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Option generation in decision making: ideation beyond memory retrieval.

Del Missier F, Visentini M, Mäntylä T - Front Psychol (2015)

Bottom Line: Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive.In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency.The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Sciences, University of Trieste Trieste, Italy ; Department of Psychology, Stockholm University Stockholm, Sweden.

ABSTRACT
According to prescriptive decision theories, the generation of options for choice is a central aspect of decision making. A too narrow representation of the problem may indeed limit the opportunity to evaluate promising options. However, despite the theoretical and applied significance of this topic, the cognitive processes underlying option generation are still unclear. In particular, while a cued recall account of option generation emphasizes the role of memory and executive control, other theoretical proposals stress the importance of ideation processes based on various search and thinking processes. Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive. In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency. The criterion tasks consisted of three different poorly-structured decision-making scenarios, and the participants were asked to generate options to solve these problems. The main criterion variable of the study was the number of valid options generated, but also the diversity and the quality of generated options were examined. The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning. Thus, ideation processes, possibly supported by search and thinking processes, seem to contribute to option generation beyond basic associative memory retrieval. The findings of the study also indicate that generating more options may have multifaceted consequences for choice, increasing the quality of the best option generated but decreasing the mean quality of the options in the generated set.

No MeSH data available.


Related in: MedlinePlus

Path analysis model for each problem. Note: Two-tailed significance levels: ***p < 0.001; **p < 0.01; *p < 0.05. The standard error for each standardized path coefficient is reported in parentheses.
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Figure 1: Path analysis model for each problem. Note: Two-tailed significance levels: ***p < 0.001; **p < 0.01; *p < 0.05. The standard error for each standardized path coefficient is reported in parentheses.

Mentions: Correlations between option generation fluency and choice quality were all non-significant (parking: r = −0.01; fund raising: r = 0.08; energy saving: r = 0.14), but Table 3 suggests the existence of indirect effects of fluency via mean quality or max quality. Thus, in order to shed further light on the network of relationships linking option generation fluency, generation quality, and quality of choice, we estimated these relationships via path analysis. In particular, starting from H3 and H4, we specified a path-analysis model and used it for further testing in each problem. The model includes the relation between fluency and mean option quality (less is more), the relation between fluency and max quality (quantity breeds quality), the two relations between the option generation quality measures and choice quality, and the structural relation between mean and max quality (Figure 1). The model was estimated in each decision problem by using the Sepath module of the Statistica 12 software (version 12, StatSoft Inc., Tulsa, OK), starting from correlation matrices and using the maximum likelihood method. Model fit is reported in Table 4.


Option generation in decision making: ideation beyond memory retrieval.

Del Missier F, Visentini M, Mäntylä T - Front Psychol (2015)

Path analysis model for each problem. Note: Two-tailed significance levels: ***p < 0.001; **p < 0.01; *p < 0.05. The standard error for each standardized path coefficient is reported in parentheses.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4302792&req=5

Figure 1: Path analysis model for each problem. Note: Two-tailed significance levels: ***p < 0.001; **p < 0.01; *p < 0.05. The standard error for each standardized path coefficient is reported in parentheses.
Mentions: Correlations between option generation fluency and choice quality were all non-significant (parking: r = −0.01; fund raising: r = 0.08; energy saving: r = 0.14), but Table 3 suggests the existence of indirect effects of fluency via mean quality or max quality. Thus, in order to shed further light on the network of relationships linking option generation fluency, generation quality, and quality of choice, we estimated these relationships via path analysis. In particular, starting from H3 and H4, we specified a path-analysis model and used it for further testing in each problem. The model includes the relation between fluency and mean option quality (less is more), the relation between fluency and max quality (quantity breeds quality), the two relations between the option generation quality measures and choice quality, and the structural relation between mean and max quality (Figure 1). The model was estimated in each decision problem by using the Sepath module of the Statistica 12 software (version 12, StatSoft Inc., Tulsa, OK), starting from correlation matrices and using the maximum likelihood method. Model fit is reported in Table 4.

Bottom Line: Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive.In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency.The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Sciences, University of Trieste Trieste, Italy ; Department of Psychology, Stockholm University Stockholm, Sweden.

ABSTRACT
According to prescriptive decision theories, the generation of options for choice is a central aspect of decision making. A too narrow representation of the problem may indeed limit the opportunity to evaluate promising options. However, despite the theoretical and applied significance of this topic, the cognitive processes underlying option generation are still unclear. In particular, while a cued recall account of option generation emphasizes the role of memory and executive control, other theoretical proposals stress the importance of ideation processes based on various search and thinking processes. Unfortunately, relevant behavioral evidence on the cognitive processes underlying option generation is scattered and inconclusive. In order to reach a better understanding, we carried out an individual-differences study employing a wide array of cognitive predictors, including measures of episodic memory, semantic memory, cognitive control, and ideation fluency. The criterion tasks consisted of three different poorly-structured decision-making scenarios, and the participants were asked to generate options to solve these problems. The main criterion variable of the study was the number of valid options generated, but also the diversity and the quality of generated options were examined. The results showed that option generation fluency and diversity in the context of ill-structured decision making are supported by ideation ability even after taking into account the effects of individual differences in several other aspects of cognitive functioning. Thus, ideation processes, possibly supported by search and thinking processes, seem to contribute to option generation beyond basic associative memory retrieval. The findings of the study also indicate that generating more options may have multifaceted consequences for choice, increasing the quality of the best option generated but decreasing the mean quality of the options in the generated set.

No MeSH data available.


Related in: MedlinePlus