Self-other differences in multiattribute decision making: Compensatory versus noncompensatory decision strategies

2018 ◽  
Vol 32 (2) ◽  
pp. 109-123 ◽  
Author(s):  
Curtis D. Von Gunten ◽  
Laura D. Scherer
Keyword(s):  
Decision Making ◽  
Decision Strategies

scholarly journals Parallel Constraint Satisfaction in Memory-Based Decisions

2011 ◽  
Vol 58 (3) ◽  
pp. 180-195 ◽  
Author(s):  
Andreas Glöckner ◽  
Sara D. Hodges
Keyword(s):  
Decision Making ◽  
Constraint Satisfaction ◽  
Information Integration ◽  
Time Pressure ◽  
Human Information Processing ◽  
Decision Task ◽  
Equal Weight ◽  
Decision Strategies ◽  
Simple Heuristics ◽  
Decision Times

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

How Well Do E-Commerce Web Sites Support Compensatory and Non-Compensatory Decision Strategies? An Exploratory Study

2011 ◽  
pp. 1592-1607
Author(s):  
Naveen Gudigantala ◽  
Jaeki Song ◽  
Donald R. Jones
Keyword(s):  
Decision Making ◽  
Web Sites ◽  
Exploratory Study ◽  
Decision Quality ◽  
Consumer Decision Making ◽  
Online Retailing ◽  
Compensatory Strategies ◽  
Decision Strategies ◽  
Web Based ◽  
Levels Of Support

The burgeoning growth of online retailing is forcing businesses to provide better support for consumer decision making on e-commerce Web sites. Consequently, researchers in information systems and marketing have been focusing on investigating the effectiveness of Web-based decision support systems (WebDSS) in providing accurate and satisfying choices for customers. We consider WebDSS implementation based on compensatory, non-compensatory decision strategies and synthesize the existing literature. The results of synthesis show that compensatory WebDSS perform better than non-compensatory WebDSS in terms of decision quality, satisfaction, effort, and confidence. We then investigate the level of Web site support provided for consumers’ execution of compensatory and non-compensatory strategies. We examined 375 U.S.-based company Web sites and found that though moderate levels of support exists for consumers to implement non-compensatory choice strategies, virtually no support exists for executing multi-attribute-based compensatory choice strategies.

Understanding Consumer Dynamic Decision Making Under Competing Loyalty Programs

2020 ◽  
Vol 57 (3) ◽  
pp. 422-444
Author(s):  
Jia Liu ◽  
Asim Ansari
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
Dynamic Decision Making ◽  
Loyalty Programs ◽  
Competitive Environment ◽  
Decision Strategies ◽  
Optimal Dynamic ◽  
Optimal Action ◽  
Promotional Strategies

The authors develop an incentive-aligned experimental paradigm to study how consumer purchase dynamics are affected by the interplay between competing firms’ loyalty programs and their pricing and promotional strategies. In this experiment, participants made sequential choices between two competing airlines in a stylized frequent traveler task for which an optimal dynamic decision policy can be numerically computed. The authors find that, on average, participants are able to partially realize the long-term benefits from loyalty programs, though most are sensitive to price. They also find that participants’ preferences and levels of bounded rationality depend on the nature of the competitive environment, the particular state of each decision scenario, and the type of optimal action. Accordingly, the authors use an approximate dynamic programming model to incorporate boundedly rational decision making. The model classifies participants into five segments that exhibit variation in their performance and decision strategies. Importantly, they find that participants are able to adapt their decision strategies to the environment they face, and thus the overall market outcome and the performance of each firm are influenced by both the competitive environment and the assumption on the extent of consumer optimality.

Decision-Making Dysfunctions in Psychiatry—Altered Homeostatic Processing?

Science ◽  
2007 ◽  
Vol 318 (5850) ◽  
pp. 602-606 ◽  
Author(s):  
Martin P. Paulus
Keyword(s):  
Decision Making ◽  
Psychiatric Disorders ◽  
Decision Maker ◽  
The State ◽  
Optimal Decision ◽  
Homeostatic Regulation ◽  
Specific Context ◽  
Decision Strategies ◽  
Homeostatic Process ◽  
Gain And Loss

Decision-making consists of selecting an action from a set of available options. This results in an outcome that changes the state of the decision-maker. Therefore, decision-making is part of a homeostatic process. Individuals with psychiatric disorders show altered decision-making. They select options that are either non-optimal or nonhomeostatic. These dysfunctional patterns of decision-making in individuals with psychiatric disorders may fundamentally relate to problems with homeostatic regulation. These may manifest themselves in (i) how the length of time between decisions and their outcomes influences subsequent decision-making, (ii) how gain and loss feedback are integrated to determine the optimal decision, (iii) how individuals adapt their decision strategies to match the specific context, or (iv) how seemingly maladaptive responses result from an attempt to establish an unstable homeostatic balance.

Simple Strategies or Simple Tasks? Dynamic Decision Making in “Complex” Worlds

1996 ◽  
Vol 40 (4) ◽  
pp. 184-188
Author(s):  
Alex Kirlik ◽  
Ling Rothrock ◽  
Neff Walker ◽  
Arthur D. Fisk
Keyword(s):  
Decision Making ◽  
Empirical Evidence ◽  
Time Pressure ◽  
Task Complexity ◽  
Empirical Finding ◽  
Decision Makers ◽  
Dynamic Decision Making ◽  
Decision Problems ◽  
Decision Strategies

Decision makers in operational environments perform in a world of dynamism, time pressure, and uncertainty. Perhaps the most stable empirical finding to emerge from naturalistic studies in these domains is that, despite apparent task complexity, performers only rarely report the use of complex, enumerative decision strategies. If we accept that decision making in these domains is often effective, we are presented with a dilemma: either decision strategies are (covertly) more complex than these performers claim, or these tasks are (subtlely) more simple than they might appear. We present a set of empirical findings and modeling results which suggest the latter explanation: that the simplicity of decision making is not merely apparent but largely real, and that tasks of high apparent complexity may yet admit to rather simple types of decision strategies. We also discuss empirical evidence that sheds light on the error forms resulting from the tendency of performers to seek and employ heuristic solutions to dynamic, uncertain decision problems.

Evaluating two-stage holistic production systems using novel CSDEA approach

2018 ◽  
Vol 13 (1) ◽  
pp. 101-118 ◽  
Author(s):  
Dujun Zhai ◽  
Minyue Jin ◽  
Jennifer Shang ◽  
Chenfeng Ji
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Production Process ◽  
Group Decision Making ◽  
Group Decision ◽  
Collective Decision ◽  
Data Envelopment ◽  
Two Stage ◽  
Decision Strategies ◽  
Content Type

Purpose The purpose of this paper is to apply data envelopment analysis (DEA) techniques to the collective decision-making environment to appraise two-stage production process under different decision preferences. Design/methodology/approach The authors propose a novel multi-criteria group decision-making approach that uses consensus-strategic data envelopment analysis (CSDEA) to appraise two-stage production process under two different decision strategies, which are efficiency- and fairness-based group decision preferences. Findings The authors find that the proposed CSDEA model evaluates the performance of the decision-making units (DMUs) not by diminishing other competitors but rather based on group interests of the entire decision set. Originality/value The authors extend Li’s two-stage model to cases that consider both intermediate inputs and outputs. The authors address the issue of incorporating collective managerial strategy into multi-criteria group decision-making and propose a novel CSDEA model that considers not only the individual-level performance of a DMU but also the group-level or collective decision strategies.

scholarly journals Decision Strategies while Intoxicated relate to Alcohol-Impaired Driving Attitudes and Intentions

2021 ◽  
Author(s):  
Sara D McMullin ◽  
Courtney Motschman ◽  
Laura Hatz ◽  
Denis McCarthy ◽  
Clintin Davis-Stober ◽  
...  
Keyword(s):  
Decision Making ◽  
Cognitive Modeling ◽  
Future Research ◽  
Service Cost ◽  
Decision Strategies ◽  
Impaired Driving ◽  
Consumption Level ◽  
Compensatory Strategy ◽  
Alcohol Impaired Driving ◽  
Aid Decision

Objective: Approximately 28 million individuals engage in alcohol-impaired driving (AID) every year. This study investigated individuals’ AID decision making strategies under intoxication, their variability across the breath alcohol concentration curve (BrAC), and the association between strategy and AID attitudes and intentions. Method: 79 adults (23.9 years, 57% women) who drank alcohol ≥2 days per week and lived >2 miles away from their typical drinking locations completed an alcohol administration protocol and AID decision making task. AID attitudes, intentions, and behaviors were assessed repeatedly across the BrAC curve. Bayesian cognitive modeling identified decision strategies used by individuals on the AID decision making task, revealing whether alcohol consumption level and/or ride service cost factored into individuals’ decisions to drive while impaired or obtain a ride. Additional analyses tested whether AID attitudes and intentions were related to individuals’ decision strategies. Results: Two decision strategies were examined on the ascending and descending limb of the BrAC curve: compensatory (both consumption level and ride service cost factored into AID decisions) and non-compensatory (only consumption level factored into AID decisions). Switching to a compensatory strategy on the descending limb was associated with lower perceived intoxication, perceiving AID as less dangerous, and being willing to drive above the legal BrAC limit. Conclusions: Results suggest that risk for engaging in AID is higher for those using a cost-sensitive, compensatory strategy when making AID decisions under intoxication. Future research is needed to test whether AID countermeasures (e.g., subsidized ride services) are differentially effective according to decision strategy type.

scholarly journals The roles of online and offline replay in planning

2020 ◽  
Author(s):  
Eran Eldar ◽  
Gaëlle Lièvre ◽  
Peter Dayan ◽  
Raymond J. Dolan
Keyword(s):  
Decision Making ◽  
Task Performance ◽  
Human Subjects ◽  
Reward Structure ◽  
Decision Strategies ◽  
Rest Periods ◽  
Decision Algorithms

AbstractAnimals and humans replay neural patterns encoding trajectories through their environment, both whilst they solve decision-making tasks and during rest. Both on-task and off-task replay are believed to contribute to flexible decision making, though how their relative contributions differ remains unclear. We investigated this question by using magnetoencephalography to study human subjects while they performed a decision-making task that was designed to reveal the decision algorithms employed. We characterized subjects in terms of how flexibly each adjusted their choices to changes in temporal, spatial and reward structure. The more flexible a subject, the more they replayed trajectories during task performance, and this replay was coupled with re-planning of the encoded trajectories. The less flexible a subject, the more they replayed previously and subsequently preferred trajectories during rest periods between task epochs. The data suggest that online and offline replay both participate in planning but support distinct decision strategies.

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