Hierarchical fuzzy TOPSIS model for selection among logistics information technologies

Abstract

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.

Citation

Kahraman, C., Yasin Ateş, N., Çevik, S., Gülbay, M. and Ayça Erdoğan, S. (2007), "Hierarchical fuzzy TOPSIS model for selection among logistics information technologies", Journal of Enterprise Information Management, Vol. 20 No. 2, pp. 143-168. https://doi.org/10.1108/17410390710725742