A fuzzy multiple attribute utility model for intelligent building assessment

Multi-Attribute Utility Theory (MAUT) is an evaluation scheme which is very popular by decision makers for evaluating their judgments. According to MAUT, the overall evaluation U(x) of an object x is defined as a weighted addition of its evaluation with respect to its relevant value dimensions. The recent years have witnessed a huge concentration and interest in intelligent buildings’ performance that is increasingly evidenced in building design and construction. Intelligent buildings (IBs) are also under assessment according to their IB related characteristics and actual circumstances. For this aim, in this paper a fuzzy multiple attribute utility model for intelligent building assessment is proposed and three alternative intelligent buildings for a business center in Istanbul are evaluated

Festival attendees’ perceptions of green hotel practices

Lodging managers and festival organizers have an incentive to understand how festival attendees perceive hotels with green practices in place. Lodging managers that understand how to segment, target, and position their offerings to festival attendees, including sustainable practices, can maximize financial gains from festivals. Festival organizers have related interests: they want to minimize negative impacts on the physical environment and maximize positive customer experiences on- and off-site. To provide insights into festival attendees’ perceptions of green hotel practices that may assist both sets of stakeholders, the manuscript presents the results of a survey of convenience samples from two food festivals. The analysis relates perceptions of hotel desirability to characteristics that have been successfully used to segment consumers in the past. While gender, education, income, and environmental values did not have significant relationships with whether thirteen sustainable hotel practices increased hotel desirability, age, festival type, and environmental self-efficacy did. The results, which include ratings of the thirteen green practices, have practical implications for festival organizers, who may want to collaborate with greener hotels to minimize negative festival outcomes, and for lodging managers, who may want to segment festival audiences and appropriately position hotel sustainable practices for festival attendees

A Framework for Prioritizing Opportunities of Improvement in the Context of Business Excellence Model in Healthcare Organization

In today\u27s world, the healthcare sector is facing challenges to improve the efficiency and effectiveness of its operations. More and more improvement projects are being adopted to enhance healthcare services, making it more patient-centric, and enabling better cost control. Healthcare organizations strive to identify and carry out such improvement initiatives to sustain their businesses and gain competitive advantage. Seeking to reach a higher operational level of excellence, healthcare organizations utilize business excellence criteria to conduct assessment and identify organizational strengths and weaknesses. However, while such assessments routinely identify numerous areas for potential improvement, it is not feasible to conduct all improvement projects simultaneously due to limitations in time, capital, and personnel, as well as conflict with other organization\u27s projects or strategic objectives. An effective prioritization and selection approach is valuable in that it can assist the organization to optimize its available resources and outcomes. This study attempts to enable such an approach by developing a framework to prioritize improvement opportunities in healthcare in the context of the business excellence model through the integration of the Fuzzy Delphi Method and Fuzzy Interface System. To carry out the evaluation process, the framework consists of two phases. The first phase utilizes Fuzzy Delphi Method to identify the most significant factors that should be considered in healthcare for electing the improvement projects. The FDM is employed to handle the subjectivity of human assessment. The research identifies potential factors for evaluating projects, then utilizes FDM to capture expertise knowledge. The first round in FDM is intended to validate the identified list of factors from experts; which includes collecting additional factors from experts that the literature might have overlooked. When an acceptable level of consensus has been reached, a second round is conducted to obtain experts\u27 and other related stakeholders\u27 opinions on the appropriate weight of each factor\u27s importance. Finally, FDM analyses eliminate or retain the criteria to produce a final list of critical factors to select improvement projects. The second phase in the framework attempts to prioritize improvement initiatives using the Hierarchical Fuzzy Interface System. The Fuzzy Interface System combines the experts\u27 ratings for each improvement opportunity with respect to the factors deemed critical to compute the priority index. In the process of calculating the priority index, the framework allows the estimation of other intermediate indices including: social, financial impact, strategical, operational feasibility, and managerial indices. These indices bring an insight into the improvement opportunities with respect to each framework\u27s dimensions. The framework allows for a reduction of the bias in the assessment by developing a knowledge based on the perspectives of multiple experts

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

The end of stigma? Understanding the dynamics of legitimisation in the context of TV series consumption

This research contributes to prior work on stigmatisation by looking at stigmatisation and legitimisation as social processes in the context of TV series consumption. Using in-depth interviews, we show that the dynamics of legitimisation are complex and accompanied by the reproduction of existing stigmas and creation of new stigmas

Decision-making and the role of feedback in complex tasks

This thesis investigates the process of decision-making in relation to complex tasks and considers the important role which dynamic information and real-time feedback play in shaping response behaviour and adaptation within such environments. Through empirical studies, the thesis explores the extent to which decision-makers can be said to act rationally when challenged by complex decision-making environments. Evidence relating to demand for information and the impact of feedback on behaviour is provided with two studies: The first uses a simulated auction platform to examine behaviour within overlapping auctions of short duration with close-to-identical items and minimal participation costs. Mouse tracking is used to capture data on relevant interactions of participants with the simulated online platform, including switching behaviour independent of bidding. The resulting data suggests that participants did behave in a manner consistent with utility maximisation, seeking to acquire the item at the lowest possible price and showing no bias in terms of auction preference. The impact of fixed-price offers in the form of a “Buy it Now” option is also examined with some evidence that participants again seek, and respond to, current information when deciding on their bidding strategy. The second study is a test of the impact of real-time feedback and demand for information within the context of financial markets. The study again uses a novel simulated environment which provides access to considerable amounts of relevant data which participants can choose to access. In addition, participants are exposed to regular feedback with regard to their own performance. Overall, demand for information is found to be dependent upon the type of feedback received and its context. Decision-makers then appear to behave objectively, apparently seeking the latest available information to support current decisions, although investor style is found to be important in determining overall trading propensity. The thesis starts by considering a number of the foundations and pathways which run through the judgment and decision-making literature. It is not a complete description, review or analysis of all of the prevailing lines of enquiry. Nevertheless, it seeks to achieve coherence in terms of bringing together some of the key themes dealing with risky choice under conditions of uncertainty and ambiguity. The field of judgment and decision-making is inevitably vast; its scope owing much to the fact that it transcends individual disciplines. The emergent behavioural sciences thus draw together important strands from various sources, notably Economics and Finance. In many areas, psychological traits can be applied to explain inconsistencies which are found in classical theory of rational behaviour. The recognition of behavioural traits has thus contributed greatly to the evolution of decisionmaking theories under conditions of uncertainty and ambiguity which are, in many cases, substantially more adaptable and robust than early normative theories of rational behaviour. The classical approach to rational decision making within Economics, together with some theoretical and empirical challenges to it, are considered in Chapter 1. It is here that we are introduced to the Rational Man. Like the mythical creatures found in Classical Antiquity, the Rational Man does not actually exist in the real world; he is nevertheless central to the concept of utility maximising rational choice which provided much of the foundation of Economics. Developments of expected utility theory (EUT) are considered, including its replacement of expected value, and the formalisation of rational behaviour within the context of axioms. When those logical axioms apply, decision-makers can be said to behave 'as if' they are utility maximises. The chapter ends with some empirical evidence, showing the types of approaches often used to explore rational decision-making. Some violations of EUT are explored, both in relation to notional gambles and consistency with regard to revealed preferences. Chapter 2 extends the narrative by considering rational decision-making in cases where there is no objective information about possible outcomes. Subjective utility theory (SEU) is then introduced, describing objective functions based upon preferences derived from combined utility and probability functions. The implications of the Allais’ and Ellsberg paradoxes are discussed, along with some possible solutions. It is here that we explore the concepts of uncertainty and ambiguity in more details and consider some theoretical formulations for addressing them. Chapter 3 covers the significant contribution to decision-making under conditions of uncertainty provided by Prospect Theory and, later, Cumulative Prospect Theory (CPT). Their evolution from the pioneering work of Markowitz is discussed within the context of reference points relative to which outcomes can be evaluated. The significance of stochastic dominance and rank dependence are explored. By this stage, we have examined numerous theories which have fundamentally transformed standard EUT into much more flexible and adaptable frameworks of rational choice. The core concepts of utility maximisation remain yet the initial, strictly concave utility function describing diminishing marginal utility is now substantially replaced by more complex weighted preference functions. From this theoretical base, the process of choice reduction and the application of heuristics in decision-making are considered. We again describe axiomatic behaviour compatible with rational choice. Therefore, decision-makers faced with multiple choices about which there may be little or no objective information about likely outcomes can nevertheless develop rational beliefs and expectations which can then be applied to reduce complex tasks to more manageable proportions. As well as considering these aspects from the point of view of actual choices, we also consider the processes by which decisions are taken. Thus, process tracing methods are introduced into the discussion. The chapter also explicitly considers the role of feedback in decision making. This includes a consideration of Bayesian inference as a process for updating probabilistic expectations subject to new information. From considering theoretical formulations form which we can judge rational behaviour, Chapter 5 looks at evidence for sub-optimal decision-making and bias. Bias with regard to probability assessments are considered along with empirical evidence of bias in relation to intertemporal discounting. Sunk cost bias is also considered as a clear example of irrational behaviour, leading in to a specific discussion about a number of persistent behavioural biases identified within financial markets. As an introduction to later chapters, this also covers the basic theoretical principles of market efficiency and evidence that real markets fail to adhere to those principles in important ways. Chapters 6 and 8 describe the empirical studies with Chapter 7 providing a more detailed introduction to the financial markets experiment, considering aspects of market efficiency, models of behaviour and other empirical evidence

A COMPREHENSIVE ASSESSMENT METHODOLOGY BASED ON LIFE CYCLE ANALYSIS FOR ON-BOARD PHOTOVOLTAIC SOLAR MODULES IN VEHICLES

This dissertation presents a novel comprehensive assessment methodology for using on-board photovoltaic (PV) solar technologies in vehicle applications. A well-to-wheels life cycle analysis based on a unique energy, greenhouse gas (GHG) emission, and economic perspective is carried out in the context of meeting corporate average fuel economy (CAFE) standards through 2025 along with providing an alternative energy path for the purpose of sustainable transportation. The study includes 14 different vehicles, 3 different travel patterns, in 12 U.S. states and 16 nations using 19 different cost analysis scenarios for determining the challenges and benefits of using on-board photovoltaic (PV) solar technologies in vehicle applications. It develops a tool for decision-makers and presents a series of design requirements for the implementation of on-board PV in automobiles to use during the conceptual design stage, since its results are capable of reflecting the changes in fuel consumption, greenhouse gas emission, and cost for different locations, technological, and vehicle sizes. The decision-supports systems developed include (i) a unique decision support systems for selecting the optimal PV type for vehicle applications using quality function deployment, analytic hierarchy process, and fuzzy axiomatic design, (ii) a unique system for evaluating all non-destructive inspection systems for defects in the PV device to select the optimum system suitable for an automated PV production line. (iii) The development of a comprehensive PV system model that for predicting the impact of using on-board PV based on life cycle assessment perspective. This comprehensive assessment methodology is a novel in three respects. First, the proposed work develops a comprehensive PV system model and optimizes the solar energy to DC electrical power output ratio. Next, it predicts the actual contribution of the on-board PV to reduce fuel consumption, particularly for meeting corporate average fuel economy (CAFE) 2020 and 2025 standards in different scenarios. The model also estimates vehicle range extension via on-board PV and enhances the current understanding regarding the applicability and effective use of on-board PV modules in individual automobiles. Finally, it develops a life cycle assessment (LCA) model (well-to-wheels analysis) for this application. This enables a comprehensive assessment of the effectiveness of an on-board PV vehicle application from an energy consumption, Greenhouse Gas (GHG) emission, and cost life-cycle perspective. The results show that by adding on-board PVs to cover less than 50% of the projected horizontal surface area of a typical passenger vehicle, up to 50% of the total daily miles traveled by a person in the U.S. could be driven by solar energy if using a typical mid-size vehicle, and up to 174% if using a very lightweight and aerodynamically efficient vehicle. In addition, the increase in fuel economy in terms of combined mile per gallon (MPG) at noon for heavy vehicles is between 2.9% to 9.5%. There is a very significant increase for lightweight and aerodynamic efficient vehicles, with MPG increase in the range of 10.7% to 42.2%, depending on location and time of year. Although the results show that the plug-in electric vehicles (EVs) do not always have a positive environmental impact over similar gasoline vehicles considering the well-to-wheel span, the addition of an on-board PV system for both vehicle configurations, significantly reduces cycle emissions (e.g., the equivalent savings of what an average U.S. home produces in a 20 month period). The lifetime driving cost ($per mile) of a gasoline vehicle with adding on-board PV, compared to a pure gasoline vehicle, is lower in regions with more sunlight (e.g., Arizona) even of the current gasoline price in the U.S. ($4.0 per gallon) assuming battery costs will decline over time. Lifetime driving cost ($per mile) of a plug-in EV with added PV versus pure plug-in EV (assuming electricity price 0.18$/kWh) is at least similar, but mostly lower, even in regions with less sunlight (e.g., Massachusetts). In places with low electricity prices (0.13 $/kWh), and with more sunlight, the costs of operating an EV with PV are naturally lower. The study reports a unique observation that placing PV systems on-board for existing vehicles is in some cases superior to the lightweighting approach regarding full fuel-cycle emissions. An added benefit of on-board PV applications is the ability to incorporate additional functionality into vehicles. Results show that an on-board PV system operating in Phoenix, AZ can generate in its lifetime, energy that is the equivalent of what an American average household residential utility customer consumes over a three-year period. However, if the proposed system operates in New Delhi, India, the PV could generate energy in its lifetime that is the equivalent of what an Indian average household residential utility customer consumes over a 33-year period. Consequently, this proposed application transforms, in times of no-use, into a flexible energy generation system that can be fed into the grid and used to power electrical devices in homes and offices. The fact that the output of this system is direct current (DC) electricity rather than alternative current (AC) electricity reduces the wasted energy cost in the generation, transmission, and conversion losses between AC-DC electricity to reach the grid. Thus, this system can potentially reduce the dependency on the grid in third world countries where the energy consumption per home is limited and the grid is unstable or unreliable, or even unavailable

Symmetric and Asymmetric Data in Solution Models

This book is a Printed Edition of the Special Issue that covers research on symmetric and asymmetric data that occur in real-life problems. We invited authors to submit their theoretical or experimental research to present engineering and economic problem solution models that deal with symmetry or asymmetry of different data types. The Special Issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, seventeen papers were accepted and published. The authors proposed different solution models, mainly covering uncertain data in multicriteria decision-making (MCDM) problems as complex tools to balance the symmetry between goals, risks, and constraints to cope with the complicated problems in engineering or management. Therefore, we invite researchers interested in the topics to read the papers provided in the book