Strategies for Realizing Industry 5.0 Inclusive Sustainability Goals for Sustainable Development: A Structured Framework for Overcoming Barriers and Guiding Transformation Mohammad Ali Beheshtinia, Ali Ghorbani, Masood Fathi, Morteza Ghobakhloo, Behzad Foroughi Business Strategy and the Environment, 2026 Industry 5.0 has emerged to address the limitations of Industry 4.0 by emphasizing inclusive sustainability through environmentalism, human‐centricity, and resilience. However, its development faces barriers across technological, organizational, and social dimensions. This study proposes a structured decision‐making framework to identify critical barriers, design targeted strategies, and prioritize them for implementation. Strategies are evaluated using seven criteria: impact, cost, timeframe, feasibility, risk, complexity, and acceptance. A hybrid fuzzy multi‐criteria decision‐making method, informed by systematic literature review and expert consultation, ensures reliable and balanced prioritization. The analysis identified 54 barriers and 35 strategies, highlighting the highest importance of “public–private partnership programs in driving digital transformation,” “resilience‐focused business continuity,” and “localized and regional digital infrastructure development,” respectively. Considering all criteria, the strategies “clarity on long‐term return on investment,” “resilience‐focused business continuity programs,” and “ethical AI adoption programs for smaller enterprises” received the highest implementation priority, respectively. This study makes three key contributions to the literature on Industry 5.0. First, it provides a comprehensive and structured summary of Industry 5.0 barriers, identifying 54 barriers across seven distinct dimensions. Second, it develops a systematic QFD‐based framework that directly links these barriers to strategies for overcoming them and facilitating the development of Industry 5.0. Third, it introduces a novel MCDM method called F‐WASKOR. The study provides a phased roadmap for advancing Industry 5.0 transformation and realizing inclusive sustainability goals.
Overcoming barriers to renewable energy adoption: A decision-making framework for strategy evaluation and implementation prioritization Mohammad Ali Beheshtinia, Seyedeh Nadia Yaghobian, Masood Fathi, Morteza Ghobakhloo, Behzad Foroughi Cleaner Environmental Systems, 2025 Transitioning from fossil fuels to renewable energy is essential for sustainable development. However, a wide range of economic, technical, regulatory, and social barriers hinder this transition. This study aims to identify these barriers and propose prioritized strategies to overcome them. A novel decision-making framework is developed, combining an adapted Quality Function Deployment (QFD) model with a new hybrid fuzzy Multi-Criteria Decision-Making (MCDM) method, named the Fuzzy ARASKOR (F-ARASKOR) method. Data collection involved one in-depth expert interview and four structured questionnaires, completed by a panel of domain experts. First, a comprehensive list of barriers to renewable energy development was identified from the literature. Their importance weights were assessed using the first questionnaire. Then, strategies to overcome the barriers were derived through expert interviews and analyzed via the second questionnaire using a QFD approach. Next, these strategies were evaluated against seven criteria: impact on barriers, implementation cost, duration, capability, risk, complexity, and acceptability. Criterion weights were obtained through the Analytic Hierarchy Process (AHP) using the third questionnaire, and strategy performance was assessed through the fourth. Final prioritization was conducted using the F-ARASKOR method. The results identified 75 barriers and 38 strategies. Among them, “Policy Stability and Long-Term Commitment,” “Promote Renewable Energy as a Climate Solution,” and “Develop Training and Certification Programs” emerged as top-priority strategies. This study offers practical guidance for governments and industries to formulate stable, targeted policies, make effective investments, and address the key barriers hindering renewable energy development.
Enhancing healthcare waste management: a novel hybrid multi-criteria decision-making method Mohammad Ali Beheshtinia, Mohammad Sajjad Safarzadeh, Masood Fathi, Morteza Ghobakhloo, Mostafa Al-Emran, Ming Lang Tseng Management of Environmental Quality, 2025 PurposeHealthcare wastes (HCWs) present substantial environmental and societal risks, including infection and exposure to hazardous substances. The aim of this study is to present a new multi-criteria decision-making (MCDM) method, named the ELECTOR method, for selecting the best healthcare waste disposal method (HCWDM) based on a comprehensive list of criteria. The main research question of this study is: What is the prioritization of HCWDMs considering economic, environmental, technical and social criteria?Design/methodology/approachThis research employs a novel hybrid MCDM method to evaluate and select suitable HCWDMs. Initially, a comprehensive set of criteria for assessing and prioritizing HCWDMs is established. Criteria weights are determined using the best-worst method. Subsequently, a hybrid MCDM method is introduced to rank the HCWDMs. Fuzzy numbers are applied to handle qualitative criteria uncertainties. The proposed method is applied to a real-world case study to prioritize HCWDMs.FindingsA total of 24 criteria, including two novel criteria (“System process speed” and “System setup speed”), for evaluating and prioritizing the HCWDMs were identified from the literature review and case study analysis. The study showed that the key criteria influencing HCWDM selection were “Operation cost”, “Occupational hazards of human resources”, and “The impact of released substances on health”. Based on the results, the autoclave, encapsulation and hydroclave methods are identified as the most suitable HCWDMs for the studied case, respectively.Originality/valueThis study introduces a novel hybrid MCDM method tailored for HCWDM selection, enhancing the robustness of the decision-making. The inclusion of innovative criteria and the integration of fuzzy numbers to address qualitative ambiguities strengthen the originality of the findings. Specifically, introducing “System process speed” and “System setup speed” contributes to expanding the criteria landscape in HCWDM research.
Enhancing Hospital Services: Achieving High Quality Under Resource Constraints Mohammad Ali Beheshtinia, Masood Fathi, Morteza Ghobakhloo, Muhammad Faraz Mubarak Health Services Insights, 2025 Objectives: This research aims to enhance the quality of hospital services by utilizing Quality Function Deployment (QFD) with a novel Multi-Dimensional House of Quality (MD-HOQ) approach. This method integrates Service Quality (SERVQUAL) analysis and considers resource constraints, such as financial and workforce limitations, to select and prioritize technical requirements effectively. Methods: The proposed MD-HOQ approach was applied to a private hospital in Tehran, Iran. Data were gathered from a sample of 8 experts and a sample of 386 patients, using 2 in-depth interviews and 4 questionnaires. The process included identifying hospital sections and determining their importance using the Analytic Hierarchy Process. Patients’ needs in each section were then identified and weighted through SERVQUAL analysis. Subsequently, technical requirements to meet these needs were listed and weighted using MD-HOQ. A mathematical model was employed to determine the optimal set of technical requirements under resource constraints. Results: Application of the MD-HOQ approach resulted in the identification of 50 patient needs across 5 hospital sections. Additionally, 40 technical requirements were identified. The highest implementation priorities were assigned to “training practitioners and nurses,” “improving the staff’s sense of responsibility,” and “using experienced specialists, physicians, and surgeons.” Conclusions: The integrated QFD approach, utilizing MD-HOQ and SERVQUAL analysis, provides a comprehensive framework for hospital managers to prioritize technical requirements effectively. By considering resource constraints and the gap between patient expectations and perceptions, this method ensures that resources are allocated to the most impactful technical requirements, leading to improved patient satisfaction and better overall hospital service quality. This approach not only enhances the quality of hospital services but also ensures efficient utilization of resources, ultimately benefiting patient satisfaction.
Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method Mohammad Ali Beheshtinia, Fatemeh Bahrami, Masood Fathi, Shahla Asadi Scientific Reports, 2023 Healthcare waste disposal center location (HCWDCL) impacts the environment and the health of living beings. Different and sometimes contradictory criteria in determining the appropriate site location for disposing of healthcare waste (HCW) complicate the decision-making process. This research presents a hybrid multi-criteria decision-making (MCDM) method, named PROMSIS, to determine the appropriate HCWDCL in a real case. The PROMSIS is the combination of two well-known MCDM methods, namely TOPSIS and PROMETHEE. Moreover, fuzzy theory is used to describe the uncertainties of the problem parameters. To provide a reliable decision on selecting the best HCWDCL, a comprehensive list of criteria is identified through a literature review and experts’ opinions obtained from the case study. In total, 40 criteria are identified and classified into five major criteria, namely economic, environmental, social, technical, and geological. The weight of the considered criteria is determined by the Analytical Hierarchy Process (AHP) method. Then, the score of the alternative HCWDCLs in each considered criterion is obtained. Finally, the candidate locations for disposing of HCWs are ranked by the proposed fuzzy PROMSIS method. The results show that the most important criteria in ranking the alternatives in the studied case are economic, environmental, and social, respectively. Moreover, the sub-criteria of operating cost, transportation cost, and pollution are identified as the most important sub-criteria, respectively.
Identifying and prioritizing marketing strategies for the building energy management systems using a hybrid fuzzy MCDM technique Mohammad Ali Beheshtinia, Shakiba Sayadinia, Masood Fathi Energy Science and Engineering, 2023 Preventing energy waste in residential and office buildings has emerged as a critical issue in both developed and developing countries over recent decades. The growing demand for oil and energy reserves has amplified the urgency of this concern. The deployment of building energy management systems (BEMSs) can lead to timely responses to changes in environmental conditions, the prevention of energy wastage, a reduction in CO2 emissions, and an increase in the longevity of building equipment. Despite the undeniable benefits of BEMSs, their market size remains small, creating challenges for providers in reaching potential customers. This research seeks to identify and prioritize the marketing strategies for BEMSs. A case study was conducted, employing the “Strengths, Weaknesses, Opportunities, and Threats” analysis as a tool for identifying marketing strategies related to BEMSs. This method resulted in the identification of 18 distinct marketing strategies. These strategies were subsequently prioritized using a novel fuzzy multicriteria decision‐making technique, VIkor‐topSIS, considering six specific criteria. The findings of the study suggested a hierarchical influence of six criteria on the BEMS market, arranged in the following order of significance: effectiveness, cost, attainability, complexity, timing, and popularity. Furthermore, the top three marketing strategies for BEMSs were found to be internet advertising strategies, discounts to consumers, and online sales. The analysis of the results has also offered valuable insights into the strengths and weaknesses of the studied BEMS provider, as well as the opportunities and threats present within the BEMS market.
Energy-efficient and sustainable supply chain in the manufacturing industry Mohammad Ali Beheshtinia, Masood Fathi Energy Science and Engineering, 2023 Abstract This study aims at reducing energy consumption in supply chain networks by providing optimal integrated production and transportation scheduling. The considered supply chain consists of one main manufacturing center, multiple production units (i.e., suppliers), and multiple heterogeneous vehicles as the transportation fleet. To schedule this complex supply chain network in an energy‐efficient way, several decisions should be made concerning the assignment of orders to suppliers and determining their production sequence, splitting orders, assigning orders to vehicles, and assigning delivery priority to orders. To cope with the problem, a mixed‐integer linear programming model is presented. Due to the complexity of the problem, a novel development of the genetic algorithm named the Multiple Reference Group Genetic Algorithm (MRGGA) is also proposed. Four objectives are considered to be optimized to meet both suitability and energy‐efficiency aspects in the supply chain network. These optimization objectives are to minimize the total orders' delivery times to the manufacturing center, fuel consumption by the vehicles, energy consumption at supplies, and maximize orders' quality. To analyze the performance of the proposed algorithm, a real case and a set of generated instances are solved. The results obtained by the proposed algorithm are compared with an existing genetic algorithm in the literature. Moreover, the results are also compared with the optimal solutions obtained from the mathematical model for small‐size problems. The results of the comparisons show the efficiency of the proposed MRGGA in finding energy‐efficient solutions for the considered supply chain network.
Optimizing disaster relief goods distribution and transportation: a mathematical model and metaheuristic algorithms Mohammad Ali Beheshtinia, Ali Jozi, Masood Fathi Applied Mathematics in Science and Engineering, 2023 The effective distribution of relief goods is critical in mitigating the impact of natural disasters and preserving human life. This study addresses a relief goods distribution problem, assuming the existence of multiple relief orders that must be delivered to various disaster-stricken regions from a network of warehouses using a fleet of diverse vehicles. The objective is to identify the most suitable warehouse for each relief order, allocate relief orders to vehicles, batch the orders in the designated vehicles, and devise routing plans to minimize the total delivery time. A mixed-integer linear programming model is formulated to tackle this problem. Owing to the problem’s NP-hard nature, a metaheuristic algorithm, known as the Multiple League Championship Algorithm, is developed. Furthermore, two innovative variants of the MLCA , namely the League Base Multiple League Championship Algorithm (L- MLCA) and the Playoff Multiple League Championship Algorithm (P-MLCA), are introduced.Experimental results indicate that the P-MLCA outperforms the other two algorithms. The solutions derived from the P-MLCA are compared with the optimal solutions obtained by a commercial solver for small-scale problems. This comparative analysis demonstrates the promising performance of the P-MLCA in finding the optimal distribution of relief goods.
A comprehensive decision-making framework for the electric vehicle charging station location problem H Khatibi, MA Beheshtinia, M Fathi Journal of Industrial and Production Engineering, 1-22 , 2026 2026
Strategies for Realizing Industry 5.0 Inclusive Sustainability Goals for Sustainable Development: A Structured Framework for Overcoming Barriers and Guiding Transformation MA Beheshtinia, A Ghorbani, M Fathi, M Ghobakhloo, B Foroughi Business Strategy and the Environment , 2026 2026
A hybrid model for prioritizing the construction of renewable power plants with sustainable development considerations F Sedady, MA Beheshtinia Managerial Modelling in Sustainable Development 1 (2), 1-26 , 2025 2025
A Fuzzy AHP–PROMSIS Hybrid Model for Nanodrug Supplier Selection: Integrating Value Chain Dynamics and Risk-Based Criteria MA Beheshtinia Strategic Value Chain Management , 2025 2025
Overcoming barriers to renewable energy adoption: A decision-making framework for strategy evaluation and implementation prioritization MA Beheshtinia, SN Yaghobian, M Fathi, M Ghobakhloo, B Foroughi Cleaner Environmental Systems, 100314 , 2025 2025 Citations: 6
Identifying and Prioritizing Required Actions for Greenhouse Smartization Using Multi-Criteria Decision-Making Methods MA Beheshtinia, Z Lashini Transactions on Soft Computing 1 (3), 180-191 , 2025 2025
Enhancing healthcare waste management: a novel hybrid multi-criteria decision-making method MA Beheshtinia, MS Safarzadeh, M Fathi, M Ghobakhloo, M Al-Emran, ... Management of Environmental Quality: An International Journal 36 (5), 1095-1124 , 2025 2025 Citations: 7
Optimizing integrated distributed flexible job-shop scheduling and customer order delivery M Fathi, MA Beheshtinia, M Ghobakhloo, M Al-Emran Journal of Industrial and Production Engineering 42 (4), 440-460 , 2025 2025 Citations: 6
Enhancing hospital services: Achieving high quality under resource constraints MA Beheshtinia, M Fathi, M Ghobakhloo, MF Mubarak Health Services Insights 18, 11786329251331311 , 2025 2025 Citations: 7
Optimizing disaster relief goods distribution and transportation: a mathematical model and metaheuristic algorithms MA Beheshtinia, A Jozi, M Fathi Applied Mathematics in Science and Engineering 31 (1), 2252980 , 2023 2023 Citations: 11
Prioritizing healthcare waste disposal methods considering environmental health using an enhanced multi-criteria decision-making method MA Beheshtinia, S Jafari Kahoo, M Fathi Environmental Pollutants and Bioavailability 35 (1), 2218568 , 2023 2023 Citations: 29
Identifying and prioritizing marketing strategies for the building energy management systems using a hybrid fuzzy MCDM technique MA Beheshtinia, S Sayadinia, M Fathi Energy science & engineering 11 (11), 4324-4348 , 2023 2023 Citations: 16
Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method MA Beheshtinia, F Bahrami, M Fathi, S Asadi Scientific Reports 13 (1), 15130 , 2023 2023 Citations: 25
A fuzzy three-dimensional house of quality to integrate and coordinate departments’ activities in organizations MA Beheshtinia, F Sedady, M Fathi, M Ghobakhloo, M Iranmanesh IEEE Access 11, 90538-90553 , 2023 2023 Citations: 12
Analyzing of Three Different Scenarios to Optimize Energy Consumption and Scheduling in Supply Chain MA Beheshtinia, SAM Khatibi Energy Engineering and Management 7 (1), 36-47 , 2023 2023 Citations: 2
Prioritize the renewable-power plants using a combination of Modified Digital Logic and fuzzy VIKOR methods MA Beheshtinia, F Sedady Energy Engineering and Management 7 (2), 52-61 , 2023 2023 Citations: 2
Energy‐efficient and sustainable supply chain in the manufacturing industry MA Beheshtinia, M Fathi Energy Science & Engineering 11 (1), 357-382 , 2023 2023 Citations: 15
Enhancing the quality of municipality services using four-dimensional house of quality P Borna, MA Beheshtinia Quality & Quantity 56 (5), 3849-3870 , 2022 2022 Citations: 3
Evaluating and ranking digital stores’ suppliers using TOPKOR method MA Beheshtinia, P Falsafi, A Qorbani, H Jalinouszade International Journal of Engineering 35 (11), 2155-2163 , 2022 2022 Citations: 7
A new genetic algorithm to solve integrated operating room scheduling problem with multiple objective functions P Shahhosseini, M Beheshtinia Journal of Industrial and Systems Engineering 13 (4), 262-287 , 2021 2021 Citations: 7
MOST CITED SCHOLAR PUBLICATIONS
A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain SH Zegordi, INK Abadi, MA Beheshti-Nia Computers & Industrial Engineering 58 (3), 373-381 , 2010 2010 Citations: 167
A hybrid MCDM approach for performance evaluation in the banking industry MA Beheshtinia, S Omidi Kybernetes 46 (8), 1386-1407 , 2017 2017 Citations: 125
A fuzzy QFD approach using SERVQUAL and Kano models under budget constraint for hotel services MA Beheshtinia, M Farzaneh Azad Total Quality Management & Business Excellence 30 (7-8), 808-830 , 2019 2019 Citations: 99
Hybrid flow shop scheduling with parallel batching MR Amin-Naseri, MA Beheshti-Nia International Journal of Production Economics 117 (1), 185-196 , 2009 2009 Citations: 83
Evaluating and prioritizing hospital service quality A Torkzad, MA Beheshtinia International journal of health care quality assurance 32 (2), 332-346 , 2019 2019 Citations: 79
A multi-population genetic algorithm for transportation scheduling SH Zegordi, MA Beheshti-Nia Transportation Research Part E: Logistics and Transportation Review 45 (6 … , 2009 2009 Citations: 72
A developed genetic algorithm for solving the multi-objective supply chain scheduling problem A Borumand, MA Beheshtinia Kybernetes 47 (7), 1401-1419 , 2018 2018 Citations: 54
Integrating production and transportation scheduling in a two-stage supply chain considering order assignment SH Zegordi, MA Beheshti-Nia The International Journal of Advanced Manufacturing Technology 44 (9-10 … , 2009 2009 Citations: 48
A novel MCDM model for prioritizing the renewable power plants’ construction F Sedady, MA Beheshtinia Management of Environmental Quality: An International Journal 30 (2), 383-399 , 2019 2019 Citations: 47
Proposing a new hybrid multi-criteria decision-making approach for road maintenance prioritization S Sayadinia, MA Beheshtinia International Journal of Quality & Reliability Management 38 (8), 1661-1679 , 2021 2021 Citations: 44
Supply chain scheduling and routing in multi-site manufacturing system (case study: a drug manufacturing company) MA Beheshtinia, A Ghasemi, M Farokhnia Journal of Modelling in Management 13 (1), 27-49 , 2018 2018 Citations: 41
A holistic fuzzy approach to create competitive advantage via quality management in services industry (case study: life-insurance services) J Vaziri, MA Beheshtinia Management decision 54 (8), 2035-2062 , 2016 2016 Citations: 41
A multi-objective and integrated model for supply chain scheduling optimization in a multi-site manufacturing system MA Beheshtinia, A Ghasemi Engineering Optimization 50 (9), 1415-1433 , 2018 2018 Citations: 38
Prioritizing healthcare waste disposal methods considering environmental health using an enhanced multi-criteria decision-making method MA Beheshtinia, S Jafari Kahoo, M Fathi Environmental Pollutants and Bioavailability 35 (1), 2218568 , 2023 2023 Citations: 29
Evaluating and prioritizing the healthcare waste disposal center locations using a hybrid multi-criteria decision-making method MA Beheshtinia, F Bahrami, M Fathi, S Asadi Scientific Reports 13 (1), 15130 , 2023 2023 Citations: 25
Supply chain optimization considering sustainability aspects MA Beheshtinia, P Feizollahy, M Fathi Sustainability 13 (21), 11873 , 2021 2021 Citations: 25
An integrated approach for healthcare services risk assessment and quality enhancement M Pourmadadkar, MA Beheshtinia, K Ghods International Journal of Quality & Reliability Management 37 (9-10), 1183-1208 , 2020 2020 Citations: 25
A robust possibilistic programming model for production-routing problem in a three-echelon supply chain MA Beheshtinia, N Salmabadi, S Rahimi Journal of Modelling in Management 16 (4), 1328-1357 , 2021 2021 Citations: 21
Optimization of delay time and environmental pollution in scheduling of production and transportation system: a novel multi-society genetic algorithm approach M Moghimi, MA Beheshtinia Management Research Review 44 (10), 1427-1453 , 2021 2021 Citations: 21
A genetic algorithm developed for a supply chain scheduling problem SMR Taheri, MA Beheshtinia Interdisciplinary Journal of Management Studies 12 (2), 281-306 , 2019 2019 Citations: 17
