A new rough ordinal priority-based decision support system for purchasing electric vehicles.

This study proposes a novel multi-criteria decision-making (MCDM) model based on a rough extension of the Ordinal Priority Approach (OPA) to determine the order of importance of users' perspectives on Electric Vehicle (EV) purchases. Unlike conventional methods that rely on predefined ranks for criteria weighting coefficients, the proposed rough OPA method employs an aggregated rough linguistic matrix, enabling a more precise and unbiased calculation of interval values. Moreover, the model addresses inherent uncertainties by incorporating nonlinear aggregation functions, accommodating decision makers' risk attitudes for flexible decision-making. To validate the model's efficacy, a large-scale post-EV test drive survey is conducted, enabling the determination of relative criterion importance. Sensitivity analysis confirms the robustness of the model, demonstrating that marginal changes in parameters do not alter the ranking order. The results unveil the significance of the reliability criterion and reveal that vehicle-related characteristics outweigh economic and environmental attributes in the decision-making process. Overall, this innovative MCDM model contributes to a more accurate and objective analysis, enhancing the understanding of users' preferences and supporting informed decision-making in EV purchases

Prioritization of Investment in Regional Transportation Infrastructure (Case Study: Gilan Province)

Increasing urbanization and the need for relocation introduces optimal transportation as a major factor in increasing the level of citizen satisfaction. As a result, governments often spend most of their budgets on repairing and building transportation infrastructure. Now, if a precise and expert decision is not made to prioritize investment in transportation infrastructure, it will cause budget waste, negative impact on the economy and environmental and social damage. Due to the limited budget of Gilan province and the economic conditions prevailing in the whole country, the purpose of this article is to determine the investment priorities in the transportation infrastructure of Gilan province. This research is applied in terms of purpose and analytical-descriptive in terms of method. Document collection was done by referring to articles, documents and books and field collection was done using a questionnaire. In the present study, the multi-criteria method of infrastructure prioritization framework or IPF was used to prioritize investment in transportation infrastructure, which is a quantitative multi-criteria prioritization method and measures socio-environmental and financial-economic indicators. In addition to budget constraints are considered. In this method, using the opinion of experts in the form of a questionnaire and collecting the required data, calculations were performed, which finally showed the results on a visible graph. The analysis of the findings and results shows that the railway infrastructure in Gilan province has the first priority of investment, followed by road infrastructure in the second place and maritime transport infrastructure in the third place, and finally the transport infrastructure. Air is a priority

An analysis of the prioritization of indicators of a child-friendly city (Case study: 5 regions of Urmia)

Introduction: The main purpose of this study is an analysis of the prioritization of indicators of a child-friendly city in the five regions of Urmia to review strategies for improving the situation of each region by examining the indicators of a child-friendly city and ranking the regions of this city.Data and Method: The research method of the present study is applied in terms of purpose and descriptive-analytical in nature. The statistical population of this study is the residents of 5 regions of Urmia. To determine the sample size, Cochran's formula was used. The sample size was 384, which was randomly distributed in the range. The criteria studied in this study include physical, access, socio-cultural and environmental criteria. Data analysis has been done quantitatively and qualitatively. One-sample t-test, Kruskal-Wallis, Spearman correlation, and THIESSEN and OPA method were used to analyze the data. The validity of the questionnaire was confirmed by experts and its reliability was confirmed by Cronbach's alpha test with a value of 0.790.Results: The findings of this study indicate that based on field data and the child-friendly city criteria questionnaire, Urmia Region 1 is ranked first and Urmia Region 2 is ranked fifth among other regions. The results of the Spearman correlation test indicate that the physical criterion has the greatest impact on a child-friendly city.Conclusion: The results of this study indicate that the city of Urmia is at a moderate level in terms of the feasibility of the criteria of a child-friendly city and needs the attention of urban management to improve the situation in regions 2 and 3 of Urmia

Rough sets based Ordinal Priority Approach to evaluate sustainable development goals (SDGs) for sustainable mining

The Sustainable Development Goals (SDGs) have been adopted by countries and companies, including mining companies around the world. The aim of this study is to investigate the degree of importance of the seventeen sustainable development goals (SDGs) on sustainable mining using a rough sets based decision making approach. This novel approach consists of three consecutive stages, namely a questionnaire (survey), data analyses, and SDGs classification. Firstly, a survey is conducted to receive a response from internationally experts across different countries. Each participant is asked to evaluate the importance of each SDG. Secondly, the analyses are carried out to make a distinction among groups of participants who respond similarly and discover viewpoints from the industry, academia, and non-governmental organizations. Finally, the degree of importance of each SDG for sustainable mining is found using a novel decision making approach including Ordinal Priority Approach (OPA) based on rough sets. The survey of the results indicated that for all the participants of the survey, independently of their background, the most important SDG for sustainable mining was “SDG8: Decent work and economic growth”, while the one perceived as the least important was “SDG14: Life below water”. The main objective of SDG8 is to promote economic growth through job opportunities and decent work for all. This in turn leads to a more sustainable, long-term economic growth. While all SDGs play an important role, the proposed rough sets based decision making method provided a rational and objective evaluation performance of their perceived priority in the mining sector

Ranking Agility Factors to Reliably Sustain a Green Industrial Supply Chain Using the Fuzzy Analytic Network Process and Ordinal Priority Approach

Suppliers can achieve high levels of supply chain sustainability by improving the related factors. An agile supply chain can support sustainability. Identifying and ranking agility factors in the SAIPA company in Iran to reach a sustainable and green supply chain is the primary purpose of this study. SAIPA is an automotive company with an extensive supply chain. The data were quantitative, and the collection was completed by reviewing the literature and questioning experts. The FANP and the OPA methods were the tools used to analyze the data. These methods are proper for facing multiple-criteria decision-making problems, as in the case of this paper. We first identified the factors (capabilities, enablers, and attributes) using a literature review. After that, we gathered the data for ranking analysis by collecting the opinions of SAIPA’s organizational experts using a pairwise comparison questionnaire for the FANP and a prioritizing list for the OPA. Both methods showed that “Quickness” is the capability with the highest priority. “Customer Sensitivity” was the most critical enabler, and “Accurate customer-based measures” was the most significant attribute of the FANP analysis. The OPA results showed that “Information Management” was the first enabler, and “Efficient funds transfer” took first place among all the attributes. Managers should pay more attention to these factors to develop agile supply chains in the SAIPA company. The results also showed that the methods proposed for multi-attribute decision-making problems like the FANP have shortcomings, such as difficulties completing the pairwise comparison matrix due to burdensome data collection in cases similar to the one in this study with many factors

A best-worst-method-based performance evaluation framework for manufacturing industry

Purpose: The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance. Design/methodology/approach: The Best Worst Method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance. Findings: The proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% to 70% throughout the year. Management performance can be seen high in percentage in the first two quarter of the financial year ranging from 70% to 80% whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year. Originality/value: This paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.Output Status: Forthcoming/Available Onlin

Benchmarking electric power companies’ sustainability and circular economy behaviors : using a hybrid PLS-SEM and MCDM approach

This research examines the impact of firms’ decision-making, crisis management, and risk-taking behaviors on their sustainability and circular economy behaviors through the mediating role of their eco-innovation behavior in the energy industry in Iraq. Firms are exploring applicable mechanisms to increase green practices. This requires the industry to possess the essential skills to overcome the challenges that reduce sustainable activities. We applied a dual-stage structural equation modeling (PLS-SEM) and a multi-criteria decision-making (MCDM) approach to explore the linear relationships between variables, determine the weight of the criteria, and rank energy companies based on a circular economy. The online questionnaire was sent to 549 managers and heads of departments of Iraqi electric power companies. Out of these, 384 questionnaires were collected. The results indicate that firms’ crisis management, decision-making, and risk-taking behaviors are significantly and positively linked to their eco-innovation behavior. This study confirms the significant and positive impact of firms’ eco-innovation behavior on their sustainability and circular economy behaviors. Likewise, eco-innovation behavior has a fully mediating role. For the MCDM methods, ranking energy companies according to the circular economy can support policymakers’ decisions to renew contracts with leading companies in the ranking. Practitioners can also impose government regulations on low-ranked companies. Thus, governments can reduce the problems of greenhouse gas emissions and other environmental pollution.peer-reviewe

Offshore wind farm site selection in Norway : using a fuzzy trigonometric weighted assessment model

Maximising the energy potential of offshore wind farms requires an in-depth assessment of technological, economic, sociopolitical, and environmental aspects. Given the large economic impact of large-scale projects, a robust site selection procedure is critical for limiting financial risks while supporting informed investments. This research uncovers a novel and multidisciplinary approach for boosting the efficacy of Norwegian and global offshore wind farm siting investments. The proposed method uses a two-stage fuzzy mathematical model that considers technical, economic, logistical, and environmental factors. It combines the Ordinal Priority Approach (F-OPA) and Trigonometric Weighted Assessment (TRWA) technique by using an in-depth techno-economic assessment. An alternative reactive power compensation model, power loss calculations, and associated techno-economic analysis were performed for the investigated offshore wind farm locations. Furthermore, the energy economic calculations are carried out to provide support for the proposed decision-making framework. The proposed methodology was tested through a case study, focusing on ranking Norwegian offshore wind farm sites selected from potential locations announced by The Norwegian Water Resources and Energy Directorate (NVE). Within the Norwegian offshore wind farm sites, the approach demonstrated a versatile and efficient decision-making process at both individual and collective levels, identifying the Sandskallen-Sørøya Nord project as a pivotal investment priority and providing valuable managerial insights to enhance Norway’s offshore wind initiatives. The model’s stability was affirmed through a sensitivity analysis, underscoring its potential to enhance renewable energy policy and decision-making globally

Tradition and Innovation in Construction Project Management

This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings