scholarly journals Cooperative Decision Support Systems

2011 ◽  
pp. 109-115 ◽  
Author(s):  
Pascale Zaraté
Keyword(s):  
Decision Making ◽  
Search Space ◽  
Optimal Decision ◽  
Decision Making Process ◽  
Collaborative Decision Making ◽  
Distributed Reasoning ◽  
Cooperative Decision Making ◽  
Optimal Decision Making ◽  
Analytical Tools ◽  
Collaborative Decision

The subject of our research aims to support in the most suitable way the collaborative decision-making process. Several scientific approaches deal with collaborative decision-making: decision analysis (Carlsson & Turban, 2002; Doyle & Thomason, 1999; Keeney & Raiffa, 1976) developing different analytical tools for optimal decision-making; in management sciences the observation of decision-making styles activity (Nuut, 2005; Fong, Wyer, & Robert 2003); decision-making as a group work (Esser, 1998; Matta & Corby, 1997); studies concerning different types of decisions focalised on number of actors: individual (Keeney & Raiffa, 1976), group (Shim, Warkentin, Courtney, Power, Sharda, & Carlsson, 2002), cooperative (Zaraté, 2005), and collaborative (Karacapilidis & Papadias, 2001). For the collaborative decision-making field, the situation is clear. In most of research studies, the concept of collaborative decision-making is used as a synonym for cooperative decision-making. Hence, the collaborative decision-making process is considered to be distributed and asynchronous (Chim, Anumba, & Carillo, 2004; Cil, Alpturk, & Yazgan, 2005). However, we can stand out several works, having different research approaches, considering collaborative decision-making process as multi-actor decision-making process, where actors have different goals. Considering (Panzarasa, Jennings, & Norman, 2002) the collaborative decision-making process is seen as “a group of logically decentralised agents that cooperate to achieve objectives that are typically beyond the capacities of an individual agent. In short, the collaborative decision-making has generally been viewed and modelled as a kind of distributed reasoning and search, whereby a collection of agents collaboratively go throughout the search space of the problem in order to find a solution.” The main interrogation of this article is to study the best way to support collaborative decision-making process.

scholarly journals Cooperative Decision Support Systems

2011 ◽  
pp. 1551-1558
Author(s):  
Pascale Zaraté
Keyword(s):  
Decision Making ◽  
Search Space ◽  
Optimal Decision ◽  
Decision Making Process ◽  
Collaborative Decision Making ◽  
Decisionmaking Process ◽  
Distributed Reasoning ◽  
Cooperative Decision Making ◽  
Optimal Decision Making ◽  
Collaborative Decision

The subject of our research aims to support in the most suitable way the collaborative decisionmaking process. Several scientific approaches deal with collaborative decision-making: decision analysis (Carlsson & Turban, 2002; Doyle & Thomason, 1999; Keeney & Raiffa, 1976) developing different analytical tools for optimal decision-making; in management sciences the observation of decision-making styles activity (Nuut, 2005; Fong, Wyer, & Robert 2003); decision-making as a group work (Esser, 1998; Matta & Corby, 1997); studies concerning different types of decisions focalised on number of actors: individual (Keeney & Raiffa, 1976), group (Shim, Warkentin, Courtney, Power, Sharda, & Carlsson, 2002), cooperative (Zaraté, 2005), and collaborative (Karacapilidis & Papadias, 2001). For the collaborative decision-making field, the situation is clear. In most of research studies, the concept of collaborative decision-making is used as a synonym for cooperative decision-making. Hence, the collaborative decision-making process is considered to be distributed and asynchronous (Chim, Anumba, & Carillo, 2004; Cil, Alpturk, & Yazgan, 2005). However, we can stand out several works, having different research approaches, considering collaborative decision-making process as multi-actor decision-making process, where actors have different goals. Considering (Panzarasa, Jennings, & Norman, 2002) the collaborative decision-making process is seen as “a group of logically decentralised agents that cooperate to achieve objectives that are typically beyond the capacities of an individual agent. In short, the collaborative decision-making has generally been viewed and modelled as a kind of distributed reasoning and search, whereby a collection of agents collaboratively go throughout the search space of the problem in order to find a solution.” The main interrogation of this article is to study the best way to support collaborative decisionmaking process.

Study on Emergency Decision-Making of Natural Disaster Based on Collaboration of Multi-Agent

2013 ◽  
Vol 411-414 ◽  
pp. 2684-2693
Author(s):  
Yue E ◽  
Ye Ping Zhu
Keyword(s):  
Decision Making ◽  
Natural Disaster ◽  
Decision Making Process ◽  
Collaborative Decision Making ◽  
Agent Theory ◽  
Emergency Decision Making ◽  
Multi Agent ◽  
Emergency Decision ◽  
Decision Making Model ◽  
Collaborative Decision

Based on the occurrence and evolution of the natural disaster is characteristic of uncertainty and complexity, in this article, Agent theory and technology is applied to emergency decision-making of natural disaster in China, built the disaster emergency collaborative decision-making framework based on multi-agent, design the collaborative decision-making model, discuss the emergency decision-making mechanism based on scenario-response, through effective collaboration based on multi-agent, achieve natural disaster dynamic emergency decision-making process.

Towards a Novel Approach for Enterprise Knowledge Capitalization Utilizing an Ontology and Collaborative Decision-Making

2016 ◽  
Vol 8 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Fatima Zohra Benkaddour ◽  
Noria Taghezout ◽  
Bouabdellah Ascar
Keyword(s):  
Decision Making ◽  
Decision Making Process ◽  
Case Based Reasoning ◽  
Collaborative Decision Making ◽  
Novel Approach ◽  
New Ideas ◽  
Collaborative Platform ◽  
Collaborative Decision ◽  
Production Industry ◽  
Reasoning Engine

In this paper, the authors describe the development of a Decision Support System (DSS) in the spunlace nonwoven production industry. The suggested DSS utilizes domain ontology and a collaborative platform that allows operators to share and exchange experiences in the industrial diagnosis in order to have new ideas and useful information for collaborative decision-making. One of the main aspects addressed in the decision-making process was the knowledge management of the most frequently breakdowns of machines as the card, aquajet etc. This paper introduces the architecture of the system, including several modules such as, Reasoning engine and Similarity module, etc. The decision-making is reinforced by a case-based reasoning to recommend solutions where previously solved cases (problem) are compared to recently encountered ones using the same ontology to define similarity between cases. Some experiments have been conducted in INOTIS enterprise to indicate the efficiency of the proposed system.

Developing effective academic accommodations in higher education: A collaborative decision-making process

2017 ◽  
Vol 36 (2) ◽  
pp. 244-258 ◽  
Author(s):  
Feilin Hsiao ◽  
Shelly Zeiser ◽  
Daniel Nuss ◽  
Keith Hatschek
Keyword(s):  
Decision Making ◽  
Students With Disabilities ◽  
Case Reports ◽  
Decision Making Process ◽  
Sources Of Information ◽  
Academic Accommodations ◽  
Structured Interviews ◽  
Collaborative Decision Making ◽  
Self Advocacy ◽  
Collaborative Decision

This case study describes a collaborative decision-making process for developing effective academic accommodations for a music major with a disability, whose prior accommodations suggested by the Disability Support Services (DSS) failed to address her needs. Cross-departmental collaboration between the DSS and the School of Music, as well as dynamic interactions among students with disabilities (SWDs), faculty members, peer tutors, and DSS specialists are emphasized. Multiple sources of information were collected, including in-depth/semi-structured interviews and a review of all relevant documentation such as case reports, weekly logs, email correspondence, results of psychological testing and academic portfolio contents. The themes that emerged from the data include resistance to the unknown, the language of negotiation, the decision-making process, and transformation (with three sub-themes: from fear of stigmatization to self-advocacy, from resentfulness to acceptance and commitment, and from reaction to pro-action). Key elements contributing to the collaborative process consist of effective communication among all members, the promotion of self-advocacy skills for SWDs, and faculty’s recognition of SWDs’ potential to succeed and while engaging flexible methods for delivering course content and assessing outcomes. A framework for delivering viable services for music majors with disabilities is outlined and discussed.

Collaborative Decision Making

2010 ◽  
pp. 731-741
Author(s):  
Marija Jankovic ◽  
Pascale Zaraté ◽  
Jean-Claude Bocquet ◽  
Julie Le Cardinal
Keyword(s):  
Decision Making ◽  
Working Conditions ◽  
Collaborative Decision Making ◽  
Face To Face ◽  
Distributed Decision Making ◽  
Team Working ◽  
Geographical Dispersion ◽  
Cooperative Decision Making ◽  
Collaborative Decision ◽  
Support Decision Making

Recent years we can hear a lot about cooperative decision-making, group or collaborative decision-making. These types of decisions are the consequences of developed working conditions: geographical dispersion, team working, and concurrent working. In the article we present two research works concerning two different collective decision situations: face-to-face decision-making and synchronous distributed decision-making. These two research studies adopt different approaches in order to support decision-making process, in view to different research objectives. Nevertheless, the conclusions show complementary aspect of these two studies.

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