MATEC Web Conf.
Volume 192, 2018The 4th International Conference on Engineering, Applied Sciences and Technology (ICEAST 2018) “Exploring Innovative Solutions for Smart Society”
|Number of page(s)||9|
|Section||Track 1: Industrial Engineering, Materials and Manufacturing|
|Published online||14 August 2018|
Environmental performance assessment using the evidential reasoning approach: The case of logistics service providers
Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, 123 Moo 16, Mittraphap Road, Khon Kaen 40002, Thailand
Corresponding author: firstname.lastname@example.org
The demand for environmental performance assessment is increasing among business practitioners, and it has nowadays become one of the key factors for a company’s self-improvement as well as for selecting suppliers and logistics providers. The assessment is, in essence, a multiple criteria decision analysis (MCDA) problem comprised of many quantitative and qualitative criteria. Frequently, the assessment data of some criterion is inevitably imprecise and/or incomplete since the nature of environmental assessment relies heavily on professional and complex methods which might not be fully available for every company. Also, qualitative criteria can only be assessed based upon human judgment. This paper, therefore, proposes an application of the evidential reasoning (ER) approach to the assessment of environmental performance for logistics service providers. The lists of criteria and indicators are adapted from ISO 14031. The ER approach is able to logically aggregate all assessment information, although different forms of data (precise or imprecise; complete or incomplete) are obtained. For this paper, assessment data from two logistics companies were gathered and analysed to illustrate the implementation process. The results are in the form of aggregated belief distributions on a unified set of evaluation grades, and the company can use this information for performance improvement and benchmarking.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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