Search results

With numerous and ambiguous sets of information and often conflicting requirements, construction management is a complex process involving much uncertainty. Decision makers may be challenged with satisfying multiple criteria using vague information. Fuzzy multi-criteria decision-making (FMCDM) provides an innovative approach for addressing complex problems featuring diverse decision makers’ interests, conflicting objectives and numerous but uncertain bits of information. FMCDM has therefore been widely applied in construction management. With the increase in information complexity, extensions of fuzzy set (FS) theory have been generated and adopted to improve its capacity to address this complexity. Examples include hesitant FSs (HFSs), intuitionistic FSs (IFSs) and type-2 FSs (T2FSs). This chapter introduces commonly used FMCDM methods, examines their applications in construction management and discusses trends in future research and application. The chapter first introduces the MCDM process as well as FS theory and its three main extensions, namely, HFSs, IFSs and T2FSs. The chapter then explores the linkage between FS theory and its extensions and MCDM approaches. In total, 17 FMCDM methods are reviewed and two FMCDM methods (i.e. T2FS-TOPSIS and T2FS-PROMETHEE) are further improved based on the literature. These 19 FMCDM methods with their corresponding applications in construction management are discussed in a systematic manner. This review and development of FS theory and its extensions should help both researchers and practitioners better understand and handle information uncertainty in complex decision problems.

This section describes sustainable development (SD) in relation to infrastructure projects and explains how to evaluate SD. SD is assessed as context-dependent, considering the project’s economic, social, and ecological context. Sustainable road infrastructure projects (SRIP) should encapsulate the complete life cycle from idea to development, functionality, and maintenance. SD should be considered as part of the evaluation process prior to project execution, but it can also serve other functions. Sustainability evaluation must start with project appraisal or evaluation and the earliest stages of project decision-making. Sustainable infrastructure projects (SIPs) are evaluated using a variety of techniques and models, such as cost-benefit analysis (CBA), multi-criteria techniques, ecological and societal impact assessments, ranking techniques, models, and evaluation guidelines. Established SD structures and modelling techniques for infrastructure projects are presented from an SD perspective, with the primary objective of investigating how they operate and determining whether existing models provide an effective method for applying the SD idea into infrastructure development. CBA is a widely used strategy for evaluating alternatives to maximize sociocultural well-being. It is based on the likelihood of costing customer advantages and negative impacts and has been discussed in scholarly articles. The multi-criteria decision analysis (MCDA) approach is an acceptable methodology for addressing complex matters involving high risk, conflicting objectives, different types of information and data, different concerns and points of view, and the representation of complex and evolving biological, ecological, and financial frameworks. It combines many methodologies and offers various advantages over more conventional ways of decision-making and plan development. It should be used to increase community participation and empower partner organizations and should apply several criteria at the same time, including those that are difficult to adjust and quantify. The key difficulty with this strategy is the usage of weightings, which has been sharply criticized by several researchers. Life-cycle assessment (LCA) is an adaptive tool used to assess the ecological effects of a particular action, task, or procedure. It is applied globally to decision-making in numerous fields, including transportation, energy, and water, and has become a typical tool for determining the ecological performance of infrastructure projects. However, it has a few flaws and could benefit from improvements to assess SD with greater precision. It is a fragmented mechanism for assessing the three components of SD, but its incorporation into other evaluation approaches is desirable. The evaluation of societal implications has been conducted using a variety of methods and techniques, but there is currently no standard method for assessing the communal and appropriation consequences of infrastructure initiatives. Social life-cycle assessments (SLCAs) are advancing, but consensus remains a challenge. The Evaluation Partnership and the Centre for European Policy Studies identified several obstacles and challenges to implementing an outstanding societal assessment, such as the term ‘societal impacts’ being potentially overbroad and not adequately defined, and the lack of a suitable method for quantitatively evaluating sociological effects. Additionally, a large section of societal assessments is biased and frequently inconsequential. The chapter discussed the theoretical and methodological stances on sustainable road infrastructure, using current SID concepts and evaluation techniques thoroughly.

Introduction: Decision making is always based on several factors which may affect the possible outcomes, especially in financial markets. Instead of having many criteria which may be required for decision making, “Multiple Criteria Decision Making” (MCDM) models might be used as a tool to reduce all criteria into a single one.

Purpose: The aim of this study is to measure the financial performance of commercial banks listed on Borsa Istanbul (BIST) by the MCDM.

Method: To this end, data from 15 different financial ratios from 11 commercial banks were used between the periods of 2002 and 2018. Both TOPSIS and gray relational analysis (GRA) models were used, which are commonly used in the literature for detecting the financial performance of listed banks in BIST based on their consolidated financial statements.

Results: According to the TOPSIS method, while the best bank is QNB Finansbank, HALKB, a public bank, was determined as the best bank using the GRA method. There is no significant correlation between financial performance indicators and market returns obtained by either method, with exceptions. There is no generally significant correlation detected between financial ratios and market returns. Accordingly, it is concluded that the bank stock prices in the study are shaped by the influence of external factors and expectations. The study results include information that can be used for different purposes among bank managers, academics and financial investors.

The chapter examines a comprehensive review of cross-disciplinary literature in the domain of supply chain forecasting during research period 1991–2017, with the primary aim of exploring the growth of literature from operational to demand centric forecasting and decision making in service supply chain systems. A noted list of 15,000 articles from journals and search results are used from academic databases (viz. Science Direct, Web of Sciences). Out of various content analysis techniques (Seuring & Gold, 2012), latent sementic analysis (LSA) is used as a content analysis tool (Wei, Yang, & Lin, 2008; Kundu et al., 2015). The reason for adoption of LSA over existing bibliometric techniques is to use the combination of text analysis and mining method to formulate latent factors. LSA creates the scientific grounding to understand the trends. Using LSA, Understanding future research trends will assist researchers in the area of service supply chain forecasting. The study will be beneficial for practitioners of the strategic and operational aspects of service supply chain decision making. The chapter incorporates four sections. The first section describes the introduction to service supply chain management and research development in this domain. The second section describes usage of LSA for current study. The third section describes the finding and results. The fourth and final sections conclude the chapter with a brief discussion on research findings, its limitations, and the implications for future research. The outcomes of analysis presented in this chapter also provide opportunities for researchers/professionals to position their future service supply chain research and/or implementation strategies.

This chapter aims to identify, analyse, classify and rank the sustainability indices and internationalisation challenges of the footwear industry in the emerging economy of Iran. This would provide deeper decision-making insights into Iranian footwear businesses. First, a list of sustainability indices and internationalisation challenges was obtained by reviewing the literature. Then, a combination of multi-criteria decision-making (MCDM) approaches was implemented. The initial sustainability indices and internationalisation challenges were screened using the fuzzy Delphi method, keeping a total of 14 criteria. The best–worst method (BWM) was employed to weigh and rank the criteria. The interpretive structural modelling (ISM) technique and cross-impact matrix applied in MICMAC were employed to visualise the conceptual model based on the levels and classification of the important criteria for the internationalisation of the Iranian footwear industry. The 14 criteria were demonstrated to be important in internationalisation. The most critical sustainability indices were reducing hazardous substances in leather tanning and labour education and training. In contrast, exchange rate instability in Iran’s economy and strict chemical regulations for clothing and footwear were found to be the most important internationalisation challenges. Hence, these criteria should be considered in the internationalisation strategies of the Iranian footwear industry. A combined multilayer sustainable decision-making approach was used to analyse the Iranian footwear industry’s essential sustainability indices and internationalisation challenges. Furthermore, implications and insights are offered to footwear businesses for future decision-making.

In this study, it is aimed to correctly weigh the criteria for the selection of qualified manager in a healthcare facility and to make the right selection among candidates with an objective method. In this study, in which the health manager selection was carried out with fuzzy Analytical Hierarchy Process (AHP) and MULTIMOORA methods, 8 candidates were evaluated according to 12 personnel selection criteria. Comparative matrices of qualified health manager selection criteria were presented to the expert opinion and analyzed with the fuzzy AHP method. According to the analysis result, among the 12 criteria; The “Crisis Management Skill” criterion is in the first place with 12.5% weight; The “Social Responsibility Awareness” criterion was found to be in the last place with 3.2% weight. The MULTIMOORA method was applied by analyzing the interview scores and criterion weightings of the candidates evaluated by the jury. According to the results of MULTIMOORA, Candidate 1 first place and Candidate 6 ranked last.

Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.

US Navy warships are capital-intensive national defense assets that require periodic depot and intermediate level maintenance availabilities (periods). Oftentimes, ship maintenance is deferred or forgone altogether due to geopolitical strife or fiscal challenges. The impacts of missed maintenance are not only a burden on ships’ crews, but they also have a deleterious effect on current and future readiness. It is a difficult task to strike a balance between current and future readiness when insufficient resources are available to sustain a fleet of warships. This paper draws from multi-attribute utility theory (MAUT) to develop a ship maintenance decision-making model that considers attributes from the current and life cycle readiness cohorts. Using the current maintenance plans for two DDG 51-class ships entering availabilities in same fiscal year, this model determines which ship is more capable of absorbing a loss of maintenance and planned modernizations relative to the context of the decision environment. Five attributes are considered for the overall decision: mandatory maintenance, non-mandatory maintenance, mission impact from maintenance, mission impact from planned modernizations, and maintenance backlog. The model presented here is generalizable to a number of U.S. Navy ships and watercraft and can be used to inform decision-makers of the short- and long-term impacts of deferring critical maintenance.