Measuring interdependencies of preferred supplier enablers
Purpose The purpose of this paper is to analyze preferred supplier enablers (PSEs) and measure the interdependencies among themselves for enhancing preferred supplier relationship. Design/methodology/approach In the current study, an approach has been developed in which the significance of various P...
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Veröffentlicht in: | Benchmarking : an international journal 2018-10, Vol.25 (7), p.2344-2369 |
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description | Purpose
The purpose of this paper is to analyze preferred supplier enablers (PSEs) and measure the interdependencies among themselves for enhancing preferred supplier relationship.
Design/methodology/approach
In the current study, an approach has been developed in which the significance of various PSEs was determined by applying Fuzzy Analytic Hierarchy Process (FAHP) and the prominent PSEs were screened out through Pareto analysis. Also, the interdependence among the prominent PSEs was measured by applying the Fuzzy Decision Making Trial and Evaluation Laboratory method in order to select the right PSEs in ascribing the Preferred Supplier Status. Finally, the weakest relationships among the PSEs were confirmed by applying the student’s t-test and then an impact relationship map of PSEs was developed.
Findings
The strength of relationships among the PSEs, grouping of PSEs into causes and effects on a causal diagram and a concise impact relationship map of PSEs were determined. Further, the PSEs that a manufacturer must primarily focus and monitor were also obtained.
Research limitations/implications
The study was conducted in an Indian electronic manufacturing environment. Therefore, the results obtained would be more relevant to the high end technology product manufacturers operating in the developing countries.
Practical implications
From the current study, a manufacturer can alleviate, favorably associate and integrate with the good suppliers and then eventually establish a strong supply base.
Originality/value
Manufacturers are looking for the closer and favored relationships by bringing in the concept of preferred supplier while dealing with their key suppliers. Thus, the results obtained from the current study would be of great assistance to a manufacturer in gaining an extra cutting-edge and, in turn, tackling the increased competitive pressures and reduced availability of resources. |
doi_str_mv | 10.1108/BIJ-02-2017-0023 |
format | Article |
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The purpose of this paper is to analyze preferred supplier enablers (PSEs) and measure the interdependencies among themselves for enhancing preferred supplier relationship.
Design/methodology/approach
In the current study, an approach has been developed in which the significance of various PSEs was determined by applying Fuzzy Analytic Hierarchy Process (FAHP) and the prominent PSEs were screened out through Pareto analysis. Also, the interdependence among the prominent PSEs was measured by applying the Fuzzy Decision Making Trial and Evaluation Laboratory method in order to select the right PSEs in ascribing the Preferred Supplier Status. Finally, the weakest relationships among the PSEs were confirmed by applying the student’s t-test and then an impact relationship map of PSEs was developed.
Findings
The strength of relationships among the PSEs, grouping of PSEs into causes and effects on a causal diagram and a concise impact relationship map of PSEs were determined. Further, the PSEs that a manufacturer must primarily focus and monitor were also obtained.
Research limitations/implications
The study was conducted in an Indian electronic manufacturing environment. Therefore, the results obtained would be more relevant to the high end technology product manufacturers operating in the developing countries.
Practical implications
From the current study, a manufacturer can alleviate, favorably associate and integrate with the good suppliers and then eventually establish a strong supply base.
Originality/value
Manufacturers are looking for the closer and favored relationships by bringing in the concept of preferred supplier while dealing with their key suppliers. Thus, the results obtained from the current study would be of great assistance to a manufacturer in gaining an extra cutting-edge and, in turn, tackling the increased competitive pressures and reduced availability of resources.</description><identifier>ISSN: 1463-5771</identifier><identifier>EISSN: 1758-4094</identifier><identifier>DOI: 10.1108/BIJ-02-2017-0023</identifier><language>eng</language><publisher>Bradford: Emerald Publishing Limited</publisher><subject>Analytic hierarchy process ; Competition ; Cost control ; Decision making ; Developing countries ; Electronics industry ; LDCs ; Manufacturers ; Manufacturing ; Pareto analysis ; Printing industry ; Reputations ; Studies ; Suppliers ; Supplies ; Supply chain management ; Supply chains</subject><ispartof>Benchmarking : an international journal, 2018-10, Vol.25 (7), p.2344-2369</ispartof><rights>Emerald Publishing Limited</rights><rights>Emerald Publishing Limited 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c311t-1e3bdfeeffb912094ee1eff7c813101aeae33598cb3b6536cae7eb0150dbfb1c3</citedby><cites>FETCH-LOGICAL-c311t-1e3bdfeeffb912094ee1eff7c813101aeae33598cb3b6536cae7eb0150dbfb1c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/BIJ-02-2017-0023/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,777,781,962,11616,21676,27905,27906,52670,53225</link.rule.ids></links><search><creatorcontrib>C.V, Sunil Kumar</creatorcontrib><creatorcontrib>Routroy, Srikanta</creatorcontrib><title>Measuring interdependencies of preferred supplier enablers</title><title>Benchmarking : an international journal</title><description>Purpose
The purpose of this paper is to analyze preferred supplier enablers (PSEs) and measure the interdependencies among themselves for enhancing preferred supplier relationship.
Design/methodology/approach
In the current study, an approach has been developed in which the significance of various PSEs was determined by applying Fuzzy Analytic Hierarchy Process (FAHP) and the prominent PSEs were screened out through Pareto analysis. Also, the interdependence among the prominent PSEs was measured by applying the Fuzzy Decision Making Trial and Evaluation Laboratory method in order to select the right PSEs in ascribing the Preferred Supplier Status. Finally, the weakest relationships among the PSEs were confirmed by applying the student’s t-test and then an impact relationship map of PSEs was developed.
Findings
The strength of relationships among the PSEs, grouping of PSEs into causes and effects on a causal diagram and a concise impact relationship map of PSEs were determined. Further, the PSEs that a manufacturer must primarily focus and monitor were also obtained.
Research limitations/implications
The study was conducted in an Indian electronic manufacturing environment. Therefore, the results obtained would be more relevant to the high end technology product manufacturers operating in the developing countries.
Practical implications
From the current study, a manufacturer can alleviate, favorably associate and integrate with the good suppliers and then eventually establish a strong supply base.
Originality/value
Manufacturers are looking for the closer and favored relationships by bringing in the concept of preferred supplier while dealing with their key suppliers. Thus, the results obtained from the current study would be of great assistance to a manufacturer in gaining an extra cutting-edge and, in turn, tackling the increased competitive pressures and reduced availability of resources.</description><subject>Analytic hierarchy process</subject><subject>Competition</subject><subject>Cost control</subject><subject>Decision making</subject><subject>Developing countries</subject><subject>Electronics industry</subject><subject>LDCs</subject><subject>Manufacturers</subject><subject>Manufacturing</subject><subject>Pareto analysis</subject><subject>Printing industry</subject><subject>Reputations</subject><subject>Studies</subject><subject>Suppliers</subject><subject>Supplies</subject><subject>Supply chain management</subject><subject>Supply chains</subject><issn>1463-5771</issn><issn>1758-4094</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNptkM1PwzAMxSMEEuPjzrES5zA7aZuMG0x8DA1xgXOUpA7q1LUlWQ_892QaFyROtqX37OcfY1cIN4ig5_erFw6CC0DFAYQ8YjNUleYlLMrj3Je15JVSeMrOUtoAQI1azNjtK9k0xbb_LNp-R7GhkfqGet9SKoZQjJECxUhNkaZx7FqKBfXWdRTTBTsJtkt0-VvP2cfjw_vyma_fnlbLuzX3EnHHkaRrAlEIboEipyHCPCivUSKgJUtSVgvtnXR1JWtvSZEDrKBxwaGX5-z6sHeMw9dEaWc2wxT7fNKI_LkutVZVVsFB5eOQUk5txthubfw2CGZPyGRCBoTZEzJ7QtkyP1hoS9F2zX-OP0zlD3ZoZ_M</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>C.V, Sunil Kumar</creator><creator>Routroy, Srikanta</creator><general>Emerald Publishing Limited</general><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>7TA</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X5</scope><scope>7XB</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>F~G</scope><scope>JG9</scope><scope>K6~</scope><scope>K8~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>M0T</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20181001</creationdate><title>Measuring interdependencies of preferred supplier enablers</title><author>C.V, Sunil Kumar ; Routroy, Srikanta</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c311t-1e3bdfeeffb912094ee1eff7c813101aeae33598cb3b6536cae7eb0150dbfb1c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Analytic hierarchy process</topic><topic>Competition</topic><topic>Cost control</topic><topic>Decision making</topic><topic>Developing countries</topic><topic>Electronics industry</topic><topic>LDCs</topic><topic>Manufacturers</topic><topic>Manufacturing</topic><topic>Pareto analysis</topic><topic>Printing industry</topic><topic>Reputations</topic><topic>Studies</topic><topic>Suppliers</topic><topic>Supplies</topic><topic>Supply chain management</topic><topic>Supply chains</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>C.V, Sunil Kumar</creatorcontrib><creatorcontrib>Routroy, Srikanta</creatorcontrib><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>Materials Business File</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Entrepreneurship Database</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Materials Research Database</collection><collection>ProQuest Business Collection</collection><collection>DELNET Management Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>Healthcare Administration Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>Benchmarking : an international journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>C.V, Sunil Kumar</au><au>Routroy, Srikanta</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring interdependencies of preferred supplier enablers</atitle><jtitle>Benchmarking : an international journal</jtitle><date>2018-10-01</date><risdate>2018</risdate><volume>25</volume><issue>7</issue><spage>2344</spage><epage>2369</epage><pages>2344-2369</pages><issn>1463-5771</issn><eissn>1758-4094</eissn><abstract>Purpose
The purpose of this paper is to analyze preferred supplier enablers (PSEs) and measure the interdependencies among themselves for enhancing preferred supplier relationship.
Design/methodology/approach
In the current study, an approach has been developed in which the significance of various PSEs was determined by applying Fuzzy Analytic Hierarchy Process (FAHP) and the prominent PSEs were screened out through Pareto analysis. Also, the interdependence among the prominent PSEs was measured by applying the Fuzzy Decision Making Trial and Evaluation Laboratory method in order to select the right PSEs in ascribing the Preferred Supplier Status. Finally, the weakest relationships among the PSEs were confirmed by applying the student’s t-test and then an impact relationship map of PSEs was developed.
Findings
The strength of relationships among the PSEs, grouping of PSEs into causes and effects on a causal diagram and a concise impact relationship map of PSEs were determined. Further, the PSEs that a manufacturer must primarily focus and monitor were also obtained.
Research limitations/implications
The study was conducted in an Indian electronic manufacturing environment. Therefore, the results obtained would be more relevant to the high end technology product manufacturers operating in the developing countries.
Practical implications
From the current study, a manufacturer can alleviate, favorably associate and integrate with the good suppliers and then eventually establish a strong supply base.
Originality/value
Manufacturers are looking for the closer and favored relationships by bringing in the concept of preferred supplier while dealing with their key suppliers. Thus, the results obtained from the current study would be of great assistance to a manufacturer in gaining an extra cutting-edge and, in turn, tackling the increased competitive pressures and reduced availability of resources.</abstract><cop>Bradford</cop><pub>Emerald Publishing Limited</pub><doi>10.1108/BIJ-02-2017-0023</doi><tpages>26</tpages></addata></record> |
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subjects | Analytic hierarchy process Competition Cost control Decision making Developing countries Electronics industry LDCs Manufacturers Manufacturing Pareto analysis Printing industry Reputations Studies Suppliers Supplies Supply chain management Supply chains |
title | Measuring interdependencies of preferred supplier enablers |
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