中国传统经济伦理思想的近代演变初论

中国传统经济伦理核心内容是对营利和私有产权的价值合理性的否定,中国传统经济伦理思想的近代(演变)可界定为鸦片战争前后至五四新文化运动时期资本主义性质的反传统衍变;其现代(演变)则是“五四”之后,资本主义和社会主义经济伦理思想相互交锋、消长、排斥与“融合”的历史进程。传统经济伦理思想近代演变的实质是为资本活动方式或资本的利益寻求工具价值和伦理合理性的过程,中国传统经济伦理的近代演变最终否定了资本主义经济制度的伦理价值合理性、确立了社会主义经济制度的伦理价值合理性。     

企业伦理:意涵及其功能

企业伦理从日常伦理衍生而来,但也具有自身的场域逻辑;企业伦理主要涵括企业之于社会系统的责任伦理和企业中“利益相关者”之间的职业伦理;企业伦理的功能渐次演绎为“约束效用”、“工具效用”以及“价值效用”;在一定情境下,企业伦理与其组织功效、经济绩效其实还存在着一种“兼容性”。     

Integrated Support from Problem Structuring through to Alternative Evaluation Using COPE and V·I·S·A

Work in the field of multiple criteria analysis has generally focused on evaluation procedures, taking as its starting point a well-defined problem with specified alternatives and criteria. However, in reality, problems are rarely so well-structured; hence, in order to usefully support decision making in practice, multiple criteria analysts need to address the issue of problem structuring. In this respect, much can be learned from the body of work stemming from operational research and systems in the U.K., known collectively as problem-structuring methods. In this paper we describe a study which sought to integrate one of these approaches, SODA (strategic options development and analysis), using the COPE software for cognitive mapping, with multiple criteria evaluation based on a multi-attribute value function using V·I·S·A. The study took the form of a 2 day action research workshop to explore the strategic direction of the Supplies and Commercial Services Department of a large U.K. NHS Hospital Trust and to develop an action plan consistent with the agreed direction. Even though the workshop was intended to be exploratory, from the point of view of both the facilitators and the participants, it enabled the group to make progress towards the definition of a strategic direction and led to an increased understanding and awareness of the issues. Drawing on this experience, we comment in general on the potential benefits arising from the integration of these two approaches and suggest fruitful areas for future research and development of the software tools and associated methodologies. © 1997 by John Wiley & Sons, Ltd. J. Multi-Crit. Decis. Anal. 6 : 115–130 (1997) No. of Figures: 9. No. of Tables: 0. No. of References: 37.     

Decomposition,Interdependence and Precision in Multiattribute Utility Measurements

Traditionally, parameters of multiattribute utility models, representing a decision maker's preference judgements, are treated deterministically. This may be unrealistic, because assessment of such parameters is potentially fraught with imprecisions and errors. We thus treat such parameters as stochastic and investigate how their associated imprecision/errors are propagated in an additive multiattribute utility function in terms of the aggregate variance. Both a no information and a rank order case regarding the attribute weights are considered, assuming a uniform distribution over the feasible region of attribute weights constrained by the respective information assumption. In general, as the number of attributes increases, the variance of the aggregate utility in both cases decreases and approaches the same limit, which depends only on the variances as well as the correlations among the single-attribute utilities. However, the marginal change in aggregate utility variance decreases rather rapidly and hence decomposition as a variance reduction mechanism is generally useful but becomes relatively ineffective if the number of attributes exceed about 10. Moreover, it was found that utilities which are positively correlated increase the aggregate utility variance, hence every effort should be made to avoid positive correlations between the single-attribute utilities. We also provide guidelines for determining under what condition and to what extent a decision maker should decompose to obtain an aggregate utility variance that is smaller than that of holistic assessments. Extensions of the current model and empirical research to support some of our behavioural assumptions are discussed. © 1997 John Wiley & Sons, Ltd.     

Approximation of Value Efficient Solutions

We introduce an approximation set to the value efficient set in multiobjective problems under partial information on the decision maker's preferences modelled by a vector value function. We show monotonicity and convergence properties based on increasingly precise vector value functions with two components, which improve the approximation and might be a support to possible solution methods. © 1997 John Wiley & Sons, Ltd.     

Personal Value,Biographical Identity,and Retrospective Attitudes

We all could have had better lives, yet often do not wish that our lives had gone differently, especially when we contemplate alternatives that vastly diverge from our actual life course. What, if anything, accounts for such conservative retrospective attitudes? I argue that the right answer involves the significance of our personal attachments and our biographical identity. I also examine other options, such as the absence of self-to-self connections across possible worlds and a general conservatism about value.     

The influence of number line estimation precision and numeracy on risky financial decision making

This study examined whether different aspects of mathematical proficiency influence one's ability to make adaptive financial decisions. “Numeracy” refers to the ability to process numerical and probabilistic information and is commonly reported as an important factor which contributes to financial decision‐making ability. The precision of mental number representation (MNR), measured with the number line estimation (NLE) task has been reported to be another critical factor. This study aimed to examine the contribution of these mathematical proficiencies while controlling for the influence of fluid intelligence, math anxiety and personality factors. In our decision‐making task, participants chose between two options offering probabilistic monetary gain or loss. Sensitivity to expected value was measured as an index for the ability to discriminate between optimal versus suboptimal options. Partial correlation and hierarchical regression analyses revealed that NLE precision better explained EV sensitivity compared to numeracy, after controlling for all covariates. These results suggest that individuals with more precise MNR are capable of making more rational financial decisions. We also propose that the measurement of “numeracy,” which is commonly used interchangeably with general mathematical proficiency, should include more diverse aspects of mathematical cognition including basic understanding of number magnitude.     

Out-of-bag Prediction Error: A Cross Validation Index for Generalized Structured Component Analysis

Cross validation is a useful way of comparing predictive generalizability of theoretically plausible a priori models in structural equation modeling (SEM). A number of overall or local cross validation indices have been proposed for existing factor-based and component-based approaches to SEM, including covariance structure analysis and partial least squares path modeling. However, there is no such cross validation index available for generalized structured component analysis (GSCA) which is another component-based approach. We thus propose a cross validation index for GSCA, called Out-of-bag Prediction Error (OPE), which estimates the expected prediction error of a model over replications of so-called in-bag and out-of-bag samples constructed through the implementation of the bootstrap method. The calculation of this index is well-suited to the estimation procedure of GSCA, which uses the bootstrap method to obtain the standard errors or confidence intervals of parameter estimates. We empirically evaluate the performance of the proposed index through the analyses of both simulated and real data.     

Forward inference in risky choice: Mapping gaze and decision processes

The study of cognitive processes is built on a close mapping between three components: overt gaze behavior, overt choice, and covert processes. To validate this overt–covert mapping in the domain of decision‐making, we collected eye‐movement data during decisions between risky gamble problems. Applying a forward inference paradigm, participants were instructed to use specific decision strategies to solve those gamble problems (maximizing expected values or applying different choice heuristics) during which gaze behavior was recorded. We revealed differences between overt behavior, as indicated by eye movements, and covert decision processes, instructed by the experimenter. However, our results show that the overt–covert mapping is for some eye‐movement measures not as close as expected by current decision theory, and hence question reverse inference as being prone to fallacies due to a violation of its prerequisite, that is, a close overt–covert mapping. We propose a framework to rehabilitate reverse inference.     

Is the victim Max (Planck) or Moritz? How victim type and social value orientation affect dishonest behavior

Does the potential victim of dishonest behavior—a family or a bank, a pensioner or an insurance firm—affect the propensity to engage in such behavior? We investigate the effect of victim type—an individual person or an impersonal institution—on dishonest behavior and test whether it interacts with potential perpetrators' social value orientation (prosocial or proself). In a between‐subjects design, we allowed experimental participants (N = 368) to misreport private information in order to increase (decrease) their profit (loss) at the expense of either another participant or the experimenter's budget. Both prosocials and proselfs engaged in dishonesty, but proselfs did so much more. Furthermore, prosocials reduced their dishonesty when the victim was another person, rather than an institution, but proselfs did not. A direct implication is that the dishonesty of prosocials may be curbed by increasing the salience of the adverse effect their dishonesty has on other individual people but that such interventions will not be effective for proselfs. In contrast with recent results, we did not find a general effect of increased dishonesty under a loss (vs. gain) frame.