Group Decision Making for Advanced Manufacturing Technology Selection Using the Choquet Integral

2011 ◽  
pp. 193-212
Author(s):  
Cengiz Kahraman ◽  
Selçuk Çebi ◽  
Ihsan Kaya
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Choquet Integral ◽  
Manufacturing Technology ◽  
Advanced Manufacturing Technology ◽  
Advanced Manufacturing ◽  
Group Members ◽  
Automated Storage ◽  
Method Of Production

Advanced manufacturing technology (AMT) is defined as a modern method of production incorporating highly automated and sophisticated computerized design and operational systems. Hence, an investment decision to adopt AMT is a strategic decision. A group decision making process is stressful when group members have different views under multiple and conflicting criteria. Satisfying group members’ opinions has a critical impact on a decision. In this chapter, a multiple criteria group decision making problem under a fuzzy environment is used for the selection among AMTs. Choquet integral methodology is used for this selection. A strategic investment problem of a company for a suitable Automated Storage/Retrieval System (AS/RS) is considered and discussed.

Group Decision Making for Advanced Manufacturing Technology Selection Using the Choquet Integral

2012 ◽  
pp. 1115-1134
Author(s):  
Cengiz Kahraman ◽  
Selçuk Çebi ◽  
Ihsan Kaya
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Choquet Integral ◽  
Manufacturing Technology ◽  
Advanced Manufacturing Technology ◽  
Advanced Manufacturing ◽  
Group Members ◽  
Automated Storage ◽  
Method Of Production

Advanced manufacturing technology (AMT) is defined as a modern method of production incorporating highly automated and sophisticated computerized design and operational systems. Hence, an investment decision to adopt AMT is a strategic decision. A group decision making process is stressful when group members have different views under multiple and conflicting criteria. Satisfying group members’ opinions has a critical impact on a decision. In this chapter, a multiple criteria group decision making problem under a fuzzy environment is used for the selection among AMTs. Choquet integral methodology is used for this selection. A strategic investment problem of a company for a suitable Automated Storage/Retrieval System (AS/RS) is considered and discussed.

A Formal Approach to Handling Conflicts in Multiattribute Group Decision Making

2005 ◽  
Vol 128 (4) ◽  
pp. 678-688 ◽  
Author(s):  
Tung-King See ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Problems ◽  
Team Leaders ◽  
Formal Approach ◽  
Aggregation Functions ◽  
Group Members ◽  
Problem Data

Supporting the decision of a group in engineering design is a challenging and complicated problem when issues like consensus and compromise must be taken into account. In this paper, we present the foundations of the group hypothetical equivalents and inequivalents method and two fundamental extensions making it applicable to new classes of group decision problems. The first extension focuses on updating the formulation to place unequal importance on the preferences of the group members. The formulation presented in this paper allows team leaders to emphasize the input from certain group members based on experience or other factors. The second extension focuses on the theoretical implications of using a general class of aggregation functions. Illustration and validation of the developments are presented using a vehicle selection problem. Data from ten engineering design groups are used to demonstrate the application of the method.

scholarly journals Learning While Deciding in Groups

2019 ◽  
Author(s):  
Scott Tindale ◽  
Jeremy R. Winget
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Processes ◽  
Learning Potential ◽  
Group Members ◽  
Actual Learning

Groups are used to make many important societal decisions. Similar to individuals, by paying attention to the information available during the decision processes and the consequences of the decisions, groups can learn from their decisions as well. In addition, group members can learn from each other by exchanging information and being exposed to different perspectives. However, groups make decisions in many different ways and the potential and actual learning that takes place will vary as a function of the manner in which groups reach consensus. This chapter reviews the literature on group decision making with a special emphasis on how and when group decision making leads to learning. We argue that learning is possible in virtually any group decision making environment but freely interacting groups create the greatest potential for learning. We also discuss when and why group may not always take advantage of the learning potential.

Decision Making Approaches for Advanced Manufacturing Technology Evaluation and Selection

2012 ◽  
pp. 403-438 ◽  
Author(s):  
Aidé Maldonado-Macías ◽  
Jorge Luis García-Alcaraz ◽  
Francisco Javier Marrodan Esparza ◽  
Carlos Alberto Ochoa Ortiz Zezzatti
Keyword(s):  
Decision Making ◽  
Manufacturing Technology ◽  
Advanced Manufacturing Technology ◽  
Advanced Manufacturing ◽  
Manufacturing Companies ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Broad Variety ◽  
Complex Decision ◽  
Selection Of

Advanced Manufacturing Technology (AMT) constitutes one of the most important resources of manufacturing companies to achieve success in an extremely competitive world. Decision making processes for the Evaluation and Selection of AMT in these companies must lead to the best alternative available. Industry is looking for a combination of flexibility and high quality by doing significant investments in AMT. The proliferation of this technology has generated a whole field of knowledge related to the design, evaluation and management of AMT systems which includes a broad variety of methodologies and applications. This chapter presents a theoretical review of the term AMT, its diverse classification and a collection of the most effective multi-attribute models and methodologies available to support these processes. Relevant advantages are found in these models since they can manage complex decision making problems which involve large amount of information and attributes. These attributes frequently can be tangible and intangible when vagueness and uncertainty exist. There are several multi-attribute methodologies which are extensively known and used in literature; nevertheless, a new fuzzy multi-attribute axiomatic design approach is explained for an ergonomic compatibility evaluation of AMT.

A Formal Approach to Handling Conflicts in Multiattribute Group Decision Making

2004 ◽  
Author(s):  
Tung-King See ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Support Group ◽  
Group Decision Making ◽  
Group Decision ◽  
Formal Approach ◽  
Attribute Weights ◽  
Decision Methods ◽  
Group Members ◽  
The Relationship ◽  
Support Decision Making

The Hypothetical Equivalents and Inequivalents Method (HEIM) has been developed to support decision making in multiattribute problems where one decision maker is making the decision. In this paper HEIM is modified to support group decision making in multiattribute problems, resulting in the Group Hypothetical Equivalents and Inequivalents Method (G-HEIM). Instead of aggregating attribute weights or overall alternative values from each individual as is common in other group decision methods, G-HEIM operates by aggregating individual preferences. It is recognized that in group decision making, common preferences among group members can rarely be guaranteed, unless individual freedom is greatly limited. G-HEIM instead allows individuals to freely express preferences over a number of hypothetical alternatives and then explores the level of conflict or differences from the aggregated group preferences. The relationship between the level of conflicting preferences and the usability of the resulting decision is also directly studied using the G-HEIM. An automotive selection example is used to illustrate the approach.

scholarly journals Influencing the physiology and decisions of groups: Physiological linkage during group decision-making

2019 ◽  
Vol 24 (1) ◽  
pp. 145-159
Author(s):  
Katherine R. Thorson ◽  
Oana D. Dumitru ◽  
Wendy Berry Mendes ◽  
Tessa V. West
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Physiological Response ◽  
Group Decision ◽  
Physiological Responses ◽  
High Status ◽  
Group Members ◽  
Physiological Linkage ◽  
To Come ◽  
Middle Status

Many of the most important decisions in our society are made within groups, yet we know little about how the physiological responses of group members predict the decisions that groups make. In the current work, we examine whether physiological linkage from “senders” to “receivers”—which occurs when a sender’s physiological response predicts a receiver’s physiological response—is associated with senders’ success at persuading the group to make a decision in their favor. We also examine whether experimentally manipulated status—an important predictor of social behavior—is associated with physiological linkage. In groups of 5, we randomly assigned 1 person to be high status, 1 low status, and 3 middle status. Groups completed a collaborative decision-making task that required them to come to a consensus on a decision to hire 1 of 5 firms. Unbeknownst to the 3 middle-status members, high- and low-status members surreptitiously were told to each argue for different firms. We measured cardiac interbeat intervals of all group members throughout the decision-making process to assess physiological linkage. We found that the more receivers were physiologically linked to senders, the more likely groups were to make a decision in favor of the senders. We did not find that people were physiologically linked to their group members as a function of their fellow group members’ status. This work identifies physiological linkage as a novel correlate of persuasion and highlights the need to understand the relationship between group members’ physiological responses during group decision-making.

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