TY - JOUR
T1 - Hierarchical fuzzy TOPSIS model for selection among logistics information technologies
AU - Kahraman, Cengiz
AU - Yasin Ateş, Nüfer
AU - Çevik, Sezi
AU - Gülbay, Murat
AU - Ayça Erdoğan, S.
PY - 2007/2
Y1 - 2007/2
N2 - Purpose To develop a multi–attribute decision making model for evaluating and selecting among logistic information technologies. Design/methodology/approach First a multi–attribute decision making model for logistic information technology evaluation and selection consisting of 4 main and 11 sub criteria is constructed, then a hierarchical fuzzy TOPSIS method is developed to solve the complex selection problem with vague and linguistic data. Sensitivity analysis is presented. Findings Reviews the literature and provides a structured hierarchical model for logistic information technology evaluation and selection based on the premise that the logistic information technology evaluation and selection problem can be viewed as a product of tangible benefits, intangible benefits, policy issues and resources. Defines tangible benefits as cost savings, increased revenue, and return on investment; intangible benefits as customer satisfaction, quality of information, multiple uses of information, and setting tone for future business; policy issues as risk and necessity level; resources as costs and completion time. Presents a methodology that is developed for the complex, uncertain and vague characteristics of the problem. Research limitations/implications Comparisons with other multi–attribute decision making techniques such as AHP, ELECTRE, PROMETHEE and ORESTE under fuzzy conditions can be done for further research. Practical implications This article is a very useful source of information both for logistic managers and stakeholders in making decisions about logistic information technology investments. Originality/value This paper addresses the logistic information technology evaluation and selection criteria for practitioners and proposes a new multi–attribute decision making methodology, hierarchical fuzzy TOPSIS, for the problem.
AB - Purpose To develop a multi–attribute decision making model for evaluating and selecting among logistic information technologies. Design/methodology/approach First a multi–attribute decision making model for logistic information technology evaluation and selection consisting of 4 main and 11 sub criteria is constructed, then a hierarchical fuzzy TOPSIS method is developed to solve the complex selection problem with vague and linguistic data. Sensitivity analysis is presented. Findings Reviews the literature and provides a structured hierarchical model for logistic information technology evaluation and selection based on the premise that the logistic information technology evaluation and selection problem can be viewed as a product of tangible benefits, intangible benefits, policy issues and resources. Defines tangible benefits as cost savings, increased revenue, and return on investment; intangible benefits as customer satisfaction, quality of information, multiple uses of information, and setting tone for future business; policy issues as risk and necessity level; resources as costs and completion time. Presents a methodology that is developed for the complex, uncertain and vague characteristics of the problem. Research limitations/implications Comparisons with other multi–attribute decision making techniques such as AHP, ELECTRE, PROMETHEE and ORESTE under fuzzy conditions can be done for further research. Practical implications This article is a very useful source of information both for logistic managers and stakeholders in making decisions about logistic information technology investments. Originality/value This paper addresses the logistic information technology evaluation and selection criteria for practitioners and proposes a new multi–attribute decision making methodology, hierarchical fuzzy TOPSIS, for the problem.
UR - http://www.scopus.com/inward/record.url?scp=33846941975&partnerID=8YFLogxK
U2 - 10.1108/17410390710725742
DO - 10.1108/17410390710725742
M3 - Article
AN - SCOPUS:33846941975
SN - 1741-0398
VL - 20
SP - 143
EP - 168
JO - Journal of Enterprise Information Management
JF - Journal of Enterprise Information Management
IS - 2
ER -