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Cognitive control is crucially involved in making (dis)honest decisions. However, the precise nature of this role has been hotly debated. Is honesty an intuitive response, or is will power needed to override an intuitive inclination to cheat? A reconciliation of these conflicting views proposes that cognitive control enables dishonest participants to be honest, whereas it allows those who are generally honest to cheat. Thus, cognitive control does not promote (dis)honesty per se; it depends on one's moral default. In the present study, we tested this proposal using electroencephalograms in humans (males and females) in combination with an independent localizer (Stroop task) to mitigate the problem of reverse inference. Our analysis revealed that the neural signature evoked by cognitive control demands in the Stroop task can be used to estimate (dis)honest choices in an independent cheating task, providing converging evidence that cognitive control can indeed help honest participants to cheat, whereas it facilitates honesty for cheaters.SIGNIFICANCE STATEMENTDishonesty causes enormous economic losses. To target dishonesty with interventions, a rigorous understanding of the underlying cognitive mechanisms is required. A recent study found that cognitive control enables honest participants to cheat, whereas it helps cheaters to be honest. However, it is evident that a single study does not suffice as support for a novel hypothesis. Therefore, we tested the replicability of this finding using a different modality (EEG instead of fMRI) together with an independent localizer task to avoid reverse inference. We find that the same neural signature evoked by cognitive control demands in the localizer task can be used to estimate (dis)honesty in an independent cheating task, establishing converging evidence that the effect of cognitive control indeed depends on a person's moral default.

Measurement of the determinants of socially undesirable behaviors, such as dishonesty, are complicated and obscured by social desirability biases. To circumvent these biases, we used connectome-based predictive modelling (CPM) on resting state functional connectivity patterns in combination with a novel task which inconspicuously measures voluntary cheating to gain access to the neurocognitive determinants of (dis)honesty. Specifically, we investigated whether task-independent neural patterns within the brain at rest could be used to predict a propensity for (dis)honest behaviour. Our analyses revealed that functional connectivity, especially between brain networks linked to self-referential thinking (vmPFC, temporal poles, and PCC) and reward processing (caudate nucleus), reliably correlates, in an independent sample, with participants’ propensity to cheat. Participants who cheated the most also scored highest on several self-report measures of impulsivity which underscores the generalizability of our results. Notably, when comparing neural and self-report measures, the neural measures were found to be more important in predicting cheating propensity.

Contains fulltext : 201325.pdf (Publisher’s version ) (Closed access) Source characteristics are a key determinant of preferences and choice in the interpersonal influence process. Extant literature documents the positive impact of similarity between oneself and an opinion provider on advice taking, but much less is known about how dissimilarity affects choice. While earlier research assumed that people ignore or discount the opinions of dissimilar others, we argue that dissimilarity can lead to preference and choice contrast. We posit that perceptions of dissimilarity trigger a more general hypothesis of dissimilarity. As a result, a preference contrast is observed, driven by people's tendency to interpret the provided opinion in a way that confirms their dissimilarity hypothesis. Five studies confirm the emergence of preference and choice contrast due to dissimilarity, and support the proposed mechanism. We discuss the relevance of proper baseline conditions for (dis)similarity research, as well as implications for research within the domain of interpersonal influence. 12 p.

There is a long-standing debate regarding the cognitive nature of (dis)honesty: Is honesty an automatic response or does it require willpower in the form of cognitive control in order to override an automatic dishonest response. In a recent study (Speer et al., 2020), we proposed a reconciliation of these opposing views by showing that activity in areas associated with cognitive control, particularly the inferior frontal gyrus (IFG), helped dishonest participants to be honest, whereas it enabled cheating for honest participants. These findings suggest that cognitive control is not needed to be honest or dishonest per se but that it depends on an individual’s moral default. However, while our findings provided insights into the role of cognitive control in overriding a moral default, they did not reveal whether overriding honest default behavior (non-habitual dishonesty) is the same as overriding dishonest default behavior (non-habitual honesty) at the neural level. This speaks to the question as to whether cognitive control mechanisms are domain-general or may be context specific. To address this, we applied multivariate pattern analysis to compare neural patterns of non-habitual honesty to non-habitual dishonesty. We found that these choices are differently encoded in the IFG, suggesting that engaging cognitive control to follow the norm (that cheating is wrong) fundamentally differs from applying control to violate this norm.

Abundant research has established the important role of ad-evoked feelings on consumers' reaction to advertising. However, measurement of feelings through explicit self-report is not without its limitations. The current study adds to previous work by showing a sophisticated way of first estimating how arousal is represented in the brain via an independent task (using EEG), and thereafter using this representation to measure arousal in response to advertisements. We then estimate the relationship between the identified process (arousal) and external measures of ad effectiveness (as measured by notability and attitude toward the ad). The results show that the neural measure of arousal is positively associated with notability of ads in the population at large, but may be negatively associated with attitude toward these ads. The implications for the application of EEG in ad testing and for understanding the relationship between arousal and effective advertising are discussed.

Many of the economically most costly forms of unethical behavior such as tax evasion, stock manipulations or movie and music piracy relate to the moral domain of (dis)honesty, in which unethical behavior is not targeted at a clearly identifiable victim. While large individual differences in (dis)honesty are evident, the neurocognitive determinants of this heterogeneity remain elusive. We combined connectome-based predictive modelling (CPM) on resting state functional connectivity patterns with a novel experimental task, which measures spontaneous and voluntary cheating inconspicuously, to investigate how these task-independent neural patterns shape our (dis)honest choices. Our analyses revealed that functional connectivity in a network of regions, including the dorsolateral prefrontal cortex and the inferior frontal gyrus, commonly linked to cognitive control processes, but also the medial prefrontal cortex and temporal pole, associated with self-referential thinking, and the caudate nucleus, linked to reward processing, are of central importance in promoting honesty. In a leave-one-out cross-validation analysis, we show that this neural model can reliably and accurately predict how much an unseen participant will cheat on our task. Participants who cheated the most, also scored highest on several impulsivity measures, which highlights the ecological validity of our task. Notably, when comparing neural and self-report measures, the neural measures were found to be significantly more important in predicting cheating. Our findings suggest that a person’s dis(honest) decisions depend on how well the self-referential thinking network is functionally connected to the control and reward networks.

Cognitive modeling and simulation studies how a human dynamically interacts with the external world. Human performance assessment based on this concept has long been researched in both cognitive sciences and engineering disciplines. However, existing methods have difficulties in describing the uncertain relationships in a human’s knowledge and in considering the uncertainties in the cognitive process. To tackle these issues, we propose a novel cognitive modeling and simulation environment (CMS-BN) by introducing Bayesian networks to represent a human’s knowledge and Monte Carlo simulation to account for the uncertainties in the cognitive process. The proposed environment explicitly models information perception, reasoning and response in a human’s cognitive process. Information perception works as a filtering mechanism to downselect signals from the external world. Reasoning and response are modeled as traversing the human knowledge base represented as a Bayesian network to retrieve knowledge and updating human belief and attention distribution accordingly. Uncertainties in the cognitive process are characterized through Monte Carlo simulation. The proposed environment also models the interplay between the cognitive process and two performance shaping factors, stress and fatigue, though additional factors can be further considered. We expect the proposed environment to be useful in human reliability analysis and human performance improvement.

Every day, we are faced with the conflict between the temptation to cheat for financial gains and maintaining a positive image of ourselves as being a ‘good person’. While it has been proposed that cognitive control is needed to mediate this conflict between reward and our moral self-image, the exact role of cognitive control in (dis)honesty remains elusive. Here, we identify this role, by investigating the neural mechanism underlying cheating. We developed a novel task which allows for inconspicuously measuring spontaneous cheating on a trial-by-trial basis in the MRI scanner. We found that activity in the Nucleus Accumbens promotes cheating, particularly for individuals who cheat a lot, while a network consisting of Posterior Cingulate Cortex, Temporoparietal Junction and Medial Prefrontal Cortex promotes honesty, particularly in individuals who are generally honest. Finally, activity in areas associated with Cognitive Control (Anterior Cingulate Cortex and Inferior Frontal Gyrus) helped dishonest participants to be honest, whereas it promoted cheating for honest participants. Thus, our results suggest that cognitive control is not needed to be honest or dishonest per se, but that it depends on an individual’s moral default.

Nuclear micro-reactors have drawn increasing attention in the nuclear industry since they can be potentially applied for a variety of purposes such as desalination and hydrogen production. Nuclear micro-reactors have unique characteristics (e.g. wider use of automation) compared with currently operating large nuclear power plants. These characteristics inevitably influence operator performance. To perform human reliability analysis and system design optimization, it is necessary to have a thorough investigation of such effects. To this end, in this paper we propose a method based on literature review and evidence theory to analyze human factor correlations for nuclear micro-reactors. A literature review is performed to identify studies related to characteristic human factors for micro-reactors. We divide human factors into independent variables that are used to characterize microreactors (e.g., level of automation) and dependent variables (e.g., situation awareness) that are influenced by the independent variables. The correlations between the independent and dependent variables are extracted from the reviewed studies. We should note that there may be conflicts between the correlations extracted from different studies. To address this problem, we use evidence theory to aggregate the potentially conflicting information to draw final conclusions about the correlations. The results obtained in this study demonstrate the high complexity of the relations between independent and dependent variables, including the uncertainties in the relations, the non-monotonic relations, and the inconsistent effects of one independent variable on different dependent variables. The potential applications of the results in human reliability analysis for nuclear micro-reactors and system design optimization are discussed.

As digital instrumentation and control systems are being progressively introduced into nuclear power plants, a growing number of related technical issues are coming to light needing to be resolved. As a result, an understanding of relevant terms and basic concepts becomes increasingly important. Under the framework of the OECD/NEA WGRISK DIGREL Task Group, the authors were involved in reviewing definitions of terms forming the supporting vocabulary for addressing issues related to the safety and reliability analysis of digital instrumentation and control (SRA of DI&C). These definitions were extracted from various standards regulating the disciplines that form the technical and scientific basis of SRA DI&C. The authors discovered that different definitions are provided by different standards within a common discipline and used differently across various disciplines. This paper raises the concern that a common understanding of terms and basic concepts has not yet been established to address the very specific technical issues facing SRA DI&C. Based on the lessons learned from the review of the definitions of interest and the analysis of dependency relationships existing between these definitions, this paper establishes a set of recommendations for the development of a consistent terminology for SRA DI&C.

People are particularly sensitive to injustice. Accordingly, deeper knowledge regarding the processes that underlie the perception of injustice, and the subsequent decisions to either punish transgressors or compensate victims, is of important social value. By combining a novel decision-making paradigm with functional neuroimaging, we identified specific brain networks that are involved with both the perception of, and response to, social injustice, with reward-related regions preferentially involved in punishment compared with compensation. Developing a computational model of punishment allowed for disentangling the neural mechanisms and psychological motives underlying decisions of whether to punish and, subsequently, of how severely to punish. Results show that the neural mechanisms underlying punishment differ depending on whether one is directly affected by the injustice, or whether one is a third-party observer of a violation occurring to another. Specifically, the anterior insula was involved in decisions to punish following harm, whereas, in third-party scenarios, we found amygdala activity associated with punishment severity. Additionally, we used a pharmacological intervention using oxytocin, and found that oxytocin influenced participants' fairness expectations, and in particular enhanced the frequency of low punishments. Together, these results not only provide more insight into the fundamental brain mechanisms underlying punishment and compensation, but also illustrate the importance of taking an explorative, multimethod approach when unraveling the complex components of everyday decision-making.SIGNIFICANCE STATEMENTThe perception of injustice is a fundamental precursor to many disagreements, from small struggles at the dinner table to wasteful conflict between cultures and countries. Despite its clear importance, relatively little is known about how the brain processes these violations. Taking an interdisciplinary approach, we combine methods from neuroscience, psychology, and economics to explore the neurobiological mechanisms involved in both the perception of injustice as well as the punishment and compensation decisions that follow. Using a novel behavioral paradigm, we identified specific brain networks, developed a computational model of punishment, and found that administrating the neuropeptide oxytocin increases the administration of low punishments of norm violations in particular. Results provide valuable insights into the fundamental neurobiological mechanisms underlying social injustice.

With the increasing dependence on digital instrumentation and control (I&C) systems in nuclear power plants, software has become a significant determinant of system safety assurance. To expand the use of digital technology in the nuclear industry, systematic methods are required for quantifying the safety of software-based I&C systems in safety critical applications. A software safety quantification model limited to the requirements phase is built in this paper based on the causal mechanisms that challenge safety. A preliminary mathematical method was developed to assess the number of requirements faults and their sub-types. A case study is conducted on a function of a reactor protection system to verify the validity of the quantification model.

A dynamic mechanistic model of human response for human reliability analysis is proposed in this paper. The model is comprised of three main components: information perception, knowledge base, and human reasoning and decision making. The activation based approach, which considers both stimulus-driven and goal-directed activations, is adopted model the impact of information perception on the reasoning process. An operator’s knowledge base is represented by a semantic network in the model. Activation propagation theory is applied to model human reasoning and decision making. Illustration of activation propagation through the relief-valve-stuck-open incident in the Three Mile Island accident demonstrates the feasibility of this approach. Additionally, the influences of two significant performance shaping factors, stress and fatigue, are integrated into the model.

PurposeThe purpose of this paper is to investigate how warehouse management, understood as a cluster of planning and control decisions and procedures, is organized and driven by task complexity (TC) and market dynamics (MD).Design/methodology/approachA multi‐variable conceptual model is developed based on the literature and tested among 215 warehouses using a survey.FindingsThe results suggest that TC and MD are the main drivers of warehouse management, measured by planning extensiveness (PE), decision rules complexity, and control sophistication. Differences between production and distribution warehouses are found with respect to the relationship between assortment changes and PE. Furthermore, TC appears to be a main driver of the specificity of the warehouse management (information) system (WMS).Research limitations/implicationsThis paper is based on 215 warehouses in The Netherlands and Flanders (Belgium); future research may test the model on a different sample. More research should be conducted to further validate the measures of the core dimensions of warehouse management.Practical implicationsDifferent levels of TC and MD characterize warehouses. Such a characterization is a first step in determining generic warehouse functionalities and helping managers to decide on the best software for their warehouse operations.Originality/valueThe paper defines the core dimensions of warehouse management, makes them measurable, tests them and assesses how these drivers impact specificity of WMS. The paper shows that PE in production warehouses is driven by different variables than in distribution centers.

Research on language abstraction has primarily been focused on the language that is used to describe (intergroup) behaviors, while limited attention has been given to communication about objects. This article aims to fill this gap and studies biases in language abstraction in the descriptions of interactions with objects. Study 1 demonstrated a linguistic expectancy bias in this setting: People described expectancy-congruent experiences with objects more abstractly than incongruent experiences. Study 2 examined a mediator, and provides data suggesting that expectancy-congruent (vs. incongruent) experiences were more likely attributed to the object (vs. the situation/user), and this causal inference mediated the effect of expectancy-(in)congruence on language use. Study 3 examined the impact of communication goals, and found that the goal to convince a receiver of the high quality of a product (vs. no persuasion goal) led to more abstract descriptions of positive experiences with objects and to more concrete language for negative experiences.

This study validates Rossiter and Percy's (1987) hook theory of presenter characteristics, for celebrity presenters. Firstly, by employing a product-alone control group, the study demonstrates that some celebrity-product pairings have a good fit and can persuade whereas others have no effect or represent such an obviously poor fit that they dissuade consumers from buying the product. Secondly, the study suggests that good fit, and thus persuasion, for celebrity presenters, depends on the audience immediately perceiving that the celebrity is an expert user of the product (for all products) and is a positive role model (for high-risk products). On the other hand, the study reveals that failure of any of four of the celebrity's characteristics causes dissuasion by celebrity presenters; these failures include lack of high visibility (i.e., not widely well-known), perceived inexpertness as a user of the product (a strong negative hook that is probably the reason for the poor fit perception), lack of trust (though this is a weak dissuasive factor for celebrities) and, paradoxically, the celebrity being too likable (for low-risk products). Thirdly, the hook(s) conceptualization of presenter characteristics is superior to the conventional linear conceptualization in that a hook-scored regression model accounted for the same amount of variance in persuasion–dissuasion as did the linear model (adjusted R 2 s of 41% vs. 43%) despite the hook model's handicap of at least one-third lower possible R 2 due to trichotomization of 7-point ratings into positive, neutral, and negative hooks.

Item does not contain fulltext People often conform to others with whom they associate. Surprisingly, however, little is known about the possible hormonal mechanisms that may underlie in-group conformity. Here, we examined whether conformity toward one's in-group is altered by oxytocin, a neuropeptide often implicated in social behavior. After administration of either oxytocin or a placebo, participants were asked to provide attractiveness ratings of unfamiliar visual stimuli. While viewing each stimulus, participants were shown ratings of that stimulus provided by both in-group and out-group members. Results demonstrated that on trials in which the ratings of the in-group and out-group were incongruent, the ratings of participants given oxytocin conformed to the ratings of their in-group but not of their out-group. Participants given a placebo did not show this in-group bias. These findings indicate that administration of oxytocin can influence subjective preferences, and they support the view that oxytocin's effects on social behavior are context dependent. 5 p.

Contains fulltext : 77104_pub.pdf (Publisher’s version ) (Closed access) Contains fulltext : 77104_pre.pdf (Author’s version preprint ) (Open Access) In word-of-mouth marketing, marketers often provide financial rewards for referrals. These rewards introduce a financial motive into an interaction among friends or acquaintances, which may harm the perceived sincerity of the referring customer. We show that this negative effect can be mitigated by disclosing the presence of financial motives, but also by the activation of a market pricing (‘sales’) relationship norm. However, such a norm has a negative effect on compliance with the referral. The effects of relationship norms are strongest when cognitive capacity is impaired, which suggests that the influence of relationship norms occurs outside the awareness of consumers. Conversely, the impact of disclosures is stronger when consumers have full cognitive capacity available. 10 p.

Previous research suggests that people form impressions of others based on their facial appearance in a very fast and automatic manner, and this especially holds for trustworthiness. However, as yet, this process has been investigated mostly in a social vacuum without taking interpersonal factors into account. In the current research, we demonstrate that both the relationship context that is salient at the moment of an interaction and the performed behavior are important moderators of the impact of facial cues on impression formation. It is shown that, when the behavior of a person we encounter is ambiguous in terms of trustworthiness, the relationship most salient at that moment is of crucial impact on whether and how we incorporate facial cues communicating (un)trustworthiness in our final evaluations. Ironically, this can result in less positive evaluations of interaction partners with a trustworthy face compared to interaction partners with an untrustworthy face. Implications for research on facial characteristics, trust, and relationship theories are discussed.

Human behavior is affected by various forms of persuasion. The general persuasive effect of high expertise of the communicator, often referred to as "expert power", is well documented. We found that a single exposure to a combination of an expert and an object leads to a long-lasting positive effect on memory for and attitude towards the object. Using functional magnetic resonance imaging (fMRI), we probed the neural processes predicting these behavioral effects. Expert context was associated with distributed left-lateralized brain activity in prefrontal and temporal cortices related to active semantic elaboration. Furthermore, experts enhanced subsequent memory effects in the medial temporal lobe (i.e. in hippocampus and parahippocampal gyrus) involved in memory formation. Experts also affected subsequent attitude effects in the caudate nucleus involved in trustful behavior, reward processing and learning. These results may suggest that the persuasive effect of experts is mediated by modulation of caudate activity resulting in a re-evaluation of the object in terms of its perceived value. Results extend our view of the functional role of the dorsal striatum in social interaction and enable us to make the first steps toward a neuroscientific model of persuasion.

One of the pressing issues in marketing is whether loyalty programs really enhance behavioral loyalty. Loyalty program members may have a much higher share-of-wallet at the firm with the loyalty program than non-members have, but this does not necessarily imply that loyalty programs are effective. Loyal customers may select themselves to become members in order to benefit from the program. Since this implies that program membership is endogenous, we estimate models for both the membership decision (using instrumental variables) and for the effect of membership on share-of-wallet, our measure of behavioral loyalty. We use panel data from a representative sample of Dutch households who report their loyalty program memberships for all seven loyalty programs in grocery retailing as well as their expenditures at each of the 20 major supermarket chains. We find a small positive yet significant effect of loyalty program membership on share-of-wallet. This effect is seven times smaller than is suggested by a naive model that ignores the endogeneity of program membership. The predictive validity of the proposed model is much better than for the naive model. Our results show that creating loyalty program membership is a crucial step to enhance share-of-wallet, and we provide guidelines on how to achieve this. (c) 2007 Elsevier B.V. All rights reserved.

Executieve functies zijn psychologische processen die een belangrijke rol spelen bij het reguleren van gedrag en het coordineren van handelingen voor specifieke doeleinden. Deze processen omvatten onder andere het vermogen om vooruit te denken, problemen op te lossen, strategieen te bepalen, selectief de aandacht op iets te richten en automatische reacties te inhiberen. In het verleden werd onderzoek op het gebied van executieve functies voornamelijk verricht vanuit een klinische context waarbij de gevolgen van frontaal hersenletsel werden onderzocht.

It has often been proposed, or assumed, that improvisation is a useful metaphor to provide insight into managing and organizing. However, improvisation is more than a metaphor. It is an orientation and a technique to enhance the strategic renewal of an organization. The bridge between theory and practice is made through exercises used to develop the capacity to improvise, borrowed from theatre improvisation. This paper describes a typical improvisation workshop in developing six key areas that link improvisation exercises to the practice of management: interpreting the environment; crafting strategy; cultivating leadership; fostering teamwork; developing individual skills; and assessing organizational culture.

Contains fulltext : 95828.pdf (Publisher’s version ) (Open Access) We often change our behavior to conform to real or imagined group pressure. Social influence on our behavior has been extensively studied in social psychology, but its neural mechanisms have remained largely unknown. Here we demonstrate that the transient downregulation of the posterior medial frontal cortex by theta-burst transcranial magnetic stimulation reduces conformity, as indicated by reduced conformal adjustments in line with group opinion. Both the extent and probability of conformal behavioral adjustments decreased significantly relative to a sham and a control stimulation over another brain area. The posterior part of the medial frontal cortex has previously been implicated in behavioral and attitudinal adjustments. Here, we provide the first interventional evidence of its critical role in social influence on human behavior.

Contains fulltext : 81685.pdf (Publisher’s version ) (Closed access) We often change our decisions and judgments to conform with normative group behavior. However, the neural mechanisms of social conformity remain unclear. Here we show, using functional magnetic resonance imaging, that conformity is based on mechanisms that comply with principles of reinforcement learning. We found that individual judgments of facial attractiveness are adjusted in line with group opinion. Conflict with group opinion triggered a neuronal response in the rostral cingulate zone and the ventral striatum similar to the "prediction error" signal suggested by neuroscientific models of reinforcement learning. The amplitude of the conflict-related signal predicted subsequent conforming behavioral adjustments. Furthermore, the individual amplitude of the conflict-related signal in the ventral striatum correlated with differences in conforming behavior across subjects. These findings provide evidence that social group norms evoke conformity via learning mechanisms reflected in the activity of the rostral cingulate zone and ventral striatum.

Hazard and operability (HAZOP) analysis technique is used to identify and analyze hazards and operational concerns of a system. It provides a structured framework that can be used to perform a step-by-step safety analysis of a system. This paper details how to apply this method to safety-related scientific software. In this paper, we have developed (1) a nomenclature that singles out 30 primary concepts (2) a canonic set of abstractions of software programming constructs as a function of the primary concepts; (3) a process of translation from an existing design representation to the target design representation in the form of finite state machines; (4) HAZOP templates for each canonical form; and (5) an input variable prioritization method. We also developed a computational tool that can be used to perform HAZOP analysis of scientific software. Its results are compared with those obtained during manual HAZOP analysis by calculating the value of Shannon entropy, correctness, and the time required to perform each analysis. Overall, this method helps identify useful information about the impact of variables in the code that can then be utilized to develop robust code for making safety-critical decisions.

De afgelopen tien jaar is de interesse voor executieve functies bij jonge kinderen sterk toegenomen. Terwijl men aanvankelijk dacht dat executieve functies niet functioneel waren voor het twaalfde levensjaar (Golden, 1981) hebben diverse onderzoekers inmiddels aangetoond dat executieve functies zelfs al bij peuters en kleuters waarneembaar zijn (zie voor een overzicht Smidts, 2003). Hierbij moet overigens wel worden aangemerkt dat executieve functies zich bij kinderen anders manifesteren dan bij volwassenen.

Most existing software reliability models estimate the failure intensity function during dynamic testing. While these models are useful engineering tools, they can not be applied to earlier life-cycle phases where pay-off is maximum in terms of avoiding later failures. Few models have been developed to capture phenomena occurring early in the life cycle and their impact on reliability and much research effort is still needed in this area. Our previous research efforts have led to the development of a stochastic model, which relates human errors committed during software development and debugging activities to the software failure intensity function. The software development schedule and other influencing factors (e.g., experience, schedule pressure, etc.) were used to predict human error rates. The model is based on several assumptions. In particular, it is assumed that repair is instantaneous. The present paper attempts to remove this assumption and assesses the impact of repair times on previous findings.

Based on measurements among 332 owner-managers, we investigate how the global shape of the utility function (i.e., S-shaped versus concave or convex over the total range of outcomes) relates to choice behavior. We find that the global shape of the utility function differs across decision makers (about one-third of the owner-managers exhibit an S-shaped utility function) and that the global shape is linked to organizational behavior (i.e., the production system employed), a result that does not change when using different methods to identify the decision maker's global shape of the utility function. The decision maker's risk attitude (risk averse or risk seeking) does not affect the choice of the production system. Whereas the degree of risk aversion, based on the local shape of the utility function, may be important in explaining owner-managers' trading behavior (Pennings and Smidts 2000), more structural organizational behavior appears to be linked to the global shape of the utility function.

In a field study, the concept of intrinsic risk attitude is investigated. Intrinsic risk attitude concerns the relationship between risk attitude, measured by the utility function u(x), and strength of preference, measured by the value function v(x). We study farmers' decision-making vis-à-vis price risk and obtain assessments of risk attitude and strength of preference in two consecutive years in a sample of 253 respondents. This design enables us to investigate the temporal stability of intrinsic risk attitude. Our findings show that risk attitude and strength of preference are two distinctive constructs. More specifically, the hypothesis of a linear relationship between u(x) and v(x) is clearly rejected in favor of an exponential relationship. This exponential relationship implies that our respondents exhibit a constant absolute intrinsic risk attitude for different price levels, during a time period. Differences between respondents in direction and degree of intrinsic risk attitude are substantial and the majority of the respondents are intrinsically risk seeking. No statistically significant change in intrinsic risk attitude could be detected between the two years of measurement. However, the correlation between measures across time appears to be low. In the discussion, issues for further research are identified.

In this paper we present the results of an experimental study of the impact of the quality of a marketing decision support system (MDSS). The experiment was conducted in the MARKSTRAT environment. The quality of an MDSS was operationalized as the predictive precision of its simulation models. The results show that marketing decision-makers using a high-quality MDSS outperform marketing decision-makers using a medium-quality MDSS. The superior performance with the high-quality MDSS was obtained for both low and high time-pressure.