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This paper aims to define an extended QoS model to accurately describe the quality of web service in the open distributed environment and propose a fuzzy evaluation approach for services selection based on the extended QoS model.

The extended QoS model classifies the quality criteria of web service as five composite quality criteria, and each composite quality criterion is composed by one or more sub‐quality criteria. Considering the multiple forms of representation for the quality criteria and different types of quality value could not be compared directly, a scaling fuzzy measure for quality criteria is introduced. Based on the scaling fuzzy measure of the quality criteria, a fuzzy synthetic evaluation system for services selection is proposed.

The quality of web service has multiple facets and multiple forms of representation. The fuzzy synthetic evaluation system can deal well with the fuzzy and implicit concepts about quality evaluations and provides higher expressive force and adaptability.

The quality of service in this paper is static preset.

The extended QoS model and the synthetic fuzzy evaluation system cover the shortage of the related researches and lay the foundations for QoS‐oriented service description and services selection.

The purpose of this paper is to present a new technique for the determination of effective criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation.

The weight values express the relative importance of criteria. In most of research works, weight values depend heavily on expert knowledge, and customer’s perspective have not been considered. The proposed approach determines the criteria weight on satisfaction using genetic algorithm and fuzzy synthetic evaluation considering Euclidean distance between the computed overall satisfaction evaluation and the surveyed overall satisfaction evaluation.

The research findings show that different segments of customer have various needs and explain causes of various needs in customers using genetic algorithm and fuzzy synthetic evaluation.

The value of the paper is in it using a new approach in order to determine the weight of criteria. The main advantage of proposed approach is that it will help managers and researchers to determine the weight of criteria on satisfaction, and this process will no longer just rely on expert knowledge.

The strategic location of city logistics facilities may help to establish more efficient urban logistics systems, reduce social and environmental costs of urban freight transport, and improve urban traffic conditions. In addition, it may allow a number of shippers or freight carriers to jointly operate freight vehicles and terminals or information systems while allowing them to have the capability to provide higher levels of services to their customers. This paper considers the problem of selecting a location for a city logistics facility while considering linguistic factors. This paper identifies the important factors in the selection of a location for a city logistics facility by performing a case study which applies the analytic hierarchy process method on data from Chongqing, China. The optimal location in Chongqing is then determined by using the fuzzy synthetic evaluation method. The results of this paper are expected to help municipal governments select appropriate locations for city logistics facilities and quantify the advantages and disadvantages of alternative locations.

This paper aims to develop a fuzzy risk assessment model for construction projects procured with target cost contracts and guaranteed maximum price contracts (TCC/GMP) using the fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in South Australia.

A total of 34 major risk factors inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such risk factors.

The most important 14 key risk factors after the computation of normalised values were selected for undertaking fuzzy evaluation analysis. Five key risk groups (KRGs) were then generated in descending order of importance as: physical risks, lack of experience of contracting parties throughout TCC/GMP procurement process, design risks, contractual risks and delayed payment on contracts. These survey findings also revealed that physical risks may be the major hurdle to the success of TCC/GMP projects in South Australia.

Although the fuzzy risk assessment model was developed for those new-build construction projects procured by TCC/GMP contracts in this paper, the same research methodology may be applied to other contracts within the wide spectrum of facilities management or building maintenance services under the target cost-based model. Therefore, the contribution from this paper could be extended to the discipline of facilities management as well.

An overall risk index associated with TCC/GMP construction projects and the risk indices of individual KRGs can be generated from the model for reference. An objective and a holistic assessment can be achieved. The model has provided a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgements. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons, and the assessment of risk levels for different types of TCC/GMP projects (including new-build or maintenance) worldwide.

Allocating risk in public–private partnership (PPP) projects based on public–private parties’ risk management (RM) capabilities is a condition for success of these projects. In practice, however, risks are allocated to these parties beyond their respective RM capabilities. Too much risk is often assigned to the private or public party, resulting in poor RM and costly contract renegotiations and terminations. This chapter proposes a methodology based on fuzzy set theory (FST) in which decision makers (DMs) use linguistic variables to assess and calculate RM capability values of public–private parties for risk events and to arrive at risk allocation (RA) decisions. The proposed methodology is based on integrating RA decision criteria, the Delphi method and the fuzzy synthetic evaluation (FSE) technique. The application of FSE allows for the introduction of linguistic variables that express DMs’ evaluations of RM capabilities. This provides a means to deal with the problems of qualitative, multi-criteria analysis, subjectivity and uncertainty that characterise decision-making in the construction domain. The methodology is outlined and demonstrated based on empirical data collected through a three-round Delphi survey. The public–private parties’ RM capability values for land acquisition risk are calculated using the proposed methodology. The methodology is helpful for performing fuzzy-based analysis in PPP projects, even in the event of limited or no data. This chapter makes the contribution of presenting a RA decision-making methodology that is easy to understand and use in PPP contracting and that enables DMs to track calculations of RM capability values.

This paper aims to evaluate the risk factors and determines the overall risk level (ORL) of public-private-partnership (PPP) power projects in Ghana using fuzzy synthetic evaluation methodology (FSEM).

In this paper review of literature led to the development of a 67-factor risk list which was ranked by experts and industry practitioners through a questionnaire survey.

These factors were grouped into principal risk factors (PRFs) using component analysis and they served as the input variables for fuzzy analysis. The seven components were: Contract and Payment risks, Environmental risks, Financial and Cost risks, Legal and Guarantee risks, Operation risks, Socio-Political and Performance risks (SPR) and Tender and Negotiation risks. Study showed that the ORL of Ghanaian PPP power projects is high implying they are risky to both the public and private sectors. Fuzzy analysis also confirmed SPR as the most critical principal factor.

This study is significant and demonstrates that fuzzy methodology can be used as a useful risk evaluation tool and risk assessment framework for private investors, policy makers and public sector.

This study presents a fuzzy synthetic evaluation of the challenges of smart city realisation in developing countries, using Nigeria as a case study. By defining and delineating the problems faced by the country, more viable directions to attaining smart city development can be achieved.

The study adopted a post-positivist philosophical stance with a deductive approach. A structured questionnaire was used to gather data from built environment professionals involved in the delivery of Nigerian public infrastructures. Six dimensions of the challenges of smart cities were identified from literature and explored. They are governance, economic, social, technological, environmental and legal issues. Data gathered were analysed using Cronbach alpha test for reliability, Shapiro-Wilks test for normality, Kruskal-Wallis H-test for consistency and fuzzy synthetic evaluation test for the synthetic evaluation of the challenges of smart city attainment.

The findings revealed that all six assessed dimensions have a significant impact on the attainment of smart cities in Nigeria. More specifically, issues relating to environmental, technological, social and legal challenges are more prominent.

The fuzzy synthetic approach adopted provides a clear, practical insight on the issues that need to be addressed before the smart city development can be attained within developing countries.

The purpose of this paper is to develop a fuzzy risk assessment model for construction projects procured with target cost contracts (TCC) and guaranteed maximum price (GMP) contracts using factor analysis (FA) and fuzzy synthetic evaluation method, based on an empirical questionnaire survey with relevant industrial practitioners in Hong Kong.

A total of 34 key risk factors (RFs) inherent with TCC/GMP contracts were identified through an extensive literature review and a series of structured interviews. A questionnaire survey was then launched to solicit the opinions of industrial practitioners on risk assessment of such RFs.

The most important 17 principal RFs after the calculation of normalised values were selected for undertaking FA. Five principal risk groups (PRGs) were then generated in descending order of importance as: design risks, pre‐contract risks, economic and financial risks, lack of experience in TCC/GMP procurement process and post‐contract risks. These survey findings also reveal that design risks may be the major hurdle to the success of TCC/GMP projects in Hong Kong.

An overall risk index (ORI) associated with TCC/GMP construction projects and the risk indices of individual PRGs can be generated from the model for reference. An objective and reliable assessment can be achieved. The model provides a solid platform to measure, evaluate and reduce the risk levels of TCC/GMP projects based on objective evidence instead of subjective judgments. The research methodology could be replicated in other countries or regions to produce similar models for international comparisons and the assessment of risk levels for different types of TCC/GMP projects worldwide.

Demands for Industrialized Construction (IC) have intensified with growing construction industry imperatives to (A) boost performance; (B) reduce reliance on “in-situ and on-site” operations; and (C) strengthen supply chain resilience (SCR) not just for survival but also to fulfill obligations to clients in the coronavirus disease 2019–induced (COVID-19–induced) “new normal”. In addressing these imperatives, this paper targets more effective leveraging of latent efficiencies of off-site-manufacture, based on findings from a Hong Kong (HK)–based study on assessing and improving SCR in IC in a high-density city.

Starting with the identification of critical supply chain vulnerabilities (CSCVs), this study developed a multilevel–multicriteria mathematical model to evaluate the vulnerability levels of IC supply chains (SCs) in HK based on an in-depth questionnaire survey followed by experts' inputs and analyzing them using fuzzy synthetic evaluation (FSE).

The overall vulnerability index indicates that IC in HK is substantially vulnerable to disruptions, while production-based vulnerabilities have the highest impact. Top management attention is needed to address these CSCVs in IC in HK.

To the authors' knowledge, this is the first structured evaluation model that measures the vulnerability level of IC, providing useful insights to industry stakeholders for well-informed decision-making in achieving resilient, sustainable and performance-enhanced SCs.

Unresolved construction dispute can be detrimental to project success. A systematic method to evaluate the seriousness of construction dispute of a construction project will assist management to take appropriate corrective actions. Evaluation of construction disputes requires an analysis on both the likelihood of occurrence and its impact, which are normally expressed by practitioners in linguistic terms. The application of classical discrete analysis will not be able to accommodate the fuzzy nature of this information. To determine how fuzzy sets theory can be applied to construction disputes evaluation (CDE), a fuzzy CDE model has been developed based on the knowledge extracted from practitioners in Hong Kong. The fuzzy CDE system consists of four components: dispute identification, dispute analysis; dispute evaluation; and dispute control. This paper describes the framework and operation of the fuzzy CDE system developed. The results indicate that CDE can be modelled by the fuzzy sets theory.