by Cheung Wai-Lam, William. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves 93-96). / Chapter chapter 1: --- introduction / Chapter 1.1 --- INTRODUCTION --- p.1 / Chapter 1.2 --- OBJECTIVES AND SCOPE --- p.2 / Chapter 1.3 --- STRUCTURE OF REPORT --- p.3 / Chapter 1.4 --- CHAPTER SUMMARY --- p.5 / Chapter chapter 2: --- decision support systems (dss) / Chapter 2.1 --- THE DECISION MAKING PROCESS --- p.6 / Chapter 2.2 --- DEFINITION OF DSS --- p.8 / Chapter 2.3 --- STRUCTURE OF DSS --- p.12 / Chapter 2.3.1 --- Users --- p.12 / Chapter 2.3.2 --- Database --- p.12 / Chapter 2.3.3 --- Model Base --- p.14 / Chapter 2.4 --- CHAPTER SUMMARY --- p.15 / Chapter chapter 3: --- dss for stock evaluation / Chapter 3.1 --- STOCK VALUATION: CAPM vs APT --- p.16 / Chapter 3.2 --- DSS FOR STOCK INVESTMENT --- p.21 / Chapter 3.3 --- THE PROPOSED STOCK EVALUATION DSS --- p.23 / Chapter 3.4 --- CHAPTER SUMMARY --- p.26 / Chapter chapter 4: --- analyticheerarchy process (ahp) / Chapter 4.1 --- WHAT IS AHP --- p.27 / Chapter 4.2 --- AN EXAMPLE: PLANT LOCATION SELECTION --- p.27 / Chapter 4.3 --- COMPUTATION PROCESS OF AHP / Chapter 4.3.1 --- Notations --- p.35 / Chapter 4.3.2 --- Principal Eigenvector --- p.35 / Chapter 4.3.3 --- Eigenvalue --- p.36 / Chapter 4.3.4 --- Consistency Ratio --- p.36 / Chapter 4.4 --- CHAPTER SUMMARY --- p.37 / Chapter chapter 5: --- an ahp model for stock evaluation / Chapter 5.1 --- ALTERNATIVES FOR STOCK EVALUATION --- p.39 / Chapter 5.2 --- THE AHP MODEL FOR STOCK SELECTION --- p.41 / Chapter 5.3 --- EXPLANATIONS AND JUSTIFICATIONS FOR PROPOSED HIERARCHY --- p.43 / Chapter 5.3.1 --- Level1 --- p.45 / Chapter 5.3.2 --- Level2 --- p.45 / Chapter 5.3.3 --- Level3 --- p.46 / Chapter 5.3.4 --- Level4 --- p.48 / Chapter 5.3.5 --- Level5 --- p.49 / Chapter 5.3.6 --- Level6 --- p.60 / Chapter 5.4 --- CHAPTER SUMMARY --- p.61 / Chapter chapter 6: --- the development of iris: a prototype / Chapter 6.1 --- SYSTEM FLOWCHART --- p.63 / Chapter 6.2 --- PROGRAM SPECIFICATION --- p.65 / Chapter 6.2.1 --- File Maintenance Module --- p.65 / Chapter 6.2.2 --- Hierarchy Setup --- p.65 / Chapter 6.2.3 --- Eigenvector Computation --- p.67 / Chapter 6.2.4 --- Overall Weight Computation --- p.67 / Chapter 6.3 --- PROTOTYPE OPERATION --- p.67 / Chapter 6.4 --- CHAPTER SUMMARY --- p.79 / Chapter chapter 7: --- user evaluationof model and prototype / Chapter 7.1 --- METHODOLOGY OF EVALUATION --- p.82 / Chapter 7.1.1 --- Participants --- p.82 / Chapter 7.1.2 --- Stock Candidates --- p.83 / Chapter 7.1.3 --- Stock Data --- p.83 / Chapter 7.1.4 --- Process of Model and Prototype Evaluation --- p.84 / Chapter 7.2 --- FINDINGS --- p.85 / Chapter 7.2.1 --- Structure the Stock Evaluation Process --- p.86 / Chapter 7.2.2 --- Time-consuming --- p.87 / Chapter 7.2.3 --- The Consistency Ratio --- p.87 / Chapter 7.2.4 --- Reconsideration of Factors --- p.87 / Chapter 7.2.5 --- Precise Amount Available --- p.88 / Chapter 7.2.6 --- Users Forced to Considered All Factors --- p.88 / Chapter 7.3 --- CONCLUSION OF EVALUATION --- p.89 / Chapter 7.4 --- CHAPTER SUMMARY --- p.90 / Chapter chapter 8: --- summary and conclusion / Chapter 8.1 --- REPORT SUMMARY --- p.91 / Chapter 8.2 --- CONCLUSION --- p.91 / references --- p.93 / appendix --- p.97

by Lau Tak Yun, Ma Kai Sun. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1990. / Bibliography: leaves 79-80. / ABSTRACT --- p.ii / TABLES OF CONTENTS --- p.iii / LIST OF ILLUSTRATIONS --- p.v / LISTS OF TABLES AND GRAPHS --- p.vii / Chapter I. --- INTRODUCTION --- p.1 / Focus of study --- p.4 / Chapter II. --- LITERATURE REVIEW --- p.7 / Jung's Theory of Psychological Types --- p.7 / Heller's Model of Leadership Style --- p.12 / Chapter III. --- THEORETICAL FRAMEWORK --- p.17 / Size of the Firm and the Decision´ؤmaking Style --- p.17 / Individual Endogenous Factors of the Entrepreneur --- p.20 / Jung's Psychological Types --- p.20 / Motivations --- p.21 / Time Horizon --- p.22 / Risk Attitude --- p.24 / Demograghic Variables --- p.25 / The Overall Theoretical Framework --- p.27 / Chapter IV. --- RESEARCH DESIGN --- p.29 / Objective --- p.29 / Sampling --- p.29 / Mailing Questionaire --- p.30 / Screening Criteria --- p.31 / Variables and their measurement --- p.32 / Analysis --- p.35 / Endogenous Factors --- p.35 / Decision-making Style --- p.39 / "Correlation between the Demographic and Individual Endogenous factors, and Decision-making Style" --- p.39 / Correlation between Decision-making Style and Company size (growth) --- p.41 / Chapter V. --- FINDINGS --- p.42 / Size of the Company --- p.42 / Demograghic Profile --- p.42 / Sex --- p.42 / Education --- p.44 / Age --- p.47 / Endogenous Factor --- p.47 / Jung's Psychological Types --- p.47 / Time Horizon --- p.50 / Motivation --- p.52 / Decision-making Style in the Seven Decision-making Areas --- p.55 / Decision-making Style and the Size of the Staff --- p.57 / "Correlation between Endogenous and Demograhic Factors, and Decision- making Style" --- p.60 / Chapter VI. --- SUMMARY Of THE STUDY --- p.69 / Chapter VII. --- DISCUSSION --- p.71 / Chapter APPENDIX I. --- SPSSPC PROGRAMS --- p.73 / Chapter APPENDIX II. --- DATA FILE --- p.77 / BIBLIOGRAPHY --- p.79

by Liu Shu Cheung, Jimmy. / Thesis (M.Ph.)--Chinese University of Hong Kong, 1988. / Bibliography: leaves 61-64.

by Jian-Wei Chen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 84-86). / Chapter Chapter 1 --- Introduction / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Bayesian approach to single variable sampling plan for the exponential distribution --- p.3 / Chapter 1.3 --- Outline of the thesis --- p.7 / Chapter Chapter 2 --- Single Variable Sampling Plan With Type II Censoring / Chapter 2.1 --- Model --- p.10 / Chapter 2.2 --- Loss function and finite algorithm --- p.13 / Chapter 2.3 --- Numerical examples and sensitivity analysis --- p.17 / Chapter Chapter 3 --- Double Variable Sampling Plan With Type II Censoring / Chapter 3.1 --- Model --- p.25 / Chapter 3.2 --- Loss function and Bayes risk --- p.27 / Chapter 3.3 --- Discretization method and numerical analysis --- p.33 / Chapter Chapter 4 --- Bayesian Approach to Single Variable Sampling Plans for General Life Distribution with Type I Censoring / Chapter 4.1 --- Model --- p.42 / Chapter 4.2 --- The case of the Weibull distribution --- p.47 / Chapter 4.3 --- The case of the two-parameter exponential distribution --- p.49 / Chapter 4.4 --- The case of the gamma distribution --- p.52 / Chapter 4.5 --- Numerical examples and sensitivity analysis --- p.54 / Chapter Chapter 5 --- Discussions / Chapter 5.1 --- Comparison between Bayesian variable sampling plans and OC curve sampling plans --- p.63 / Chapter 5.2 --- Comparison between single and double sampling plans --- p.64 / Chapter 5.3 --- Comparison of both models --- p.66 / Chapter 5.4 --- Choice of parameters and coefficients --- p.66 / Appendix --- p.78 / References --- p.84

Tse Ka Ling Carol. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 72-76). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Factor Analysis Model --- p.1 / Chapter 1.2 --- Main Objectives --- p.2 / Chapter 1.2.1 --- Investigate the distribution of the estimated Factor Scores --- p.2 / Chapter 1.2.2 --- Propose an alternative method for getting the estimates of the LISREL model --- p.4 / Chapter 1.3 --- Summary --- p.4 / Chapter 2 --- Joint Bayesian Approach of the Factor Analysis Model --- p.6 / Chapter 2.1 --- Conditional Distribution --- p.7 / Chapter 2.1.1 --- Conditional distribution of Z given Y and θ --- p.7 / Chapter 2.1.2 --- Conditional distribution of θ given Y and Z --- p.7 / Chapter 2.2 --- Implementation of the Gibbs sampler for generating the random observations --- p.11 / Chapter 2.3 --- Bayesian Estimates and their Statistical Properties --- p.13 / Chapter 2.3.1 --- Estimates of unknown parameter --- p.13 / Chapter 2.3.2 --- Estimates of Factor Score --- p.14 / Chapter 3 --- Examine the distribution of the estimated factor scores --- p.15 / Chapter 3.1 --- The 1st Simulation Study --- p.15 / Chapter 3.2 --- The 2nd Simulation Study --- p.30 / Chapter 3.3 --- The 3rd Simulation Study --- p.31 / Chapter 4 --- An Alternative method for getting the parameter estimatesin the LISREL Model --- p.44 / Chapter 4.1 --- Full LISREL model --- p.44 / Chapter 4.2 --- Our proposed method --- p.46 / Chapter 4.3 --- Simulation Studies --- p.49 / Chapter 4.3.1 --- The 1st Simulation Study --- p.49 / Chapter 4.3.2 --- The 3rd Simulation Study --- p.50 / Chapter 4.4 --- Conclusion --- p.53 / Appendix --- p.56 / Bibliography --- p.72

The objectives are to examine the tension between the ethics of care and the ethics of justice, offer critical analysis and develop an amalgam of key elements from both. A more sufficient framework for moral decision-making will be proposed and its validity assessed. Part One investigates the ethics of care, beginning with a critical analysis of Carol Gilligan's approach to the ethics of care and justice, leading to an exploration of the nature and content of care from key authors in the debate. By focusing on nursing the tensions surrounding care are highlighted. Critical analysis draws out key themes from care including persons, relationships, context and responsibilities. Part Two examines the ethics of justice, concentrating on the substantive theories of John Rawls and Alasdair MacIntyre. Through critical analysis the need for minimum standards of protection for the vulnerable in society is highlighted. The thesis emphasises and argues for justice as equality, fairness and equity, the importance of persons, community, rationality, justification, fittingness, morality, duties and obligations. Part Three argues for an amalgam of key themes from both the ethics of care and justice. This model consists of the crucial role of context, persons and relationships, responsibilities, justice and appropriateness in moral decision-making as a framework for a middle way. After arguing for its sufficiency in theory, it is tested in practice by application to the Child B case. The thesis argues a middle way model is more adequate than either the ethics of care or justice alone for critically examining the decisions and justifications offered in this case. In conclusion, critical reflection on the theory and practice of a middle way model is offered, and its potential for further application and development regarding moral decision-making and training for the caring professions explored.

We investigate algorithms for different steps in the decision making process, focusing on systems where we are uncertain about the outcomes but can quantify how probable they are using random variables. Any decision one makes in such a situation leads to a distribution of outcomes and requires a way to evaluate a decision. The standard approach is to marginalise the distribution of outcomes into a single number that tries in some way to summarise the value of each decision. After selecting a marginalisation approach, mathematicians and decision makers focus their analysis on the marginalised value but ignore the distribution. We argue that we should also be investigating the implications of the chosen mathematical approach for the whole distribution of outcomes. We illustrate the effect different mathematical formulations have on the distribution with one-stage and sequential decision problems. We show that different ways to marginalise the distributions can result in very similar decisions but each way has a different complexity and computational cost. It is often computationally intractable to approximate optimal decisions to high precision and much research goes into developing algorithms that are suboptimal in the marginalised sense, but work within the computational budget available. If the performance of these algorithms is evaluated they are mainly judged based on the marginalised values, however, comparing the performance using the full distribution provides interesting information: We provide numerical examples from dynamic pricing applications where the suboptimal algorithm results in higher profit than the optimal algorithm in more than half of the realisations, which is paid for with a more significant underperformance in the remaining realisations. All the problems discussed in this thesis lead to continuous optimisation problems. We develop a new algorithm that can be used on top of existing optimisation algorithms to reduce the cost of approximating solutions. The algorithm is tested on a range of optimisation problems and is shown to be competitive with existing methods.

在日常生活和科学研究中产生大量偏好数据，其反应一组被关注对象受偏好的程度。通常用排序数据或多元选择数据来记录观察结果。有时候关于两个对象的偏好没有明显强弱之分，导致排序产生节点，也就是所谓的删失排序。为了研究带有删失的排序数据，基于Thurstone的随机效用假设理论我们建立了一个对称贝叶斯probit模型。然而，参数识别是probit模型必须解决的问题，即确定一组潜在效用的位置和尺度。通常方法是选择其中一个对象为基，然后用其它对象的效用减去这个基的效用，最后我们关于这些效用差来建模。问题是，在用贝叶斯方法处理多元选择数据时，其预测结果对基的选择有敏感性，即选不同对象为基预测结果是不一样的。本文，我们虚构一个基，即一组对象偏好的平均。依靠这个基，我们为多元选择probit模型给出一个不依赖于对象标号的识别方法，即对称识别法。进一步，我们设计一种贝叶斯算法来估计这个模型。通过仿真研究和真实数据分析，我们发现这个贝叶斯probit模型被完全识别，而且消除通常识别法所存在的敏感性。接下来，我们把这个关于多元选择数据建立的probit模型推广到处理一般删失排序数据，即得到对称贝叶斯删失排序probit 模型。最后，我们用这个模型很好的分析了香港赌马数据。 / Vast amount of preference data arise from daily life or scientific research, where observations consist of preferences on a set of available objects. The observations are usually recorded by ranking data or multinomial data. Sometimes, there is not a clear preference between two objects, which will result in ranking data with ties, also called censored rank-ordered data. To study such kind of data, we develop a symmetric Bayesian probit model based on Thurstone's random utility (discriminal process) assumption. However, parameter identification is always an unavoidable problem for probit model, i.e., determining the location and scale of latent utilities. The standard identification method need to specify one of the utilities as a base, and then model the differences of the other utilities subtracted by the base. However, Bayesian predictions have been verified to be sensitive to specification of the base in the case of multinomial data. In this thesis, we set the average of the whole set of utilities as a base which is symmetric to any relabeling of objects. Based on this new base, we propose a symmetric identification approach to fully identify multinomial probit model. Furthermore, we design a Bayesian algorithm to fit that model. By simulation study and real data analysis, we find that this new probit model not only can be identifed well, but also remove sensitivities mentioned above. In what follows, we generalize this probit model to fit general censored rank-ordered data. Correspondingly, we get the symmetric Bayesian censored rank-ordered probit model. At last, we apply this model to analyze Hong Kong horse racing data successfully. / Detailed summary in vernacular field only. / Pan, Maolin. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 50-55). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.2 / Chapter 1.1.1 --- The Ranking Model --- p.2 / Chapter 1.1.2 --- Discrete Choice Model --- p.4 / Chapter 1.2 --- Methodology --- p.7 / Chapter 1.2.1 --- Data Augmentation --- p.8 / Chapter 1.2.2 --- Marginal Data Augmentation --- p.8 / Chapter 1.3 --- An Outline --- p.9 / Chapter 2 --- Bayesian Multinomial Probit Model Based On Symmetric I-denti cation --- p.11 / Chapter 2.1 --- Introduction --- p.11 / Chapter 2.2 --- The MNP Model --- p.14 / Chapter 2.3 --- Symmetric Identification and Bayesian Analysis --- p.17 / Chapter 2.3.1 --- Symmetric Identification --- p.18 / Chapter 2.3.2 --- Bayesian Analysis --- p.21 / Chapter 2.4 --- Case Studies --- p.25 / Chapter 2.4.1 --- Simulation Study --- p.25 / Chapter 2.4.2 --- Clothes Detergent Purchases Data --- p.27 / Chapter 2.5 --- Summary --- p.29 / Chapter 3 --- Symmetric Bayesian Censored Rank-Ordered Probit Model --- p.30 / Chapter 3.1 --- Introduction --- p.30 / Chapter 3.2 --- Ranking Model --- p.33 / Chapter 3.2.1 --- Ranking Data --- p.33 / Chapter 3.2.2 --- Censored Rank-Ordered Probit Model --- p.35 / Chapter 3.2.3 --- Symmetrically Identified CROP Model --- p.36 / Chapter 3.3 --- Bayesian Analysis on Symmetrically Identified CROP Model --- p.37 / Chapter 3.3.1 --- Model Estimation --- p.38 / Chapter 3.4 --- Application: Hong Kong Horse Racing --- p.41 / Chapter 3.5 --- Summary --- p.44 / Chapter 4 --- Conclusion and Further Studies --- p.45 / Chapter A --- Prior for covariance matrix with trace augmented restriction --- p.47 / Chapter B --- Derivation of sampling intervals --- p.49 / Bibliography --- p.50

Despite the importance of roofs, improved roof selection has not been explored in significant depth. Therefore this research explores the possibilities that roofs offer to improve the value and sustainability of buildings. It is concerned with the roof as a system, explicitly connected with the building and their impacts on wider society. This research, develops and tests techniques to better understand what constitutes value and sustainability for a building project’s context through action research. The sustainability and value themes output through the use of such techniques are then considered as a basis for the selection of roof attributes through Keeney’s value focused thinking approach. Once the roof performance attributes have been established, designers and clients then require quantitative data to decide which roof type represents the highest value / most sustainable option. Thus the research also collates and maps peer reviewed quantitative performance data on the performance of roofing systems in relation to climate type as well as providing information from leading modelling packages for different roof options. An approach for selecting the most appropriate data is then developed. This allows the practitioner to be able to access reliable peer reviewed information and utilise leading modelling techniques to quickly gain information regarding the performance of various roof systems for use in the project context. An approach is developed to bring this information together with the important sustainability considerations for the project to inform sustainable roof selection. This combines the different types of roof performance with the relevant decision attributes early in the design process, to provide insight into which roof option represents the best overall economic, environmental and social value and therefore the most sustainable roof option. The primary contribution to knowledge presented in this thesis is the development of a pragmatic realist approach to sustainable roof selection.

We propose an axiomatization of the Choquet integral model for the general case of a heterogeneous product set X = X1 Xn. Previous characterizations of the Choquet integral have been given for the particular cases X = Y n and X = Rn. However, this makes the results inapplicable to problems in many fields of decision theory, such as multicriteria decision analysis (MCDA), state-dependent utility (SD-DUU), and social choice. For example, in multicriteria decision analysis the elements of X are interpreted as alternatives, characterized by criteria taking values from the sets Xi. Obviously, the identicalness or even commensurateness of criteria cannot be assumed a priori. Despite this theoretical gap, the Choquet integral model is quite popular in the MCDA community and is widely used in applied and theoretical works. In fact, the absence of a sufficiently general axiomatic treatment of the Choquet integral has been recognized several times in the decision-theoretic literature. In our work we aim to provide missing results { we construct the axiomatization based on a novel axiomatic system and study its uniqueness properties. Also, we extend our construction to various particular cases of the Choquet integral and analyse the constraints of the earlier characterizations. Finally, we discuss in detail the implications of our results for the applications of the Choquet integral as a model of decision making.