An approach for measuring a manufacturer’s preferred supplier status

An approach for measuring a manufacturer’s preferred supplier status PurposeThe purpose of this paper is to assist a manufacturer with a process to measure the level of preferred supplier status (PSS) of its key suppliers along the timeline.Design/methodology/approachIn measuring the PSS, the prominent preferred supplier enablers (PSEs) were identified and were broadly categorized under manufacturer’s interest component, common interest component and supplier’s characteristic component. These PSEs were further analyzed by using fuzzy analytic hierarchy process, Euclidean distance measurement and grey relation analysis methods. In order to demonstrate the application and utility of the proposed approach, a case study conducted in an Indian automotive component manufacturing company has been presented.FindingsBy applying the proposed methodology in a case company, the PSSs of five of its key suppliers were measured and then the suppliers’ characteristic scores were determined. Based on these scores, a preferential status plot of the suppliers was developed. Through the status plot, the manufacturer was suggested with whom the proposed initiatives can be productive and with whom the manufacturer has to appeal for improvement strategies.Research limitations/implicationsSince the methodology was tried in the Indian manufacturing environment, the emphasis laid on the PSEs and in turn the measurement of PSS may not address the concern at large.Practical implicationsMeasuring PSS would not only earn competitive advantages for the manufacturers but also facilitate the evolution of competitive suppliers.Originality/valueMeasuring PSS along the time would assist a manufacturer to effectively manage the preferences given to its suppliers and thereby enhance the supply base contribution in the value addition process. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asia Pacific Journal of Marketing and Logistics Emerald Publishing

An approach for measuring a manufacturer’s preferred supplier status

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1355-5855
DOI
10.1108/APJML-12-2015-0194
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to assist a manufacturer with a process to measure the level of preferred supplier status (PSS) of its key suppliers along the timeline.Design/methodology/approachIn measuring the PSS, the prominent preferred supplier enablers (PSEs) were identified and were broadly categorized under manufacturer’s interest component, common interest component and supplier’s characteristic component. These PSEs were further analyzed by using fuzzy analytic hierarchy process, Euclidean distance measurement and grey relation analysis methods. In order to demonstrate the application and utility of the proposed approach, a case study conducted in an Indian automotive component manufacturing company has been presented.FindingsBy applying the proposed methodology in a case company, the PSSs of five of its key suppliers were measured and then the suppliers’ characteristic scores were determined. Based on these scores, a preferential status plot of the suppliers was developed. Through the status plot, the manufacturer was suggested with whom the proposed initiatives can be productive and with whom the manufacturer has to appeal for improvement strategies.Research limitations/implicationsSince the methodology was tried in the Indian manufacturing environment, the emphasis laid on the PSEs and in turn the measurement of PSS may not address the concern at large.Practical implicationsMeasuring PSS would not only earn competitive advantages for the manufacturers but also facilitate the evolution of competitive suppliers.Originality/valueMeasuring PSS along the time would assist a manufacturer to effectively manage the preferences given to its suppliers and thereby enhance the supply base contribution in the value addition process.

Journal

Asia Pacific Journal of Marketing and LogisticsEmerald Publishing

Published: Nov 14, 2016

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