Model Decision
Decision-making in complex systems: Relationship between scale of change and performance
Kambiz Maani & Anson Li
Systems Research and Behavioral Science, September/October 2010, Pages 567-584
Abstract:
Empirical research as well as numerous cases studying managers across diverse disciplines, cultures, and industries reveal consistent patterns of counter-productive decision-making. In this regard, decision-makers appear to exhibit an unmistakable tendency to ‘over-intervene' in the systems (companies, organizations, cities, communities, etc.) they are responsible for. This suggests an inadequate appreciation and understanding of the dynamics underlying decision-making, generating unwarranted and excessive fluctuations and instability in organizations. Numerous studies have observed such phenomena in simulated and experimental settings. Research results, as well as in-depth case studies highlight a number of assumptions and mental models commonly held by decision-makers and managers with adverse effect on organizational dynamics and performance. This paper reports on extensive empirical research and findings elicited from subjects interacting with realistic simulation models of organizations (microworlds) to investigate the relationship between scale of intervention and performance. The results show that while large-scale interventions appear to be effective in the start-up phase of systems (e.g. new products, markets, companies) they are generally counter-productive in mature systems operating at steady state. The results support findings from organizational case studies, notably, the extensive study of ‘Good to Great' firms.
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Joseph Arvai & Ann Froschauer
Journal of Risk Research, forthcoming
Abstract:
Process-based considerations are generally accepted by experts and analysts as being the fundamental drivers of decision quality. However, little work has been done to account for the role of a risk management decision's outcome as a key driver of the public judgments about decision quality. To this end, the objective of the research reported here was straightforward to determine - via an experiment - the relative importance of decision-making process and the associated outcome in lay evaluations of decision quality. Our results demonstrate that people seem to have a difficult time unpacking decision-making processes, even ones they strongly prefer, from their associated outcomes when evaluating decision quality. From a practical standpoint, our results cast doubt on the generally accepted belief that participatory and deliberative decision-making processes (e.g., for risk management) will - on their own - contribute to positive evaluations of decision quality.
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Predicting behavior in economic games by looking through the eyes of the players
Barbara Mellers, Michael Haselhuhn, Philip Tetlock, José Silva & Alice Isen
Journal of Experimental Psychology: General, forthcoming
Abstract:
Social scientists often rely on economic experiments such as ultimatum and dictator games to understand human cooperation. Systematic deviations from economic predictions have inspired broader conceptions of self-interest that incorporate concerns for fairness. Yet no framework can describe all of the major results. We take a different approach by asking players directly about their self-interest - defined as what they want to do (pleasure-maximizing options). We also ask players directly about their sense of fairness - defined as what they think they ought to do (fairness-maximizing options). Player-defined measures of self-interest and fairness predict (a) the majority of ultimatum-game and dictator-game offers, (b) ultimatum-game rejections, (c) exiting behavior (i.e., escaping social expectations to cooperate) in the dictator game, and (d) who cooperates more after a positive mood induction. Adopting the players' perspectives of self-interest and fairness permits better predictions about who cooperates, why they cooperate, and when they punish noncooperators.
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Itamar Simonson & Aner Sela
Journal of Consumer Research, forthcoming
Abstract:
While constructed preferences have received a great deal of attention, there has been virtually no research regarding the genetic basis of consumer judgment and choice. In this research, we examine a wide range of previously unexplored heritable effects on consumer choices and judgments. Moreover, whereas prior research on heritable traits has typically employed a piecemeal approach, demonstrating each heritable trait separately, we propose an alternative way to simultaneously explore common mechanisms and links among heritable traits and behaviors. Using a classic twins study design, we find a large heritable effect on preferences for (a) compromise (but not dominating) options, (b) sure gains, (c) an upcoming feasible, dull assignment, (d) maximizing, (e) utilitarian options, and (f) certain products. Conversely, we do not find significant heritable effects regarding judgment heuristics, discounting, and other decision problems. We tentatively propose that the pattern of findings might reflect a generic heritable individual difference relating to "prudence." We discuss the implications of our research with respect to the determinants of preferences and future research on heritable aspects of judgment and choice.
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Do Decisions Shape Preference? Evidence From Blind Choice
Tali Sharot, Cristina Velasquez & Raymond Dolan
Psychological Science, September 2010, Pages 1231-1235
Abstract:
Psychologists have long asserted that making a choice changes a person's preferences. Recently, critics of this view have argued that choosing simply reveals preexisting preferences, and that all studies claiming that choice shapes preferences suffer from a fundamental methodological flaw. Here we address this question directly by dissociating preexisting preferences from decision making. We studied participants who rated different vacation destinations both before and after making a blind choice that could not be guided by preexisting preferences. As an additional control, we elicited ratings in a condition in which a computer made the decision for the participants. We found that preferences were altered after participants made a blind choice, but not after a computer dictated the decision. The results suggest that just as preferences form choices, choices shape preferences.
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When the future feels worse than the past: A temporal inconsistency in moral judgment
Eugene Caruso
Journal of Experimental Psychology: General, forthcoming
Abstract:
Logically, an unethical behavior performed yesterday should also be unethical if performed tomorrow. However, the present studies suggest that the timing of a transgression has a systematic effect on people's beliefs about its moral acceptability. Because people's emotional reactions tend to be more extreme for future events than for past events, and because such emotional reactions often guide moral intuitions, judgments of moral behavior may be more extreme in prospect than in retrospect. In 7 studies, participants judged future bad deeds more negatively, and future good deeds more positively, than equivalent behavior in the equidistant past. In addition, participants thought that future unfair actions deserved more punishment than past unfair actions, and were more willing to sacrifice their own financial gain to be treated fairly in the future compared with in the past. These patterns were explained in part by the stronger emotions that were evoked by thoughts of future events than by thoughts of past events. Taken together, the results suggest that permission for actions with ethical connotations may be harder to get than forgiveness for those same actions, and demonstrate a systematic way in which moral judgments of the same action are inconsistent across time.
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Amitai Shenhav & Joshua Greene
Neuron, 26 August 2010, Pages 667-677
Abstract:
Many important moral decisions, particularly at the policy level, require the evaluation of choices involving outcomes of variable magnitude and probability. Many economic decisions involve the same problem. It is not known whether and to what extent these structurally isomorphic decisions rely on common neural mechanisms. Subjects undergoing fMRI evaluated the moral acceptability of sacrificing a single life to save a larger group of variable size and probability of dying without action. Paralleling research on economic decision making, the ventromedial prefrontal cortex and ventral striatum were specifically sensitive to the "expected moral value" of actions, i.e., the expected number of lives lost/saved. Likewise, the right anterior insula was specifically sensitive to outcome probability. Other regions tracked outcome certainty and individual differences in utilitarian tendency. The present results suggest that complex life-and-death moral decisions that affect others depend on neural circuitry adapted for more basic, self-interested decision making involving material rewards.
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Relating Introspective Accuracy to Individual Differences in Brain Structure
Stephen Fleming, Rimona Weil, Zoltan Nagy, Raymond Dolan & Geraint Rees
Science, 17 September 2010, Pages 1541-1543
Abstract:
The ability to introspect about self-performance is key to human subjective experience, but the neuroanatomical basis of this ability is unknown. Such accurate introspection requires discriminating correct decisions from incorrect ones, a capacity that varies substantially across individuals. We dissociated variation in introspective ability from objective performance in a simple perceptual-decision task, allowing us to determine whether this interindividual variability was associated with a distinct neural basis. We show that introspective ability is correlated with gray matter volume in the anterior prefrontal cortex, a region that shows marked evolutionary development in humans. Moreover, interindividual variation in introspective ability is also correlated with white-matter microstructure connected with this area of the prefrontal cortex. Our findings point to a focal neuroanatomical substrate for introspective ability, a substrate distinct from that supporting primary perception.
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The Calculus of Committee Composition
Eric Libby & Leon Glass
PLoS ONE, September 2010, e12642
Abstract:
Modern institutions face the recurring dilemma of designing accurate evaluation procedures in settings as diverse as academic selection committees, social policies, elections, and figure skating competitions. In particular, it is essential to determine both the number of evaluators and the method for combining their judgments. Previous work has focused on the latter issue, uncovering paradoxes that underscore the inherent difficulties. Yet the number of judges is an important consideration that is intimately connected with the methodology and the success of the evaluation. We address the question of the number of judges through a cost analysis that incorporates the accuracy of the evaluation method, the cost per judge, and the cost of an error in decision. We associate the optimal number of judges with the lowest cost and determine the optimal number of judges in several different scenarios. Through analytical and numerical studies, we show how the optimal number depends on the evaluation rule, the accuracy of the judges, the (cost per judge)/(cost per error) ratio. Paradoxically, we find that for a panel of judges of equal accuracy, the optimal panel size may be greater for judges with higher accuracy than for judges with lower accuracy. The development of any evaluation procedure requires knowledge about the accuracy of evaluation methods, the costs of judges, and the costs of errors. By determining the optimal number of judges, we highlight important connections between these quantities and uncover a paradox that we show to be a general feature of evaluation procedures. Ultimately, our work provides policy-makers with a simple and novel method to optimize evaluation procedures.
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The role of impulses in shaping decisions
Judith Avrahami & Yaakov Kareev
Journal of Behavioral Decision Making, forthcoming
Abstract:
This paper explores the extent to which decision behavior is shaped by short-lived reactions to the outcome of the most recent decision. We inspected repeated decision-making behavior in two versions of each of two decision-making tasks, an individual task and a strategic one. By regressing behavior onto the outcomes of recent decisions, we found that the upcoming decision was well predicted by the most recent outcome alone, with the tendency to repeat a previous action being affected both by its actual outcome and by the outcomes of actions not taken. Because the goodness of predictions based on the most recent outcome did not diminish as participants gained experience with the task, we conclude that repeated decisions are continuously affected by impulsive reactions.
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Chris Smerecnik, Ilse Mesters, Loes Kessels, Robert Ruiter, Nanne De Vries & Hein De Vries
Risk Analysis, September 2010, Pages 1387-1398
Abstract:
Risk communications are an integral aspect of health education and promotion. However, the commonly used textual risk information is relatively difficult to understand for the average recipient. Consequently, researchers and health promoters have started to focus on so-called decision aids, such as tables and graphs. Although tabular and graphical risk information more effectively communicate risks than textual risk information, the cognitive mechanisms responsible for this enhancement are unclear. This study aimed to examine two possible mechanisms (i.e., cognitive workload and attention). Cognitive workload (mean pupil size and peak pupil dilation) and attention directed to the risk information (viewing time, number of eye fixations, and eye fixation durations) were both measured in a between-subjects experimental design. The results suggest that graphical risk information facilitates comprehension of that information because it attracts and holds attention for a longer period of time than textual risk information. Graphs are thus a valuable asset to risk communication practice for two reasons: first, they tend to attract attention and, second, when attended to, they elicit information extraction with relatively little cognitive effort, and finally result in better comprehension.
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Some Epistemological Implications of Economic Complexity
Roger Koppl
Journal of Economic Behavior & Organization, forthcoming
Abstract:
I review some epistemological implications of economic complexity, with an emphasis on Turing computability and algorithmic information theory. I examine an argument from F. A. Hayek's theory of complex phenomena in this context and discuss the apparent implication that economic complexity prevents us from eliminating literary methods from economic science. If literary methods are a necessary part of economic science, then the highest level of mathematical rigor may not ensure high quality analysis if the literary methods we use are not equally rigorous. Hayek seems to point to a literary tradition in social science that may have established informative standards of rigor for the literary parts of economic science.
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Social and Psychological Challenges of Poker
Kyle Siler
Journal of Gambling Studies, September 2010, Pages 401-420
Abstract:
Poker is a competitive, social game of skill and luck, which presents players with numerous challenging strategic and interpersonal decisions. The adaptation of poker into a game played over the internet provides the unprecedented opportunity to quantitatively analyze extremely large numbers of hands and players. This paper analyzes roughly twenty-seven million hands played online in small-stakes, medium-stakes and high-stakes games. Using PokerTracker software, statistics are generated to (a) gauge the types of strategies utilized by players (i.e. the ‘strategic demography') at each level and (b) examine the various payoffs associated with different strategies at varying levels of play. The results show that competitive edges attenuate as one moves up levels, and tight-aggressive strategies--which tend to be the most remunerative--become more prevalent. Further, payoffs for different combinations of cards, varies between levels, showing how strategic payoffs are derived from competitive interactions. Smaller-stakes players also have more difficulty appropriately weighting incentive structures with frequent small gains and occasional large losses. Consequently, the relationship between winning a large proportion of hands and profitability is negative, and is strongest in small-stakes games. These variations reveal a meta-game of rationality and psychology which underlies the card game. Adopting risk-neutrality to maximize expected value, aggression and appropriate mental accounting, are cognitive burdens on players, and underpin the rationality work--reconfiguring of personal preferences and goals--players engage into be competitive, and maximize their winning and profit chances.
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Alterations in choice behavior by manipulations of world model
C.S. Green, C. Benson, D. Kersten & P. Schrater
Proceedings of the National Academy of Sciences, 14 September 2010, Pages 16401-16406
Abstract:
How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) "probability matching" - a consistent example of suboptimal choice behavior seen in humans - occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning.
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Garry Young & Monica Whitty
Computers in Human Behavior, November 2010, Pages 1228-1236
Abstract:
When assessing the appropriateness of massively multiplayer online role-playing games, it is our contention that questions dealing with the morality of their content - especially regarding the more ‘adult' nature of potential interactions - are the wrong sorts of questions to ask. Instead, when considering the permissibility of such games, a more informative strategy is to focus on what gamers are able to deal with, psychologically, especially regarding taboo violation. Thus, we argue that there is nothing morally problematic with online gamespace per se, no matter how prohibitive the simulated behaviour is offline (as long as the space is frequented by adults only). Instead, we should concern ourselves with whether the potential moral freedoms afforded the online gaming community are psychologically healthy: For it is our contention that underlying any change to the gamer's behaviour offline is the need (in some) to seek psychological parity across domains (making congruent one's identity and actions in both the virtual and offline worlds). It is therefore not so much what games are doing to us that is of concern, here, but what we are doing to ourselves through the process of seeking psychological parity.
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The Role of Human-Automation Consensus in Multiple Unmanned Vehicle Scheduling
M.L. Cummings, Andrew Clare & Christin Hart
Human Factors: The Journal of the Human Factors and Ergonomics Society, February 2010, Pages 17-27
Objective: This study examined the impact of increasing automation replanning rates on operator performance and workload when supervising a decentralized network of heterogeneous unmanned vehicles.
Background: Futuristic unmanned vehicles systems will invert the operator-to-vehicle ratio so that one operator can control multiple dissimilar vehicles connected through a decentralized network. Significant human-automation collaboration will be needed because of automation brittleness, but such collaboration could cause high workload.
Method: Three increasing levels of replanning were tested on an existing multiple unmanned vehicle simulation environment that leverages decentralized algorithms for vehicle routing and task allocation in conjunction with human supervision.
Results: Rapid replanning can cause high operator workload, ultimately resulting in poorer overall system performance. Poor performance was associated with a lack of operator consensus for when to accept the automation's suggested prompts for new plan consideration as well as negative attitudes toward unmanned aerial vehicles in general. Participants with video game experience tended to collaborate more with the automation, which resulted in better performance.
Conclusion: In decentralized unmanned vehicle networks, operators who ignore the automation's requests for new plan consideration and impose rapid replans both increase their own workload and reduce the ability of the vehicle network to operate at its maximum capacity.
Application: These findings have implications for personnel selection and training for futuristic systems involving human collaboration with decentralized algorithms embedded in networks of autonomous systems.