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Emergency situations may differ in many ways but they share some common characteristics, such as the sudden onset and the need to transparently evaluate various usually conflicting objectives. In nuclear power generation, however, emergency situations constitute a special challenge. The focus of this paper is to highlight the role of multi‐criteria decision analysis (MCDA) in nuclear emergency and recovery management on the basis of a hypothetical case study.

Multi‐attribute value theory as one field of research within MCDA is introduced. Special emphasis is placed on the modelling of the decision makers' preferences which is a crucial part in any multi‐criteria analysis. A central aim is to facilitate the preference elicitation in group decision processes.

The management of emergency situations in nuclear power generation necessitates the consideration of technical, economic, environmental, socio‐psychological and political aspects. Furthermore, various stakeholder and expert groups with diverse background knowledge and different views, responsibilities and interests are involved in such a decision‐making process. MCDA can help to take into account various incommensurable aspects and the subjective preferences of the decision makers and thus contribute to transparency and traceability of decision‐making processes. Since the preference parameters are inherently afflicted with uncertainties, thorough sensitivity analyses are important to visualise the impact of the uncertainties in an understandable way.

A new approach to sensitivity analysis is proposed, allowing one to comprehensibly visualise and communicate the impact of the uncertainties associated with the subjective preference parameters on the results of the decision analysis.

Over the last three decades, construction projects have increasingly been delivered through alternative delivery methods. As a result, many owners have a range of delivery methods to choose from and aim to use the right one for each of their projects. Researchers have developed several tools and decision-support processes to facilitate this selection procedure. The purpose of this study is to review and discuss differences and common themes across selection tools developed by academic researchers and project owners.

The study reviews prominent selection processes and tools used for infrastructure projects by conducting an in-depth literature review and using the content analysis method to elicit findings on the methodologies and criteria presented in the literature.

This study presents three principal findings. First, findings show three common themes emerge within the selection criteria—characteristics, goals and risks. Second, while academic studies most commonly suggest employing multi-attribute analysis, this study reveals that, in practice, selection tools most frequently employ a staged or gated evaluation based on the type of criteria and their importance to the decision. Finally, this review further highlights the importance of institutional context in decision-making.

This work contributes to the body of knowledge by providing guidance to practitioners and opening new directions for researchers around the way selection criteria are categorized in the relevant literature and the institutional context considerations when structuring or evaluating a selection process or tool.

Suggests that many quantitative methods have been developed in an attempt to acknowledge uncertainty in decision making and to manage the inherent risk during economic planning for new technology implementation. Outlines a relatively simple and practical risk analysis, accompanied by the implementation of advanced manufacturing technology. Employs the proven analytical hierarchy process (AHP) approach, coupled with confidence intervals from data gathered through simulation techniques or through observations and empirical sampling. Describes a case study in which simulation models were developed using a software package SIMFACTORY II.5, which is based on the concept of visual interactive simulation. A number of simulation experiments were performed in order to investigate the influence of various flexible manufacturing system and cellular manufacturing system configurations. An AHP multi‐attribute analysis is performed by using AUTOMAN, a decision support software package. This package evaluates and combines the qualitative and quantitative factors for different configuration designs.

It is crucial to consider the multitude of possible building adaptation design strategies for improving the existing conditions of building stock as an alternative to demolition.

Integration of physics-based simulation tools and decision-making tools such as Multi-Attribute Utility (MAU) and Interactive Multi-objective Optimization (IMO) in the design process enable optimized design decision-making for high-performing buildings. A methodology is presented for improving building adaptation design decision making, specifically in the early-stage design feasibility analysis. Ten residential building adaptation strategies are selected and applied to one primary building system for eight performance metrics using physics-based simulation tools. These measures include energy use, thermal comfort, daylighting, natural ventilation, systems performance, life cycle, cost-benefit and constructability. The results are processed using MAU and IMO analysis and are validated through sensitivity analysis by testing one design strategy on three building systems.

Quantifiable comparison of building adaptation strategies based on multiple metrics derived from physics-based simulations can assist in the evaluation of overall environmental performance and economic feasibility for building adaptation projects.

The current methodology presented is limited to the analysis of one decision-maker at a time. It can be improved to include multiple decision-makers and capture varying perspectives to reflect common practices in the industry.

The methodology presented supports affordable generation and analysis of a large number of design options for early-stage design optimization.

Given the practical implications, more space and time is created for exploration and innovation, resulting in potential for improved benefits.

Recent literature has proposed many theoretical methods to help decision makers choose an appropriate project delivery system (PDS) in a rational manner. None of these articles however systematically compare and systematize the available PDS selection methods and guide decision makers in choosing a method that best meets their PDS decision‐making circumstances. This paper aims to bridge this gap.

Four groups of PDS selection methods, namely, guidance (e.g. decision charts and guidelines), multi‐attribute analysis (e.g. multi‐attribute utility theory and analytical hierarchical process), knowledge‐ and experience‐based (e.g. case‐based reasoning), and mix‐method approaches are reviewed, compared and systematized.

The discussed methods vary in their underlying concepts, complexities of implementation and levels of required information. They also differ in the ways how decision makers' preferences are elucidated, expressed and measured. A conceptual framework is proposed to help decision makers match a PDS selection method with their decision‐making circumstances.

The paper highlights limitations of the discussed methods, and presents areas for future research.

This paper helps decision makers develop a fundamental understanding of the available PDS selection methods, and match a PDS selection method with their unique decision‐making circumstances. Using a suitable method will improve the decision‐making efficiency.

Despite persistent levels of participation in cycling, little research has been undertaken in the context of competitive cycling event management and marketing. This study explored participant preferences using conjoint measurement and plausible market segmentations. Results of the survey conducted at three southeastern US cycling events (N=199) suggest that travel distance has primacy across nearly all segment groups and differences in recreational specialisation in cycling are reflected among other preferred event attributes.

While there is an established body of literature that discusses the importance of stakeholder management, and also the need for involvement of all stakeholders so that all values of a heritage site can be captured in a heritage management plan, the concepts are not generally developed in ways that make them useful in practice. This research seeks to bring greater clarity to the practice of stakeholder engagement in built heritage, so that organisations can manage their stakeholders in ways that meet their strategic goals. This study proposes a novel method to identify stakeholders, a stakeholder preference mapping approach, which will depict their influence on decisions based on a of power-interest scale.

This research posits a stakeholder preference mapping approach. Virtual Stakeholder Groups (VSG) were identified and stakeholder's significance impacts were measured using the RIBA Plan of Work 2013 to determine in-depth consideration of each stakeholder's power and interest against differing stages of a heritage project. Participants were convened through a 5-day workshop, consisting of 20 Malaysian and 19 international participants (80% academics and 20% Malaysian civil servants). The Multi-Attribute Decision Analysis (MADA) technique was then used to demonstrate how stakeholder identification and analysis can be used to help heritage teams meet their mandates.

The research identified eight virtual VSG (Extremist, Expert, Economic, Social, Governance and Tourists) and their scale of power-interest influence at different stages of the heritage management process. The findings reveal varying levels of engagement from each of the different groups of stakeholders at each work stage – with Stage 5 (Construction) being the least engaged.

It is anticipated that through stakeholder preference mapping, heritage teams can increase the robustness of their strategies by identifying and effectively managing the important concepts; heritage teams can effectively manage the interface between the many (often competing) demands of differing stakeholders. Using Georgetown as a case study, the research team were able to delineate the interaction and interplay between the various stakeholders in the complex decision-making processes for a UNESCO heritage site. Applying the RIBA 2013 Plan of Work as a framework to the heritage management process enables a formalised mapping approach to the process.

This study aims to answer the ‘what’ and ‘how’ questions about the key role players’ influence on the overall productivity outcomes in the lifecycle of residential buildings procured through the traditional route.

A mix of exploratory and descriptive research methods was used to obtain feedback from 179 role-players involved in various phases of the residential building lifecycle (RBLC) in New Zealand. Empirical data were analysed using content analysis, multi-attribute method and Friedman’s two-way analysis of variance.

Results showed that designers, building owners, main contractors and project managers were the greatest influencers of the productivity outcomes in the RBLC. The priority drivers of these key role-players’ influences on the RBLC productivity outcomes comprised poor brief interpretation, inclination to lowest tender, inadequate prior risk analysis and miscommunication of owner’s requirements and preferences to service providers, respectively. By taking proactive steps to redress their productivity inhibiting acts/omissions as identified in this study, the various role-players could contribute to significant improvement of productivity outcomes in the building lifecycle.

It was not possible to interview all participants that made up the representative random samples from each role-player group due largely to workload related excuses. As a result, the findings and the conclusions may not be generalised beyond the study scope. However, the study achieved its purpose, as the main intent was to provide hypothetical constructs that could guide further confirmatory/experimental studies for residential buildings as well as for other building types.

A succinct and easy-to-follow model was developed as implementation pathway for operationalising the key findings of the study in the industry. The model highlights the Owner-Architect-Contractor Influence Triangle (OACIT) as the 20 per cent of the solutions that could deliver 80 per cent of the productivity improvement in the RBLC.

This study re-examines productivity issues not only from a life-cycle perspective but also from the perspectives of the majority of the key role-players. In addition, the OACIT concept offers a novel productivity improvement tool; it stresses that productivity in the traditionally procured building lifecycle could be optimised if the architect could focus greater attention on brief articulation and the issuance and review of design and specification information. Also, the owner should adopt productivity-enhancing procurement and contract strategies and emphasise more on value-addition and less on lowest tender price.

The work described in this paper aims to reflect the natural evolution of longstanding dialogue between the Association of Research Libraries (ARL), Johns Hopkins University (JHU), and Bielefeld University.

This study looks at how each institution has combined library and assessment expertise and developed evaluation methodologies that emphasize different, but interrelated aspects of library services.

The resulting tools may be viewed as an integrated decision support system (DSS) that can offer librarians and library administrators a comprehensive framework for choosing appropriate tools, methodologies, and resources for evaluation of both existing and future library services.

This paper provides an excellent introduction and overview for practitioners new to the topics described.

The purpose of this paper is to define an evaluation model for cloud services to deal with the fuzzy information and propose a novel fuzzy evaluation method based on consistency intensity to analyze the quantitative value from the fuzzy information.

The cloud service evaluation framework is constructed, and different trusted indicators for the infrastructure services and the application services are designed, respectively. In the novel fuzzy evaluation method, the interval values can be aggregated by the Dempster-Shafer Theory and be transformed into the certain value by linguistic discount factor. The consistency intensity is proposed to determine the value of the linguistic discount factor, which can reflect the mainstream opinions in the assessment.

The proposed method can solve the problem on the analysis and synthesis of the fuzzy evaluation information. An instance of trust evaluation of cloud storage service is illustrated to verify that the proposed method can express the opinions of all evaluators more adequately.

A serial of experiments are carried out on NetLogo, and the results show that the proposed method is practical and efficient.

Instead of obtaining only the qualitative results by the multi-attribute decision-making method, the fuzzy evaluation method based on consistency intensity can obtain the quantitative results from the fuzzy information according to linguistic discount factor and consistency intensity.