digital banking and the development of related models can contribute to reducing operational costs in the banking network, optimizing energy consumption, increasing financial inclusion, and delivering more efficient services, thereby facilitating sustainable development. The primary contribution of this study is the development of an analytical and practical framework based on system dynamics modeling, which can support private banks in formulating strategies for sustainable digital transformation and serve as a roadmap for improving their economic, social, and environmental performance. The findings of this research can assist policymakers, banking executives, and researchers in the digital banking domain to better understand the factors influencing sustainability and to design effective interventions.IntroductionAs the banking industry experiences rapid digitalization driven by emerging technologies and evolving customer expectations, the necessity of aligning digital transformation with sustainability imperatives has become increasingly evident. This shift transcends traditional financial performance and calls for banking institutions to engage with social and environmental responsibilities while sustaining innovation. Particularly in developing economies such as Iran, the dual challenge of digital modernization and sustainable development presents a unique strategic frontier. In response to these dynamics, the present study proposes a comprehensive and dynamic model of sustainable digital banking, focusing on the private banking sector in Iran.Research BackgroundWhile digitalization and sustainability have been widely studied, there exists a significant gap in integrated models that account for the systemic interactions between the two domains. The prevailing literature tends to analyze digital banking from a technological perspective, often overlooking its environmental and social consequences (Del Carmen, 2022; Migliorelli & Dessertine, 2023). Similarly, sustainability-focused frameworks rarely include the disruptive potential of digital technologies such as blockchain, artificial intelligence (AI), and mobile banking. Some studies have suggested the relevance of digital sustainability in areas like waste reduction, financial inclusion, and eco-efficiency (Castro et al., 2021; Di Vaio et al., 2021), yet empirical applications remain sparse. By building on these foundations, this research aims to bridge conceptual and practical gaps by designing a policy-oriented, simulation-based model grounded in a system thinking approach.Materials and MethodsThis study adopted a hybrid methodology by integrating three complementary techniques—Fuzzy Delphi, Interpretive Structural Modeling (ISM), and System Dynamics (SD). Initially, a structured literature review spanning 2016 to 2023 was conducted using scholarly databases such as Scopus and Google Scholar. This led to the identification of 26 preliminary variables, which were refined and validated through expert consensus using the Fuzzy Delphi method. Experts were selected based on their experience in digital transformation initiatives and their roles in IT, innovation, or strategic planning within private banks. The Delphi rounds applied fuzzy logic to quantify agreement levels, ensuring rigor in variable selection. To structure the relationships among the validated variables, ISM was employed. This method facilitated the construction of a hierarchical framework to determine which variables serve as inputs, intermediaries, and outputs in the sustainability process. The final phase involved constructing a system dynamics model with feedback loops and flow diagrams to simulate the behavior of key sustainability indicators over time and under different scenarios. The sustainability model incorporated variables reflecting organizational, technological, social, and environmental dimensions. These include elements such as process improvement, trust, profitability, service quality, digital culture, smart leadership, electronic KYC, stakeholder satisfaction, employee welfare, and business model adaptability. By embedding these interconnected elements into the system structure, the model is designed to capture the complexity of digital sustainability transitions in a banking context.Data Analysis and FindingsThe system dynamics model as shown in Figure (1) was simulated across multiple scenarios to understand how different policy strategies would influence long-term outcomes. The simulation process ensured that model behavior aligned with historical data and logical expectations. Scenario analysis provided valuable insights into how banks can prioritize investments and strategic decisions to balance economic growth with sustainability. For instance, increasing investment in digital infrastructure and employee training led to noticeable gains in trust, customer acquisition, and organizational resilience. Similarly, enhancing authentication systems and E-KYC protocols improved operational efficiency while supporting environmental and social performance through reduced paperwork and increased accessibility. Findings confirmed that sustainability in digital banking is best achieved through a synergistic approach that combines internal cultural transformation with technological innovation and regulatory collaboration. Variables such as digital culture, smart leadership, and business model flexibility played a central role in facilitating systemic resilience. The results emphasize that merely focusing on digital upgrades is insufficient without aligning human capital and governance frameworks with sustainability objectives. Scenario comparisons further revealed that a balanced investment strategy targeting both operational excellence and environmental awareness yields the most robust outcomes.Figure 1:SD model ConclusionThe results of this research highlight the imperative for private banks in Iran and similar emerging markets to adopt integrated strategies that harmonize digital transformation with sustainability goals. This study makes a significant contribution by constructing and validating a system dynamics model that incorporates 26 interdependent variables derived from theory and practice, offering a holistic view of the sustainability landscape in digital banking. The model is unique in that it not only captures the technological enablers of sustainable banking but also embeds social and environmental dimensions, reflecting the true complexity of this transformation. The integration of Fuzzy Delphi and ISM methods with SD modeling allows for both structural clarity and dynamic simulation, enabling banks to test and adjust strategies before implementation. By embedding feedback loops and behavioral equations, the model delivers actionable insights into how various factors—such as trust, service quality, organizational agility, and stakeholder alignment—can collectively drive sustainability in the digital era. This comprehensive approach moves beyond linear planning, providing a real-time decision-making tool for managers, regulators, and researchers alike.Further Research IdeasFuture research can extend the current model by integrating real-time behavioral data through machine learning algorithms or agent-based modeling, offering more granular and predictive insights. Comparative studies across multiple banking systems or geographic regions would also enhance generalizability. In addition, introducing ESG indicators and green finance parameters could further enrich the environmental scope of the model. Finally, longitudinal studies using historical banking data can help validate the dynamic behavior of the system across different economic cycles.Managerial SuggestionsFrom a managerial perspective, several strategic recommendations emerge. First, banks should prioritize long-term investment in digital literacy and workforce development to foster a resilient culture aligned with sustainability values. Second, integrating advanced E-KYC and biometric verification tools can enhance customer trust and operational transparency. Third, collaborative governance involving fintechs, third parties, and regulatory bodies is essential for ecosystem resilience. Fourth, it is crucial to continuously monitor and update business models to reflect technological, societal, and environmental shifts. Finally, the adoption of sustainability-oriented performance metrics should be institutionalized to ensure that growth and digitalization are guided by ethical and ecological responsibility
uncertainty
Hossein Firouzi; Javad Rezaeian; Mohammad Mehdi Movahedi; Alireza Rashidi Komijan
Abstract
This paper presents a multi-objective mathematical model for the reverse supply chain of hospital waste management in Iran during the COVID-19 pandemic, incorporating dimensions of sustainability. The objectives of the model are as follows: 1) Minimizing the costs associated with building facilities ...
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This paper presents a multi-objective mathematical model for the reverse supply chain of hospital waste management in Iran during the COVID-19 pandemic, incorporating dimensions of sustainability. The objectives of the model are as follows: 1) Minimizing the costs associated with building facilities and waste treatment centers, vehicle fuel costs, and environmental costs due to pollutant emissions; 2) Maximizing the energy generated from the waste combustion process; 3) Minimizing the risk of virus transmission resulting from inadequate waste management; and 4) Maximizing the number of job opportunities in the established centers. It is important to note that existing uncertainties are addressed through the application of fuzzy set theory. Given the multi-objective nature of the model, two multi-objective algorithms, namely the Pareto archive-based Krill Herd Algorithm and Non-dominated Sorting Genetic Algorithm II (NSGA-II), are employed to solve the defined problem. The results indicate that the proposed Krill Herd Algorithm converges to a solution with higher quality and dispersion compared to NSGA-II. Additionally, through a comparison of the spacing index and running time of the two algorithms, it is observed that NSGA-II explores the solution space with higher uniformity and solves the model in less time.IntroductionHospital waste encompasses a broad spectrum of both hazardous and non-hazardous materials. The management of hospital waste involves the development of a suitable supply chain network for handling waste generated in the healthcare sector. Improper disposal or mishandling of contaminated waste not only contributes to environmental pollution but also poses a risk of transferring viral pathogens to healthcare and recycling personnel. Research has shown that inadequate disposal of medical waste can lead to the transmission of up to 30% of hepatitis B, 1-3% of hepatitis C, and 0.3% of HIV infections from patients to healthcare workers. This paper aims to design a multi-objective mathematical model for the reverse supply chain of hospital waste management in Iran during the COVID-19 pandemic while considering the dimensions of sustainability.Literatur ReviewIn recent years, various studies have delved into the complexities of medical and hospital waste management, proposing mathematical models to address this intricate issue. The current study is built upon the work of Valizadeh et al. (2021). In their paper, a hybrid mathematical modeling approach was introduced, featuring a Bi-level programming model specifically tailored for infectious waste management during the COVID-19 pandemic. The outcomes revealed that, at the higher level of the model, governmental decisions aiming to minimize total costs associated with infectious waste management were crucial. This involved the conversion of collected infectious waste into energy, with the generated revenue being reinvested back into the system. The findings indicated that, through energy production from waste during the COVID-19 pandemic, approximately 34% of the total costs related to waste collection and transportation could be offset. The uniqueness of this study lies in its consideration of three sustainability dimensions: risk, vehicle routing, energy production, employment, and emission of polluting gases. Consequently, the novelty of this research, when compared to previous studies and the article by Valizadeh et al. (2021), is evident in several aspects. It introduces an integrated multi-objective positioning-routing model for the supply chain of waste management under pandemic conditions, taking into account sustainability dimensions, notably the economic aspect, and employs meta-heuristic algorithms for model resolution.MethdologyTo ensure the proper management of hospital waste, the waste is categorized into two groups: infectious and non-infectious waste. It is assumed that waste in hospitals and health centers is segregated and placed in infectious and non-infectious waste bins. The collected waste undergoes further processing: infectious waste is transported to incineration centers, where it is burned and converted into electrical energy, while non-infectious waste is sent to waste recycling centers, where it is reprocessed and returned to the production cycle in the industry. A multi-objective mathematical model is presented to integrate location-routing decisions in the supply chain of hospital waste management, with the following modeling assumptions:Waste segregation at the source helps prevent all waste from becoming viral, reducing the spread of viruses through waste.The risk of spreading viruses is assumed to be relatively equal for each type of waste.Two types of vehicles are considered for transporting waste: the first type carries non-infectious waste, while the second type carries infectious waste.The number of cars, waste collectors, and the capacity of waste incinerators are considered constant in this study.The mathematical model is multi-objective, with the objectives being to optimize the three dimensions of sustainability (economic, social, and environmental).The economic goal is to minimize system costs, including the cost of site location, recycling, collection, segregation of non-infectious waste, and incineration.The environmental goal is to minimize the emission of pollutants in the transportation and processing system in various facilities, as well as to maximize the production of electrical energy.The social goal is to minimize the risk of virus transmission and maximize the employment rate.Results and DiscussionThis research presents a multi-objective mathematical model for the reverse supply chain of hospital waste management during the COVID-19 pandemic in Iran and solves it. The pandemic period is considered a time of maximum utilization of health centers and waste disposal. In this context, a three-objective mathematical model was initially introduced. To solve the model, the krill herd optimization algorithm was employed. The performance of the krill herd optimization algorithm was scientifically and practically evaluated by comparing it with the well-known NSGA-II algorithm. After designing the model, both the multi-objective krill herd algorithm based on Pareto Archive and the NSGA-II algorithm were utilized to solve the model. The results of solving the model demonstrated that the proposed krill herd algorithm, designed in combination with VNS, effectively solved the model and determined the optimal solution within a boundary. Comparing the results of this algorithm with those obtained by the renowned NSGA-II algorithm revealed that the krill herd algorithm produced solutions of much higher quality.ConclusionThe comparison of the Index of dispersion between the two algorithms indicates that the krill herd optimization algorithm explores more points in the solution space, leading to a lower probability of getting stuck in local optima compared to the NSGA-II algorithm. On the other hand, the index of uniformity for the NSGA-II algorithm is lower than that of the krill herd algorithm (lower values are better), suggesting that the multi-objective genetic algorithm explores the solution space more uniformly. Considering the execution time of the two algorithms, it was observed that the NSGA-II algorithm solved the model in less time. Additionally, the increasing trend of execution time in both algorithms confirms the NP-HARD nature of the hospital waste management problem. According to the output of the MATLAB software, considering the presented model, the results affirm the capability to optimally select hospital waste recycling centers.
supply chain management
Mehrdad kiani; davood andalib ardakani; Habib Zare Ahmadabadi; Seid Heydar Mirfakhraddini
Abstract
Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society ...
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Circular economy and Industry 4.0 are concepts that have garnered significant attention from businesses and universities in recent years. They are currently being promoted by many governments worldwide. The synergy between these two concepts offers the potential to move towards a more sustainable society and address the environmental and economic challenges related to managing organizational operations. This research aims to analyze the factors enabling the implementation of circular economy and Industry 4.0 in the supply chain of Yazd glass factories. In the initial phase of the research, a review of various articles was conducted using the meta-synthesis method to identify and categorize relevant enablers. This process resulted in the identification of 15 enablers categorized into four dimensions: economic, human resources, organizational management, and infrastructure. In the subsequent step, the Fuzzy DEMATEL technique was employed to examine the cause-and-effect relationships. The findings indicate that, within the economic dimension, the most influential enablers are "budget allocation for the implementation of circular economy and Industry 4.0" and "stimulation of demand for circular products." In the human resources dimension, "training and development of employees" and "organizational culture" play crucial roles. In the organizational-management dimension, "support and commitment of senior management" and "cooperation and networking with supply chain partners (industrial coexistence)" are highly significant. Lastly, within the infrastructure dimension, "development of information technology standards and infrastructures" and "security and protection of intellectual property rights" are considered the most effective enablers for the implementation of circular economy and Industry 4.0 in the Yazd glass factories. The results indicate that the Ardakan glass factories of Yazd should prioritize attention to economic and infrastructural enablers when implementing circular economy and Industry 4.0.
Introduction
The concept of the circular economy can be regarded as a solution to reduce production costs within a sustainable supply chain. In this context, the integration of cyber-physical systems, big data, data mining, data analytics, the Internet of Things, and novel business models can offer significant opportunities for the creation of sustainable industrial value, value capture, and the promotion of the circular economy (Antikainen et al., 2018). Industry 4.0, often referred to as the future of supply chains, can have numerous implications for sustainability, including the optimal utilization of resources and technology (Quezada et al., 2017). Based on the sustainability axis, the concept of Industry 4.0 aids industrial managers in encompassing not only environmental protection and control initiatives but also aspects of process safety, such as resource efficiency, human resource and societal well-being, and the development of smarter and more flexible supply chain processes (Luthra & Mangla, 2018). Numerous studies have explored the factors that impact the implementation of circular economy and Industry 4.0, and these factors have been broadly classified into categories such as barriers, challenges, drivers, and enablers (Fedotkina et al., 2019). Identifying the enablers that are effective in implementation is a crucial step in enhancing the performance of a circular and intelligent supply chain. Until these enablers are identified, it is impossible to determine their relative importance. Following their identification, industry practitioners and policymakers can develop appropriate strategies for their implementation. As such, this current research aims to identify, categorize, and analyze the effective enablers for implementing circular economy and Industry 4.0 at the Ardakan Glass Factory in Yazd, which is the largest glass factory in West Asia. To achieve this, both a qualitative method for enabler identification and the technical Dimtel method using fuzzy logic for establishing cause-and-effect relationships between enablers are employed. What sets this research apart from others is its focus on identifying the combined enablers for implementing the circular economy and Industry 4.0 at the Ardakan Glass Factory Group of Yazd, as well as the network approach that examines the relationships and interactions between these enablers. Given these key elements, this research aims to address the following questions:
-What are the effective enablers for implementing the circular economy and Industry 4.0 at the Ardakan glass factories in Yazd?
-What is the effectiveness and influence, including cause-and-effect relationships, of these enablers?
Materials and Methods
This research is categorized as applied-developmental research in terms of its purpose and is classified as a field-library study in terms of its methodology. Its objective is to formulate a novel scientific model of enablers for implementing circular economy and Industry 4.0 within organizational supply chains. Given the significant number of qualitative articles that have explored the enablers of Industry 4.0 and the circular economy across various industries and the need to establish a shared understanding of these enablers, the first stage of this research involved identifying effective enablers using the meta-synthesis qualitative method. Their validity was assessed through content validity, which involved obtaining opinions from 15 organizational experts. In the second phase of the research, the researchers evaluated the effectiveness and impact of these enablers using the Fuzzy DEMATEL method. The statistical population for the first stage of the research comprised all studies published in the Scopus database, the largest text database, related to the enablers that influence the implementation of circular economy and Industry 4.0 within organizational supply chains up until the commencement of this research. In the second stage of the research, the statistical population included all professors and managers with expertise in sustainability, familiar with circular economy, and knowledgeable about Industry 4.0 technologies at Ardakan Glass Factories in Yazd. For this phase, a purposeful sampling method was used to select ten participants.
Discussion and Results
The purpose of the current research is to analyze the enablers that are effective in implementing the circular economy and Industry 4.0 within the supply chain of Ardakan Glass Factories in Yazd. In the first stage of the research, various articles were reviewed, and the meta-combination method was employed to identify and categorize relevant enablers. This process led to the identification of 15 enablers across four dimensions: economic, human resources, organizational management, and infrastructure. In the second stage, the Fuzzy DEMATEL technique was utilized to investigate the cause-and-effect relationships between these enablers. The research results revealed that the economic and infrastructural enablers are considered influential dimensions that affect human resources and organizational management dimensions. Within the economic dimension, "budget allocation for the implementation of the circular economy and Industry 4.0" and "stimulation of demand for circular products" emerged as the most effective enablers. Additionally, in the infrastructure dimension, "development of IT standards and infrastructure" was identified as the most influential enabler for the implementation of the circular economy and Industry 4.0 within the supply chain. In the organizational management dimension, "the support and commitment of senior management" was recognized as the most influential enabler.
Conclusion
While the enablers mentioned are considered among the most effective ones in implementing circular economy and Industry 4.0 in the Ardakan Glass Factories of Yazd, it's crucial for the glass industry to prioritize the most important enablers. It's essential to pay adequate attention to all identified enablers. Using specific guidelines and a checklist of effective enablers during decision-making can facilitate the decision-making process and enhance decision-making capabilities. Therefore, based on the identified enablers and their importance in this research, it's recommended to develop and provide guidelines and checklists for executive managers. Among the significant limitations of this research is the reliance on a single scientific database, Scopus, for sourcing research. It's advisable to supplement this by utilizing other databases such as Google Scholar and Web of Science. Additionally, the classification of enablers was conducted using a qualitative approach. Researchers are encouraged to name and categorize enablers using survey and quantitative methods, such as cluster analysis, to expand their research scope. Another limitation pertains to the research's statistical population, which was restricted to Ardakan Glass Factories in Yazd due to time and cost constraints. To generalize the research results, it's advisable to investigate the same research topic in other glass factories across the country. Future researchers could employ methods like fuzzy cognitive mapping and systems dynamics to examine relationships and interactions between enablers. Moreover, the enablers identified and analyzed in this research were primarily based on international studies. To adapt these enablers to the specific conditions of Iran's industries, it's suggested that in-depth interviews be conducted with industry owners. This way, certain enablers that may be unique to Iran's circumstances or require different interpretations can be revised.
Adel Azar; Ali rajabzadeh ghatromi; Atieh akhavan
Abstract
Measuring sustainable production indicators is becoming an important environmental activity due to government directives and increasing awareness among the people to protect the environment and reduce waste. Sustainable production indicators can be used to evaluate the effect of different production ...
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Measuring sustainable production indicators is becoming an important environmental activity due to government directives and increasing awareness among the people to protect the environment and reduce waste. Sustainable production indicators can be used to evaluate the effect of different production and management activities and as a result, a reliable mechanism will be created for monitoring sustainable production performance in achieving company's sustainability. The purpose of this paper is to enhance the level of sustainability in Isfahan oil refinery through identifying sustainable production indicators and determining the relationships between them in order to develop sustainable production model and also determining the indicators effects intensity on each other. After reviewing related literature and interviewing with experts, 12 sustainable production indicators in the refinery are identified. Then, using ISM technique relationship between indicators are determined. Also we used fuzzy DEMATEL to determine the intensities of relationships. The results show that implementation of supervision and control, resources with high productivity, technology with high productivity, and optimizing the production schedule to improve productivity are the main indicators in achieving sustainable production in the refinery
