About this paper

Appears in:
Pages: 6057-6064
Publication year: 2011
ISBN: 978-84-615-0441-1
ISSN: 2340-1117

Conference name: 3rd International Conference on Education and New Learning Technologies
Dates: 4-6 July, 2011
Location: Barcelona, Spain

FUZZY GROUP DECISION MAKING IN RESEARCH MANAGEMENT

J.M. Merigó, M. Casanovas

University of Barcelona (SPAIN)
Research management involves all the topics regarding the administration of research in any kind of organization. In our modern world, the need for an efficient research department in a wide range of organizations is very important in order to stay competitive with all the changes that are occurring in our environment. In order to do so, the enterprises need to use a wide range of strategies based on the use of the appropriate decision making processes. In the literature, we find a wide range of decision making processes. A very useful one for dealing with imprecise environments is fuzzy group decision making. Its main advantages are the possibility of dealing with uncertain environments that can be assessed with fuzzy numbers (FNs) and the use of the opinion of several experts that provide a more robust representation of the information. In this paper, we use a fuzzy group decision making approach based on the use of the fuzzy induced probabilistic ordered weighted averaging weighted averaging (FIPOWAWA) operator. It is a new aggregation operator that unifies the probability, the weighted average and the OWA operator in the same formulation considering the degree of importance that each concept has in the analysis and in an imprecise environment assessed with FNs. Thus, it can deal with subjective and objective information and considering the attitudinal character of the decision maker in the analysis. Moreover, it also uses order inducing variables that deals with complex reordering processes that represent complex environments that cannot be easily quantified numerically. We see that this new aggregation operator can be implemented in a wide range of areas such as statistics, physics, business and engineering. We develop a fuzzy group decision making approach by using fuzzy multi-person aggregation operators. Thus, we form the multi-person FIPOWAWA (MP-FIPOWAWA) operator. It uses the opinion of several experts in the analysis providing a deeper representation of the imprecise information. We analyze the selection of the optimal research strategy in a university.
@InProceedings{MERIGO2011FUZ,
author = {Merig{\'{o}}, J.M. and Casanovas, M.},
title = {FUZZY GROUP DECISION MAKING IN RESEARCH MANAGEMENT},
series = {3rd International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN11 Proceedings},
isbn = {978-84-615-0441-1},
issn = {2340-1117},
publisher = {IATED},
location = {Barcelona, Spain},
month = {4-6 July, 2011},
year = {2011},
pages = {6057-6064}}
TY - CONF
AU - J.M. Merigó AU - M. Casanovas
TI - FUZZY GROUP DECISION MAKING IN RESEARCH MANAGEMENT
SN - 978-84-615-0441-1/2340-1117
PY - 2011
Y1 - 4-6 July, 2011
CI - Barcelona, Spain
JO - 3rd International Conference on Education and New Learning Technologies
JA - EDULEARN11 Proceedings
SP - 6057
EP - 6064
ER -
J.M. Merigó, M. Casanovas (2011) FUZZY GROUP DECISION MAKING IN RESEARCH MANAGEMENT, EDULEARN11 Proceedings, pp. 6057-6064.
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