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The purpose of this paper is to utilise a “Wuli-Shili-Renli (WSR)” system approach to create models for complex smart building energy management and evaluate the establishment of a building energy management platform.

The complexity and diversity of the data and demands of the energy management platform mean that it is necessary to analyse comprehensively. This paper uses a WSR system approach to handle, and optimise, the relationship between demands and participants and improve the whole platform. Then, this paper establishes comprehensive evaluation models to analysis the current energy management platforms by using the best integration platform as the baseline.

The WSR conceptual model clarifies the relationship between the elements and elements of the energy management platform clearly and provides the appropriate analytical methods with which to resolve key platform construction issues. The comprehensive evaluation based on a WSR system approach can take into account the systematic effect, so it is more accurate.

The correlation degree between the layers of the energy management platform is rarely reflected.

This paper improves the modelling method used in the WSR system approach and demonstrates that the comprehensive evaluation based on the WSR system approach analyses the energy management platform for public buildings in a synthetic approach.

Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes. In recent marketplace, the number of robot manufacturers has increased remarkably offering a wide range of models and specifications; thus, robot selection has become indeed confusing as well as complicated task. Selection of an appropriate robot is a sensitive process; it may result massive letdown, if not chosen properly. Therefore, for unravel the selection problem; the purpose of this paper is to explore the preference ranking organization method for enrichment evaluation (PROMETHEE) II method.

Apart from a large variety of robotic systems, existence of various multi-criteria decision making (MCDM) tools and techniques may create confusion to the decision makers’ in regards of application feasibility as well as superiority in performance to work under different decision-making situations. In this context, the PROMETHEE II method has been found as an efficient decision-making tool which provides complete ranking order of all available alternatives prudently, thus avoiding errors in decision making.

In this context, the present paper highlights application potential of aforesaid PROMETHEE II method in relation to robot selection problem subjected to a set of quantitative (objective) evaluation data collected from the available literature resources. Advantages and disadvantages of PROMETHEE II method have also been reported in comparison to other existing MCDM approaches.

The study bears significant managerial implications. Proper evaluation and selection of appropriate candidate robot would be helpful for the industries in order to improve product quality as well as to increase productivity. Proper utilization of resources could be ensured. Functioning would be accurate with reduced timespan. As a consequence, company can increase its profit margin in long run.

This paper aims to discuss how to apply the evolutionary resilience theory in the housing sector, aiming to develop an alternative resilience framework for planning social housing programmes.

Based on the literature review, it was developed a theoretical framework for building evolutionary resilience. Based on this framework, the outline for the empirical research was specified through interviews with 21 multidisciplinary experts. The statements of these experts were examined through content analysis, as a means to assign a set of requirements for resilient buildings.

The analysis showed that the holistic framework based on evolutionary resilience could constitute a comprehensive and innovative resilience approach. The main contribution of the set of requirements was to adapt theoretical concepts by proposing operational surrogates, enabling such knowledge to be more applicable to devising resilience to the housing sector.

Resilience is establishing itself as one of the top agendas on the built environment. The construction sector, however, has yet to embrace the concept and little research has been conducted on a practical approach to assess the building’s resilience. This paper presents a list of practical requirements showing that the housing sector must to build differently to have a resilient future.

Different housing development stakeholders need to cooperate and collaborate to perform various project activities. Housing development requires infrastructure development, which includes preparation of sand material embankment as much as ± 200,000 m³. The objectives are to find a model for agreement options and coalition, to validate the algorithms of the best fit for material locations and to determine how much the proposed agreement option was achieved. This study provides a structured methodology that can lead to systematic support system and automated negotiation for decision-making on housing development process.

Agreement option on group decision techniques was applied to determine the relative value of the alternative solutions for performing the function of project solutions. Analytical hierarchy process based on satisficing option was applied for decision process and game theory-based agent system for coalition formation. It is conducted in two stages that determine the decision preference and decision process consisting of four steps. The steps are constructing decision hierarchy, making judgment and synthesis, determining payoff optimum and analyzing the best fit option for all decision-makers.

The proposed model enables each decision-maker to select individually its coalition. It will improve the value of strategic decision. All solutions are chosen by more than one decision-maker and coalitions, where all decision-makers agree with the result. It becomes possible location for the material of a housing development. A support model enables negotiation process in group decision. Decision algorithms are based on the cooperative game theory to develop the agreement options and coalition formation. Similar research studies were carried out in this area, but this research is – to the knowledge of the authors – the first to apply the satisficing of value-based on desirable and considerable.

The result is limited to the first-round negotiation of collaborative decision. A trade-off algorithm among decision-maker preference is needed for negotiation process. Future research is to continue working on multi-attribute decision-making, specifically on the process of eliciting user preference models such as neural network application and value function, and on establishing expert quantitative data from qualitative description of the feature of the alternative solution. It will need the development of trade-off algorithms to analyze value of technical solution in real time.

The support model can be extended to an automated negotiation and in different strategic decision on all stages of housing development.

The satisficing algorithm of the coalition will satisfy all stakeholders. This will reduce any potential conflict.

Combination of value-based decision, group decision and collaborative support. Application of coalition formation for agreement options is used to select the best fit material location. It is based on satisficing game theory rather than optimization.

The purpose of this paper is to depict the developmental process of a buildability assessment model for use at the scheme design stage of building projects, which have a priority requirement for functional performance rather than aesthetic performance.

First, major decisions made at the scheme design stage of building projects were identified through pilot interviews and a questionnaire survey on designers. Second, these decisions were rated for their relative importance towards buildability through another questionnaire survey on contractors, analysed using the reliability interval method. Based on these results, a list of buildable and non‐buildable features and their impacts is compiled by interviewing major contractors. These findings were incorporated into a modified framework of buildability assessment for complete design, substituting information available at the scheme design stage. Validation was carried out using four sample projects and feedback from practitioners.

The results obtained from the Scheme Design Buildability Assessment Model have been demonstrated as reflective of actual buildability level. Buildable and non‐buildable features, as exemplified by typical building projects in Hong Kong Special Administrative Region, have been identified.

This is the first model which provides a tool for use by the design team to evaluate the buildability of their designs at an early stage, so that necessary improvements can be made without affecting the development program.

Integrates perspectives across operations, marketing, human resources, and organizational theory in a conceptualization of the theoretical relationships between customer competency and marketing and operations practices in service firms. Suggests service firm strategies to leverage customer competency by managing process variation in an industry through service firm co‐operation when altering process structure does not support or achieve a differentiated market position for individual firms; by using market segmentation on the basis of customer productcore competency to develop new service offerings; by balancing the mix of customers at different competency levels with the firm’s productive capacity; and by optimizing socialization of four types of new customers: “Virgin Newcomers”, “Virtual Newcomers”, “Value Switchers” and “Vagabond Switchers” who have different levels of experience with competing firms and expectations for competency fit with new firms.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

Recent changes in climate, rainfall patterns, snow melt and rising sea levels coupled with an increase in urban development have increased the threat of flooding. To curb these threats and mitigate these damages, property-level approaches to improving resilience are now being encouraged as part of an integrated approach to flood risk management. This raises questions such as, what are the flood resilient attributes within individual properties, what is their importance and how can these be quantified. This research sought to develop a quantitative approach for the measurement of property-level flood resilience.

A synthesis of literature was undertaken to establish the main resilient attributes and their relevant sub-attributes. This process led to the development of a new method, named the Composite Flood Resilient Index (CFRI) to weight the attributes and sub-attributes of flood resilience based on their importance. The approach adopts the use of the fuzzy-analytic hierarchy process (F-AHP) approach to quantify flood resilience.

The implications of the proposed methodology in determining the flood resilience of individual property, including the potential use in retrofitting activities, and the benefits to a range of stakeholders are considered.

The methodology offers the potential to support the measurement of flood resilience of individual properties, allowing the identification and prioritisation of specific interventions to improve the resilience of a property.

Whereas previous attempts to quantify flood resilience have adopted qualitative approaches with some level of subjectivity, this proposed methodology represents an important advancement in developing a scientific and quantitative approach.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

Taiwan experiences frequent seismic activity. Major earthquakes in recent history have seriously damaged the school buildings. School buildings in Taiwan are intended to serve both as places of education and as temporary shelters in the aftermath of major earthquakes. Therefore, the seismic performance assessments of school buildings are critical issues that deserve investigation.

This paper develops a methodology that uses principal component analysis to generalize the seismic factors from the basic seismic parameters of school buildings, uses data mining to cluster different school building sizes and uses grey theory to analyze the relationship between seismic factors and the seismic performance of school buildings. Additionally, this paper employs the Artificial Neural Network (ANN) to deduce the seismic assessment model for school buildings. Finally, it adopts support vector machine to validate the ANN’s deductive results.

An empirical study was conducted on 326 school buildings in the central area of Taichung City, Taiwan, to illustrate the effectiveness of the proposed approach. Results show that thickness of wall and width of middle-row column relate significantly with school-building seismic performance.

This paper provides a model that structural engineers or architects may use to design school buildings that are adequately resistant to earthquakes as well as a reference for future academic research.