{"title":"通过多渠道数字服务为客户参与信息设计的大数据属性","authors":"Panant Krairojananan, Sakuna Anuvareepong","doi":"10.1109/ICSITECH.2016.7852635","DOIUrl":null,"url":null,"abstract":"The growth of Big Data plays an important role to transform data generated by online consumers in valuable assets. This paper aims to explore the design of big data properties, which are composed of volume, velocity, variety, and veracity, for managing customer engagement information; including intrinsic, extrinsic, and economic drive. Accordingly, the customer engagement information is derived from customer activities via multi-channel digital services comprised social media, blogs, and Webboards. The implications of this study lead to be used as the useful information for the big data infrastructure enablers. The results from the study reveal that most of single female in higher education whose average income at 10,000 – 30,000 Thai Baht were respondents who used Facebook and LINE app everyday at night time. Besides, the result also shows the significance of big data properties to support customer engagement.","PeriodicalId":447090,"journal":{"name":"2016 2nd International Conference on Science in Information Technology (ICSITech)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Big data properties designed for customer engagement information via multi-channel digital services\",\"authors\":\"Panant Krairojananan, Sakuna Anuvareepong\",\"doi\":\"10.1109/ICSITECH.2016.7852635\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The growth of Big Data plays an important role to transform data generated by online consumers in valuable assets. This paper aims to explore the design of big data properties, which are composed of volume, velocity, variety, and veracity, for managing customer engagement information; including intrinsic, extrinsic, and economic drive. Accordingly, the customer engagement information is derived from customer activities via multi-channel digital services comprised social media, blogs, and Webboards. The implications of this study lead to be used as the useful information for the big data infrastructure enablers. The results from the study reveal that most of single female in higher education whose average income at 10,000 – 30,000 Thai Baht were respondents who used Facebook and LINE app everyday at night time. Besides, the result also shows the significance of big data properties to support customer engagement.\",\"PeriodicalId\":447090,\"journal\":{\"name\":\"2016 2nd International Conference on Science in Information Technology (ICSITech)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd International Conference on Science in Information Technology (ICSITech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSITECH.2016.7852635\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd International Conference on Science in Information Technology (ICSITech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSITECH.2016.7852635","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big data properties designed for customer engagement information via multi-channel digital services
The growth of Big Data plays an important role to transform data generated by online consumers in valuable assets. This paper aims to explore the design of big data properties, which are composed of volume, velocity, variety, and veracity, for managing customer engagement information; including intrinsic, extrinsic, and economic drive. Accordingly, the customer engagement information is derived from customer activities via multi-channel digital services comprised social media, blogs, and Webboards. The implications of this study lead to be used as the useful information for the big data infrastructure enablers. The results from the study reveal that most of single female in higher education whose average income at 10,000 – 30,000 Thai Baht were respondents who used Facebook and LINE app everyday at night time. Besides, the result also shows the significance of big data properties to support customer engagement.