{"title":"数字经济与教育市场的时频依赖关系及动态联系","authors":"Wang Gao","doi":"10.1016/j.techsoc.2025.102907","DOIUrl":null,"url":null,"abstract":"<div><div>This study utilizes a comprehensive analytical framework, incorporating both time and frequency domain methodologies, to investigate the complex interdependencies between the digital economy and the education market. The evaluation encompasses several critical dimensions, including return, volatility, and liquidity interconnectedness. The principal findings of this research are as follows: (1) There is a substantial co-dependence observed between the digital economy and the education sector, with a particular focus on components such as mobile internet, artificial intelligence, and big data—elements that exhibit the most pronounced linkages to educational infrastructures. Frequency domain analysis indicates that return spillover effects are potent in the short term, whereas spillovers related to volatility become increasingly significant in the long term. (2) The analysis reveals cloud computing and big data as the principal sources of spillover effects, while artificial intelligence, mobile internet, virtual reality, and online education serve as critical intermediaries. Importantly, vocational and K-12 education emerge as the primary beneficiaries of these spillover phenomena. (3) The interrelationships between the digital economy and educational markets exhibit time-varying characteristics, particularly marked by heightened fluctuations during pivotal events such as the COVID-19 pandemic and the implementation of the \"Double Reduction\" policy. Additionally, a notable strengthening of these trends has been observed after 2022. (4) The study demonstrates that assets associated with cloud computing, 5G technology, big data, artificial intelligence, and online education possess robust hedging effectiveness. The findings of this research aspire to inform educational policymakers regarding optimal resource allocation strategies, facilitate the seamless integration of digital technologies within educational frameworks, and provide strategic insights for asset investors seeking to navigate cross-market investments while enhancing risk management practices.</div></div>","PeriodicalId":47979,"journal":{"name":"Technology in Society","volume":"82 ","pages":"Article 102907"},"PeriodicalIF":10.1000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Time-frequency dependence and dynamic linkages between digital economy and education markets\",\"authors\":\"Wang Gao\",\"doi\":\"10.1016/j.techsoc.2025.102907\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study utilizes a comprehensive analytical framework, incorporating both time and frequency domain methodologies, to investigate the complex interdependencies between the digital economy and the education market. The evaluation encompasses several critical dimensions, including return, volatility, and liquidity interconnectedness. The principal findings of this research are as follows: (1) There is a substantial co-dependence observed between the digital economy and the education sector, with a particular focus on components such as mobile internet, artificial intelligence, and big data—elements that exhibit the most pronounced linkages to educational infrastructures. Frequency domain analysis indicates that return spillover effects are potent in the short term, whereas spillovers related to volatility become increasingly significant in the long term. (2) The analysis reveals cloud computing and big data as the principal sources of spillover effects, while artificial intelligence, mobile internet, virtual reality, and online education serve as critical intermediaries. Importantly, vocational and K-12 education emerge as the primary beneficiaries of these spillover phenomena. (3) The interrelationships between the digital economy and educational markets exhibit time-varying characteristics, particularly marked by heightened fluctuations during pivotal events such as the COVID-19 pandemic and the implementation of the \\\"Double Reduction\\\" policy. Additionally, a notable strengthening of these trends has been observed after 2022. (4) The study demonstrates that assets associated with cloud computing, 5G technology, big data, artificial intelligence, and online education possess robust hedging effectiveness. The findings of this research aspire to inform educational policymakers regarding optimal resource allocation strategies, facilitate the seamless integration of digital technologies within educational frameworks, and provide strategic insights for asset investors seeking to navigate cross-market investments while enhancing risk management practices.</div></div>\",\"PeriodicalId\":47979,\"journal\":{\"name\":\"Technology in Society\",\"volume\":\"82 \",\"pages\":\"Article 102907\"},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2025-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technology in Society\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0160791X25000971\",\"RegionNum\":1,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"SOCIAL ISSUES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology in Society","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0160791X25000971","RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"SOCIAL ISSUES","Score":null,"Total":0}
Time-frequency dependence and dynamic linkages between digital economy and education markets
This study utilizes a comprehensive analytical framework, incorporating both time and frequency domain methodologies, to investigate the complex interdependencies between the digital economy and the education market. The evaluation encompasses several critical dimensions, including return, volatility, and liquidity interconnectedness. The principal findings of this research are as follows: (1) There is a substantial co-dependence observed between the digital economy and the education sector, with a particular focus on components such as mobile internet, artificial intelligence, and big data—elements that exhibit the most pronounced linkages to educational infrastructures. Frequency domain analysis indicates that return spillover effects are potent in the short term, whereas spillovers related to volatility become increasingly significant in the long term. (2) The analysis reveals cloud computing and big data as the principal sources of spillover effects, while artificial intelligence, mobile internet, virtual reality, and online education serve as critical intermediaries. Importantly, vocational and K-12 education emerge as the primary beneficiaries of these spillover phenomena. (3) The interrelationships between the digital economy and educational markets exhibit time-varying characteristics, particularly marked by heightened fluctuations during pivotal events such as the COVID-19 pandemic and the implementation of the "Double Reduction" policy. Additionally, a notable strengthening of these trends has been observed after 2022. (4) The study demonstrates that assets associated with cloud computing, 5G technology, big data, artificial intelligence, and online education possess robust hedging effectiveness. The findings of this research aspire to inform educational policymakers regarding optimal resource allocation strategies, facilitate the seamless integration of digital technologies within educational frameworks, and provide strategic insights for asset investors seeking to navigate cross-market investments while enhancing risk management practices.
期刊介绍:
Technology in Society is a global journal dedicated to fostering discourse at the crossroads of technological change and the social, economic, business, and philosophical transformation of our world. The journal aims to provide scholarly contributions that empower decision-makers to thoughtfully and intentionally navigate the decisions shaping this dynamic landscape. A common thread across these fields is the role of technology in society, influencing economic, political, and cultural dynamics. Scholarly work in Technology in Society delves into the social forces shaping technological decisions and the societal choices regarding technology use. This encompasses scholarly and theoretical approaches (history and philosophy of science and technology, technology forecasting, economic growth, and policy, ethics), applied approaches (business innovation, technology management, legal and engineering), and developmental perspectives (technology transfer, technology assessment, and economic development). Detailed information about the journal's aims and scope on specific topics can be found in Technology in Society Briefings, accessible via our Special Issues and Article Collections.