{"title":"有效供应链关系行为属性的情感分析:一种模糊目标设定方法","authors":"M. F. Shipley, R. Cao, R. McKee","doi":"10.1504/ijbpscm.2020.10031445","DOIUrl":null,"url":null,"abstract":"Sentiments expressed through social media can reflect behavioural attributes of trust, commitment, collaboration, and information sharing between or among actors in supply chain management (SCM) relationships. These four attributes are generally considered to enhance SCM performance if each is at a high level. In this study, sentiment mining was undertaken using three different web crawler algorithms focusing on blog, forum, and Twitter sources. After classifying the mined sentiment data, scores were evaluated using a fuzzy model to address uncertainty and ambiguity. The least degree of fit of each attribute and combination of attributes was determined by industry for pharmaceuticals, software, retailing, and healthcare. Results indicate that the importance attributed to levels of interactions for the behavioural attributes necessitated in SCM relationships differs for the industries studied. However, overall, the most consequential attribute seems to be trust between the individuals involved. This work contributes to SCM research through the utilisation of techniques to focus on human attributes for decision making that may improve SCM performance; specifically for the industries studied.","PeriodicalId":37630,"journal":{"name":"International Journal of Business Performance and Supply Chain Modelling","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sentiment analysis of behavioural attributes for effective supply chain relationships: a fuzzy goal-setting approach\",\"authors\":\"M. F. Shipley, R. Cao, R. McKee\",\"doi\":\"10.1504/ijbpscm.2020.10031445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sentiments expressed through social media can reflect behavioural attributes of trust, commitment, collaboration, and information sharing between or among actors in supply chain management (SCM) relationships. These four attributes are generally considered to enhance SCM performance if each is at a high level. In this study, sentiment mining was undertaken using three different web crawler algorithms focusing on blog, forum, and Twitter sources. After classifying the mined sentiment data, scores were evaluated using a fuzzy model to address uncertainty and ambiguity. The least degree of fit of each attribute and combination of attributes was determined by industry for pharmaceuticals, software, retailing, and healthcare. Results indicate that the importance attributed to levels of interactions for the behavioural attributes necessitated in SCM relationships differs for the industries studied. However, overall, the most consequential attribute seems to be trust between the individuals involved. This work contributes to SCM research through the utilisation of techniques to focus on human attributes for decision making that may improve SCM performance; specifically for the industries studied.\",\"PeriodicalId\":37630,\"journal\":{\"name\":\"International Journal of Business Performance and Supply Chain Modelling\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Business Performance and Supply Chain Modelling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijbpscm.2020.10031445\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Business, Management and Accounting\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Business Performance and Supply Chain Modelling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijbpscm.2020.10031445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Business, Management and Accounting","Score":null,"Total":0}
Sentiment analysis of behavioural attributes for effective supply chain relationships: a fuzzy goal-setting approach
Sentiments expressed through social media can reflect behavioural attributes of trust, commitment, collaboration, and information sharing between or among actors in supply chain management (SCM) relationships. These four attributes are generally considered to enhance SCM performance if each is at a high level. In this study, sentiment mining was undertaken using three different web crawler algorithms focusing on blog, forum, and Twitter sources. After classifying the mined sentiment data, scores were evaluated using a fuzzy model to address uncertainty and ambiguity. The least degree of fit of each attribute and combination of attributes was determined by industry for pharmaceuticals, software, retailing, and healthcare. Results indicate that the importance attributed to levels of interactions for the behavioural attributes necessitated in SCM relationships differs for the industries studied. However, overall, the most consequential attribute seems to be trust between the individuals involved. This work contributes to SCM research through the utilisation of techniques to focus on human attributes for decision making that may improve SCM performance; specifically for the industries studied.
期刊介绍:
IJBPSCM covers original, high-quality and cutting-edge research on all aspects of supply chain modelling, aiming at bridging the gap between theory and practice with applications analysing the real situation to improve business performance. Topics covered include Business performance modelling, strategy Vendor/supplier selection, supplier development, purchasing management Supply chain management (SCM), green supply chain modelling Reverse logistics, closed loop/knowledge-based supply chains, 3PL/4PL Sustainable/quality based/agile/leagile/intelligent SCM Supply chain performance/optimisation/risk/decision making/support systems AI, information sharing in SCM, systems approach to SCM Coordinated/global/flexible SCM, risk mitigation strategies Stochastic supply chain games IT-enabled SCM, fuzzy modelling, data mining Supply chain network management, modelling/simulation, implementation Training/education, information security, RFID Supply chain analysis, transportation decisions, vehicle routing, bullwhip effect Logistics in disaster management Cross-country comparison.