Information Processing, Motivation and Decision Making

1996 ◽  
pp. 233-250 ◽  
Author(s):  
Luis Miguel Botelho ◽  
Helder Coelho
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Processing Motivation

“Little Plants in the Country”: Henry Ford's Village Industries and the Beginning of Decentralized Technology in Modern America

Prospects ◽  
1988 ◽  
Vol 13 ◽  
pp. 181-223 ◽  
Author(s):  
Howard P. Segal
Keyword(s):  
United States ◽  
Decision Making ◽  
New York ◽  
Information Processing ◽  
Real Estate ◽  
New York Times ◽  
The United States ◽  
Physical Proximity ◽  
The World ◽  
Word Processors

“Technology Spurs Decentralization Across the Country.” So reads a 1984 New York Times article on real-estate trends in the United States. The contemporary revolution in information processing and transmittal now allows large businesses and other institutions to disperse their offices and other facilities across the country, even across the world, without loss of the policy- and decision-making abilities formerly requiring regular physical proximity. Thanks to computers, word processors, and the like, decentralization has become a fact of life in America and other highly technological societies.

scholarly journals A new measure of group decision-making efficiency

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Cheng-Ju Hsieh ◽  
Mario Fifić ◽  
Cheng-Ta Yang
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Group Decision Making ◽  
Group Decision ◽  
Detection Task ◽  
Detection Sensitivity ◽  
System Level ◽  
Workload Capacity ◽  
Individual Decisions ◽  
Collective Benefit

Abstract It has widely been accepted that aggregating group-level decisions is superior to individual decisions. As compared to individuals, groups tend to show a decision advantage in their response accuracy. However, there has been a lack of research exploring whether group decisions are more efficient than individual decisions with a faster information-processing speed. To investigate the relationship between accuracy and response time (RT) in group decision-making, we applied systems’ factorial technology, developed by Townsend and Nozawa (Journal of Mathematical Psychology 39, 321–359, 1995) and regarded as a theory-driven methodology, to study the information-processing properties. More specifically, we measured the workload capacity CAND(t), which only considers the correct responses, and the assessment function of capacity AAND(t), which considers the speed-accuracy trade-off, to make a strong inference about the system-level processing efficiency. A two-interval, forced-choice oddball detection task, where participants had to detect which interval contains an odd target, was conducted in Experiment 1. Then, in Experiment 2, a yes/no Gabor detection task was adopted, where participants had to detect the presence of a Gabor patch. Our results replicated previous findings using the accuracy-based measure: Group detection sensitivity was better than the detection sensitivity of the best individual, especially when the two individuals had similar detection sensitivities. On the other hand, both workload capacity measures, CAND(t) and AAND(t), showed evidence of supercapacity processing, thus suggesting a collective benefit. The ordered relationship between accuracy-based and RT-based collective benefit was limited to the AAND(t) of the correct and fast responses, which may help uncover the processing mechanism behind collective benefits. Our results suggested that AAND(t), which combines both accuracy and RT into inferences, can be regarded as a novel and diagnostic tool for studying the group decision-making process.

Information transformation: Some missing links

2007 ◽  
Vol 26 (3) ◽  
pp. 157-172
Author(s):  
Ivan P. Vaghely ◽  
Pierre-André Julien ◽  
André Cyr
Keyword(s):  
Decision Making ◽  
Grounded Theory ◽  
Information Processing ◽  
Knowledge Creation ◽  
Best Practice ◽  
Participant Observation ◽  
Human Information Processing ◽  
Process Information ◽  
Information Transformation ◽  
Efficient Information

Using grounded theory along with participant observation and interviews the authors explore how individuals in organizations process information. They build a model of human information processing which links the cognitivist-constructionist perspective to an algorithmic-heuristic continuum. They test this model using non-parametric procedures and find interesting results showing links to efficient information processing outcomes such as contributions to decision-making, knowledge-creation and innovation. They also identify some elements of best practice by efficient human information processing individuals whom they call the “information catalysts”.

Information processing and age differences in social decision-making.

1986 ◽  
Vol 22 (4) ◽  
pp. 500-508 ◽  
Author(s):  
Chia-chen Chao ◽  
George P. Knight ◽  
Alan F. Dubro
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Age Differences ◽  
Social Decision ◽  
Social Decision Making

Making one-sided exercise decisions: The influence of exercise-related cognitive errors

2016 ◽  
Vol 23 (9) ◽  
pp. 1240-1249 ◽  
Author(s):  
Sean R Locke ◽  
Lawrence R Brawley
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Relevant Information ◽  
Future Research ◽  
Cognitive Errors ◽  
Online Questionnaire ◽  
Cognitive Error ◽  
Biased Processing

Exercise-related cognitive errors reflect biased processing of exercise-relevant information. The purpose of this study was to examine whether differences existed between individuals reporting low and high exercise-related cognitive errors on information processed about a relevant exercise decision-making situation. In all, 138 adults completed an online questionnaire. The high exercise-related cognitive error group primarily focused on negative content about the situation compared to the low exercise-related cognitive error group who focused on both positive and negative content. The high exercise-related cognitive error group displayed biased processing of exercise information, as suggested by the cognitive errors model. Future research should examine whether biasing information processing caused by exercise-related cognitive errors can be modified and attenuated.

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