Decision-making with measure modeled uncertain payoffs and multiple goals

2019 ◽  
Vol 5 (2) ◽  
pp. 149-154
Author(s):  
Ronald R. Yager
1979 ◽  
Vol 3 (4) ◽  
pp. 31-41 ◽  
Author(s):  
Sang M. Lee ◽  
Robert T. Justis ◽  
Lori Sharp Franz

There are few analytical and managerial tools available to assist the small business decision maker. This paper presents a practical goal Programming model which can be easily generalized to fit the planning needs of most small businesses. Specifically the model explicitly considers the multiple goals and priorities of the owner-manager and determines if these goals can be accomplished under various demand Projections. An illustrative example of the use of this model with a small fast-food business is given.


Author(s):  
Daniel A. Levinthal ◽  
Claus Rerup

In the Carnegie School tradition of experiential learning, learning processes are driven by the encoding of performance outcomes as a success or failure relative to a goal. We expand this line of inquiry by highlighting how conflicting and thus ambiguous outcomes across multiple goals make interpretation a critical aspect of organizational learning processes. In early work in the Carnegie tradition, interpretation played a role in the demarcation between what constituted success or failure on a given outcome metric. However, in March’s latter writings, learning and decision making produce an arena or even an opportunity for generating interpretations and broader meanings regarding roles, values, and identities. We explore how the two interpretive approaches in March’s work play out across three modes of responses to ambiguity. First, the process of self-enhancement whereby participants interpret conflictual outcomes so that they, the participants, appear in a positive light. Second, an explicit political process regarding the contestation of how to interpret conflicting outcomes. Third, from the perspective of the organizations’ literature on wisdom, participants may embrace ambiguity either to enhance learning or simply to enrich individuals’ interpretation of their experiences. Although these three modes of response do not offer a complete set of responses for learning in a world of ambiguity, they constitute valuable touchstones for the perspective we wish to put forward and, collectively, help enrich our understanding of the role of learning, ambiguity and interpretation within the Carnegie School.


1980 ◽  
Vol 12 (1) ◽  
pp. 199-204 ◽  
Author(s):  
George F. Patrick ◽  
Brian F. Blake

Farmers and other business people commonly consider multiple goals or objectives in their-decisions, especially investment or other long-run decisions. Various techniques, such as discussed by Keeney and Raiffa, have been developed to incorporate multiple goals or objectives in decision making. These techniques differ in how the decision-making process is viewed, empirical data required about goals, and solution algorithms. Considerable emphasis has been given to development of alternative models and solution algorithms, but problems (Willis and Perlack), of quantifying farmers' goals for use in these models have received relatively little attention.


1974 ◽  
Vol 6 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Roy E. Hatch ◽  
Wyatte L. Harman ◽  
Vernon R. Eidman

Although the importance of multiple goals in the decision-making process has been recognized for years by economists, economic analyses typically are based on the assumption of maximization or minimization of a single goal. Some firm growth analyses have considered two or more goals by maximizing one goal subject to constraints on the remaining goals. In other cases, utility functions that incorporate expected income and income variability have been estimated for individual farm operators. Although these approaches are an effort to incorporate more than one goal in the decision process, firm growth research in general has not been based on multiple-goal decision models.


2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.


2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.


2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.


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