Systems Simulation of Design for End-of-Life Recovery Under Uncertainty

2013 ◽  
Author(s):  
Sara Behdad ◽  
Aaron T. Joseph ◽  
Deborah Thurston
Keyword(s):  
Decision Making ◽  
Product Design ◽  
End Of Life ◽  
Reverse Logistics ◽  
Cognitive Biases ◽  
Design Features ◽  
Product Life ◽  
Return Flows ◽  
Human Decision ◽  
The Impact

Design for End of Life (DfEOL) recovery is a complex process that requires consideration of various design aspects including design for product life extension, design for reliability, design for disassembly, design for components reuse, and design for recyclability. There is a need for an analytical tool that helps designers integrate all these design aspects together and moreover investigate the impact of design features on the recovery network. The designer needs to predict the variability that design features bring into the reverse logistics network, including the variability in the amount, quality and timing of return flows and uncertainty in the remanufacturing operations such as disassembly time. In addition to the product design, the EOL recovery system performance is also affected by human decision making. The willingness of customers to keep used products in storage, the qualitative criteria used by remanufacturing companies to sort and categorize the returned used products and the manual disassembly operations influenced by the operator’s cognitive biases are examples of human decision making processes that impact product recovery. The nonlinear character of reverse logistics system along with the dynamic complexity as a result of uncertainties and cognitive biases are particularly troublesome. This paper establishes a simulation-based System Dynamics (SD) model of product life cycle to check interrelationship among product design features and their impacts on the amount, quality and timing of the return flows to the waste stream. The complex product take back process and recovery operations are modeled. Designers could use the results of the model to compare different design scenarios and to receive information about what design features bring problems or create opportunities for EOL recovery.

scholarly journals The Influence of Cognitive Biases in Production Planning and Control: Considering the Human Factor for the Design of Decision Support Systems

2021 ◽  
Author(s):  
Julia Bendul ◽  
Melanie Zahner
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Production Planning ◽  
Cognitive Biases ◽  
Production Planning And Control ◽  
Due Date ◽  
Planning And Control ◽  
Human Decision ◽  
And Control ◽  
The Impact

Production planning and control (PPC) requires human decision-making in several process steps like production program planning, production data management, and performance measurement. Thereby, human decisions are often biased leading to an aggravation of logistic performance. Exemplary, the lead time syndrome (LTS) shows this connection. While production planners aim to improve due date reliability by updating planned lead times, the result is actually a decreasing due date reliability. In current research in the field of production logistics, the impact of cognitive biases on the decision-making process in production planning and control remains at a silent place. We aim to close this research gap by combining a systematic literature review on behavioral operation management and cognitive biases with a case study from the steel industry to show the influence of cognitive biases on human decision-making in production planning and the impact on logistic performance. The result is the definition of guidelines considering human behavior for the design of decision support systems to improve logistic performance.

scholarly journals Decision Aiding to Overcome Biases in Object Identification

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Mary Fendley ◽  
S. Narayanan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Cognitive Biases ◽  
Target Identification ◽  
Object Identification ◽  
Identification Accuracy ◽  
Human Decision ◽  
The Impact

Human decision makers typically use heuristics under time-pressured situations. These heuristics can potentially degrade task performance through the impact of their associated biases. Using object identification in image analysis as the context, this paper identifies cognitive biases that play a role in decision making. We propose a decision support system to help overcome these biases in this context. Results show that the decision support system improved human decision making in object identification, including metrics such as time taken to identify targets in an image set, accuracy of target identification, accuracy of target classification, and quantity of false positive identification.

scholarly journals How Human Decision-making Biases Influence Health Outcomes in Patient Care

2021 ◽  
Vol 29 (2) ◽  
pp. 64-72
Author(s):  
Rainer Sibbel ◽  
Angelina Huber
Keyword(s):  
Decision Making ◽  
Healthcare Professionals ◽  
Cognitive Biases ◽  
Meta Analysis ◽  
Delayed Diagnosis ◽  
Medical Decision ◽  
Future Research ◽  
Literature Study ◽  
Human Decision ◽  
The Impact

Purpose: Medical treatments and medical decision making are mostly human based and therefore in risk of being influenced by cognitive biases. The potential impact could lead to bad medical outcome, unnecessary harm or even death. The aim of this comprehensive literature study is to analyse the evidence whether healthcare professionals are biased, which biases are most relevant in medicine and how these biases may be reduced. Approach/Findings: The results of the comprehensive literature based meta-analysis confirm on the one hand that several biases are relevant in the medical decision and treatment process. On the other hand, the study shows that the empirical evidence on the impact of cognitive biases on clinical outcome is scarce for most biases and that further research is necessary in this field. Value/Practical Implications: Nevertheless, it is important to determine the extent to which biases in healthcare professionals translate into negative clinical outcomes such as misdiagnosis, delayed diagnosis, or mistreatment. Only this way, the importance of incorporating debiasing strategies into the clinical setting, and which biases to focus on, can be properly assessed. Research Limitations/Future Research: Though recent literature puts great emphasis on cognitive debiasing strategies, there are still very few approaches that have proven to be efficient. Due to the increasing degree of specialization in medicine, the relevance of the different biases varies. Paper type: Theoretical.

Adding Infectious Insult to Traumatic Injury: The Impact of Infectious Complications in End-of-Life Decision Making

2021 ◽  
Author(s):  
Elizabeth W. Tindal ◽  
Daithi S. Heffernan ◽  
Tareq Kheirbek ◽  
Andrew Stephen ◽  
Stephanie N. Lueckel
Keyword(s):  
Decision Making ◽  
End Of Life ◽  
Traumatic Injury ◽  
Infectious Complications ◽  
End Of Life Decision ◽  
The Impact ◽  
Life Decision

Conflict of Interest and Decision Making

2021 ◽  
pp. 265-282
Author(s):  
Geneviève Helleringer
Keyword(s):  
Decision Making ◽  
Conflict Of Interest ◽  
Cognitive Biases ◽  
Institutional Design ◽  
Conflicts Of Interest ◽  
Self Regulation ◽  
Central Element ◽  
Professional Norms ◽  
The Impact ◽  
Harmful Effects

This chapter looks at conflicts of interest (COI). It first considers tools of analytic philosophy to highlight the notion of COI, and in particular, the connection between COIs, choice and judgment, emphasising why decision making is a central element in the characterisation of COIs. Drawing on these elements, it is clear that any question of regulation and institutional design requires a sophisticated understanding of the capacity of individuals to recognise and resist bias in themselves and others when making judgments and decisions. The chapter then studies two specific mechanisms—bounded rationality and cognitive biases—that affect the behaviour of people in COI situations. It starts by analysing how rationalisation can reframe questionable behaviour as appearing acceptable, and how a sense of invulnerability encourages people to downplay the impact of COIs. The chapter then looks at techniques (policies, procedures, incentives, etc.) used to address COI situations in the light of insights from psychological studies. It concludes that both fiduciary duties and procedural requirements reflect an erroneous understanding of psychology and have led institutions and policies to deal ineffectively—if not indeed counterproductively—with the problems caused by COIs. Finally, the chapter assesses how alternative mechanisms may overcome the highlighted deficiencies. It specifically focuses on the key role that professional norms can play in dealing with unavoidable COIs while preserving trust between the affected parties, and the potential for self-regulation to provide worthwhile tools in combatting the harmful effects of COIs.

scholarly journals How Concept Selection Tools Impact the Development of Creative Ideas in Engineering Design Education

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Xuan Zheng ◽  
Sarah C. Ritter ◽  
Scarlett R. Miller
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Design Education ◽  
Cognitive Biases ◽  
Design Stage ◽  
Concept Selection ◽  
Engineering Design Education ◽  
Student Teams ◽  
The Impact ◽  
Selection Tools

Concept selection tools have been heavily integrated into engineering design education in an effort to reduce the risks and uncertainties of early-phase design ideas and aid students in the decision-making process. However, little research has examined the utility of these tools in promoting creative ideas or their impact on student team decision making throughout the conceptual design process. To fill this research gap, the current study was designed to compare the impact of two concept selection tools, the concept selection matrix (CSM) and the tool for assessing semantic creativity (TASC) on the average quality (AQL) and average novelty (ANV) of ideas selected by student teams at several decision points throughout an 8-week project. The results of the study showed that the AQL increased significantly in the detailed design stage, while the ANV did not change. However, this change in idea quality was not significantly impacted by the concept selection tool used, suggesting other factors may impact student decision making and the development of creative ideas. Finally, student teams were found to select ideas ranked highly in concept selection tools only when these ideas met their expectations, indicating that cognitive biases may be significantly impeding decision making.

SHARED DECISION MAKING IN ONCOLOGY AND PALLIATIVE CARE

2020 ◽  
Author(s):  
Paul A Glare
Keyword(s):  
Decision Making ◽  
Palliative Care ◽  
Shared Decision Making ◽  
Cognitive Biases ◽  
Treatment Options ◽  
Care Plan ◽  
Treatment Modalities ◽  
Shared Decision ◽  
Human Decision ◽  
Based Medicine

Background: Cancer raises many questions for people afflicted by it. Do I want to have genetic testing? Will I comply with screening recommendations? If I am diagnosed with it, where will I have treatment? What treatment modalities will I have? Will I go on a clinical trial? Am I willing to bankrupt my family in the process of pursuing treatment? Will I write an advance care plan? Will I accept hospice if I have run out of available treatment options? Most of these questions have more than one correct answer, and the evidence for the superiority of one option over another is either not available or does not allow differentiation. Often the best choice between two or more valid approaches depends on how individuals value their respective risks and benefits; “preference-based medicine” may be more important than “evidence-based medicine.” There are various models for eliciting preferences, but applying them can raise a number of challenges. Objectives: To present the concepts, the value, the strategies, the quandaries, and the potential pitfalls of Shared Decision Making in Oncology and Palliative Care. Method: Narrative review. Results: Some challenges to practicing preference-based medicine in oncology and palliative care include: some patients don’t want to participate in shared decision making (SDM); the whole situation needs to be addressed, not just part of it; but are some topics out of bounds? Cognitive biases apply as much in SDM as any other human decision making, affecting the choice; how numerically equivalent data are framed can also affect the outcome; conducting SDM is also important at the end of life. Conclusions: By being aware of the potential pitfalls with SDM, clinicians are more able to facilitate the discussion so that the patients’ choices truly reflect their informed preferences, at a time when stakes and emotions are high.

scholarly journals The odd case when cognitive biases are more prevalent in researchers than in samples

2017 ◽  
Author(s):  
Jose D. Perezgonzalez
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Strong Evidence ◽  
Cognitive Biases ◽  
Statistical Significance ◽  
The Impact ◽  
Result Interpretation

Walmsley and Gilbey (2016) reported on the impact of cognitive biases on pilots’ decision-making, concluding that there was strong evidence that cognitive bias impacted decision making thus putting pilots' lives in danger. However, their methodology was not free of the same biases they set to research and, more importantly, they relied far too much on statistical significance as the only standard for result interpretation. Consequently, while the results obtained may have been technically correct, their divorce from the underlying methodological context made them factually wrong. Therefore, the conclusions achieved also misrepresented the true impact of cognitive biases on pilots' decision-making.

scholarly journals Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making

2021 ◽  
Author(s):  
Carmen Kohl ◽  
Michelle Wong ◽  
Jing Jun Wong ◽  
Matthew Rushworth ◽  
Bolton Chau
Keyword(s):  
Decision Making ◽  
Causal Link ◽  
Decision Space ◽  
Binary Decision ◽  
Distractor Effect ◽  
Divisive Normalization ◽  
Human Decision ◽  
The Impact ◽  
Alternative Decision ◽  
Different Parts

Abstract There has been debate about whether addition of an irrelevant distractor option to an otherwise binary decision influences which of the two choices is taken. We show that disparate views on this question are reconciled if distractors exert two opposing but not mutually exclusive effects. Each effect predominates in a different part of decision space: 1) a positive distractor effect predicts high-value distractors improve decision-making; 2) a negative distractor effect, of the type associated with divisive normalisation models, entails decreased accuracy with increased distractor values. Here, we demonstrate both distractor effects coexist in human decision making but in different parts of a decision space defined by the choice values. We show disruption of the medial intraparietal area (MIP) by transcranial magnetic stimulation (TMS) increases positive distractor effects at the expense of negative distractor effects. Furthermore, individuals with larger MIP volumes are also less susceptible to the disruption induced by TMS. These findings also demonstrate a causal link between MIP and the impact of distractors on decision-making via divisive normalization.

scholarly journals How design features affect evaluations of participatory platforms

2020 ◽  
Author(s):  
Henrik Serup Christensen
Keyword(s):  
Decision Making ◽  
Generation Time ◽  
Design Features ◽  
Political Decision ◽  
Identity Verification ◽  
Information Availability ◽  
Prior Use ◽  
Conjoint Experiment ◽  
The Impact ◽  
Political Decision Making

Online participatory platforms are introduced to boost citizen involvement in political decision-making. However, the design features of these platforms vary considerably, and these are likely to affect how prospective users evaluate the usefulness of these platforms. Previous studies explored how prevalent different design features are and how they affect the success of platforms in terms of impact, but the attitudes of prospective users remain unclear. Since these evaluations affect the prospects for launching successful participatory platforms, it is imperative to assess what citizens want from such digital possibilities for participation. This study uses a conjoint experiment (n=1048) conducted in Finland that explore the impact of seven design features: Discussion possibilities; Interaction with politicians and experts; Information availability, Aim of participation; Identity verification; Anonymous participation and Accessibility. Furthermore, it is examined whether the effects differ across use of ICTs measured by generation, time online and prior use of participatory platforms. The results suggest that most design features have clear effects on evaluations, and that deliberative features have the strongest effects. Furthermore, the effects are relatively stable across prior use although the less experienced put a stronger emphasis on verification.

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