{"title":"基于力分析的ing扩散加速度尺度模型","authors":"Li Wang, Chenxiao Wang, Qingpu Zhang","doi":"10.1080/0022250X.2019.1642337","DOIUrl":null,"url":null,"abstract":"ABSTRACT The diffusion of Internet-based Intangible Network Goods (IINGs) shows new characteristics completely different from that of traditional material products. This paper aims to establish new models to describe and predict IING’s diffusion at the aggregate level. Firstly, we transform the key factors affecting IING’s diffusion into driving forces, resistant forces, and variable forces. Secondly, we analyse the dynamic changes of these forces in different diffusion stages and obtain the acceleration model of IING’s diffusion. Then, since acceleration is the second derivative of scale, we further establish the scale model of IING’s diffusion. As the scale model can predict the number of IING’s adopters at a particular time and the acceleration model can explain the dynamic changes of scale, we combine them as the acceleration-scale model to describe IING’s diffusion. Finally, we make comparisons between the acceleration-scale model and the Bass model based on three cases. Different from the previous studies, we found that IING’s diffusion rate is asymmetric. The diffusion rate of successful IING is right skewed while the diffusion rate of failed IING is left skewed. The results also shows that the acceleration-scale model has a better predictive performance than the Bass model, no matter the diffusion is successful or failed","PeriodicalId":50139,"journal":{"name":"Journal of Mathematical Sociology","volume":"44 1","pages":"127 - 99"},"PeriodicalIF":1.3000,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/0022250X.2019.1642337","citationCount":"0","resultStr":"{\"title\":\"An acceleration-scale model of IING’s diffusion based on force analysis\",\"authors\":\"Li Wang, Chenxiao Wang, Qingpu Zhang\",\"doi\":\"10.1080/0022250X.2019.1642337\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT The diffusion of Internet-based Intangible Network Goods (IINGs) shows new characteristics completely different from that of traditional material products. This paper aims to establish new models to describe and predict IING’s diffusion at the aggregate level. Firstly, we transform the key factors affecting IING’s diffusion into driving forces, resistant forces, and variable forces. Secondly, we analyse the dynamic changes of these forces in different diffusion stages and obtain the acceleration model of IING’s diffusion. Then, since acceleration is the second derivative of scale, we further establish the scale model of IING’s diffusion. As the scale model can predict the number of IING’s adopters at a particular time and the acceleration model can explain the dynamic changes of scale, we combine them as the acceleration-scale model to describe IING’s diffusion. Finally, we make comparisons between the acceleration-scale model and the Bass model based on three cases. Different from the previous studies, we found that IING’s diffusion rate is asymmetric. The diffusion rate of successful IING is right skewed while the diffusion rate of failed IING is left skewed. The results also shows that the acceleration-scale model has a better predictive performance than the Bass model, no matter the diffusion is successful or failed\",\"PeriodicalId\":50139,\"journal\":{\"name\":\"Journal of Mathematical Sociology\",\"volume\":\"44 1\",\"pages\":\"127 - 99\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2020-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/0022250X.2019.1642337\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mathematical Sociology\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1080/0022250X.2019.1642337\",\"RegionNum\":4,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical Sociology","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1080/0022250X.2019.1642337","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
An acceleration-scale model of IING’s diffusion based on force analysis
ABSTRACT The diffusion of Internet-based Intangible Network Goods (IINGs) shows new characteristics completely different from that of traditional material products. This paper aims to establish new models to describe and predict IING’s diffusion at the aggregate level. Firstly, we transform the key factors affecting IING’s diffusion into driving forces, resistant forces, and variable forces. Secondly, we analyse the dynamic changes of these forces in different diffusion stages and obtain the acceleration model of IING’s diffusion. Then, since acceleration is the second derivative of scale, we further establish the scale model of IING’s diffusion. As the scale model can predict the number of IING’s adopters at a particular time and the acceleration model can explain the dynamic changes of scale, we combine them as the acceleration-scale model to describe IING’s diffusion. Finally, we make comparisons between the acceleration-scale model and the Bass model based on three cases. Different from the previous studies, we found that IING’s diffusion rate is asymmetric. The diffusion rate of successful IING is right skewed while the diffusion rate of failed IING is left skewed. The results also shows that the acceleration-scale model has a better predictive performance than the Bass model, no matter the diffusion is successful or failed
期刊介绍:
The goal of the Journal of Mathematical Sociology is to publish models and mathematical techniques that would likely be useful to professional sociologists. The Journal also welcomes papers of mutual interest to social scientists and other social and behavioral scientists, as well as papers by non-social scientists that may encourage fruitful connections between sociology and other disciplines. Reviews of new or developing areas of mathematics and mathematical modeling that may have significant applications in sociology will also be considered.
The Journal of Mathematical Sociology is published in association with the International Network for Social Network Analysis, the Japanese Association for Mathematical Sociology, the Mathematical Sociology Section of the American Sociological Association, and the Methodology Section of the American Sociological Association.