Fuzzy Analytic Hierarchy Process Utilization in Government Projects : A Systematic Review of Implementation Processes

Uncertain assessments challenge the aggregation of expert knowledge in the field of decision-making. Valuable, yet sometimes hesitant, insight of expert decision makers needs to be converted into numerically comparative form in the age of information management. . Fuzzy Analytic Hierarchy Process (FAHP) enables the comparison of decision elements through expert judgements, even when the information at hand is uncertain. The present study explores Fuzzy Analytic Hierarchy Process (FAHP) implementation in government projects in a systematic literature review. Theoretical framework for Analytic Hierarchy Process (AHP), Fuzzy Set Theory (FST) and their combination, namely Fuzzy Analytic Hierarchy Process (FAHP) is provided. The systematic literature review categorizes research results under three categories and examines each paper by utilizing review questions. Three main application purposes rise from the literature review; policy planning and assessment, project selection and project and performance evaluation. Overall implementation processes of the three application areas are discussed. The conclusion provides comprehensive evaluation of the approach and considerations for practitioners.Asiantuntijanäkemysten epävarmuus vaikeuttaa tiedon keräämistä päätöksenteossa. Päätöksentekoprosessin kannalta arvokkaat, vaikkakin joskus epävarmat, asiantuntijanäkemykset tulee voida muuttaa numerollisesti vertailtavaan muotoon tietojohtamisen aikakautena. Sumea Analyyttinen Hierarkiaprosessi mahdollistaa päätöksenteossa käytettävien elementtien vertailun asiantuntija-arviointien avulla, jopa silloin kun käytettävissä oleva tieto on epävarmaa. Opinnäytetyössä tutkitaan systemaattisen kirjallisuuskatsauksen keinoin Sumean Analyyttisen Hierarkiaprosessin, eng. Fuzzy Analytic Hierarchy Process (FAHP), implementointia julkishallinnon hankkeissa. Tutkimus sisältää teoreettisen viitekehyksen Analyyttisen Hierarkiaprosessin, Sumean joukko-opin, eng. Fuzzy Set Theory (FST) ja niiden yhdistelmän, Sumean Analyyttisen Hierarkiaprosessin, eng. Fuzzy Analytic Hierarchy Process (FAHP), ymmärtämisen tueksi. Systemaattisen kirjallisuuskatsauksen myötä valittu aineisto luokitellaan kolmeen kategoriaan ja jokaista tutkimusta tarkastellaan ennalta määrättyjen kysymysten avulla. Systemaattisen kirjallisuuskatsaukseen myötä valittujen tutkimusten kolme olennaisinta käyttötarkoitusta ovat; käytännön suunnittelu ja arviointi, hankevalinta sekä hankkeiden ja suoritusten arviointi. Aineiston luokittelun jälkeen tutkimus etenee tarkastelemaan erilaisiin käyttötarkoituksiin suunnattujen Sumean Analyyttisen Hierarkiaprosessi -metodin implementointiprosesseja. Johtopäätös -osio tarjoaa pohdintaa ja huomioita siitä, miten päätöksentekijät voivat suhtautua Sumean Analyyttisen Hierarkiaprosessin hyödyntämiseen julkishankkeiden yhteydessä

Sustainable consumption and production in emerging markets

This special issue addresses sustainable consumption and production (SCP) in emerging markets by examining novel methods, practices, and opportunities. The articles present and analyze top-down sustainability efforts as well as bottom-up efforts on firms, supply chain networks, government regulations, and solution methods. This editorial note summarizes the discussions on the firm's operational attributes, sustainable consumption and production practices, and on evaluation and implementation methods. A dominant finding is that the issues of SCP should be explored in different ways within different contexts in emerging countries

Environmental Impacts of Heavy-Duty Natural Gas Vehicle Incentives in California

Society has an interest in reducing pollutants emitted from the vehicles used for transporting people and goods. The main goal of heavy-duty natural gas vehicle (NGV) incentive projects is to offer upfront monetary incentives to reduce greenhouse gas emissions and the production of regulated pollutants in the state. However, these incentives are often based on vehicle weight and do not account for environmental impacts. In addition, although heavy-duty NGVs are being used in a variety of vocation types, conventional emission models only support a limited number of these vocation types. Because of this, it is challenging to assess the precise impacts of the heavy-duty NGV (HD NGV) adoption and predict the specific environmental benefits per given operational conditions and vocation type. If government agencies realize the environmental benefits of alternative fuel vehicles (AFVs), like NGVs, with respect to vocation type and operating characteristics, it would be beneficial to design cost-effective incentive structures and implementation plans. This study primarily focused on the operational characteristics and environmental impacts of the HD NGVs incentivized in California. This study conducted pattern clustering and classification analyses to obtain drive mode compositions (DMC) over duty cycles and showed the heterogeneity of operational and emission characteristics of the vocational HD NGVs. The vocational impact analysis computed the adoption impact of 40 NGVs operating in California across ten different vocation types. The proposed evaluation framework included life-cycle nitrogen oxides (NOx) and carbon dioxide (CO2) emissions of natural gas, renewable natural gas and diesel fuel pathways and compared the lifetime NOx emission reduction potential of the considered vocation type vehicles. The resulting emission benefits of the fuel pathways were used to determine the most incentive-effective vocation types among the considered NGV applications. The multi-criteria decision-making analysis prioritized the fuel pathways based on multiple criteria which are related to an incentive effectiveness index as well as life cycle emissions. Refuse truck and transit bus pathways are likely to achieve the highest return for the total incentive granted when the vehicles are renewable natural gas (RNG)-powered. For compressed natural gas (CNG) fuel pathways, school and transit buses take the highest ranks over the various analysis scenarios. Each vocation type showed different incentive effects and emission reduction potential, which means that some vocational vehicles can play a critical role in the state’s funding and emission reduction plans. The suggested decision-making tool and assessment framework can provide useful reference data to improve the performance of future alternative fuel vehicle incentive programs

A view of MCDM application in education

The effectiveness of the teaching and learning process by educators plays a significant role for countries to prepare students' potential in the forthcoming new industrial revolution (IR). However, the current COVID-19 pandemic and dynamic changes in the curriculum have created a significant shift of emphasis to educators. Hence, the teaching and learning process problems nowadays, including selecting appropriate effectiveness learning, have become a tough decision for educators. It can be solved using multi-criteria decision-making (MCDM) methods. The MCDM technique is widely applied and accepted in various fields but less in the teaching and learning context. This paper reviews and analyses the type of decision problems that were paid most attention to MCDM approaches, the adopted fuzzy set theory as well as inadequacies of those approaches. The purpose is to analyse and identify the literature review related to the applications of MCDM in education so new attributes and appropriate MCDM models for decision making can be suggested. The process involved comparing and analysing the MCDM application and fuzzy set theory in education by reviewing related articles in international scientific journals and well-known international conferences. Some improvements and more future works are recommended based on the inadequacies. The reviewed result may create an interest to the Ministry of Education (MoE) as it proposes teaching and learning process improvement, which will help to achieve greater satisfaction among educators and students

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc

Sustainable Assessment in Supply Chain and Infrastructure Management

In the competitive business environment or public domain, the sustainability assessment in supply chain and infrastructure management are important for any organization. Organizations are currently striving to improve their sustainable strategies through preparedness, response, and recovery because of increasing competitiveness, community, and regulatory pressure. Thus, it is necessary to develop a meaningful and more focused understanding of sustainability in supply chain management and infrastructure management practices. In the context of a supply chain, sustainability implies that companies identify, assess, and manage impacts and risks in all the echelons of the supply chain, considering downstream and upstream activities. Similarly, the sustainable infrastructure management indicates the ability of infrastructure to meet the requirements of the present without sacrificing the ability of future generations to address their needs. The complexities regarding sustainable supply chain and infrastructure management have driven managers and professionals to seek different solutions. This Special Issue aims to provide readers with the most recent research results on the aforementioned subjects. In addition, it offers some solutions and also raises some questions for further research and development toward sustainable supply chain and infrastructure management

The foundation of capability modelling: A study of the impact and utilisation of human resources

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This research aims at finding a foundation for assessment of capabilities and applying the concept in a human resource selection. The research identifies a common ground for assessing individuals’ applied capability in a given job based on literature review of various disciplines in engineering, human sciences and economics. A set of criteria is found to be common and appropriate to be used as the basis of this assessment. Applied Capability is then described in this research as the impact of the person in fulfilling job requirements and also their level of usage from their resources with regards to the identified criteria. In other words how their available resources (abilities, skills, value sets, personal attributes and previous performance records) can be used in completing a job. Translation of the person’s resources and task requirements using the proposed criteria is done through a novel algorithm and two prevalent statistical inference techniques (OLS regression and Fuzzy) are used to estimate quantitative levels of impact and utilisation. A survey on post graduate students is conducted to estimate their applied capabilities in a given job. Moreover, expert academics are surveyed on their views on key applied capability assessment criteria, and how different levels of match between job requirement and person’s resources in those criteria might affect the impact levels. The results from both surveys were mathematically modelled and the predictive ability of the conceptual and mathematical developments were compared and further contrasted with the observed data. The models were tested for robustness using experimental data and the results for both estimation methods in both surveys are close to one another with the regression models being closer to observations. It is believed that this research has provided sound conceptual and mathematical platforms which can satisfactorily predict individuals’ applied capability in a given job. This research has contributed to the current knowledge and practice by a) providing a comparison of capability definitions and uses in different disciplines, b) defining criteria for applied capability assessment, c) developing an algorithm to capture applied capabilities, d) quantification of an existing parallel model and finally e) estimating impact and utilisation indices using mathematical methods

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

Multiple-Criteria Decision Making

Decision-making on real-world problems, including individual process decisions, requires an appropriate and reliable decision support system. Fuzzy set theory, rough set theory, and neutrosophic set theory, which are MCDM techniques, are useful for modeling complex decision-making problems with imprecise, ambiguous, or vague data.This Special Issue, “Multiple Criteria Decision Making”, aims to incorporate recent developments in the area of the multi-criteria decision-making field. Topics include, but are not limited to:- MCDM optimization in engineering;- Environmental sustainability in engineering processes;- Multi-criteria production and logistics process planning;- New trends in multi-criteria evaluation of sustainable processes;- Multi-criteria decision making in strategic management based on sustainable criteria

Barrier analysis to improve big data analytics capability of the maritime industry: A mixed-method approach

The maritime industry is facing increasing challenges due to decarbonization requirements, trade disruptions, and geoeconomic fragmentation, such as International Maritime Organization (IMO) sets out clear framework to reach net zero emissions by 2050, Russia-Ukraine war disrupted maritime activities in the Black and Azov seas, and increased trade tensions between the United States and China. To enhance their sustainability, operational efficiency, and competitiveness, maritime organizations are therefore very keen to build big data analytics capability (BDAC). However, various barriers, mean that only a handful are able to do so. We adopt a mixed-method approach to analyze these barriers. Thematic analysis is used to identify five categories of barriers and 16 individual barriers based on empirical data collected from 26 maritime organizations. These are then prioritized using the analytic hierarchy process (AHP), followed by total interpretive structural modelling (TISM) to understand their interrelationships. Finally, cross-impact matrix multiplications applied to classification (MICMAC) is employed to differentiate the role of each barrier based on its driving and dependence power. This paper makes several theoretical contributions. First, China's hierarchical cultural value orientation encourages competition and obedience to rules, resulting in unwillingness to share knowledge, lack of coordination, and lack of error correction mechanisms. These cultural barriers hinder BDAC development. Second, organizational learning category barriers are found to be the most important in impeding BDAC development. This study also raises practitioners' awareness of the need to tackle cultural and organizational learning barriers