Tailoring value elicitation to decision makers' numeracy and fluency: Expressing value judgments in numbers or words

In organizational settings, options evaluation requires managers to express value judgments on multiple criteria. This research investigates the influence of decision makers' numeracy (ability to use appropriate numerical principles) and fluency (ability to express oneself in words) on their subjective experience of value elicitation as supported by two different techniques: direct rating and MACBETH. The former asks for value judgments to be expressed numerically, the latter non-numerically. The results of our experiment indicate that the two techniques are not psychologically equivalent: decision makers with higher numeracy express values more easily when assisted by the numerical technique whereas decision makers with higher fluency find value elicitation easier with the non-numerical technique. These findings highlight the importance of tailoring value elicitation to decision makers' numeracy and fluency. Implications for decision scientists and analysts are discussed.     

A Consistency Test for AHP Decision Makers

Saaty's analytic hierarchy process assessed attribute importance by soliciting decision makers' (DM) importance ratios to compute weights. Saaty suggested a decision rule for accepting DM judgments based on a consistency measure derived from the DM's importance ratios. This paper investigates the distribution of random inconsistency and decision rule implications. Stricter consistency requirements for three- and four-attribute criteria matrices are suggested.     

The Efficacy of a Decision Support System in Enhancing Risk Assessment Performance

A pervasive challenge for decision‐makers is evaluating data of varying form (e.g., quantitative vs. qualitative) and credibility in arriving at an overall risk assessment judgment. The current study tests the efficacy of a Decision Support System (DSS) for facilitating auditors’ evaluation and assimilation of financial and nonfinancial information in accurately assessing the risk of material misstatements (RMM) in financial information. Utilizing the proximity compatibility principle, the DSS manipulates the display of cues either in an integral (where pieces of information are displayed on one computer screen) or separable (where pieces of information are displayed on different computer screens) format. Based on cognitive fit theory, we expect that the integral (separable) display best supports financial (nonfinancial) information processing, leading to enhanced risk assessment performance. In addition, we predict that consistent DSS display of financial and nonfinancial information facilitates risk assessment performance. Further, this study accentuates the importance of auditors’ preference for presentation of financial and nonfinancial information and consistent presentation of all the information in strengthening the effect of DSS display format on risk assessment performance. We design a case which includes a seeded high fraud risk. A total of 112 audit seniors participated in the experiment where the DSS display format was manipulated and the auditors’ RMM assessments and display preferences were measured. The results support the hypotheses and highlight the value of the DSS in enhancing risk assessment performance.     

Propensity to adopt technological innovations: the impact of personal characteristics and organizational context

This study investigated how personal characteristics and organizational context are associated with strategic decision makers' intentions to adopt technological innovations. Positive significant relationships were found between hospital top managers' intentions to adopt potential innovations and risk propensity, self-efficacy, perceived organizational strategy, perceived information processing capacity, and perceived resource availability. The impact of personal and organizational factors on intentions to adopt, implications of our results, and future research directions are discussed.     

Effects of Information Sequence and Irrelevant Distractor Information When Using a Computer‐based Decision Aid*

Computer‐based decision aids are intended to support and improve human judgments. Frequently, the largest portion of the design effort is devoted to the technical aspects of the system; behavioral aspects are often overlooked. As a result, the decision aid may be ineffective. An experiment was conducted to examine the effects of two information structure variables that theoretically affect judgments: information sequence and irrelevant distractor information. Auditor subjects made continuing existence judgments for client‐banks after interacting with one of four alternative decision aids. The decision aids are modifications of a system developed by an international CPA firm. Judgments were predicted to be more accurate when: (1) diagnostic information is presented late rather than early in the information sequence and (2) when no irrelevant distractor information is presented. Further, judgment confidence was predicted to be unrelated to either information sequence or irrelevant distractor information. The experimental data support all three predictions.     

Summarizing Risk Using Risk Measures and Risk Indices

Our society is fascinated with risk in many different areas and disciplines. One of the main ways to describe and communicate the level of risk is through risk indices, which summarize risk using numbers or categories such as words, letters, or colors. These indices are used to communicate risks to the public, understand how risk is changing over time, compare among different risks, and support decision making. Given the different methods to construct risk indices, including flawed methods such as risk matrices, this article develops specific steps that analysts can follow to create a risk index. This article emphasizes the importance of describing risk with a probability distribution, developing a numerical risk measure that summarizes the probability distribution, and finally translating the risk measure to an index. Measuring the risk is the most difficult part and requires the analyst to summarize a probability distribution into one or possibly a few numbers. The risk measure can then be transformed to a numerical or categorical index. I apply the method outlined in this article to construct a risk index that compares the risk of fatalities in aviation and highway transportation.     

Sizing Up a Superstorm: Exploring the Role of Recalled Experience and Attribution of Responsibility in Judgments of Future Hurricane Risk

Research suggests that hurricane‐related risk perception is a critical predictor of behavioral response, such as evacuation. Less is known, however, about the precursors of these subjective risk judgments, especially when time has elapsed from a focal event. Drawing broadly from the risk communication, social psychology, and natural hazards literature, and specifically from concepts adapted from the risk information seeking and processing model and the protective action decision model, we examine how individuals’ distant recollections, including attribution of responsibility for the effects of a storm, attitude toward relevant information, and past hurricane experience, relate to risk judgment for a future, similar event. The present study reports on a survey involving U.S. residents in Connecticut, New Jersey, and New York (n = 619) impacted by Hurricane Sandy. While some results confirm past findings, such as that hurricane experience increases risk judgment, others suggest additional complexity, such as how various types of experience (e.g., having evacuated vs. having experienced losses) may heighten or attenuate individual‐level judgments of responsibility. We suggest avenues for future research, as well as implications for federal agencies involved in severe weather/natural hazard forecasting and communication with public audiences.     

Individual differences in numerical representations of risk in health decision making: A fuzzy-trace theory approach

Fuzzy-trace theory predicts that decisionmakers process numerical information about risk at multiple levels in parallel: the simplest level, nominal (categorical some-none) gist, and at more fine-grained levels, involving relative comparison (ordinal less-more gist) and exact quantities (verbatim representations). However, little is known about how individual differences in these numerical representations relate to judgments and decisions, especially involving health tradeoffs and relative risks. To investigate these differences, we administered measures of categorical and ordinal gist representations of number, objective numeracy, and intelligence in two studies (Ns = 978 and 956). In both studies, categorical and ordinal gist representations of number predicted risk judgments and decisions beyond objective numeracy and intelligence. Participants with higher scores in categorical gist were more likely to choose options to avoid cancer recurrence risks; those who were higher in ordinal gist of numbers were more likely to discriminate relative risk of skin cancer; and those with higher scores in objective numeracy were more likely to choose options that were numerically superior overall in terms of relative risk of skin cancer and of genetic risks of breast cancer (e.g., lower numerical probability of cancer). Results support parallel-processing models that assume multiple representations of numerical information about risk, which vary in precision, and illustrate how individual differences in numerical representations are relevant to tradeoffs and risk comparisons in health decisions. These representations cannot be reduced to one another and explain psychological variations in risk processing that go beyond low versus high levels of objective numeracy.     

Capturing and Integrating Knowledge for Managing Risks in Tunnel Works

Risk‐related knowledge gained from past construction projects is regarded as potentially extremely useful in risk management. This article describes a proposed approach to capture and integrate risk‐related knowledge to support decision making in construction projects. To ameliorate the problem related to the scarcity of risks information often encountered in construction projects, Bayesian Belief Networks are used and expert judgment is elicited to augment available information. Particularly, the article provides an overview of judgment‐based biases that can appear in the elicitation of judgments for constructing Bayesian Networks and the provisos that can be made in this respect to minimize these types of bias. The proposed approach is successfully applied to develop six models for top risks in tunnel works. More than 30 tunneling experts in the Netherlands and Germany were involved in the investigation to provide information on identifying relevant scenarios than can lead to failure events associated with tunneling risks. The article has provided an illustration of the applicability of the developed approach for the case of “face instability in soft soils using slurry shields.”     

Stochastic Judgments in the AHP: The Measurement of Rank Reversal Probabilities

This paper presents a methodology for analyzing Analytic Hierarchy Process (AHP) rankings if the pairwise preference judgments are uncertain (stochastic). If the relative preference statements are represented by judgment intervals, rather than single values, then the rankings resulting from a traditional (deterministic) AHP analysis based on single judgment values may be reversed, and therefore incorrect. In the presence of stochastic judgments, the traditional AHP rankings may be stable or unstable, depending on the nature of the uncertainty. We develop multivariate statistical techniques to obtain both point estimates and confidence intervals of the rank reversal probabilities, and show how simulation experiments can be used as an effective and accurate tool for analyzing the stability of the preference rankings under uncertainty. If the rank reversal probability is low, then the rankings are stable and the decision maker can be confident that the AHP ranking is correct. However, if the likelihood of rank reversal is high, then the decision maker should interpret the AHP rankings cautiously, as there is a subtantial probability that these rankings are incorrect. High rank reversal probabilities indicate a need for exploring alternative problem formulations and methods of analysis. The information about the extent to which the ranking of the alternatives is sensitive to the stochastic nature of the pairwise judgments should be valuable information into the decision-making process, much like variability and confidence intervals are crucial tools for statistical inference. We provide simulation experiments and numerical examples to evaluate our method. Our analysis of rank reversal due to stochastic judgments is not related to previous research on rank reversal that focuses on mathematical properties inherent to the AHP methodology, for instance, the occurrence of rank reversal if a new alternative is added or an existing one is deleted.     

Group leadership and shared task representations in decision making groups

The development of adequate shared understanding of the task is of critical importance to group functioning. Group leaders play an important role in this respect, as a key function of leadership is to shape group members' understanding of their job. In the present study we focus on decision making groups with distributed information and examine how group leaders shape members' mental representations of the group decision task through leadership behavior rooted in their own representations of the task. We propose that the extent to which the group leader has task representations that emphasize information exchange and integration affects group members' task representations, group information elaboration, and decision quality. We tested these hypotheses in an experiment (N = 94 three-person groups) in which we manipulated whether a group leader was present and whether this leader held representations emphasizing information elaboration. Results supported the hypotheses, and suggest that team leaders may play an important role in creating a socially shared understanding of team tasks.     

Does Concern‐Driven Risk Management Provide a Viable Alternative to QRA?

This article discusses a concept of concern-driven risk management, in which qualitative expert judgments about whether concerns warrant specified risk management interventions are used in preference to quantitative risk assessment (QRA) to guide risk management decisions. Where QRA emphasizes formal quantitative assessment of the probable consequences caused by the recommended actions, and comparison to the probable consequences of alternatives, including the status quo, concern-driven risk management instead emphasizes perceived urgency or severity of the situation motivating recommended interventions. In many instances, especially those involving applications of the precautionary principle, no formal quantification or comparison of probable consequences for alternative decisions is seen as being necessary (or, perhaps, possible or desirable) prior to implementation of risk management measures. Such concern-driven risk management has been recommended by critics of QRA in several areas of applied risk management. Based on case studies and psychological literature on the empirical performance of judgment-based approaches to decision making under risk and uncertainty, we conclude that, although concern-driven risk management has several important potential political and psychological advantages over QRA, it is not clear that it performs better than (or as well as) QRA in identifying risk management interventions that successfully protect human health or achieve other desired consequences. Therefore, those who advocate replacing QRA with concern-driven alternatives, such as expert judgment and consensus decision processes, should assess whether their recommended alternatives truly outperform QRA, by the criterion of producing preferred consequences, before rejecting the QRA paradigm for practical applications.     

A fuzzy AHP application in government-sponsored R&D project selection

Due to the funding scale and complexity of technology, the selection of government sponsored technology development projects can be viewed as a multiple-attribute decision that is normally made by a review committee with experts from academia, industry, and the government. In this paper, we present a fuzzy analytic hierarchy process method and utilize crisp judgment matrix to evaluate subjective expert judgments made by the technical committee of the Industrial Technology Development Program in Taiwan. Our results indicate that the scientific and technological merit is the most important evaluation criterion considered in overall technical committees. We demonstrate how the relative importance of the evaluation criteria changes under various risk environments via simulation.     

Experiments in Lay Cues to the Relative Validity of Positions Taken by Disputing Groups of Scientists

Risk analysis and hazard management can prompt varied intra‐scientific disputes, some which have or will become public, and thus potentially available for lay judgments of the relative validity of the positions taken. As attentive laypeople may include elites as well as the general public, understanding whether and how cues to credibility of disputing groups of scientists might shape those lay judgments can be important. Relevant literatures from philosophy, social studies of science, risk analysis, and elsewhere have identified potential cues, but not tested their absolute or relative effects. Two experiments with U.S. online panel members tested multiple cues (e.g., credentials, experience, majority opinions, research quality) across topics varying in familiarity subject to actual intra‐science disputes (dark matter, marijuana, sea‐level rise). If cues supported a position, laypeople were more likely to choose it as relatively more valid, with information quality, majority “vote,” experience, and degree source as the strongest, and interest, demographic, and values similarity as the weakest, cues. These results were similar in overall rankings to those from implicit rankings of cue reliability ratings from an earlier U.S. online survey. Proposed moderators were generally nonsignificant, but topic familiarity and subjective topic knowledge tended to reduce cue effects. Further research to confirm and extend these findings can inform both theory about citizen engagement with scientific and risk disputes, and practice in communication about science and risk.     

The Impact of Ethical Tools on Aggressiveness in Financial Reporting

The proposed adoption of International Financial Reporting Standards (IFRS) in the United States has ignited a debate as to whether the principles‐based nature of these standards better serves the interests of investors. While it is argued that these principled‐based standards will encourage more transparent financial reporting than the current rules‐based U.S. standards, critics argue that IFRS will invite more aggressive financial reporting through the liberal exercising of professional judgment. This empirical study aims to understand what individual and organizational factors may affect aggressiveness when making accounting judgments. In particular, we examine the influence that prior ethics training, codes of ethics and an individual's predominant moral reasoning schema have on adherence to company policy in an accounting‐related (depreciation) judgment. Results of the study show that respondents with prior ethics training are more likely to adhere to company accounting policy than those who have not had formal ethics education. Respondents presented with a company ethics code also were less aggressive in their accounting judgments than those who were not presented with a code prior to reading the scenario. Finally, decision aggressiveness was moderated by individuals who used conventional moral reasoning schemas.     

What Motivates Individuals to Protect Themselves from Risks: The Case of Wildland Fires

This research investigates the cognitive perceptual process that homeowners go through when faced with the decision to protect themselves from the risk of wildfires. This decision can be examined by looking at the interaction between the integrated protection motivation theory-transtheoretical model and different levels of homeowners' subjective knowledge related to wildfire risks. We investigated the role of motivation, decision stages of risk readiness, and subjective knowledge on the number of risk-mitigating actions undertaken by homeowners living in high-risk communities. The results indicate that homeowners who are in an early or precontemplative stage (both low and high subjective knowledge) as well as low knowledge contemplatives are motivated by their perceived degree of vulnerability to mitigate the risk. In contrast, high knowledge contemplatives' potential behavioral changes are more likely to be motivated by increasing their perceptions of the severity of the risk. Risk-mitigating behaviors undertaken by high knowledge action homeowners are influenced by their perceptions of risk severity, self-efficacy, and response efficacy. In contrast, the low knowledge action homeowners engage in risk reduction behaviors without the influence of any of the PMT variables; demonstrating their motivation to emulate others in their community. These results have implications for the type of information that should be used to effectively communicate risks in an effort to influence the diverse homeowner segments to engage in risk-reduction behaviors.     

审计师关注客户所在地区社会信任水平吗? ——基于Pecking Order模型的研究

文章利用CGSS调查数据度量客户所在地区的社会信任水平,进而考察其对审计师决策的影响。文章首先分别考察了社会信任水平与审计定价、出具非标审计意见的倾向、审计师变更之间的关系,结果发现,公司所在地区的社会信任水平与审计定价、审计师变更均呈显著负向关系,表明审计师会对位于高社会信任地区的客户收取更低的审计费用、审计契约更为稳定,但社会信任与审计师出具非标意见的倾向之间没有显著关联。有序Logistic检验结果表明,在审计定价和审计师变更决策之间,审计师存在优先选择次序:对于低社会信任地区客户,他们会优先通过提高审计收费的手段来控制相关风险。只有在风险超出其承受力、不能通过提高审计费用来控制时,才会放弃客户。此外,文章还发现,地区法治水平能够缓解社会信任对审计师决策的影响。这一研究有助于加深社会信任与审计师决策之间关系的理解,并有助于理解审计师的风险管理策略。     

多专家判断的模糊偏好信息集结规划方法

本文给出了一种群决策中通过专家判断矩阵集结专家判断信息的方法。在考虑各专家具有不同强度的偏好效用和容许部分专家给出不完整信息的情况下,将专家判断信息集结转化为一类模糊规划问题,通过最大化群组满意度获得最终的群决策结果。最后,本文通过一个算例说明该方法的可行性及有效性。     

Decision Making with Uncertain Judgments: A Stochastic Formulation of the Analytic Hierarchy Process*

In the analytic hierarchy process (AHP), priorities are derived via a deterministic method, the eigenvalue decomposition. However, judgments may be subject to error. A stochastic characterization of the pairwise comparison judgment task is provided and statistical models are introduced for deriving the underlying priorities. Specifically, a weighted hierarchical multinomial logit model is used to obtain the priorities. Inference is then conducted from the Bayesian viewpoint using Markov chain Monte Carlo methods. The stochastic methods are found to give results that are congruent with those of the eigenvector method in matrices of different sizes and different levels of inconsistency. Moreover, inferential statements can be made about the priorities when the stochastic approach is adopted, and these statements may be of considerable value to a decision maker. The methods described are fully compatible with judgments from the standard version of AHP and can be used to construct a stochastic formulation of it.