考虑不确定性影响的银行服务质量评价

本文研究了不确定性对服务质量评价的影响,建立了服务质量评价的均值—方差模型,并进行了实证分析和检验。这一模型被应用来对我国主要商业银行的服务质量和顾客满意度进行排序分析,其结果显示银行服务质量的提高应该从服务的平均水平和一致性两个方面来努力。     

Risk—Its Priority and Probability: The Analytic Hierarchy Process

Risk estimation involves priorities and probabilities which are themselves a form of priority of natural alternatives. This paper provides illustrations of how one can deal with risk and uncertainty using the Analytic Hierarchy Process, a new approach to measurement by ratio scales. The paper also includes a discussion of how to deal with risk strategies involving interdependence. Particular emphasis is made on the siting of nuclear power plants.     

Uses of Probabilistic Exposure Models in Ecological Risk Assessments of Contaminated Sites

Food web models have two uses in assessments of environmental contaminants. First, they are used to determine whether remediation is needed by estimating exposure of end-point species and subsequent effects. Second, they are used to establish cleanup goals by estimating concentrations of contaminants in ambient media that will not cause significant effects. This paper demonstrates how achievement of these goals can be enhanced by the use of stochastic food web models. The models simulate the dynamics of PCBs and mercury in the food webs of mink and great blue herons. All parameters of the models are treated as having knowledge uncertainty, due to imperfect knowledge of the actual parameter values for the site, chemicals, and species of interest. This uncertainty is an indicator of the potential value of additional measurements. In addition, those parameters that are responsible for variance among individual organisms are assigned stochastic uncertainty. This uncertainty indicates the range of body burdens that are expected when the end-point species are monitored. These two types of uncertainty are separately accounted for in Monte Carlo simulations of the models. Preliminary monitoring results indicate that the models give reasonably good estimates of heron egg and nestling body burdens and of variance among individuals.     

Expert Judgment in Risk Analysis and Management: Process, Context, and Pitfalls

The regulation and management of hazardous industrial activities increasingly rely on formal expert judgment processes to provide wisdom in areas of science and technology where traditional "good science" is, in practice, unable to supply unambiguous "facts." Expert judgment has always played a significant, if often unrecognized, role in analysis; however, recent trends are to make it formal, explicit, and documented so it can be identified and reviewed by others. We propose four categories of expert judgment and present three case studies which illustrate some of the pitfalls commonly encountered in its use. We conclude that there will be an expanding policy role for formal expert judgment and that the openness, transparency, and documentation that it requires have implications for enhanced public involvement in scientific and technical affairs.     

Therapeutic Ambition,Uncertainty, and Psychotherapy with Heterosexually Married Gay Men: A Short Commentary

A Short Commentary on the article 'Staying Put in the Closet: Examining Clinical Practice and Countertransference Issues in Work with Gay Men Married to Straight Women' by Edward Alessi. The focus is upon countertransference issues, especially therapeutic ambition, in working clinically with heterosexually married gay men. The work of the interpersonal school is emphasized as providing a creative approach to therapeutic ambition with Otto Allen Will's concept of the governing principle of uncertainty.

The effects of demand,competitive, and technological uncertainty on board monitoring and institutional ownership of IPO firms

This paper considers industry-specific contingencies that may account for some of the inter-firm heterogeneity in the deployment of specific corporate governance mechanisms in IPO firms. We examine how differences in demand, competitive, and technological uncertainty in the industry influence the levels of IPO firm monitoring by board outsiders and institutional investors. We test our theory using a sample of U.S. firms that completed an IPO in 24 manufacturing industries. The results indicate that industry uncertainty is, indeed, significantly related to the use of corporate governance mechanisms. In particular, the empirical results indicate that industry effects on IPO firm board monitoring and institutional investor ownership are the strongest and most consistent for demand uncertainty and competitive uncertainty.

Uncertainty Reduction Approaches,Uncertainty Coping Approaches,and Process Performance in Financial Services

Developing a better understanding of the impact of uncertainty on process performance has been recognized as an important research opportunity in service design ( Hill, et al., 2002 ). Within this general research stream, our study focuses on the question of what managers can do to most effectively address operational uncertainty and mitigate its negative effects. To begin to address this question, we report on an exploratory study using a sample of professionals in the financial‐services industry who acted as informants on 108 financial‐services processes. These professionals were sampled from a population of graduates of a university in the northeastern region of the United States who were employed in the financial‐services industry. Based on these processes, we empirically examine the relationship between responses to operational uncertainty and process performance after controlling for customer mix, other uncertainty sources, and process type characteristics. Our findings suggest that process improvement—an uncertainty reduction approach related to the internal functioning of the process—as well as several uncertainty coping approaches are associated with better performing processes. However, uncertainty reduction approaches related to customer involvement with, and demands on, the process are not associated with better performing processes. We discuss the implications of our findings for determining what actions managers can take to reduce the negative performance effects of operational uncertainty and how managers can decide which of these actions to take. We conclude with a discussion of the limitations of our study.     

Event Exchangeability: Probabilistic Sophistication Without Continuity or Monotonicity

Building on the Ramsey–de Finetti idea of event exchangeability, we derive a characterization of probabilistic sophistication without requiring any of the various versions of monotonicity, continuity, or comparative likelihood assumptions imposed by Savage (1954), Machina and Schmeidler (1992), and Grant (1995). Our characterization identifies a unique and finitely‐additive subjective probability measure over an algebra of events.     

Bayesian calibration of computer models

We consider prediction and uncertainty analysis for systems which are approximated using complex mathematical models. Such models, implemented as computer codes, are often generic in the sense that by a suitable choice of some of the model's input parameters the code can be used to predict the behaviour of the system in a variety of specific applications. However, in any specific application the values of necessary parameters may be unknown. In this case, physical observations of the system in the specific context are used to learn about the unknown parameters. The process of fitting the model to the observed data by adjusting the parameters is known as calibration. Calibration is typically effected by ad hoc fitting, and after calibration the model is used, with the fitted input values, to predict the future behaviour of the system. We present a Bayesian calibration technique which improves on this traditional approach in two respects. First, the predictions allow for all sources of uncertainty, including the remaining uncertainty over the fitted parameters. Second, they attempt to correct for any inadequacy of the model which is revealed by a discrepancy between the observed data and the model predictions from even the best-fitting parameter values. The method is illustrated by using data from a nuclear radiation release at Tomsk, and from a more complex simulated nuclear accident exercise.     

Production under Uncertainty and Choice under Uncertainty in the Emergence of Generalized Expected Utility Theory

This paper presents a personal view of the interaction between the analysis of choice under uncertainty and the analysis of production under uncertainty. Interest in the foundations of the theory of choice under uncertainty was stimulated by applications of expected utility theory such as the Sandmo model of production under uncertainty. This interest led to the development of generalized models including rank-dependent expected utility theory. In turn, the development of generalized expected utility models raised the question of whether such models could be used in the analysis of applied problems such as those involving production under uncertainty. Finally, the revival of the state-contingent approach led to the recognition of a fundamental duality between choice problems and production problems. This revised version was published online in June 2006 with corrections to the Cover Date.