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Purchasing performance of engineering procurement and construction companies using a fuzzy quality function deployment approach

Purchasing performance of engineering procurement and construction companies using a fuzzy... This paper aims to empirically validate an integrated model, combining fuzzy analytical hierarchy processing and quality function deployment, used to construct a purchasing performance (PP) matrix for engineering procurement and construction companies (EPCs). The relationship is established by linking internal customer needs (“whats”; product-related factors), with engineering requirements (“hows”; buyer-related factors [BRFs] and organization-related factors). Three different of buying types are included: new task, straight rebuy and modified rebuy.Design/methodology/approachThe paper uses qualitative and quantitative techniques to determine the factors affecting PP and the extent of their influence. Evaluation of the factors affecting the PP of EPC companies is based on 32 industry experts’ opinions, supported by the academic literature.FindingsThe most significant finding is that researchers should explicitly consider BRFs like buyer knowledge, which has been missing in earlier PP models. BRFs appear to be a link between different types of buying; ignoring their importance can lead to less optimized PP and erroneous findings.Originality/valueThis research is unique, as PP models of EPC firms have neither been published nor validated empirically, either nationally or internationally. This exploratory study adds to the body of knowledge both by identifying the emerging factors that constitute the construct of the PP of EPCs and by filling the gap between theory and practice concerning an evaluation of the PP of EPCs. Theoretical and practical implications are discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Business & Industrial Marketing Emerald Publishing

Purchasing performance of engineering procurement and construction companies using a fuzzy quality function deployment approach

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0885-8624
DOI
10.1108/jbim-04-2019-0166
Publisher site
See Article on Publisher Site

Abstract

This paper aims to empirically validate an integrated model, combining fuzzy analytical hierarchy processing and quality function deployment, used to construct a purchasing performance (PP) matrix for engineering procurement and construction companies (EPCs). The relationship is established by linking internal customer needs (“whats”; product-related factors), with engineering requirements (“hows”; buyer-related factors [BRFs] and organization-related factors). Three different of buying types are included: new task, straight rebuy and modified rebuy.Design/methodology/approachThe paper uses qualitative and quantitative techniques to determine the factors affecting PP and the extent of their influence. Evaluation of the factors affecting the PP of EPC companies is based on 32 industry experts’ opinions, supported by the academic literature.FindingsThe most significant finding is that researchers should explicitly consider BRFs like buyer knowledge, which has been missing in earlier PP models. BRFs appear to be a link between different types of buying; ignoring their importance can lead to less optimized PP and erroneous findings.Originality/valueThis research is unique, as PP models of EPC firms have neither been published nor validated empirically, either nationally or internationally. This exploratory study adds to the body of knowledge both by identifying the emerging factors that constitute the construct of the PP of EPCs and by filling the gap between theory and practice concerning an evaluation of the PP of EPCs. Theoretical and practical implications are discussed.

Journal

Journal of Business & Industrial MarketingEmerald Publishing

Published: May 25, 2021

Keywords: Exploratory research; House of quality (HoQ); Quality function deployment (QFD); Engineering procurement and construction companies; Fuzzy analytical hierarchy processing (FAHP); Purchasing performance

References