Environmental performance assessment using the evidential reasoning approach: The case of logistics service providers

Abstract

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.

Presenting an environmental performance evaluation model for gas refineries: A case study in the South Pars Gas Complex, Iran

“…Stage 1: Identifying the criteria and indicators of environmental performance in gas refineries using the fuzzy Delphi method (21,(27)(28)(29).…”

Evaluating Innovation Capability in Banking Under Uncertainty

“…For dealing with this problem, the ER approach for multiattribute decision analysis, proposed by Yang and Singh [28], can provide a method for multiattribute aggregation under various uncertainties. Although the ER approach has been widely applied in evaluations of services [29]- [33], this study can be regarded as the first attempt to apply the ER approach in combination with the AHP for IC evaluation. Finally, the utility function introduced by Yang and Xu [34], Huynh et al [35], and Huynh et al [30] is used as a tool for ranking the banks based on the aggregated IC assessments.…”