The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

scholarly journals Balancing ecosystem services with energy and food security – Assessing trade-offs from reservoir operation and irrigation investments in Kenya's Tana Basin

2014 ◽  
Vol 18 (8) ◽  
pp. 3259-3277 ◽  
Author(s):  
A. P. Hurford ◽  
J. J. Harou
Keyword(s):  
Ecosystem Services ◽  
Optimal Allocation ◽  
Search Algorithm ◽  
Management Strategies ◽  
Decision Makers ◽  
Pareto Optimal ◽  
Management Problem ◽  
Economic Sectors ◽  
Trade Off ◽  
Trade Offs

Abstract. Competition for water between key economic sectors and the environment means agreeing allocations is challenging. Managing releases from the three major dams in Kenya's Tana River basin with its 4.4 million inhabitants, 567 MW of installed hydropower capacity, 33 000 ha of irrigation and ecologically important wetlands and forests is a pertinent example. This research seeks firstly to identify and help decision-makers visualise reservoir management strategies which result in the best possible (Pareto-optimal) allocation of benefits between sectors. Secondly, it seeks to show how trade-offs between achievable benefits shift with the implementation of proposed new rice, cotton and biofuel irrigation projects. To approximate the Pareto-optimal trade-offs we link a water resources management simulation model to a multi-criteria search algorithm. The decisions or "levers" of the management problem are volume-dependent release rules for the three major dams and extent of investment in new irrigation schemes. These decisions are optimised for eight objectives covering the provision of water supply and irrigation, energy generation and maintenance of ecosystem services. Trade-off plots allow decision-makers to assess multi-reservoir rule-sets and irrigation investment options by visualising their impacts on different beneficiaries. Results quantify how economic gains from proposed irrigation schemes trade-off against the disturbance of ecosystems and local livelihoods that depend on them. Full implementation of the proposed schemes is shown to come at a high environmental and social cost. The clarity and comprehensiveness of "best-case" trade-off analysis is a useful vantage point from which to tackle the interdependence and complexity of "water-energy-food nexus" resource security issues.

Comparing the Effects of Decision Time and Direct Decision Processing Information on (Moral) Character Evaluations

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Moral Character ◽  
Decision Time ◽  
Cognitive Capacity ◽  
Process Information ◽  
Information Hypothesis ◽  
Competence Evaluation ◽  
Information Time ◽  
Within Subjects ◽  
Processing Information

Which decision processing information is most diagnostic for assessing (moral) character? We test if decision time is a more ambiguous cue than more direct types of decision processing information, such as difficulty, doubt, or effort. Our direct information hypothesis predicts that these more direct cues will have a larger effect on competence, warmth, and morality ratings than decision time. Participants (N = 871) evaluated a decision maker who made a moral or monetary choice in four scenarios (within-subjects) and were provided with five different types decision process information (time, difficulty, doubt, effort, control condition with no information). Inconsistent with the hypothesis, the effect of direct types of process information on warmth and morality evaluations were no different than that of decision time. However, for competence we found that doubt and (marginally) difficulty had stronger effects on competence ratings than decision time, thus partially supporting our hypothesis. Observers may use any type of decision process information, ambiguous or direct, as a cue to make inferences about the decision maker’s moral motives. For competence evaluation, however, results suggest that this same decision process information may be interpreted differently, as cognitive capacity.

scholarly journals A Trade-Off Navigation Framework as a Decision Support for Conflicting Sustainability Indicators within Circular Economy Implementation in the Manufacturing Industry

2020 ◽  
Vol 13 (1) ◽  
pp. 314
Author(s):  
Mariia Kravchenko ◽  
Daniela C. A. Pigosso ◽  
Tim C. McAloone
Keyword(s):  
Manufacturing Industry ◽  
Development Process ◽  
Decision Makers ◽  
Bottom Line ◽  
Trade Off ◽  
Sustainability Performance ◽  
Sustainability Criteria ◽  
Trade Offs ◽  
Potential Risks ◽  
Structured Approach

Integration of sustainability criteria from a triple bottom line perspective is considered a challenge for manufacturing actors, who are engaged in developing sustainability-oriented initiatives. The earlier in the development process the criteria are integrated and sustainability potential is evaluated, the more opportunities exist to introduce improvements and select an initiative with a highest sustainability potential. The challenge does not only lie in understanding what sustainability criteria to use to assess sustainability performance, but in managing conflicting results, known as trade-offs. Trade-offs are situations characterized by conflicts between the desired objectives, where it is impossible to satisfy all criteria simultaneously. Although sustainability trade-offs are common, there is a gap in the existing approaches for sustainability measurements to support trade-off dialogue and decision-making. If trade-offs are not acknowledged, there is a risk of accepting an initiative leading to sub-optimizations or higher impacts. Therefore, this study proposes a framework to support trade-off analysis in the early development stages of sustainability-oriented initiatives. The trade-off navigation framework relies on input data and a structured guidance, with the twofold objective: (i) help making trade-offs explicit, and (ii) provide a structured approach to support trade-off analysis and acceptability in a transparent manner. The purpose is to encourage a dynamic decision process and reinforce the knowledge of decision-makers about potential risks and opportunities behind their choices. Using a case of a product development involving CE principles, this paper discusses how a trade-off navigation framework was applied and evaluated by industrial and academic experts, leading to its improvement and identification of strengths and limitations.

Are Morally Motivated Decision Makers Insensitive to the Consequences of Their Choices?

2007 ◽  
Vol 18 (1) ◽  
pp. 24-28 ◽  
Author(s):  
Daniel M. Bartels ◽  
Douglas L. Medin
Keyword(s):  
Decision Making ◽  
Human Life ◽  
Preference Assessment ◽  
Decision Makers ◽  
Trade Off ◽  
Trade Offs ◽  
Protected Values ◽  
Quantity Sensitivity

Is morally motivated decision making different from other kinds of decision making? There is evidence that when people have sacred or protected values (PVs), they reject trade-offs for secular values (e.g., “You can't put a price on a human life”) and tend to employ deontological rather than consequentialist decision principles. People motivated by PVs appear to show quantity in-sensitivity. That is, in trade-off situations, they are less sensitive to the consequences of their choices than are people without PVs. The current study examined the relation between PVs and quantity insensitivity using two methods of preference assessment: In one design, previous results were replicated; in a second, PVs were related to increased quantity sensitivity. These and other findings call into question important presumed properties of PVs, suggesting that how PVs affect willingness to make tradeoffs depends on where attention is focused, a factor that varies substantially across contexts.

scholarly journals Balancing ecosystem services with energy and food security – assessing trade-offs for reservoir operation and irrigation investment in Kenya's Tana basin

2014 ◽  
Vol 11 (1) ◽  
pp. 1343-1388 ◽  
Author(s):  
A. P. Hurford ◽  
J. J. Harou
Keyword(s):  
Ecosystem Services ◽  
Optimal Allocation ◽  
Search Algorithm ◽  
Management Strategies ◽  
Decision Makers ◽  
Pareto Optimal ◽  
Management Problem ◽  
Economic Sectors ◽  
Trade Off ◽  
Trade Offs

Abstract. Competition for water between key economic sectors and the environment means agreeing on allocation is challenging. Managing releases from the three major dams in Kenya's Tana River basin with its 4.4 million inhabitants, 567 MW of installed hydropower capacity, 33 000 ha of irrigation and ecologically important wetlands and forests is a pertinent example. This research seeks to identify and help decision-makers visualise reservoir management strategies which result in the best possible (Pareto-optimal) allocation of benefits between sectors. Secondly we seek to show how trade-offs between achievable benefits shift with the implementation of new proposed rice, cotton and biofuel irrigation projects. To identify the Pareto-optimal trade-offs we link a water resources management model to a multi-criteria search algorithm. The decisions or "levers" of the management problem are volume dependent release rules for the three major dams and extent of investment in new irrigation schemes. These decisions are optimised for objectives covering provision of water supply and irrigation, energy generation and maintenance of ecosystem services which underpin tourism and local livelihoods. Visual analytic plots allow decision makers to assess multi-reservoir rule-sets by understanding their impacts on different beneficiaries. Results quantify how economic gains from proposed irrigation schemes trade-off against disturbance of the flow regime which supports ecosystem services. Full implementation of the proposed schemes is shown to be Pareto-optimal, but at high environmental and social cost. The clarity and comprehensiveness of "best-case" trade-off analysis is a useful vantage point from which to tackle the interdependence and complexity of water-energy-food "nexus" challenges.

Dual Goals for Speed and Accuracy on the Same Performance Task

2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt
Keyword(s):  
Memory Scanning ◽  
Performance Task ◽  
Performance Tasks ◽  
Trade Off ◽  
Test Experiment ◽  
Trade Offs ◽  
New Finding ◽  
Sternberg Paradigm ◽  
Speed Accuracy ◽  
Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

Predicting Undesired Treatment Outcome in Mental Healthcare: Machine Learning Study (Preprint)

2019 ◽  
Author(s):  
Kasper Van Mens ◽  
Joran Lokkerbol ◽  
Richard Janssen ◽  
Robert de Lange ◽  
Bea Tiemens
Keyword(s):  
Machine Learning ◽  
Treatment Outcome ◽  
Mental Health Treatment ◽  
Mental Healthcare ◽  
Machine Learning Algorithms ◽  
Gradient Boosting ◽  
Trade Off ◽  
Trade Offs ◽  
Outcome Monitoring ◽  
Extreme Gradient Boosting

BACKGROUND It remains a challenge to predict which treatment will work for which patient in mental healthcare. OBJECTIVE In this study we compare machine algorithms to predict during treatment which patients will not benefit from brief mental health treatment and present trade-offs that must be considered before an algorithm can be used in clinical practice. METHODS Using an anonymized dataset containing routine outcome monitoring data from a mental healthcare organization in the Netherlands (n = 2,655), we applied three machine learning algorithms to predict treatment outcome. The algorithms were internally validated with cross-validation on a training sample (n = 1,860) and externally validated on an unseen test sample (n = 795). RESULTS The performance of the three algorithms did not significantly differ on the test set. With a default classification cut-off at 0.5 predicted probability, the extreme gradient boosting algorithm showed the highest positive predictive value (ppv) of 0.71(0.61 – 0.77) with a sensitivity of 0.35 (0.29 – 0.41) and area under the curve of 0.78. A trade-off can be made between ppv and sensitivity by choosing different cut-off probabilities. With a cut-off at 0.63, the ppv increased to 0.87 and the sensitivity dropped to 0.17. With a cut-off of at 0.38, the ppv decreased to 0.61 and the sensitivity increased to 0.57. CONCLUSIONS Machine learning can be used to predict treatment outcomes based on routine monitoring data.This allows practitioners to choose their own trade-off between being selective and more certain versus inclusive and less certain.

Challenges in the Empirical Study of Global Governance Legitimacy

2018 ◽  
Author(s):  
Steven Bernstein
Keyword(s):  
Empirical Study ◽  
Global Governance ◽  
Research Agenda ◽  
Cultural Factors ◽  
Theory Building ◽  
Trade Off ◽  
Trade Offs ◽  
Different Types ◽  
Political Communities

This commentary discusses three challenges for the promising and ambitious research agenda outlined in the volume. First, it interrogates the volume’s attempts to differentiate political communities of legitimation, which may vary widely in composition, power, and relevance across institutions and geographies, with important implications not only for who matters, but also for what gets legitimated, and with what consequences. Second, it examines avenues to overcome possible trade-offs from gains in empirical tractability achieved through the volume’s focus on actor beliefs and strategies. One such trade-off is less attention to evolving norms and cultural factors that may underpin actors’ expectations about what legitimacy requires. Third, it addresses the challenge of theory building that can link legitimacy sources, (de)legitimation practices, audiences, and consequences of legitimacy across different types of institutions.

scholarly journals Expert Advisory Groups: Exploring the Sensemaking Proces s During a Public Health C risis R esponse

2018 ◽  
Author(s):  
Iva Seto ◽  
David Johnstone ◽  
Jennifer Campbell-Meier
Keyword(s):  
Public Health ◽  
Decision Makers ◽  
Process Information ◽  
Unexpected Event ◽  
Health Crisis ◽  
Creation Process ◽  
Public Health Crisis ◽  
Advisory Groups ◽  
Expert Advisory ◽  
Meaning Creation

In a public health crisis, experts (such as epidemiologists, public health officers, physicians and virologists) support key decision  makers with advice in a highly dynamic, pressured,  and time-sensitive context. Experts must process information (to provide advice) as quickly as possible, yet this must be balanced with ensuring the information is credible, reliable,  and relevant. When an unexpected event occurs, it may lead to a gap between what is  experienced and what was expected; sensemaking is a meaning creation process which is engaged to fill the gap. This research explores how experts engage in sensemaking during a  public health crisis.

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