Kosar Omrani, Abdul Sattar Safaei, Mohammad Mahdi Paydar, Maryam Nikzad,
Volume 31, Issue 1 (3-2020)
Abstract
| Regarding population growth and prompt development in developing countries, municipal solid waste management is always a great challenge for governments. Waste to energy conversion is an efficient approach with respect to overcoming not only the challenge of municipal solid waste management but also environmental challenges related to energy consumption like global warming and fossil fuel depletion. One of the substantial problems throughout the implementation of waste to energy approach is process selection. The selected process should be technically feasible and should have a high level of compliance with environmental standards. Owing to an inevitable significance of process selection, this paper focuses on defining the best process by relying on multi-criteria decision-making tools and network analytic process. Considering the effective parameters such as cost, efficiency in material diversity, productivity rate, energy consumption, pollutant emissions, toxic substances, and process time, the result indicates that the physico-chemical process is superior process for pretreatment of material. |
Seyed Erfan Mohammadi, Emran Mohammadi,
Volume 31, Issue 3 (9-2020)
Abstract
Today due to the globalization and competitive conditions of the market, decisions are generally made in group and in accordance with different attributes. In addition, all of the information is associated with uncertainty. In such situation, the emergence of inconsistency and facing with the contradictions will be obvious. Having regarded this fact, the development and application of tools that adequately address the uncertainty in decision making process and also be appropriate for group decision making is an important area of multi-criteria decision making (MCDM). Therefore, in this paper, firstly we developed the traditional best-worst method (BWM) and proposed an interval-valued intuitionistic fuzzy best-worst method (IVIFBWM), then introduced a novel approach for fuzzy multi-attribute group decision making based on the proposed method. Finally, in order to demonstrate how the introduced approach can be applied in practice, it is implemented in an Iranian investment company and the experimental results are examined. From the experimental results, we can extract that not only the introduced approach is simple in calculation but also it is convenient in implementation especially in interval-valued intuitionistic fuzzy environments.
Moreza Rasti-Bazroki, Pegah Amini,
Volume 32, Issue 3 (9-2021)
Abstract
Due to the intensity of competition and economical condition in different countries, a group of manufacturers tried to add new products in their product portfolios in order to gain superiority against their competitors. However, the strategy and the manner of adding the products to the portfolio is one of the biggest challenges in the manufacturing process. As a result, researchers have used a variety of methods to evaluate the alternatives, such as ranking, mathematical optimization and multi criteria decision making. Hybrid methods using multi criteria decision making have gained popularity in recent years. This article uses a novel hybrid strategy using multi criteria decision making in order to find the best alternative. It is concluded that the ‘making’ alternative is superior to joint venturing and buying alternatives using the net outranking flow index.
Amir Mohamadghasemi, Abdollah Hadi-Vencheh, Farhad Hosseinzadeh Lotfi,
Volume 32, Issue 4 (12-2021)
Abstract
Preventive maintenance (PM) of machines has the critical role in a factory or enterprise. It decreases number of failures, increases reliability, as well as minimizes costs of production systems. The managers’ duty of maintenance section is to prioritize machines and then, implement PM programs for them. Since machines have the different measures with respect to the maintenance costs, reliability, mean time between failures (MTBF), availability of spare parts, etc., the machines evaluation problem can be considered as a multiple criteria decision-making (MCDM) problem. Accordingly, the MCDM techniques can be applied to solve them. The aim of this paper is to extend the ELECTRE III (eLimination et choix traduisant la realite´– elimination and choice translation reality) method to interval type-2 fuzzy sets (IT2FSs) using curved (such as Gaussian) membership functions (MFs). The extended ELECTRE III methodology is then utilized to a maintenance group MCDM (GMCDM) matrix including the quantitative and qualitative criteria. In the proposed approach, the criteria weights, the assessment of alternatives with respect to criteria, and the thresholds are stated with Gaussian interval type-2 fuzzy sets (GIT2FSs). In order to show the effectiveness and applicability of the proposed approach, a case study and an illustrative example are exhibited using real decision-making problems. Due to the high correlation coefficients between our method and the others, as well as the results obtained by the proposed method, it can be taken into account as a valid and reliable approach to prioritize machines for PM.
Fatemeh Faghidian, Mehdi Khashei, Mohammad Khalilzadeh,
Volume 33, Issue 1 (3-2022)
Abstract
This study seeks to introduce the influential factors in controlling and dealing with uncertainty in intermittent demand. Hybrid forecasting and Grey Theory, due to their potential in facing complex nature, insufficient data, have been used simultaneously. Different modeling, unbiased weighting results have been used in estimating the safety stock(SS) by both theoretical and experimental methods. In other words, this work deals with the less studied feature of various modeling errors and their effect on SS determination and recommends its use to address the uncertainty of intermittent demand as a criterion for introducing a superior model in the field of inventory.
Inna Irtyshcheva, Yevheniya Boiko, Olena Pavlenko, Iryna Kramarenko, Kseniia Chumakova, Natalia Hryshyna, Olena Ishchenko, Anastasiia Zubko,
Volume 34, Issue 1 (3-2023)
Abstract
The research is devoted to the theoretical and applied
organizational bases to held of the comparative analysis of the economic development of the regions of the Black Sea region. The main purpose of the article is the process of comparative
analysis of economic development of the Black Sea region. The article tests the authors' hypothesis about the adequacy of the indicators defined for evaluation through the proposed number of relative indicators, which in the complex will characterize the achievements of the region in ensuring the economic stability of the regional system, quality of transformation processes and indirectly the conditions created by public authorities for economic development. There is confirmed the dependence of the use of the proposed methodological approaches and the constructed comparative profile of the regions of the region, which can be useful for identifying the strengths and weaknesses of the region, outlining key issues and developing regional development plans and programs. It is determined that the largest vector length in the Mykolaivska region, which indicates that in the region on a number of economic indicators achieved higher results than in other regions of the Black Sea region and on average in other regions of Ukraine during the study period.
Nor Mazlina Ghazali, Aqilah Yusoff, Wan Marzuki Wan Jaafar, Salleh Amat, Edris Aden, Azzahrah Anuar,
Volume 34, Issue 2 (6-2023)
Abstract
The research aimed to determine the best components of Malaysia-Counsellor Performance Indicator in measuring the counsellor’s performance in Malaysia. This is the first development phase of the M-CPI. This study involved two type of research designs; quantitative and qualitative approach (Mixed Method). The quantitative data has been obtained from 102 respondents and interview with eight (8) counsellors from different settings. Stratified random sampling technique was utilized to select the respondent and proportional stratification was used to determine the sample size of each stratum. A Need Assessment questionnaire has been developed by the researchers as well as the protocol interview. These two instruments were developed based on the literature reviews of previous instruments that have been invented from the western perspective to measure the performance and competency of counsellors. The results of the study were analysed using the descriptive analysis and thematic analysis. Findings have shown that majority counsellors possessed knowledge and skills in conducting counselling session. Most counsellors in the study demonstrated good interpersonal relationship, interaction, multicultural and religiosity and ethics and professionalism. Through this study, to measure the performance of counsellors, the researchers have found that they must equip themselves with knowledge, skill, interpersonal relationship, interaction, multicultural and religiosity and ethics and professionalism aspects. Based on the interview data, there were new components that have been identified to be added in the Malaysia Counsellor Performance Indicator (M-CPI) which include knowledge (theoretical and knowledge transfer), skills (case management, practical skills and academic/professional writing), interpersonal relationship and interaction, cultural and religiosity, professional roles and expertise, ethics and legality, attitudes and personality, referral and articulate philosophy of profession. In future, research should also focus on the validity and reliability of the components listed in the M-CPI.
Harwati Harwati, Anna Maria Sri Asih, Bertha Maya Sopha,
Volume 34, Issue 3 (9-2023)
Abstract
In recent years, research on halal supply chain resilience (HSCRES) has been growing to deal with the vulnerabilities caused by halal risks that disrupt global halal supply chains. However, empirical studies in this field have been hindered by the lack of identifying halal capabilities that represent the strength of HSCRES. This study aimed to determine and prioritize halal resilience capability. In the first step, extant literature is reviewed to identify capability factors in the context of the halal supply chain. In the second step, the fuzzy analytical hierarchy process (FAHP) approach was used to rank the halal capability indicators. The results of this study indicate that halal integrity is the most important capability factor in enhancing a resilient halal supply chain. The results also reveal that mandatory regulation is the most significant indicator in HSCRES, followed by halal teams, official halal logos, internal halal audits, and communication channels. This finding offers stakeholder recommendations on which capabilities should be prioritized to reduce the impact of halal risks that disrupt supply chains’ resilience
Ali Mostafaeipour, Ghasem Ghorbannia Ganji, Hasan Hosseini-Nasab, Ahmad Sadegheih,
Volume 34, Issue 4 (12-2023)
Abstract
Compared to coal and other fossil fuels, renewable energy (RE) sources emit significantly less carbon dioxide (CO2). In this sense, switching to such sources brings many positive effects to the environment through mitigating climate change, so the terms green energy and clean energy, have been derived from these constructive environmental impacts. Given the utmost importance of RE development, the primary objective of this study was to identify and prioritize the effective RE development strategies in Mazandaran Province, Iran, using different methods, including the Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, along with other decision-making techniques. Recruiting a team of 11 industrial and academic experts, the strategies to implement in this region were developed in line with the RE development plans. For this purpose, the Multi-Criteria Decision-Making (MCDM) methodologies were utilized within the gray fuzzy environment to manage the existing uncertainties. The Gray-Additive Ratio Assessment System (Gray ARAS) was further applied to rank the main factors at each level. According to the SWOT analysis and the Stepwise Weight Assessment Ratio Analysis (SWARA) outcomes, among the major factors shaping RE development in Mazandaran Province, Iran, the economic criterion, with the final weight of 0.24, was ranked first; and then the geographical and environmental criteria, having the final weights of 0.23 and 0.19, were put in the second and third places, respectively. In this regard, appropriate location, with the final weight of 0.226, was ranked first; and subsequently pollution reduction and energy production costs, receiving the final weights of 0.103 and 0.094, were the second and third sub-criteria, respectively. As a final point, the validation results based on the Gray-Weighted Aggregated Sum Product Assessment (Gray-WASPAS) and ranking obtained through the Gray-ARAS were confirmed.
Che Hafizan Che Hassan, Zainura Zainon Noor, Azmi Aris, Norelyza Hussein, Nur Syamimi Zaidi, Nor Zaiha Arman, Muhammad Azmi,
Volume 35, Issue 1 (3-2024)
Abstract
Life cycle assessment (LCA) is a valuable tool not only for analyzing the environmental impact of a product but also for assisting in early-stage product development before incurring scaling-up costs. When validating a new process or project, it may be constrained to align with existing regulations or standards. Therefore, combining LCA with other applicable standards is essential to demonstrate the project's feasibility. In this regard, the water quality index (WQI) and Water Exploitation Index (WEI) provide additional information that reflects the overall water quality at a specific location and time. The objective of this study is to utilize the LCA framework in conjunction with the Malaysia WQI and WEI to protect the water quantity and water quality of the river. A negative change in the WQI score indicates that the current effluent from the process is degrading the river's classification, rendering it undesirable and necessitating a reduction in concentration. The findings demonstrate that the method for determining effluent requirements for a water treatment system is straightforward and replicable. Such an approach could be employed, for example, in an environmental impact analysis of a project to verify its viability.
Maryam Arshi, Abdollah Hadi-Vencheh, Adel Aazami, Ali Jamshidi,
Volume 35, Issue 4 (12-2024)
Abstract
Linguistic variables (LVs) provide a reliable expression of cognitive information. By inheriting the advantages of LVs, we can express uncertain and incomplete cognitive information in multiple attribute decision-making (MADM), and they do so better than existing methods. In the decision-making process, we can consider decision experts’ (DEs’) bounded rationality, such as cognition toward loss caused by the DEs’ cognitive limitations during the decision process. Therefore, it is necessary to propose a novel cognitive decision approach to handle MADM problems in which the cognitive information is expressed by LVs. In this paper, we employ LVs to represent uncertain and hesitant cognitive information. Then, we propose a mathematical programming approach to solve the MADM problems where attributes or cognitive preferences are not independent. Moreover, the validity and superiority of the presented approach are verified by dealing with a practical problem.
Mehdi Ajalli, Narges Soleiman Ekhtiyari, Peyman Zandi,
Volume 36, Issue 2 (6-2025)
Abstract
This study aims to evaluate the traditional, lean and agility criteria that are effective in evaluating the performance of suppliers and ranking them with the combined approach Path Analysis (PA), SWARA (Stepwise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) in Automation Industry. The research method is applied from the perspective of the objective and is descriptive-survey in terms of data collection. For this purpose, the sub-criteria were first extracted by reviewing the literature. Then, using PA approach, the effectiveness of these criteria in automation industry was investigated. The statistical population in this section includes 60 experts and managers of the industry, which due to the smal size, all members of the community were considered as a sample. The PA output showed that after evaluating twentycriteria, seventeen criteria were finally approved by the experts. Then, using the SWARA and the opinions of experts, the criteria importance and weight was calculated. The results showed that the criterion of "agility" was in the first place, "lean" was in the second place and "traditional" was in the last place. Then, considering the importance of ranking of lean and agile suppliers in the industry, using TOPSIS and based on the weight of the criteria, six suppliers were evaluated by experts. The results showed that the fourth supplier was ranked first. The first supplier was also ranked sixth. Finally, a sensitivity analysis of the ranking was conducted. Overall, the results show a high degree of stability of the rankings according to the method used. Thus, the model proposed in this study provides a suitable framework for evaluating industry suppliers based on key criteria of traditional, lean and agility.
Mehdi Abdollahi Kamran, Samira Afsharfar, Fatma Al Mawali, Reza Babazadeh, Marya Al Balushi,
Volume 36, Issue 2 (6-2025)
Abstract
One of the most critical concerns in supply chain management (SCM) is supplier selection, which significantly impacts an organization's efficiency and market agility. Balancing ordinal and basic criteria in supplier selection has become increasingly crucial in recent years within SCM. This research presents three multi-criteria decision-making (MCDM) methods including Fuzzy analytic hierarchy process (AHP) and Fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods to assess and select suppliers in oil and gas (O&G) industry. The critical criteria for supplier selection in the O&G sector have been reviewed in the literature and validated by experts actively working in the field. Initially, the Fuzzy AHP technique determines criterion weights and ranks suppliers. Subsequently, the Fuzzy TOPSIS approach is applied to rank prospective suppliers identified through objective evaluation. The findings show the capability of the utilized approaches in supplier selection procedure in O&G industry.
Nadera Hourani,
Volume 36, Issue 2 (6-2025)
Abstract
Artificial intelligence (AI) has been integrated into human resource management (HRM), enabling the transformation of the field through routine job automation, decision-making enhancement, and evidence-based strategies. This article will systematically review the role of AI in HRM, focusing on applications related to recruitment, employee engagement, workforce planning, and retention. This systematic review article underlines the significant benefits of AI adoption by analyzing ten peer-reviewed studies using advanced statistical analysis. These benefits include efficiency gains, increased employee satisfaction, and strategic workforce optimization. Yet, there are significant challenges in the form of algorithmic bias, data privacy concerns, and organizational readiness. Regression and correlation analyses show a strong positive relationship between AI use and HR performance metrics, with a greater effect on recruitment and retention. Though AI has a huge potential for transformation, the findings have brought into focus the need for ethical guidelines, strong data protection, and employee upskilling for the full realization of AI's capabilities in HRM. Thus, this study provides practical insights for organizations seeking to adopt AI technologies while addressing the associated challenges.
Sri Kaidah, Tajuddin Bantacut, Muslich Muslich, Khaswar Syamsu,
Volume 36, Issue 3 (9-2025)
Abstract
The initial stage in agro-industrial development planning involves identifying high-potential raw materials. Assessing commodity competitiveness requires a comprehensive analytical approach to ensure that decisions are both accurate and sustainable. The development potential of aquaculture-based agro-industries can strengthen linkages between upstream and downstream sectors, particularly between fishery production and processing industries. However, in four coastal regencies of West Java Province, aquaculture-based agro-industries have not yet been developed, despite aquaculture recording the highest export value at the provincial level. At present, the region remains dominated by manufacturing industries. This study aims to identify priority aquaculture commodities for coastal agro-industrial development. Commodity competitiveness was assessed using five analytical methods: Location Quotient (LQ), Dynamic Location Quotient (DLQ), Sectoral Contribution Index (SCI), Growth Ratio Model (GRM), and Shift Share Analysis (SSA). A multi-method approach was employed to generate complementary results and enhance the validity of the superior commodity designation. The findings reveal that shrimp is categorized as a highly competitive commodity across all four regencies. These results serve as a strategic foundation for regional agro-industrial development policies and can be replicated in other coastal areas.
Raden Pujiyono, Marimin Marimin, Arif Imam Suroso, Setiadi Djohar,
Volume 36, Issue 3 (9-2025)
Abstract
| The Indonesian paint industry contributes significantly to the national economy but remains highly dependent on imported raw materials, constituting approximately 77% of the total supply. This study aims to develop strategic solutions to increase local content and reduce import dependency by applying the Analytic Hierarchy Process (AHP) and Interpretive Structural Modeling (ISM). Based on AHP results, Capacity Building and Workforce Development emerged as the top-ranked strategy, with a final priority value of 0.330, followed by Strengthening Local Supply Chain (0.262). ISM analysis identified the Centre for Increasing Local Content as a key institutional driver influencing other actors in the supply chain. The sensitivity analysis confirmed the robustness of the AHP prioritization, showing less than 5% variation in rankings across multiple expert input scenarios. This indicates that the proposed strategies are stable and reliable under varying assumptions. The research provides a structured, multi-criteria framework aligning local strategies with national policy and international trade obligations. The study offers policymakers and industry leaders practical insights by integrating technology, human capital, and supply chain optimization to support a resilient and sustainable local content policy. Integrating AHP and ISM methods presents a novel approach, contributing original insights to the industrial strategy literature. |
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Mohammad Reza Zare Banadkouki, Mohammad Hossein Abdorrahimian,
Volume 36, Issue 3 (9-2025)
Abstract
Nowadays, it is very important to pay attention to the influential factors and economic and social drivers in developing countries, and identifying and evaluating the performance of Strategic value chains (SVCs) is in this direction. Evaluating local VCs and planning to upgrade them to the region and the world can be part of the development programs of each country. The correct selection of SVCs, considering the economic and competitive environment of the region, causes economic and social transformation. In this research, considering the development programs of Iran and especially Yazd province, the value-creating sectors of Yazd province were considered. After studying the upstream documents, the active VCs in the Yazd province were first extracted. Then, by reviewing the literature on the subject and asking for opinions from experts, the criteria for evaluating SVCs from the economic, social, and regional perspectives were determined. The Shannon entropy method was used to weight the evaluation criteria, and the fuzzy TOPSIS method was used to select the most effective VCs. From the literature review, documents, and field observations, 20 local VCs and 8 evaluation criteria were extracted and approved by experts. The study results revealed that the evaluation criteria of “High job creation” and “Positive effect on gross domestic product (GDP)” had the highest weights, and “Tourism and handicrafts”, “Textile and clothing”, “Commercial logistics and transportation”, and “Non-metallic minerals” had the highest impacts in Yazd Province, according to the evaluation criteria known as SVCs. Moreover, a sensitivity analysis was performed to determine the stability and robustness of the proposed approach by changing the weights of the desired criteria.
Mohamed Hadi Al Najdawi , Tamadher Al Dabbagh, Raghda Raafat, Ahmad Aburayya,
Volume 36, Issue 3 (9-2025)
Abstract
This study investigates the role of administrative governance mechanisms in enhancing institutional integrity and transparency while reducing administrative corruption in public institutions. Employing a quantitative analytical approach, primary data were collected through a structured questionnaire distributed to 50 respondents across oversight bodies, inspection departments, and academic experts in Jordan, yielding a 90% response rate (n = 45). The analysis, based on descriptive and inferential statistics (Ka² tests, α = 0.05), demonstrated that the application of governance principles, particularly transparency, accountability, and administrative oversight, was significantly associated with improved institutional performance and a measurable decline in perceived corruption. Specifically, the study found that respondents largely agreed (mean = 4.04; SD = 1.10) on the effectiveness of regulatory and legal frameworks in combating corruption, while 88% supported the role of continuous monitoring in promoting integrity. Sensitivity analyses confirmed the robustness of these relationships across stakeholder categories. From the findings, a major standing for the immediate modernization of legal-administrative frameworks, training for governance implementation, and institutionalization of oversight mechanisms emerges. Concluding that administrative governance is vital to institutional integrity and sustainability, this study's contribution lies in filling the gap by providing an evidence-based argument pertinent to anti-corruption policies, legal reforms, and modernizing the public sector within developing contexts.
Emad Hajjat, Leqaa Al-Othman, Khaled Al-Tamimi, Issa Alrawashdeh,
Volume 36, Issue 3 (9-2025)
Abstract
This study determines the effects of investment institutions on improving business earnings and governance quality in Jordanian industrial businesses for the period (2018-2023), using the descriptive analytical approach to accomplish study goals. The study participants included (46) Jordanian industrial companies while the sample amounted to (45.7%) of commercial enterprises’ representatives research community. The annual reports of industrial businesses provided data for study variables found on the Amman Stock Exchange's website and on Securities Depository Center. Researchers used the descriptive and inferential statistical method; provided by E-Views software to accomplish the study's goals. The study results indicate that investing had a favorable impact for institutions on enhancing corporate governance, and a negative effect of investment institutions on the earnings quality. The study recommended encouraging investment institutions to increase their stakes in industrial companies to enhance oversight and transparency, and motivating them to adhere to governance standards by imposing regulations requiring them to apply good governance practices to ensure the sustainability of institutional investment, in addition to adhering to accounting practices.
Muhammad Faisal Ibrahim, Imam Santoso, Siti Asmaul Mustaniroh, Retno Astuti,
Volume 37, Issue 1 (3-2026)
Abstract
This study systematically reviews the application of Multi-Criteria Decision-Making (MCDM) methods in risk management, aiming to map their use to the ISO 31000:2018 framework and consolidate fragmented literature into a structured synthesis. More than 3,000 studies were screened using a PRISMA-based methodology, and 104 were analyzed in depth to examine how MCDM methods support different stages of the risk management process. The findings reveal hybrid MCDM approaches significantly enhance decision-making effectiveness across multiple stages. The most frequently applied methods are the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), often combined for risk prioritization and mitigation strategy selection. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) also effectively analyzes interdependencies between risk factors and mitigation strategies. Nonetheless, challenges such as expert judgment subjectivity and the complexity of integrating multiple techniques remain critical issues. Building on these insights, the study proposes a six-stage conceptual framework that integrates MCDM techniques across risk identification, analysis, evaluation, and treatment. The key contribution lies in providing a unified, adaptive, and data-driven framework that enhances comparative understanding and strengthens structured risk management practices across industries.
