Journal of Resource Management and Decision Engineering

About the Journal

The Journal of Resource Management and Decision Engineering is a pioneering open access, peer-reviewed journal committed to disseminating cutting-edge research and practical insights into the complex world of resource management and decision-making processes. Our mission is to foster a dialogue among professionals, researchers, and practitioners to enhance the understanding and practice of efficient resource allocation and decision-making strategies across various disciplines. Our open access mandate supports a broader global exchange of knowledge, making research freely available to the international community without any barriers.

This journal adheres to the ethical standards in publications and complies with the regulations of the Committee on Publication Ethics (COPE). It also follows the executive bylaw for the prevention and handling of academic misconduct.

Aims and Scopes

JRMDE aims to:

Advance the theoretical foundations and practical applications of decision engineering and resource management across various engineering disciplines, including computer, electrical, civil, mechanical, and industrial engineering.
Promote interdisciplinary research that addresses significant challenges in the allocation and management of resources across diverse sectors.
Provide a platform for innovative ideas and novel methodologies that can influence policy-making and operational practices.
Encourage the integration of technology and analytical tools in decision-making processes to enhance effectiveness and efficiency within the fields of computer, electrical, civil, mechanical, and industrial engineering.

Scope

The scope of JRMDE encompasses a wide array of topics within resource management and decision engineering, including but not limited to:

Theoretical models and practical applications of decision analysis across computer, electrical, civil, mechanical, and industrial engineering.
Resource allocation policies and strategies pertinent to various engineering disciplines.
Sustainability and environmental impact assessments in resource management, with applications in civil and environmental engineering.
Technological advancements and their impact on resource planning in computer, electrical, mechanical, and industrial engineering.
Ethical considerations and societal impacts of decision-making processes in engineering fields.

Fields and Areas Covered

JRMDE covers a broad spectrum of fields and areas, reflecting the interdisciplinary nature of resource management and decision engineering:

Business and Economics: Corporate decision-making processes, economic planning, and financial impacts of resource management strategies.
Environmental Sciences: Environmental policy, natural resource management, and strategies for sustainable development.
Engineering and Technology:
- Computer Engineering: Development of algorithms and software for decision support systems, and the role of artificial intelligence in resource management.
- Electrical Engineering: Optimization of electrical grids, smart grid technologies, and energy resource management.
- Civil Engineering: Infrastructure planning, construction resource allocation, and sustainable urban development.
- Mechanical Engineering: Efficiency improvements in mechanical systems, manufacturing resource management, and automation technologies.
- Industrial Engineering: Process optimization, supply chain management, and integration of industrial systems for resource efficiency.
Public Policy and Administration: Governance of resources, public health decision-making, and infrastructure planning.
Healthcare and Life Sciences: Resource allocation in healthcare, biomedical decision support systems, and public health logistics.
Data Science and Analytics: Big data applications in decision-making, predictive analytics for resource management, and machine learning techniques.

Current Issue

Vol. 5 No. 4 (2026): Serial Number 17

Published: 2026-07-01

Articles

Potential Improvement of Hydraulic Resistance in Coastal Soils Using Optimized Microbially Induced Calcium Carbonate Precipitation (MICP): A Case Study of Kish Island

Alireza Zeynali (Author); Somayeh Taheri; Hossein Ali Alikhani, Seyed Saeid Hosseini (Author)

1-14
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.235
Design and Optimization of a Real-Time Audio Simulation Engine on Mobile Devices

Mahdi Habibi; Amirhossein Mirahmadi, Mohammad Mahdi Jalili (Author)

1-13
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.237
Environmental Life Cycle Assessment of Gasoline Production Process in Khuzestan Using an Ecosystem Approach in Environmental Planning

Eghbal Sekhavati (Author); Mehdi Esmaeili Bidhendi; Reza Jalilzadeh-Yengejeh , Farhad Baqi-Asl (Author)
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.278
Designing a Model for Reducing Behavioral Conflicts among Employees in the Information Technology Sector

Mohammad Mahdavi Nik, Yousef Mohammadi Moghaddam, Majid Ramezan (Author)

1-16
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.244
Explanation and Prioritization of Factors Influencing the Location of Resilient Schools Against Natural Hazards with an Emphasis on Collective Intelligence (Case Study: Nowshahr City)

Mehdi Elkaei Behjati (Author); Seyed Ali Seydian; Mehdi MirzaGoltabar Roshan (Author)

1-14
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.283
Analysis of Social and Cultural Factors Affecting the Development of Tourism Culture in Iran: A Case Study of Border Regions

Alireza Pariro (Author); Khalil Mirzaei; Zahra Ghasemi (Author)

1-12
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.253
An Enhanced Hybrid Statistical–Learning Approach for Detecting Fake Feedback in Cloud Environments Using Hierarchical Clustering with Reptile Search Algorithm and Particle Swarm Optimized Extreme Learning Machine

Hussein Kadhim Almamoori (Author); Golnaz Aghaee Ghazvini; Ali Albu-Rghaif, Fariba Majidi (Author)

1-27
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.285
Detection of Attacks in Internet of Things Devices Using an Optimized Ensemble Classification Based on Deep Transfer Learning and the Harris Hawks Algorithm

Farqad Abdullah Mohammed (Author); Saba Joudaki; Mezher H Mezher, Mahdi Mosleh (Author)

1-16
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.294
Investigating the Relationship between Job Characteristics and the Growth of Professional Ethics among Employees of the East Azerbaijan Gas Company

Ali Reza Abbasian (Author); Jafar Beikzad

1-12
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.297
Identification of Key Causes of Disputes in Construction Projects and Preventive Strategies: A Systematic Review

Mohammad Taghi Nazarpour; Negin Kheradmand (Author)

1-13
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.298
Presenting a Sustainable Supply Chain Model Based on Blockchain Technology in Iran’s Oil and Gas Industry (Case Study: Fajr Jam Refinery)

Seyed Amirali Didegah (Author); Ahmad Jafarnejad Choqoshi; Mohammadreza Taghizadeh Yazdi (Author)

1-19
- PDF
DOI: https://doi.org/10.61838/kman.jrmde.234

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A Systematic Review of Bilevel Optimization Methods Using a Meta-Synthesis Approach: Algorithms, Complexity, and Applications in Resource Allocation

Nazanin Zarei iD , Ehsan Korani ^* iD , Mohammad Fallah iD , Ali Shahabi iD

This study seeks to provide a comprehensive overview of bilevel optimization methods through a systematic review and meta-synthesis of the literature, focusing on solution algorithms, computational complexity, and applications in resource allocation. Using a meta-synthesis approach and a systematic literature review, the study identifies 64 credible sources from Scopus, Web of Science, and Google Scholar and analyzes them within four main streams: (1) theory and exact and metaheuristic solution algorithms, (2) uncertainty modeling and robust optimization, (3) policy applications in energy and supply chains, and (4) multifollower structures and security games. The analytical criteria include computational complexity, the type of mathematical reformulation (KKT/MPCC), and the approach to uncertainty. Exact methods based on reformulations using the Karush–Kuhn–Tucker (KKT) optimality conditions and mathematical programs with complementarity constraints (MPCC) are highly effective for convex problems, but face computational challenges in nonconvex or large-scale problems. Continuous regularization and smoothing methods strike an appropriate balance between accuracy and scalability. Regarding uncertainty, scenario-based approaches and the conditional value-at-risk (CVaR) measure are less conservative than classical robust optimization and are more suitable for resource allocation problems involving discrete scenarios. A significant research gap was also identified in simultaneously integrating heterogeneous multifollower structures with downside risk control in science and technology policymaking. By proposing a conceptual framework and identifying research gaps, this study paves the way for developing robust bilevel optimization models with a multifollower approach. The proposed framework can serve as a roadmap for researchers working on optimization and its applications in national resource allocation.

Designing a Meta-Synthesis Model for Identifying Risks in Knowledge-Based Companies Based on Information Technology

Asdollah Honardoost iD , Amir Mohammadzadeh ^* iD , Mohsen Torabian iD

This study aimed to design an integrated meta-synthesis model for identifying the major risks confronting knowledge-based companies from an information-technology perspective. This qualitative study employed a meta-synthesis design to integrate and reinterpret findings from previous research on information technology, knowledge management, organizational risk, cybersecurity, innovation, and knowledge-based enterprises. An initial search identified 436 potentially relevant documents from major national and international academic databases. After duplicate removal, title and abstract screening, full-text assessment, and methodological appraisal based on predefined inclusion and exclusion criteria, 42 studies were retained for final analysis. Data were extracted using a researcher-designed document-review form and analyzed through iterative coding, constant comparison, conceptual integration, and progressive abstraction. The analytical process involved identifying meaningful statements, generating primary codes, merging conceptually similar codes, forming subcategories, and synthesizing them into higher-order risk dimensions until theoretical saturation was achieved. The meta-synthesis yielded 118 primary codes organized into 28 subcategories and eight overarching dimensions: technological and digital infrastructure risk, cybersecurity and information security risk, strategic and innovation risk, organizational and operational risk, knowledge and human capital risk, financial and economic risk, legal and regulatory risk, and environmental, market, and ecosystem risk. The findings indicated that these dimensions were strongly interconnected rather than independent. Information technology emerged simultaneously as an independent source of risk, a transmission mechanism capable of amplifying risks across organizational domains, and a capability for mitigating uncertainty through improved governance, analytics, knowledge integration, and monitoring. Technological vulnerabilities were particularly linked to operational disruption, financial exposure, knowledge loss, legal liability, and weakened innovation capacity. The proposed model demonstrates that risk identification in knowledge-based companies requires a systemic and multidimensional approach in which technological, organizational, knowledge-related, financial, legal, and environmental risks are assessed jointly, enabling managers to identify interdependencies and design more coordinated risk-management strategies.

The Impact of Water Challenges on Social Security and Their Consequences for the Development of Khuzestan Province

Sohila Afsharpour ^* iD

This study aimed to investigate the impact of water-related challenges on social security and to identify their consequences for the development of Khuzestan Province. This qualitative study employed an applied, interpretive research design. The study population consisted of university faculty members, researchers, policy specialists, public-sector experts, and professionals in water resources management, environmental studies, sociology, social policy, security studies, regional planning, and sustainable development in Tehran. Participants were selected purposively based on relevant academic or professional expertise, and sampling continued until theoretical saturation was achieved. A total of 24 participants were included. Data were collected through semi-structured, in-depth interviews addressing water scarcity, drought, declining river flows, water quality, wetland degradation, governance, livelihood insecurity, migration, institutional trust, social cohesion, and developmental consequences. Interviews were transcribed verbatim and analyzed using thematic analysis through iterative coding, categorization, constant comparison, and abstraction. MAXQDA software was used to organize and manage the qualitative data, and trustworthiness was enhanced through credibility, dependability, confirmability, and transferability procedures. The analysis identified eight major themes: structural and environmental water pressures, livelihood and economic insecurity, social instability and weakening of social cohesion, migration and demographic disruption, institutional distrust and governance challenges, deterioration in public health and quality of life, constraints on regional development, and intensification of social-security risks. Water insecurity was found to operate through a cascading pathway in which hydrological and environmental pressures weakened livelihoods, increased migration and perceived inequality, reduced institutional trust, intensified social tensions, and ultimately constrained agricultural, industrial, demographic, environmental, infrastructural, and institutional development. Feedback mechanisms also indicated that underdevelopment, human-capital loss, weak governance, and environmental degradation could further intensify future water insecurity. Water challenges in Khuzestan should be understood as an integrated environmental, social, security, and developmental issue requiring coordinated policies that combine sustainable water governance, ecological restoration, livelihood resilience, distributive justice, institutional trust, and balanced regional planning.

Organizational Resilience Architecture in Crisis: Formulating a Grounded Theory Model for the Mazandaran Red Crescent Society

Seyed Adel Rezaei Jamnani iD , Seyed Mohammad Hossein Hashemi Nasab ^* iD , Ghasemali Talebi Panbeh Choleh iD , Mohammad Reza Zand Moghadam iD

The present study was conducted with the aim of formulating a paradigmatic model of organizational resilience under crisis conditions within the Mazandaran Red Crescent Society. In terms of purpose, this research was applied, and in terms of approach, it employed an exploratory mixed-method design. In the qualitative phase, data were collected and analyzed using Grounded Theory based on the systematic approach of Strauss and Corbin through semi-structured interviews with 16 experts in organizational behavior, human resource management, and managers of the Mazandaran Red Crescent Society. Through the processes of open, axial, and selective coding, 428 final codes were identified and organized into 33 main categories and 125 subcategories. The qualitative findings indicated that organizational resilience during crises in this organization is shaped by causal conditions including effective leadership, a flexible organizational culture, advanced information systems, human resource capabilities, support mechanisms, crisis preparedness, and preventive capacities. These factors operate within contextual conditions such as organizational structure, physical resources and facilities, policies and regulations, access to emerging technologies, and developmental infrastructure. Furthermore, intervening conditions, including stress management, team coordination, change management, support systems, motivation, and commitment, influence the effectiveness of strategies such as planning, effective communication, strengthening support networks, process innovation, stakeholder participation, optimal resource allocation, enhanced decision-making, and training and preparedness. These strategies ultimately lead to outcomes including organizational sustainability, improved performance, increased public trust, reduced recovery time, enhanced organizational credibility, greater flexibility, and strengthened innovative capacities. In the quantitative phase, the extracted model was validated using Structural Equation Modeling (SEM) based on data collected from 625 employees of the Mazandaran Red Crescent Society. The results demonstrated an acceptable model fit. Accordingly, the proposed model can serve as an analytical and operational framework for strengthening organizational resilience in emergency response organizations under crisis conditions.

A Mathematical Integrated Model for Shop Scheduling Routing Considering Reliability and Maintenance under Uncertainty Conditions

Mohammad Rajabpour iD , Masoomeh Zeinalnezhad ^* iD , Vahid Hajipour iD

This study presents an integrated mathematical model for shop routing and scheduling while considering machine reliability and maintenance under uncertainty conditions. The primary objective of the proposed model is to optimize production time and system costs through effective machine management, activity scheduling, and preventive maintenance planning. To achieve this objective, the mathematical model incorporates a set of decision variables and parameters, including machine-related costs, energy consumption costs, and maintenance and repair costs. Furthermore, the model includes constraints related to activity continuity, precise activity scheduling, compliance with time restrictions, costs associated with machine utilization, and machine maintenance levels. The proposed model is particularly applicable to manufacturing environments that require efficient management of resources and machinery and can assist production managers in reducing operational costs and production lead times. The model can be solved using numerical optimization algorithms, and its results can support optimal decision-making regarding scheduling, routing, and machine maintenance in manufacturing systems.

The Ecosystem Model of the Country’s Prisons with an Emphasis on Prisoner Behavioral Reform (Case Study: Tehran Prisons Organization)

Pedram Mohammadzadeh iD , Seyed Mehdi Alvani ^* iD , Seyed Ahmad Hosseini Golafshani iD , Afsaneh Zamani Moghadam iD , Seyed Abdullah Sajjadi Jaghargh iD

Prisoners, as a vulnerable group within society, face numerous challenges that not only affect their quality of life but also influence their successful reintegration into society. Prison conditions are recognized as a determining factor in the process of prisoner rehabilitation and reformation. In this regard, various factors, including hygiene and sanitation, security, the social environment, and educational and support programs, can play a significant role in reducing tensions and improving prisoners’ quality of life. This study seeks to examine the environmental and social conditions of prisons and identify the impact of rehabilitative and educational programs on prisoners’ capacity for successful reintegration into society. Furthermore, it investigates the economic and social support mechanisms that may facilitate this process. This research was conducted using a qualitative approach and employed in-depth interview content analysis methods. The study population consisted of inmates from several selected prisons, as well as staff members and specialists working in the field of correction and rehabilitation. Data were collected through semi-structured interviews using purposive sampling to ensure a comprehensive examination of diverse perspectives. Data analysis was performed using thematic analysis to identify key patterns and concepts. Through ongoing data collection and continuous analysis, theoretical saturation was ultimately achieved, such that no new data contributed substantial additional information to the findings. This process enabled the generation of more precise results regarding the effects of prison conditions and rehabilitative programs on prisoner rehabilitation.

Development of a Model of Factors Affecting Startup Success Using Directed Content Analysis

Fatemeh Aminsaffar iD , Gholamreza Tavakoli ^* iD , Abolfazl Bagheri iD , Manoochehr Manteghi iD

Startup success is a multidimensional phenomenon, and explaining it solely through a single factor such as an innovative idea, venture financing, or market growth is insufficient. This study aims to identify the factors affecting startup success and to develop its conceptual model based on case-based evidence. The research is applied in terms of purpose and qualitative in terms of approach. In the first stage, relevant studies on startup success were reviewed using Sandelowski and Barroso’s seven-step meta-synthesis method, and the main factors were extracted. Then, to develop the model, three startups with different conditions, including a successful and developing startup, a growing startup, and an unsuccessful and discontinued startup, were examined as case studies. The meta-synthesis findings indicated that the factors affecting startup success can be classified into five main categories: leadership and team, product or service, market and customer, business model and finance, and external environment. The case study results showed that sustainable startup success depends not only on the existence of these factors but also on their alignment and executability. Accordingly, components such as strategic focus, simplicity of value proposition, specialized trust-building, continuous customer support, revenue model executability, stakeholder alignment, and ecosystem leverage were added to the initial model. The developed model can be used to assess startups’ growth status, sustainability, and investment readiness.

Designing a Crowdfunding Investment Marketing Model for Enhancing Sustainable Urban Revenues: A Case Study of Tehran Municipality

Abolghasem Yousef Soltanieh iD , Mahmoud Ahmadi Sharif ^* iD , Arezo Ahmadi Danyali iD , Nader Gharibnavaz iD

https://doi.org/10.61838/kman.jrmde.372

This study aimed to design and validate a crowdfunding investment marketing model for enhancing sustainable urban revenues in Tehran Municipality, with emphasis on the role of innovation drivers. This applied study was conducted using a mixed-methods exploratory–confirmatory design. In the qualitative phase, the Delphi technique was used to identify and validate the main dimensions and indicators of the model based on the opinions of 15 experts in urban management, municipal finance, innovation, investment, and crowdfunding. In the quantitative phase, a structured questionnaire was administered to 250 managers and senior experts of Tehran Municipality who were involved in financial, investment, planning, innovation, and public participation domains. Data were analyzed using exploratory factor analysis, confirmatory factor analysis, reliability testing, and structural equation modeling through SPSS and SmartPLS/AMOS. Inferential findings confirmed the adequacy of the measurement model. The KMO values for innovation in urban management, crowdfunding investment marketing, and sustainable urban revenue were 0.874, 0.884, and 0.893, respectively, and Bartlett’s tests were significant at p < 0.001. The extracted factors explained 57.45% of the variance in innovation, 68.30% of the variance in crowdfunding investment marketing, and 72.63% of the variance in sustainable urban revenue. Reliability was also confirmed, with Cronbach’s alpha coefficients of 0.907, 0.931, and 0.923, respectively. Structural equation modeling showed that innovation drivers had a positive and significant effect on crowdfunding investment marketing (β = 0.78, t = 8.45). Crowdfunding investment marketing significantly affected sustainable urban revenue (β = 0.65, t = 6.12). The direct effect of innovation drivers on sustainable urban revenue was also significant (β = 0.32, t = 3.11), and the indirect effect through crowdfunding investment marketing was confirmed (β = 0.51, t = 5.88). The results indicate that innovation drivers provide the institutional, technological, and organizational foundation for effective crowdfunding investment marketing, while crowdfunding marketing functions as a strategic mechanism for converting citizen trust and participation into sustainable municipal revenues.

Journal of Resource Management and Decision Engineering

About the Journal

Current Issue

Articles

Potential Improvement of Hydraulic Resistance in Coastal Soils Using Optimized Microbially Induced Calcium Carbonate Precipitation (MICP): A Case Study of Kish Island

Design and Optimization of a Real-Time Audio Simulation Engine on Mobile Devices

Environmental Life Cycle Assessment of Gasoline Production Process in Khuzestan Using an Ecosystem Approach in Environmental Planning

Designing a Model for Reducing Behavioral Conflicts among Employees in the Information Technology Sector

Explanation and Prioritization of Factors Influencing the Location of Resilient Schools Against Natural Hazards with an Emphasis on Collective Intelligence (Case Study: Nowshahr City)

Analysis of Social and Cultural Factors Affecting the Development of Tourism Culture in Iran: A Case Study of Border Regions

An Enhanced Hybrid Statistical–Learning Approach for Detecting Fake Feedback in Cloud Environments Using Hierarchical Clustering with Reptile Search Algorithm and Particle Swarm Optimized Extreme Learning Machine

Detection of Attacks in Internet of Things Devices Using an Optimized Ensemble Classification Based on Deep Transfer Learning and the Harris Hawks Algorithm

Investigating the Relationship between Job Characteristics and the Growth of Professional Ethics among Employees of the East Azerbaijan Gas Company

Identification of Key Causes of Disputes in Construction Projects and Preventive Strategies: A Systematic Review

Presenting a Sustainable Supply Chain Model Based on Blockchain Technology in Iran’s Oil and Gas Industry (Case Study: Fajr Jam Refinery)

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