{"title":"建模物联网和大数据对业务绩效的影响","authors":"Jonny, Kriswanto, Matsumura Toshio","doi":"10.1109/IEEM50564.2021.9673066","DOIUrl":null,"url":null,"abstract":"With the existence of Internet of Things that have ability to connect various devices through censors, the growth of data volume is increasing rapidly known as Big Data. Through this Big Data, many companies gained its insights as basis for better decision making to gain competitive advantage. However, past literatures have shown that these empirical results are still fragmented. Therefore, this paper aims to propose a model on how IoT Big Data impacts business performance. For modeling purposes, some elements are included such as: 1) Business Process Improvement, 2) Marketing Strategies, 3) Business Management Innovation, 4) Business Models and Organizational Culture, 5) Privacy and Ethics, 6) Business Performance. Furthermore, sampling of managers in manufacturing industry are gained to answer several questions regarding the model development. For analysis purposes, Smart PLS 3.0 is run to evaluate the fitness of the model with requirement of Goodness of Fit (GoF) above 0.38. After careful conduct, the model is robust and accurate. From this model it can be said that 1) Business Models & Organizational Culture positively influence Business Process Improvement while Privacy and Ethics negatively influence it, 2) Business Process Improvement positively influences Marketing Strategies, Business Management Innovation and Business Performance, and 3) both Marketing Strategies and Business Management Innovation positively influence Business Performance.","PeriodicalId":6818,"journal":{"name":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"155 1","pages":"1127-1131"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modeling IoT and Big Data Impacts to Business Performance\",\"authors\":\"Jonny, Kriswanto, Matsumura Toshio\",\"doi\":\"10.1109/IEEM50564.2021.9673066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the existence of Internet of Things that have ability to connect various devices through censors, the growth of data volume is increasing rapidly known as Big Data. Through this Big Data, many companies gained its insights as basis for better decision making to gain competitive advantage. However, past literatures have shown that these empirical results are still fragmented. Therefore, this paper aims to propose a model on how IoT Big Data impacts business performance. For modeling purposes, some elements are included such as: 1) Business Process Improvement, 2) Marketing Strategies, 3) Business Management Innovation, 4) Business Models and Organizational Culture, 5) Privacy and Ethics, 6) Business Performance. Furthermore, sampling of managers in manufacturing industry are gained to answer several questions regarding the model development. For analysis purposes, Smart PLS 3.0 is run to evaluate the fitness of the model with requirement of Goodness of Fit (GoF) above 0.38. After careful conduct, the model is robust and accurate. From this model it can be said that 1) Business Models & Organizational Culture positively influence Business Process Improvement while Privacy and Ethics negatively influence it, 2) Business Process Improvement positively influences Marketing Strategies, Business Management Innovation and Business Performance, and 3) both Marketing Strategies and Business Management Innovation positively influence Business Performance.\",\"PeriodicalId\":6818,\"journal\":{\"name\":\"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"155 1\",\"pages\":\"1127-1131\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM50564.2021.9673066\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM50564.2021.9673066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling IoT and Big Data Impacts to Business Performance
With the existence of Internet of Things that have ability to connect various devices through censors, the growth of data volume is increasing rapidly known as Big Data. Through this Big Data, many companies gained its insights as basis for better decision making to gain competitive advantage. However, past literatures have shown that these empirical results are still fragmented. Therefore, this paper aims to propose a model on how IoT Big Data impacts business performance. For modeling purposes, some elements are included such as: 1) Business Process Improvement, 2) Marketing Strategies, 3) Business Management Innovation, 4) Business Models and Organizational Culture, 5) Privacy and Ethics, 6) Business Performance. Furthermore, sampling of managers in manufacturing industry are gained to answer several questions regarding the model development. For analysis purposes, Smart PLS 3.0 is run to evaluate the fitness of the model with requirement of Goodness of Fit (GoF) above 0.38. After careful conduct, the model is robust and accurate. From this model it can be said that 1) Business Models & Organizational Culture positively influence Business Process Improvement while Privacy and Ethics negatively influence it, 2) Business Process Improvement positively influences Marketing Strategies, Business Management Innovation and Business Performance, and 3) both Marketing Strategies and Business Management Innovation positively influence Business Performance.