scholarly journals Optimal policy for attention-modulated decisions explains human fixation behavior

2020 ◽  
Author(s):  
Anthony Jang ◽  
Ravi Sharma ◽  
Jan Drugowitsch
Keyword(s):  
Decision Making ◽  
Real Life ◽  
Relevant Information ◽  
Decision Makers ◽  
Cognitive Resources ◽  
Decision Performance ◽  
Human Decision ◽  
Behavioral Predictions ◽  
Decision Making Model ◽  
Fixation Bias

AbstractTraditional accumulation-to-bound decision-making models assume that all choice options are processed simultaneously with equal attention. In real life decisions, however, humans tend to alternate their visual fixation between individual items in order to efficiently gather relevant information [46, 23, 21, 12, 15]. These fixations also causally affect one’s choices, biasing them toward the longer-fixated item [38, 2, 25]. We derive a normative decision-making model in which fixating a choice item boosts information about that item. In contrast to previous models [25, 39], we assume that attention enhances the reliability of information rather than its magnitude, consistent with neurophysiological findings [3, 13, 29, 45]. Furthermore, our model actively controls fixation changes to optimize information gathering. We show that the optimal model reproduces fixation patterns and fixation-related choice biases seen in human decision-makers, and provides a Bayesian computational rationale for the fixation bias. This insight led to additional behavioral predictions that we confirmed in human behavioral data. Finally, we explore the consequences of changing the relative allocation of cognitive resources to the attended versus the unattended item, and show that decision performance is benefited by a more balanced spread of cognitive resources.

scholarly journals Optimal policy for attention-modulated decisions explains human fixation behavior

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Anthony Injoon Jang ◽  
Ravi Sharma ◽  
Jan Drugowitsch
Keyword(s):  
Decision Making ◽  
Optimal Policy ◽  
Real Life ◽  
Relevant Information ◽  
Information Gathering ◽  
Visual Fixation ◽  
Optimal Model ◽  
Human Data ◽  
Decision Performance ◽  
Decision Making Model

Traditional accumulation-to-bound decision-making models assume that all choice options are processed with equal attention. In real life decisions, however, humans alternate their visual fixation between individual items to efficiently gather relevant information (Yang et al., 2016). These fixations also causally affect one's choices, biasing them toward the longer-fixated item (Krajbich et al., 2010). We derive a normative decision-making model in which attention enhances the reliability of information, consistent with neurophysiological findings (Cohen and Maunsell, 2009). Furthermore, our model actively controls fixation changes to optimize information gathering. We show that the optimal model reproduces fixation-related choice biases seen in humans and provides a Bayesian computational rationale for this phenomenon. This insight led to additional predictions that we could confirm in human data. Finally, by varying the relative cognitive advantage conferred by attention, we show that decision performance is benefited by a balanced spread of resources between the attended and unattended items.

CAN BAYESIAN METHODS MAKE DATA AND ANALYSES MORE RELEVANT TO DECISION MAKERS?

2001 ◽  
Vol 17 (1) ◽  
pp. 114-122 ◽  
Author(s):  
Steven H. Sheingold
Keyword(s):  
Decision Making ◽  
Bayesian Methods ◽  
Paradigm Shift ◽  
Relevant Information ◽  
Decision Makers ◽  
Evidence Based ◽  
Critical Importance ◽  
Bayesian Approaches ◽  
Bayesian Analyses ◽  
And Performance

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or “frequentist” methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

Who’s making the decisions? How managers can harness artificial intelligence and remain in charge

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pooya Tabesh
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Digital Transformation ◽  
Decision Processes ◽  
Decision Makers ◽  
Content Type ◽  
Human Decision ◽  
Practical Implications

Purpose While it is evident that the introduction of machine learning and the availability of big data have revolutionized various organizational operations and processes, existing academic and practitioner research within decision process literature has mostly ignored the nuances of these influences on human decision-making. Building on existing research in this area, this paper aims to define these concepts from a decision-making perspective and elaborates on the influences of these emerging technologies on human analytical and intuitive decision-making processes. Design/methodology/approach The authors first provide a holistic understanding of important drivers of digital transformation. The authors then conceptualize the impact that analytics tools built on artificial intelligence (AI) and big data have on intuitive and analytical human decision processes in organizations. Findings The authors discuss similarities and differences between machine learning and two human decision processes, namely, analysis and intuition. While it is difficult to jump to any conclusions about the future of machine learning, human decision-makers seem to continue to monopolize the majority of intuitive decision tasks, which will help them keep the upper hand (vis-à-vis machines), at least in the near future. Research limitations/implications The work contributes to research on rational (analytical) and intuitive processes of decision-making at the individual, group and organization levels by theorizing about the way these processes are influenced by advanced AI algorithms such as machine learning. Practical implications Decisions are building blocks of organizational success. Therefore, a better understanding of the way human decision processes can be impacted by advanced technologies will prepare managers to better use these technologies and make better decisions. By clarifying the boundaries/overlaps among concepts such as AI, machine learning and big data, the authors contribute to their successful adoption by business practitioners. Social implications The work suggests that human decision-makers will not be replaced by machines if they continue to invest in what they do best: critical thinking, intuitive analysis and creative problem-solving. Originality/value The work elaborates on important drivers of digital transformation from a decision-making perspective and discusses their practical implications for managers.

scholarly journals A Multicriteria Decision Making Approach Based on Fuzzy Theory and Credibility Mechanism for Logistics Center Location Selection

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Bowen Wang ◽  
Haitao Xiong ◽  
Chengrui Jiang
Keyword(s):  
Decision Making ◽  
Fuzzy Theory ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Location Selection ◽  
Logistics Center ◽  
Multicriteria Decision ◽  
Model Based ◽  
Center Location ◽  
Decision Making Model

As a hot topic in supply chain management, fuzzy method has been widely used in logistics center location selection to improve the reliability and suitability of the logistics center location selection with respect to the impacts of both qualitative and quantitative factors. However, it does not consider the consistency and the historical assessments accuracy of experts in predecisions. So this paper proposes a multicriteria decision making model based on credibility of decision makers by introducing priority of consistency and historical assessments accuracy mechanism into fuzzy multicriteria decision making approach. In this way, only decision makers who pass the credibility check are qualified to perform the further assessment. Finally, a practical example is analyzed to illustrate how to use the model. The result shows that the fuzzy multicriteria decision making model based on credibility mechanism can improve the reliability and suitability of site selection for the logistics center.

Multi-Attribute Group Decision Making Method for Preference Conflicting with Heterogeneous Information

2018 ◽  
Vol 7 (4) ◽  
pp. 1-14 ◽  
Author(s):  
Kai-Rong Liang
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Makers ◽  
Heterogeneous Information ◽  
Multi Objective ◽  
Attribute Weights ◽  
Relative Closeness ◽  
Decision Making Model

The aim of this article is to propose a multi-objective decision-making method for researching and solving multi-attribute heterogeneous group decision-making problems. This is in the case that the characters of the decision information and decision makers' preferences are heterogeneous, and the weight information is incomplete. In this method, the multi-objective decision-making model, which considers the alternatives decision relative closeness and the preference of heterogeneous degree of decision makers in the objective function, is put forward. In addition, this article uses the minimax method to derive the multi-objective decision-making model and obtain the attribute weights and decision makers weights, and then the optimal scheme is established. Finally, an illustrative example shows the effectiveness of the proposed method.

scholarly journals The Effect of Accounting Information and Organizational Culture on Decision Making

2020 ◽  
Vol 3 (1) ◽  
pp. 522-530
Author(s):  
Teresa Paulina Sihombing ◽  
Nasirwan Nasirwan ◽  
Chandra Situmeang
Keyword(s):  
Decision Making ◽  
Organizational Culture ◽  
Catholic Education ◽  
Accounting Information ◽  
Relevant Information ◽  
Partial Least Square ◽  
Least Square ◽  
Education Foundations ◽  
Organizational Culture Theory ◽  
Decision Making Model

This study examines the educational foundation's organizational decision making model that is the influence of accounting information and organizational culture on decision making. This research is a quantitative study with descriptive and inferential analysis. The sample of this study was 72 Catholic education foundations in Indonesia, which were tested by Partial Least Square (PLS) based analysis and data processing methods with the Smart PLS 3.0 program. This study obtains some empirical evidence, namely, first, accounting information significantly influences decision making. These results are consistent with the theory that the main purpose of the foundation's financial statements is to provide relevant information to meet the foundation's internal and external interests to help decision makers make the best decisions for the organization. Second, organizational culture significantly influences decision making. This result is in line with organizational culture theory which states that organizational culture is a value that is used as a reference in all decisions and actions of members of the organization and that reflects the goals, identity, and standard of evaluation of everything in the organization. So it was concluded that the best decision was a decision made based on accounting information and organizational culture at a Catholic education foundation in Indonesia

scholarly journals Fixation patterns in simple choice reflect optimal information sampling

2019 ◽  
Author(s):  
Frederick Callaway ◽  
Antonio Rangel ◽  
Tom Griffiths
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Sequential Sampling ◽  
Empirical Work ◽  
Reaction Times ◽  
Optimal Solution ◽  
Cognitive Resources ◽  
Human Decision ◽  
Information Sampling ◽  
Optimal Information

When faced with a decision between several options, people rarely fully consider every alternative. Instead, we direct our attention to the most promising candidates, focusing our limited cognitive resources on evaluating the options that we are most likely to choose. A growing body of empirical work has shown that attention plays an important role in human decision making, but it is still unclear how people choose with option to attend to at each moment in the decision making process. In this paper, we present an analysis of how a rational decision maker should allocate her attention. We cast attention allocation in decision making as a sequential sampling problem, in which the decision maker iteratively selects from which distribution to sample in order to update her beliefs about the values of the available alternatives. By approximating the optimal solution to this problem, we derive a model in which both the selection and integration of evidence are rational. This model predicts choices and reaction times, as well as sequences of visual fixations. Applying the model to a ternary-choice dataset, we find that its predictions align well with human data.

Decision-Making Model for Convention Site Selection

2012 ◽  
Vol 538-541 ◽  
pp. 895-900 ◽  
Author(s):  
Han Chen Huang
Keyword(s):  
Decision Making ◽  
Site Selection ◽  
Political Conflict ◽  
Decision Makers ◽  
City Image ◽  
Analytic Hierarchy ◽  
Number Of Factors ◽  
Decision Making Model ◽  
Hierarchy Process

A number of factors must be considered when selecting a convention site. Typically, most selections are based on the decision makers’ knowledge and experience, which may lead to biased decisions based on the decision makers’ subjective judgment. This study establishes decision-making evaluation factors and attributes for convention site selection based on a literature review. After surveying experts’ opinions using questionnaires, we employed the fuzzy analytic hierarchy process (FAHP) to analyze the weighting of the factors and attributes. The results show that of the five evaluation factors, site environment is the most important, followed by meeting and accommodation facilities, local support, extraconference opportunities, and costs. Additionally, the five most important attributes among the 20 evaluation attributes are the suitability of convention facilities, suitability and quality of local infrastructure, climate, city image, and political conflict or terrorist threats.

Constructing a Hierarchy and Simulation Model to Assess Digital Recorder Sensor System

2012 ◽  
Vol 263-266 ◽  
pp. 857-860
Author(s):  
Kuang Jung Tseng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Safety Evaluation ◽  
Decision Makers ◽  
Sensor System ◽  
Model Following ◽  
Proposed Model ◽  
Digital Recorder ◽  
Decision Making Model

This work presents group decision making model, following a university safety evaluation to demonstrate the effectiveness of the proposed model. Importantly, the proposed model can assist university decision makers to buy the feasibility of digital recorder sensor system, making it highly applicable for academic and commercial purposes.

Conceptualizing Emergency Department Scenarios

2015 ◽  
pp. 1351-1368 ◽  
Author(s):  
Maya Kaner ◽  
Tamar Gadrich ◽  
Shuki Dror ◽  
Yariv N. Marmor
Keyword(s):  
Emergency Department ◽  
Real Life ◽  
Relevant Information ◽  
Literature Survey ◽  
Decision Makers ◽  
Simulation Experiments ◽  
Management Staff ◽  
Ed Operations ◽  
Relevant Factors

To handle problems and trends in emergency department (ED) operations, designers and decision makers often simulate and evaluate various case-specific scenarios before testing them in a real-life environment. However, conceptualizing broad possible scenarios for ED operations prior to simulation operationalization is usually neglected. The authors developed a methodology that integrates design of simulation experiments (DSE) as follows: 1) From a literature survey, they culled generic factors whose varying levels determine possible scenarios; 2) the authors drew up a set of generic interactions among these generic factors; 3) a questionnaire was constructed to serve as an instrument to gather the relevant information from management staff about relevant factors, their levels and interactions for a specific ED. Questionnaire responses support a schematic conceptualization of scenarios that should be simulated for a specific ED. They illustrate the application of the authors' methodology for conceptualization of ED simulation scenarios in two different EDs.

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