Context Effects on Effort and Accuracy in Choice: An Enquiry into Adaptive Decision Making

Klein, Noreen M.; Yadav, Manjit S.

doi:10.1086/209181

Cited by 90 publications

(51 citation statements)

References 10 publications

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“…Consumers' decisions are found to be highly contextdependent (e.g., [19,27,28]). Decision context differs from the consumption situation because decision context variables describe the features of the decision task, whereas a situation describes psychological, physiological and social surroundings of the shopping event.…”

Section: How People Do Decisionsmentioning

confidence: 99%

The future of consumer decision making

Willman-Iivarinen

2017

Eur J Futures Res

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Mediatisation of the world and the increasing power of social networks, means that consumers' choices are more and more based on identity play, gaining social currency and self-branding. Furthermore the choices are significantly influenced by the changes in decision making context for example time pressure and endless opportunities. All these changes affect consumer's decision making that is the choice of decision making strategy. This study is based on theoretical reasoning and empirical data. The results show that the choice of decision making strategy will depend on the social potential the products have. The approach is multidisciplinary, taking elements and ideas from several theoretical frames related to consumer's decision making. This topic is of outmost importance to all BtoC marketers. It is important to know how customers decide and what changes to anticipate. Furthermore, it is important for policymakers who wish to be able to influence consumers' consumption habits in order to make them healthier, greener, more ethical or to favour domestic products. Future developments of variables affecting consumers' choices are estimated and implications for marketing are discussed.

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Section: How People Do Decisionsmentioning

confidence: 99%

The future of consumer decision making

Willman-Iivarinen

2017

Eur J Futures Res

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“…In summary, handicaps fit closely with the definitions afforded relatively high attribute-based complexity: weights assigned to horses are designed to make the race more competitive (Hogarth, 1975), complicated relationships exist between attributes that confound analysis of the set of attributes resulting from subtle interactions between the effect of weight and other factors (Klein & Yadav, 1989), and there is ambiguity in the value of attributes, to the extent that it is difficult to discern to what degree weight allocations can be relied upon. Each of these factors can hinder discrimination between horses based on their past performances because fewer alternatives can be easily eliminated (e.g., Ritov and Baron, 1990).…”

Section: Cognitive Error Propositionmentioning

confidence: 90%

“…However, this is not supported by the fact that no FLB exists in high attribute complexity races (handicaps). Equally, the heuristics explanation does not accord with the existence of FLB in low attribute complexity races, where one might expect the task of selecting a potential winner to involve less effort (Klein & Yadav, 1989), less use of simplifying heuristics (Payne et al, 1993), and less errors (Reason, 1990).…”

Section: Cognitive Error Explanations: Simple Heuristicsmentioning

confidence: 99%

“…A variety of factors has been shown to be related to such ''attribute-based complexity'', including the presence of complicated relationships between attributes (Klein & Yadav, 1989;Sung & Johnson, 2007), relative similarity (e.g., Biggs, Bedard, Gaber, & Linsmeirer, 1985;Bockenholt, Albert, Aschenbrenner, & Schmalhofer, 1991), and ambiguity in the value of attributes (e.g., Ritov & Baron, 1990).…”

Section: Oddsmentioning

confidence: 99%

“…It is not surprising, therefore, that increasing complexity has been shown to be associated with an increase in effort, confusion and choice time (Klein & Yadav, 1989), a rise in the number of errors (Reason, 1990), and a consequent reduction in performance (Jacoby, Speller, & Berning, 1975;Jacoby, Speller, & Kohn, 1974;Malhotra, 1982).…”

Section: Oddsmentioning

confidence: 99%

See 2 more Smart Citations

Complexity as a guide to understanding decision bias: A contribution to the favorite‐longshot bias debate

Sung¹,

Johnson²,

Dror³

2008

Behavioral Decision Making

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This paper investigates the origins of a widespread decision bias in betting markets, the favorite-longshot bias (FLB); in particular, whether it is caused by cognitive errors on the part of bettors or by the pricing policies of bookmakers. The methodology is based on previous literature, which has suggested that: (i) races, as decision tasks for bettors, can be distinguished by their degree of complexity and their attractiveness to those with access to privileged information (insiders), (ii) cognitive errors increase as complexity increases, and (iii) bookmakers set odds in a manner to protect themselves from insiders. The degree of FLB was examined in races of varying complexity and attractiveness to insiders using a dataset of 8545 races drawn from the parallel bookmaker and pari-mutuel markets operating in the UK in 2004. The results, interpreted in the light of the cognitive error and complexity literature, suggest that neither bettors' nor bookmakers' cognitive errors are the main cause of the bias. Rather, bettors' preferences for risk and the deliberate pricing policies of bookmakers play key roles in influencing the bias in markets where bookmakers and pari-mutuel operators coexist.

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Risk strategy under task complexity: a multivariate analysis of behaviour in a naturalistic setting

Johnson

Bruce

1998

J. Behav. Decis. Making

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This study complements the existing literature on decision‐making processes and outcomes in complex settings by exploring the impact of different types of complexity on risk strategies in a naturalistic setting. The study analyses a large sample of decisions made by individuals in UK offcourse betting markets, a fertile environment for observing both a variety of risk strategies and a range of task complexities. Specifically, the investigation focuses on the comparative impacts of complexity defined in terms, respectively, of alternatives and attributes. The results suggest that the risk strategy employed is affected by task complexity. Complexity does not affect the size of risk accepted but alternative‐ and attribute‐based complexity together influence the propensity to accept greater degrees of risk. In addition, the effect of attribute‐based complexity on risk taking appears to be modified by the use of risk‐hedging strategies. The results are observed to corroborate some earlier work on decision process and outcome; where differences with earlier findings are identified, some possible explanations are offered. © 1998 John Wiley & Sons, Ltd.

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Context Effects on Effort and Accuracy in Choice: An Enquiry into Adaptive Decision Making

Cited by 90 publications

References 10 publications

The future of consumer decision making

The future of consumer decision making

Complexity as a guide to understanding decision bias: A contribution to the favorite‐longshot bias debate

Risk strategy under task complexity: a multivariate analysis of behaviour in a naturalistic setting

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