A framework for context-aware heterogeneous group decision making in business processes

2016 ◽  
Vol 102 ◽  
pp. 39-50 ◽  
Author(s):  
Carmen De Maio ◽  
Giuseppe Fenza ◽  
Vincenzo Loia ◽  
Francesco Orciuoli ◽  
Enrique Herrera-Viedma
Mathematics ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 93
Author(s):  
Marcelo Loor ◽  
Ana Tapia-Rosero ◽  
Guy De Tré

A flexible attribute-set group decision-making (FAST-GDM) problem consists in finding the most suitable option(s) out of the options under consideration, with a general agreement among a heterogeneous group of experts who can focus on different attributes to evaluate those options. An open challenge in FAST-GDM problems is to design consensus reaching processes (CRPs) by which the participants can perform evaluations with a high level of consensus. To address this challenge, a novel algorithm for reaching consensus is proposed in this paper. By means of the algorithm, called FAST-CR-XMIS, a participant can reconsider his/her evaluations after studying the most influential samples that have been shared by others through contextualized evaluations. Since exchanging those samples may make participants’ understandings more like each other, an increase of the level of consensus is expected. A simulation of a CRP where contextualized evaluations of newswire stories are characterized as augmented intuitionistic fuzzy sets (AIFS) shows how FAST-CR-XMIS can increase the level of consensus among the participants during the CRP.


2010 ◽  
Vol 25 (2) ◽  
pp. 31-39 ◽  
Author(s):  
Goreti Marreiros ◽  
Ricardo Santos ◽  
Carlos Ramos ◽  
Jose Neves

2014 ◽  
Vol 693 ◽  
pp. 237-242
Author(s):  
Kateřina Kashi ◽  
Jiří Franek

The aim of this applied research is to focus on real-life application of multiple attribute decision making (MADM) methods and their adaptation in a way which can be acceptable for business practice. The study will apply the group decision making methods on a Balanced Scorecard (BSC) as a type of performance measurement and strategic decision making. The study is mainly concerned with multiple criteria decomposition method of analytic network process (ANP) method, WINGS technique and entropy. This group of methods had been already applied in several business domains. However, majority of the implementation was only presented as an example how it could work in practice, but they were not investigated from the perspective of how much information they could provide to the management. In this paper, proposed methods will be used to determine which criteria are most important for the company within the Balanced Scorecard and results of all methods will be compared. The aim of this study is, by utilizing group MADM approach, to discover the areas of the BSC which must be improved so that a total performance increases.


2005 ◽  
Vol 9 (3) ◽  
pp. 47-52
Author(s):  
Alpana M. Desai

The technical management of important natural resources such as oil and gas resources is a challenging responsibility that faces oil companies. The increasing global demand for oil and gas coupled with declining oil and gas reserves has forced the oil industry to make significant changes in its business processes. Major oil companies have exploration and production operations that span several continents. Massive amount of data that is generated at all levels in an oil company has to be stored, analyzed and disseminated. In this paper, the changes in the management practices and business processes in the oil industry are traced over the past several decades. The use and application of information technology as change agents is also explored and evaluated. In particular, this paper focuses on the role of visualization centers in the oil and gas industry in revolutionizing effective group decision making that has enabled teams to be more productive, innovative, and outcome-focused.


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