A system's model for maintenance support and decision making in building services systems

Modern buildings are designed to enhance the match between environment, spaces and the people carrying out work, so that the well-being and the performance of the occupants are all in harmony. Building services are systems that facilitate a healthy working environment within which workers productivity can be optimised in the buildings. However, the maintenance of these services is fraught with problems that may contribute to up to 50% of the total life cycle cost of the building. Maintenance support is one area which is not usually designed into the system as this is not common practice in the services industry. The other areas of shortfall for future designs are; client requirements, commissioning, facilities management data and post occupancy evaluation feedback which needs to be adequately planned to capture and document this information for use in future designs. At the University of Reading an integrated approach has been developed to assemble the multitude of aspects inherent in this field. The means records required and measured achievements for the benefit of both building owners and practitioners. This integrated approach can be represented in a Through Life Business Model (TLBM) format using the concept of Integrated Logistic Support (ILS). The prototype TLBM developed utilises the tailored tools and techniques of ILS for building services. This TLBM approach will facilitate the successful development of a databank that would be invaluable in capturing essential data (e.g. reliability of components) for enhancing future building services designs, life cycle costing and decision making by practitioners, in particular facilities managers.

Integrated clinical pathway management for medical quality improvement-based on a semiotically inspired systems architecture

Clinical pathway is an approach to standardise care processes to support the implementations of clinical guidelines and protocols. It is designed to support the management of treatment processes including clinical and non-clinical activities, resources and also financial aspects. It provides detailed guidance for each stage in the management of a patient with the aim of improving the continuity and coordination of care across different disciplines and sectors. However, in the practical treatment process, the lack of knowledge sharing and information accuracy of paper-based clinical pathways burden health-care staff with a large amount of paper work. This will often result in medical errors, inefficient treatment process and thus poor quality medical services. This paper first presents a theoretical underpinning and a co-design research methodology for integrated pathway management by drawing input from organisational semiotics. An approach to integrated clinical pathway management is then proposed, which aims to embed pathway knowledge into treatment processes and existing hospital information systems. The capability of this approach has been demonstrated through the case study in one of the largest hospitals in China. The outcome reveals that medical quality can be improved significantly by the classified clinical pathway knowledge and seamless integration with hospital information systems.

Accounting information systems as institutional carriers: a case study of regulatory compliance in UK asset management houses

Previously, governments have responded to the impacts of economic failures and consequently have developed more regulations to protect employees, customers, shareholders and the economic wellbeing of the state. Our research addresses how Accounting Information Systems (AIS) may act as carriers for institutionalised practices associated with maintaining regulatory compliance within the context of UK Asset Management Houses. The AIS was found to be a strong conduit for institutionalized compliance related practices, utilising symbolic systems, relational systems, routines and artefacts to carry approaches relating to regulative, normative and cultural-cognitive strands of institutionalism. Thus, AIS are integral to the development and dissipation of best practice for the management of regulatory compliance. As institutional elements are clearly present we argue that AIS and regulatory compliance provide a rich context to further institutionalism. Since AIS may act as conduits for regulatory approaches, both systems adopters and clients may benefit from actively seeking to codify and abstract best practices into AIS. However, the application of generic institutionalized approaches, which may be applied across similar organizations, must be tempered with each firm’s business environment and associated regulatory exposure. A balance should be sought between approaches specific enough to be useful but generic enough to be universally applied.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

Deconstruction plan assessment using multi-criteria decision-making methods

The purpose of this paper is to present two multi-criteria decision-making models, including an Analytic Hierarchy Process (AHP) model and an Analytic Network Process (ANP) model for the assessment of deconstruction plans and to make a comparison between the two models with an experimental case study. Deconstruction planning is under pressure to reduce operation costs, adverse environmental impacts and duration, in the meanwhile to improve productivity and safety in accordance with structure characteristics, site conditions and past experiences. To achieve these targets in deconstruction projects, there is an impending need to develop a formal procedure for contractors to select a most appropriate deconstruction plan. Because numbers of factors influence the selection of deconstruction techniques, engineers definitely need effective tools to conduct the selection process. In this regard, multi-criteria decision-making methods such as AHP have been adopted to effectively support deconstruction technique selection in previous researches. in which it has been proved that AHP method can help decision-makers to make informed decisions on deconstruction technique selection based on a sound technical framework. In this paper, the authors present the application and comparison of two decision-making models including the AHP model and the ANP model for deconstruction plan assessment. The paper concludes that both AHP and ANP are viable and capable tools for deconstruction plan assessment under the same set of evaluation criteria. However, although the ANP can measure relationship among selection criteria and their sub-criteria, which is normally ignored in the AHP, the authors also indicate that whether the ANP model can provide a more accurate result should be examined in further research.

Judgments, forecasts and decisions: an analysis of fund managers over time

Decision theory is the study of models of judgement involved in, and leading to, deliberate and (usually) rational choice. In real estate investment there are normative models for the allocation of assets. These asset allocation models suggest an optimum allocation between the respective asset classes based on the investors’ judgements of performance and risk. Real estate is selected, as other assets, on the basis of some criteria, e.g. commonly its marginal contribution to the production of a mean variance efficient multi asset portfolio, subject to the investor’s objectives and capital rationing constraints. However, decisions are made relative to current expectations and current business constraints. Whilst a decision maker may believe in the required optimum exposure levels as dictated by an asset allocation model, the final decision may/will be influenced by factors outside the parameters of the mathematical model. This paper discusses investors' perceptions and attitudes toward real estate and highlights the important difference between theoretical exposure levels and pragmatic business considerations. It develops a model to identify “soft” parameters in decision making which will influence the optimal allocation for that asset class. This “soft” information may relate to behavioural issues such as the tendency to mirror competitors; a desire to meet weight of money objectives; a desire to retain the status quo and many other non-financial considerations. The paper aims to establish the place of property in multi asset portfolios in the UK and examine the asset allocation process in practice, with a view to understanding the decision making process and to look at investors’ perceptions based on an historic analysis of market expectation; a comparison with historic data and an analysis of actual performance.

The impact of Group Intelligence software on enquiry-based learning

Despite the increasing use of groupware technologies in education, there is little evidence of their impact, especially within an enquiry-based learning (EBL) context. In this paper, we examine the use of a commercial standard Group Intelligence software called GroupSystems®ThinkTank. To date, ThinkTank has been adopted mainly in the USA and supports teams in generating ideas, categorising, prioritising, voting and multi-criteria decision-making and automatically generates a report at the end of each session. The software was used by students carrying out an EBL project, set by employers, for a full academic year. The criteria for assessing the impact of ThinkTank on student learning were those of creativity, participation, productivity, engagement and understanding. Data was collected throughout the year using a combination of interviews and questionnaires, and written feedback from employers. The overall findings show an increase in levels of productivity and creativity, evidence of a deeper understanding of their work but some variation in attitudes towards participation in the early stages of the project.

Random-walk-based characterisation of multiple access interference in a DS/SSMA system

The problem of calculating the probability of error in a DS/SSMA system has been extensively studied for more than two decades. When random sequences are employed some conditioning must be done before the application of the central limit theorem is attempted, leading to a Gaussian distribution. The authors seek to characterise the multiple access interference as a random-walk with a random number of steps, for random and deterministic sequences. Using results from random-walk theory, they model the interference as a K-distributed random variable and use it to calculate the probability of error in the form of a series, for a DS/SSMA system with a coherent correlation receiver and BPSK modulation under Gaussian noise. The asymptotic properties of the proposed distribution agree with other analyses. This is, to the best of the authors' knowledge, the first attempt to propose a non-Gaussian distribution for the interference. The modelling can be extended to consider multipath fading and general modulation

Sustainability assessment indicators and methodology for intelligent buildings

The sustainable intelligent building is a building that has the best combination of environmental, social, economic and technical values. And its sustainability assessment is related with system engineering methods and multi-criteria decision-making. Therefore firstly, the wireless monitoring system of sustainable parameters for intelligent buildings is achieved; secondly, the indicators and key issues based on the “whole life circle” for sustainability of intelligent buildings are researched; thirdly, the sustainable assessment model identified on the structure entropy and fuzzy analytic hierarchy process is proposed.

Multi-attribute collaborative filtering recommendation based on improved group decision-making

Currently researchers in the field of personalized recommendations bear little consideration on users' interest differences in resource attributes although resource attribute is usually one of the most important factors in determining user preferences. To solve this problem, the paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multi-attribute group decision-making algorithm, and introduces an algorithm to solve the recommendation problem of k-neighbor similar users. Considering the characteristics of collaborative filtering recommendation, the paper addresses the issues on the preference differences of similar users, incomplete values, and advanced converge of the algorithm. Thus the paper realizes multi-attribute collaborative filtering. Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment. The experimental results show that the algorithm has a high accuracy on predicting target users' attribute preferences and has a strong anti-interference ability on deviation and incomplete values.

The use of a multiple criteria decision analysis to evaluate the effectiveness of landscape and habitat enhancement mechanisms: an example from the South Downs

A range of funding schemes and policy instruments exist to effect enhancement of the landscapes and habitats of the UK. While a number of assessments of these mechanisms have been conducted, little research has been undertaken to compare both quantitatively and qualitatively their relative effectiveness across a range of criteria. It is argued that few tools are available for such a multi-faceted evaluation of effectiveness. A form of Multiple Criteria Decision Analysis (MCDA) is justified and utilized as a framework in which to evaluate the effectiveness of nine mechanisms in relation to the protection of existing areas of chalk grassland and the creation of new areas in the South Downs of England. These include established schemes, such as the Countryside Stewardship and Environmentally Sensitive Area Schemes, along with other less common mechanisms, for example, land purchase and tender schemes. The steps involved in applying an MCDA to evaluate such mechanisms are identified and the process is described. Quantitative results from the comparison of the effectiveness of different mechanisms are presented, although the broader aim of the paper is that of demonstrating the performance of MCDA as a tool for measuring the effectiveness of mechanisms aimed at landscape and habitat enhancement.

Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a ‘tool’ for ‘comparative’ rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers.

Are power calculations useful? A multicentre neuroimaging study

There are now many reports of imaging experiments with small cohorts of typical participants that precede large-scale, often multicentre studies of psychiatric and neurological disorders. Data from these calibration experiments are sufficient to make estimates of statistical power and predictions of sample size and minimum observable effect sizes. In this technical note, we suggest how previously reported voxel-based power calculations can support decision making in the design, execution and analysis of cross-sectional multicentre imaging studies. The choice of MRI acquisition sequence, distribution of recruitment across acquisition centres, and changes to the registration method applied during data analysis are considered as examples. The consequences of modification are explored in quantitative terms by assessing the impact on sample size for a fixed effect size and detectable effect size for a fixed sample size. The calibration experiment dataset used for illustration was a precursor to the now complete Medical Research Council Autism Imaging Multicentre Study (MRC-AIMS). Validation of the voxel-based power calculations is made by comparing the predicted values from the calibration experiment with those observed in MRC-AIMS. The effect of non-linear mappings during image registration to a standard stereotactic space on the prediction is explored with reference to the amount of local deformation. In summary, power calculations offer a validated, quantitative means of making informed choices on important factors that influence the outcome of studies that consume significant resources.