Dynamic decision making with feasibility goals: A procedural-rationality approach

This paper applies a social learning model to the optimal consumption rule of Allen and Carroll [Macroeconomic Dynamics 5(2001), 255–271] and delivers convincing convergence dynamics toward the optimal rule. These findings constitute a significant improvement over previous results in the literature, in terms of both speed of convergence and parsimony of the learning model. The learning model exhibits several appealing features: it is frugal, is easy to apply to a various range of learning objectives, and requires few procedures and little information. Particular care is given to behavioral interpretation of the modeling assumptions in light of evidence from the fields of psychology and social science. Our results highlight the need to depart from the genetic metaphor, and account for intentional decision-making, based on agents' relative performances. By contrast, we show that convergence is strongly hindered by exact imitation processes, or random exploration mechanisms, which are usually assumed when modeling social learning behavior. Our results suggest a method for modeling bounded rationality, which could be interestingly tested in a wide range of economic models with adaptive dynamics.

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“…NOTES 1. A similar question arises in the case of optimal portfolio selection during life cycles; see Binswanger (2011).…”

Section: Discussionmentioning

confidence: 91%

Social Learning About Consumption

Salle

Seppecher

2015

Macroecon. Dynam.

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“…The definition of organizational goals covers the scope of organization performance, evaluation, structureandrelationship (Binswanger,2011;Bouskila-Yam&Kluger,2011;Lepmetsetal.,2012;Raoetal.,2012;Sharma&Osei-Bryson,2008).Withrespecttothepreviousstudies (Binswanger, 2011;Bouskila-Yam&Kluger,2011;Lepmetsetal.,2012;Raoetal.,2012;Sharma&Osei-Bryson, 2008),thereisnostudythatfocusesontheachievementoftheorganizationalgoalsbasedonan ontology.Inthisthesis,weaimtodevelopaframeworkbasedonanontologytoevaluatetheextent towhichtheorganizationalgoalshavebeenachieved.Wesuggestanontologyasonewaytodevelop therelationshipbetweenorganizationalgoalselements.…”

Section: Limited Definition Of the Organizational Goals Ontologymentioning

confidence: 98%

Key Issues and the Requirements for an Effective Enterprise Decision-Making Using an Ontology-Based GOAL-Framework for Evaluation of the Organizational Goals Achievement

Izhar

Torabi

Bhatti

2019

International Journal of Knowledge-Based Organizations

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This article proposes the GOAL-Framework for the evaluation of organizational goals based on an ontology. The aim is to capture and analyze relevant data for the organization goals because determining relevant data is a key to delivering value from massive amounts of data for better decision-making in relation to the organizational goals achievement. The framework will allow the domain experts and entrepreneurs to evaluate relevant organizational data to assist the decision-making process with respect to the organizational goals. Hence, they will be able to identify to what extent certain organizational goals could be achieved. In order to test the flexibility and applicability of the GOAL-Framework, a case study is presented to explain how the framework is implemented and applied to a real world situation. The outcome of the case study demonstrates that the framework can be applied for analysis and decision-making based on the metrics using the dashboard to evaluate the extent to which the organizational goals could be achieved.

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“…There are limited studies on the evaluation of organizational goals, especially in terms of evaluating the organizational data. Most studies on organizational goals focus on organizational performance, setting and behaviour [6], [16], [17]. There are several limitations in the existing literature in relation to structure and evaluation.…”

Section: Literature Reviewmentioning

confidence: 99%

Managing Information for The Organizational Goal: Relationship and Function

Izhar¹,

Torabi²

2018

IJI

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Data is important to assist organization with decision-making in order to achieve the organizational goals. However, the trustworthiness of data is questioned because of the vast amount of data produced. This paper proposes an approach to utilize information from operational data to support the organizational goal. The challenge is to convert this data into meaningful information. This is critical for all enterprises to remain competitive. The aim of this paper is to propose a model to emphasize the dependency relationship involve between the variables such as organizational goal, sub-goals, actions, data input and data output. The relationship is important to assist the development of data measurement, data analysis and data modeling to measure the level of the organizational goals achievement. The contribution of this paper may serve as a first step to understand the dependency relationship between data and organizational goals to utilize meaningful information for efficient decisionmaking.

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Dynamic decision making with feasibility goals: A procedural-rationality approach

Cited by 11 publications

References 21 publications

Social Learning About Consumption

Social Learning About Consumption

Key Issues and the Requirements for an Effective Enterprise Decision-Making Using an Ontology-Based GOAL-Framework for Evaluation of the Organizational Goals Achievement

Managing Information for The Organizational Goal: Relationship and Function

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