Supporting decision-making in service supplier selection using a hybrid fuzzy extended AHP approach

Purpose: Service supplier selection is a multi-criteria decision-making (MCDM) problem assuming a strategic role for the competitiveness of high-tech manufacturing companies. Nevertheless, especially for service quality evaluation, there is little empirical evidence of the practical usefulness of MCDM methodologies. Aiming to cover this gap between theoretical approaches and empirical applications, the purpose of this paper is to propose a fuzzy extended analytic hierarchy process (FEAHP) approach for service supplier evaluation. Design/methodology/approach: A hybrid approach which combines some of the strengths of the analytic hierarchy process (AHP) and of the fuzzy set theory is presented, as organized into five steps. A case study is used to evaluate the applicability in a real company context. Findings: The usability of the approach is demonstrated in an aerospace company for solving the supplier selection problem of a business software whose applications are still in infancy: a Test Data Management System (TDMS). The illustrative application contains both “general” criteria to be used for other service supplier selection contexts as well as service-specific criteria related to software selection. Research limitations/implications: Even if the application regards the selection of a software supplier, the methodology can be generically extended to other services’ selection in complex manufacturing industries through the personalization of some criteria. Practical implications: Implications can be derived both for business managers involved into the decision-making process and for suppliers identifying the most promising features of software quality. Originality/value: The originality consists in the combination into a hybrid approach of the strong points of the AHP with the fuzzy set; the inclusion of multiple perspectives of decision criteria for service supplier selection, basically the “software product” and “supplier” ones; a real empirical application to test and demonstrate the efficacy and the practical utility of the proposed approac

Generating texts in different styles

Natural Language Generation (nlg) systems generate texts in English and other human languages from non-linguistic input data. Usually there are a large number of possible texts that can communicate the input data, and nlg systems must choose one of these. This decision can partially be based on style (interpreted broadly). We explore three mechanisms for incorporating style into nlg choice-making: (1) explicit stylistic parameters, (2) imitating a genre style, and (3) imitating an individual's style