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This research’s main objective is to develop an expert-based approach to rank critical asset assessment factors for health-care facilities. This approach will improve the asset management of health-care buildings. This paper aims to study and prioritize the relative importance of asset criticality factors.

The research methodology begins with a comprehensive literature review of state-of-the-art health-care facilities management, asset management tools, critical asset assessment and approaches to model techniques. Then, using the expert-based opinion and the collected data through the analytical hierarchy process approach to developing the asset assessment model contains physical, environmental, general safety and revenue loss assessment models.

Results showed that the general safety factors and the sub-factors of life safety and physical safety contributed to asset condition assessment.

The proposed critical asset assessment ranking will benefit health-care facility organizations by assessing their asset performance according to capital renewal needs.

This study offers a novel conceptual framework to understand and determine rank critical asset assessment factors for health-care facilities.

The phenomenon of traffic crash under-reporting has been extensively documented in terms of its extent, but not equally analysed in terms of its reasons. As police distrust has been recently identified as a major reason for crash under-reporting, the purpose of this paper is to look at the police service quality for handling the reporting of traffic crashes.

This study introduces a novel approach to evaluate service quality that combines multi-criteria decision analysis (MCDA) with latent class analysis (LCA). Moreover, this study presents the design of a web-based survey on the basis of the SERVQUAL approach to detecting strengths, opportunities and threats with crash reporting to the police at a strategic level. Transportation stakeholders (e.g. researchers, authorities, consultants, NGO representatives, suppliers) with an interest in traffic safety in Denmark participated in the survey that yielded 86 complete responses.

The novel approach was successfully applied and its implementation demonstrated the usefulness of the tool even in countries with a high police service. Results showed that the participating stakeholders perceived human factors as more important than physical factors in order to increase the crash reporting, with responsiveness as the most important and tangibles as the least important dimensions. Nevertheless, most stakeholders viewed a mixture of human and physical factors as crucial to increase crash reporting rates.

This study advances the knowledge about police service quality with a novel expert-based decision support tool based on SERVQUAL, MCDA and LCA, demonstrates its applicability in countries with a high-police service, and opportunities and barriers for increasing the crash reporting rate.

The paper is aimed at identifying, analysing and prioritizing the critical constraints affecting efficient management of historic buildings in remote areas of Saudi Arabia.

Thematic content analysis and expert-based evaluation approaches were used to identify and evaluate the constraints. The DEMATEL technique was deployed to define the interrelationship complexities between the constraints and evaluate the impact of these interrelationships to ascertain the influential constraints.

The results identify “lack of clearly defined roles for the multiple government agencies” as the most influential constraint for managing historic sites and buildings in remote areas of Saudi Arabia.

The contextual interrelationship between the constraints is due to the experts' perceptions, which may be biased due to their proficiencies and professional backgrounds. Since the evidence on which the findings of this paper are established is predominantly from experiences related to historic sites and buildings in remote areas of Saudi Arabia, the results of this paper may not be entirely applicable elsewhere.

The paper provides invaluable methodology that can support practitioners and policymakers to establish sustainable strategies that can enhance the management and protection of historic buildings in remote areas of Saudi Arabia.

This study noticeably contributes to knowledge by providing comprehensive understanding of the major impediments to the successful management of historic buildings in remote areas of Saudi Arabia, which can assist in mitigating the potential impacts of these constraints and to advocate for the achievement of efficient management and protection of the historic sites and buildings.

The purpose of this paper is to present and discuss the methodological approach and the results of the investigation of greenhouse gas emission abatement costs in Upper Austria.

The assessment covers the quantification of marginal abatement costs (MACs) of greenhouse gas (GHG) emissions and the emission reduction potentials of various energy efficiency and fuel switch measures with a special emphasis on the heat, electricity and transport sectors in Upper Austria during the period from 2010 to 2030.

The expert‐based assessment in Upper Austria shows negative abatement costs for 19 of 56 evaluated strategies. While these measures are very efficient from an economic point of view, the remaining 37 measures are associated with higher costs. The evaluation reveals a significant reduction potential of 5.2 million tons CO₂e (which represent 21 per cent) of the current GHG emissions in Upper Austria for the examined period.

MACs are generally limited to a certain time frame. Furthermore, the expert‐based approach is based on several assumptions and neglects behavioural and learning aspects.

This contribution uses a multi‐criteria approach that reveals the economic efficiency and the ecological effectiveness of the considered strategies/technologies with regard to greenhouse gas emission reductions, the improvement of the overall energy efficiency, and the competitiveness of a fuel switch towards renewable energy sources. Drawing upon the findings of this study, policy recommendations can be elaborated and the necessary improvements of the regulative framework can be implemented.

The paper focuses on the question of the extent to which individual preference-based values are suitable in guiding environmental policy and damage assessment decisions. Three criteria for “suitableness” are reviewed: conceptual, moral and legal. Their discussion suggests that: (i) the concept of economic value as applied to environmental resources is a meaningful concept based on the notion of trade-off; (ii) the limitations of the moral foundations of cost-benefit analysis do not invalidate its use as a procedure for guiding environmental decision making; (iii) the input of individual preferences into damage assessment is compatible with the basic foundations of tort law; (iv) using individual preference-based methods provides incentives for efficient levels of due care; (v) determining standing is still very contentious for various categories of users as well as for aggregating non-use values. Overall, the discussion suggests that the use of preference-based approaches in both the policy and legal arenas is warranted provided that they are accurately applied, their limitations are openly acknowledged and they assume an information-providing rather than a determinative role.

The aim of this paper is to develop a methodology of computer‐assisted roadmapping to supplement an expert‐based approach, which is time‐consuming and subjective.

A computer‐based approach using citation network analysis is used to depict technology trends, and build the first draft of science and technology roadmaps. A case study in energy research is performed, and emerging research domains are tracked in it by citation network analysis.

The analysis confirms that the fuel cell and solar cell are rapidly growing domains in energy research. The detailed research structures were investigated further by clustering. Each citation cluster has characteristic research topics, and there is a variety of growth trends among the clusters.

Constructing a corpus to analyze is not an easy task and one that affects the results, and therefore further research to evaluate the adequacy and validity of the corpus before citation network analysis is necessary. Including patents and analyzing relationships between academic papers and patents for roadmapping is a challenging future research topic.

While science and technology roadmaps are an attractive tool in R&D management and have been widely used, they are typically constructed by gathering and stimulating expert opinion and therefore highly time‐consuming. As demonstrated in this paper, a computer‐based approach using citation network analysis is a powerful tool to support roadmapping. By using the approach, planners and R&D managers can make decisions on effective investment in promising and emerging technologies, especially under circumstances of limited resources with the broader coverage of scientific and technological research.

By using citation network analysis, we can track emerging research domains among a range of publications efficiently and effectively.

The purpose of this paper is to introduce and conceptualize the topic of Cognitive Centres. It emphasizes the importance of complexity management and cognitive technologies in management practice.

It elaborates the relevance of different types of models for management: Stafford Beer's operations room, viable system model, subject‐object and subject‐subject management models, expert‐based mathematical modelling and computational experiment, organizational‐activity games theory and cybernetic (Viplan) methodology.

The paper suggests models and approaches for strategic management. It shows the inadequacy of a subject‐object management model for industrial or regional governance. It integrates a communicative management approach, complexity management methods, the USSR's Gosplan experience of long‐term planning, the Keldysh Institute of Applied Mathematics experience of modelling extremely complex systems and modern cognitive and information technologies into the concept of a Cognitive Centre.

Cognitive Centres can enhance the adaptation and viability of a large network of small organizations: public enterprises, business and not‐for‐profit regional industries. The paper describes two cases of practical implementation.

The paper contributes to research on management models that integrates cybernetics, cognitive technologies and computational experiments.

Construction is a highly dynamic environment with numerous interacting factors that affect construction processes and decisions. Uncertainty is inherent in most aspects of construction engineering and management, and traditionally, it has been treated as a random phenomenon. However, there are many types of uncertainty that are not naturally modelled by probability theory, such as subjectivity, ambiguity and vagueness. Fuzzy logic provides an approach for handling such uncertainties. However, fuzzy logic alone has some limitations, including its inability to learn from data and its extensive reliance on expert knowledge. To address these limitations, fuzzy logic has been combined with other techniques to create fuzzy hybrid techniques, which have helped solve complex problems in construction. In this chapter, a background on fuzzy logic in the context of construction engineering and management applications is presented. The chapter provides an introduction to uncertainty in construction and illustrates how fuzzy logic can improve construction modelling and decision-making. The role of fuzzy logic in representing uncertainty is contrasted with that of probability theory. Introductory material is presented on key definitions, properties and methods of fuzzy logic, including the definition and representation of fuzzy sets and membership functions, basic operations on fuzzy sets, fuzzy relations and compositions, defuzzification methods, entropy for fuzzy sets, fuzzy numbers, methods for the specification of membership functions and fuzzy rule-based systems. Finally, a discussion on the need for fuzzy hybrid modelling in construction applications is presented, and future research directions are proposed.

The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint.

A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint.

The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior.

The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation.

Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective.

Several different simulation techniques, such as discrete event simulation (DES), system dynamics (SD) and agent-based modelling (ABM), have been used to model complex construction systems such as construction processes and project management practices; however, these techniques do not take into account the subjective uncertainties that exist in many construction systems. Integrating fuzzy logic with simulation techniques enhances the capabilities of those simulation techniques, and the resultant fuzzy simulation models are then capable of handling subjective uncertainties in complex construction systems. The objectives of this chapter are to show how to integrate fuzzy logic and simulation techniques in construction modelling and to provide methodologies for the development of fuzzy simulation models in construction. In this chapter, an overview of simulation techniques that are used in construction is presented. Next, the advancements that have been made by integrating fuzzy logic and simulation techniques are introduced. Methodologies for developing fuzzy simulation models are then proposed. Finally, the process of selecting a suitable simulation technique for each particular aspect of construction modelling is discussed.