{"title":"链成员对链绩效的感知:关系质量的作用","authors":"A. Molnar, X. Gellynck, R. Weaver","doi":"10.3920/JCNS2010.X103","DOIUrl":null,"url":null,"abstract":"The purpose of the paper is to measure perceived performance of bilateral relationships in the chain. Therefore, quantitative data were collected from 270 chain members from 3 EU countries in 6 traditional food product categories. First, perceived performance of bilateral relationships was analysed which revealed a generally high perceived contribution of each chain member to its partners' performance. Second, cluster analysis was conducted resulting in 4 clusters: 1) Low performing chains; 2) Low perceived food manufacturer's (FM) performance by supplier (S) and customer (C); 3) High perceived FM performance by S and C; 4) High performing chains. Third, binary logistic regression was used to identify 7 relationship constructs that significantly predict cluster membership: trust, economic satisfaction, social satisfaction, dependency, coercive power, reputation, conflict and integration.","PeriodicalId":17677,"journal":{"name":"Journal on Chain and Network Science","volume":"72 1","pages":"27-49"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Chain member perception of chain performance: the role of relationship quality\",\"authors\":\"A. Molnar, X. Gellynck, R. Weaver\",\"doi\":\"10.3920/JCNS2010.X103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The purpose of the paper is to measure perceived performance of bilateral relationships in the chain. Therefore, quantitative data were collected from 270 chain members from 3 EU countries in 6 traditional food product categories. First, perceived performance of bilateral relationships was analysed which revealed a generally high perceived contribution of each chain member to its partners' performance. Second, cluster analysis was conducted resulting in 4 clusters: 1) Low performing chains; 2) Low perceived food manufacturer's (FM) performance by supplier (S) and customer (C); 3) High perceived FM performance by S and C; 4) High performing chains. Third, binary logistic regression was used to identify 7 relationship constructs that significantly predict cluster membership: trust, economic satisfaction, social satisfaction, dependency, coercive power, reputation, conflict and integration.\",\"PeriodicalId\":17677,\"journal\":{\"name\":\"Journal on Chain and Network Science\",\"volume\":\"72 1\",\"pages\":\"27-49\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal on Chain and Network Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3920/JCNS2010.X103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal on Chain and Network Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3920/JCNS2010.X103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Chain member perception of chain performance: the role of relationship quality
The purpose of the paper is to measure perceived performance of bilateral relationships in the chain. Therefore, quantitative data were collected from 270 chain members from 3 EU countries in 6 traditional food product categories. First, perceived performance of bilateral relationships was analysed which revealed a generally high perceived contribution of each chain member to its partners' performance. Second, cluster analysis was conducted resulting in 4 clusters: 1) Low performing chains; 2) Low perceived food manufacturer's (FM) performance by supplier (S) and customer (C); 3) High perceived FM performance by S and C; 4) High performing chains. Third, binary logistic regression was used to identify 7 relationship constructs that significantly predict cluster membership: trust, economic satisfaction, social satisfaction, dependency, coercive power, reputation, conflict and integration.