Robust interactive decision-analysis (RID): Behavioral results and implications

We have proposed a novel interactive procedure for performing decision analysis, called Robust Interactive Decision Analysis (RID), which permits a decision maker (DM) to voluntarily and interactively express strong (viz, sure) binary preferences for actions, partial decision functions, and full decision functions, and only imprecise probability and utility function assessments. These serve as INPUTS TO operators to prune the state probability space and decision space until an optimal choice strategy is obtained. The viability of the RID approach depends on a DM's ability to provide such information consistently and meaningfully. On a limited scale we experimentally investigate the behavioral implications of the RID method in order to ascertain its potential operational feasibility and viability. More specifically, we examine whether a DM can (1) express strong preferences between pairs of vectors of unconditional and conditional payoffs or utilities consistently; (2) provide imprecise (ordinal and interval) state probabilities that are individually as well as mutually consistent with the state probabilities imputed from the expressed strong preferences. The results show that a DM can provide strong individually and mutually consistent preference and ordinal probability information. Moreover, most individuals also appear to be able to provide interval probabilities that are individually and mutually consistent with their strong preference inputs. However, the several violations observed, our small sample size, and the limited scope of our investigation suggest that further experimentation is needed to determine whether and/or how such inputs should be elicited. Overall, the results indicate that the RID method is behaviorally viable.     

All's well that ends well? Outcome bias in pilots during instrument flight rules

The objective of the present study was to examine if the Outcome Bias also occurs in pilots flying under instrument flight rules (IFR). In a scenario-based survey, 60 pilots evaluated weather-related decisions made by hypothetical pilots. Participants rated the decisions as better, less risky, and regarded the probability that they would have made the same decision as higher when they were followed by a positive outcome, than when they were followed by a negative outcome. This effect showed likewise for novice pilots and for experienced pilots. These findings could be relevant for the flight-related decision-making of pilots, which sometimes is affected by the decisions made by third-party pilots. In particular, decisions made by other pilots that have led to positive outcomes might be hastily followed, whereas those that have led to negative outcomes might be hastily rejected.     

不同情境中幼儿情绪表达规则认知发展的追踪研究

用追踪研究方法,对60名幼儿在高兴、惊讶与害怕情境中的情绪表达规则认知两年的发展进行探讨,并考察情绪情境、性别和人际背景对其发展的影响。结果表明：(1)幼儿的情绪表达规则知识、目标和策略水平均随年龄增长显著提升;(2)幼儿在害怕情境中为自我保护而较多使用掩饰策略,在惊讶情境中较多使用掩饰和夸大策略,在高兴情境中综合运用掩饰、弱化和夸大策略;(3)性别和人际背景均对幼儿情绪表达规则认知发展有显著影响。     

Psychological determinants of decision attitude

Decision attitude — an analog of risk attitude — is the propensity to make (or avoid making) a decision: in decision aversion, a person finds it more desirable to receive through fiat the better of two options than to have a choice between them; in decision seeking, the choice is more desirable, even though it can lead to nothing better than the best option. Both decision aversion and decision seeking were found in hypothetical scenarios. Experimental manipulations and subjects' justifications point to anticipated regret, fear of blame for poor outcomes, and desire for equitable distributions as sources of decision aversion. One source of decision seeking (for self) and decision aversion (when deciding for others) appears to be the desire for the self-determination of the affected parties. We consider the implications of our results for personal choice and public policy decisions.     

A compensatory approach to optimal selection with mastery scores

A Bayesian approach for simultaneous optimization of test-based decisions is presented using the example of a selection decision for a treatment followed by a mastery decision. A distinction is made between weak and strong rules where, as opposed to strong rules, weak rules use prior test scores as collateral data. Conditions for monotonicity of optimal weak and strong rules are presented. It is shown that under mild conditions on the test score distributions and utility functions, weak rules are always compensatory by nature. The authors are indebted to Wilbert Kallenberg for his valuable comments and to Jan Gulmans for providing the data for the empirical example. The names of the authors are alphabetical; they are equally responsible for the contents of this paper.     

The application of the satir model of family therapy to the families in Hong Kong: A personal reflection

Practitioners in Hong Kong have shown an increasing interest in various family therapy approaches since the 1980s. This paper offers a critique of the major concepts and techniques of the Satir model applied to families in Hong Kong. Cultural considerations are examined in relation to the family structure and hierarchy, the Chinese self and self-esteem, communication patterns, and family rules. Implications for the application of the Satir model of family therapy in Hong Kong are discussed.     

Decisions,actions, and the appropriateness of confidence in knowledge

This research examines the appropriateness of confidence (i.e., subjective probability judgments) in knowledge associated with decisions and actions of social importance. One hundred and thirty seven participants completed a 50 item questionnaire assessing their knowledge of the two leading candidates in the 1988 presidential election in the U.S.A. Ninety one of the respondents completed the questionnaire one week prior to the election, whereas the other 46 completed the questionnaire on election day shortly after voting. After each item in the questionnaire, all respondents indicated whether or not the item content represented a reason why they voted (or intended to vote) for or against the candidate to whom the item referred. Within-person results indicated that, in comparison to items that were not cited as reasons for voting intentions or voting behavior, items endorsed as reasons were characterized by better accuracy and resolution, but worse overconfidence. Between groups, decision makers were significantly more accurate and better calibrated than those who had not made a decision between the candidates. Implications of inappropriate confidence on decision making effectiveness are discussed.     

Do medical decision analyses' largest gains grow from the smallest trees?

Some decision analysts recommend reserving their models for careful, complete study of complex problems. Others believe simple problem analyses provide the greatest gains. To clarify these issues, I tested: (1) whether simple published analyses compared to complex ones, produced results as non-intuitive; and (2) whether non-intuitiveness represented analytic gain (or equivalently, intuitive loss). Very limited data also examined (3) the gain from adding model intricacy for a given problem vs. selecting more complex problems for analysis. To assess two non-intuitiveness measures, 75 subjects (33 physicians and 42) non-physicians stated their intuitive preferences in 40 (22 published and 18 unpublished) medical dilemmas. For both physicians and non-physicians, simpler models (those with lees than 30 terminal branches in the decision tree) had about one third the non-intuitiveness of more complex ones. Three tests also supported the premise that analyses outperform intuition, therefore that on average the formers' non-intuitiveness reflects less analytic gain. In addition, for different models of the same problem, tree complexity did not correlate with gain. Thus, simpler trees may not generally gain less because they inadequately describe problems. Instead, simpler analyses may represent simpler problems, with more similar intuitive and formal solutions. If so, these findings may help us avoid some costly but unnecessary simple analyses.     

Decision Support System and Multi‐Criteria Decision Aid: A State of the Art and Perspectives

The aim of this paper is to highlight the role of the Decision Support System within the field of multi‐criteria decision aid (MCDA). The MCDA tools have been incorporated into systems to create Multi‐Criteria Decision Support Systems (MCDSSs). In our literature review, we noticed that more than 100 papers have been written over a 20‐year period in which MCDSS was used as a decision‐making tool. The present paper describes some real applications of MCDSS in different fields, harmoniously combined with decision‐making methods such as analytic hierarchy process, Utility Additive, and Goal Programming. The present study proposes an integrative MCDSS evaluation through guidance on the tools most useful for a specific user with a particular decision problem. Copyright © 2014 John Wiley & Sons, Ltd.