The recent outbreak of COVID-19 has increased uncertainty across financial markets; therefore, examining the influences of oil price uncertainly on stock rewards is of considerable significance in this context. This article applies the crude oil volatility index (OVX) as a synthetic, precise measure of oil price uncertainty to explore how Chinese and U.S. stock returns respond differently to OVX changes prior to and during COVID-19. This issue is addressed by adopting a nonparametric causality-in-quantiles method, which can provide a more robust investigation of nonlinear impacts in various market situations. Our results indicate that stock returns in response to OVX changes across China and the U.S. are heterogeneous around the COVID-19 period. Before the epidemic, Chinese stock returns were considerably less responsive to the OVX shocks compared with the U.S. In contrast, China’s stock returns responded more strongly to OVX changes during the outbreak, while U.S. stock returns reacted in the opposite way.
{"title":"Economic analysis for the impacts of oil price uncertainty on Chinese and U.S. stock returns before and during the COVID-19 pandemic","authors":"Xiaofan Wang, Mengdie Xu","doi":"10.62051/2fbfrx75","DOIUrl":"https://doi.org/10.62051/2fbfrx75","url":null,"abstract":"The recent outbreak of COVID-19 has increased uncertainty across financial markets; therefore, examining the influences of oil price uncertainly on stock rewards is of considerable significance in this context. This article applies the crude oil volatility index (OVX) as a synthetic, precise measure of oil price uncertainty to explore how Chinese and U.S. stock returns respond differently to OVX changes prior to and during COVID-19. This issue is addressed by adopting a nonparametric causality-in-quantiles method, which can provide a more robust investigation of nonlinear impacts in various market situations. Our results indicate that stock returns in response to OVX changes across China and the U.S. are heterogeneous around the COVID-19 period. Before the epidemic, Chinese stock returns were considerably less responsive to the OVX shocks compared with the U.S. In contrast, China’s stock returns responded more strongly to OVX changes during the outbreak, while U.S. stock returns reacted in the opposite way.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The healthcare big data industry is rapidly developing globally, and data mining and knowledge services in the healthcare field have become one of the core demands for its development. Data mining in healthcare is beneficial to improve the efficiency of diagnosis and treatment of patients, which is helpful to formulate more effective treatment plans and reduce medical costs. In this paper, we searched the core journals on China Knowledge Network and web of science by subject terms, and eliminated the irrelevant articles for literature counting. In this paper, the commonly used models and algorithms of data mining in healthcare are firstly elaborated; then the progress of the application of this technology in assisting medical tasks, optimizing resource allocation and improving health information services are respectively reviewed, summarizing the segmentation, classic algorithms and representative studies implied by each application. However, the application of data mining technology in healthcare also faces some problems, from data collection, to data cleaning, preprocessing, visualization, to the selection of algorithms and evaluation of results, each link is full of difficulties and challenges. Finally, this paper proposes future research directions such as diversifying data sources, strengthening security and privacy protection, developing visualization and analysis tools, accurately using big data to improve the service level of healthcare institutions, semanticizing electronic medical records mining, and improving cancer prevention. At the same time, data mining is deeply integrated with cloud computing, artificial intelligence and other fields to jointly promote scientific and technological progress in the field of health care.
医疗大数据产业正在全球范围内迅速发展，医疗领域的数据挖掘和知识服务已成为其发展的核心需求之一。医疗领域的数据挖掘有利于提高患者的诊断和治疗效率，有利于制定更有效的治疗方案，降低医疗成本。本文通过主题词检索中国知网和web of science上的核心期刊，剔除不相关的文章进行文献统计。本文首先阐述了数据挖掘在医疗卫生领域的常用模型和算法，然后分别回顾了该技术在辅助医疗任务、优化资源配置和改善医疗信息服务等方面的应用进展，总结了各项应用所蕴含的细分领域、经典算法和代表性研究。然而，数据挖掘技术在医疗卫生领域的应用也面临着一些问题，从数据采集，到数据清洗、预处理、可视化，再到算法选择和结果评估，每个环节都充满了困难和挑战。最后，本文提出了未来的研究方向，如丰富数据来源、加强安全和隐私保护、开发可视化分析工具、准确利用大数据提高医疗机构服务水平、电子病历挖掘语义化、提高癌症预防水平等。同时，将数据挖掘与云计算、人工智能等领域深度融合，共同推动医疗卫生领域的科技进步。
{"title":"Research on the application of data mining in the field of healthcare","authors":"Wanwan Ding, Juntao Fang","doi":"10.62051/4pdg6558","DOIUrl":"https://doi.org/10.62051/4pdg6558","url":null,"abstract":"The healthcare big data industry is rapidly developing globally, and data mining and knowledge services in the healthcare field have become one of the core demands for its development. Data mining in healthcare is beneficial to improve the efficiency of diagnosis and treatment of patients, which is helpful to formulate more effective treatment plans and reduce medical costs. In this paper, we searched the core journals on China Knowledge Network and web of science by subject terms, and eliminated the irrelevant articles for literature counting. In this paper, the commonly used models and algorithms of data mining in healthcare are firstly elaborated; then the progress of the application of this technology in assisting medical tasks, optimizing resource allocation and improving health information services are respectively reviewed, summarizing the segmentation, classic algorithms and representative studies implied by each application. However, the application of data mining technology in healthcare also faces some problems, from data collection, to data cleaning, preprocessing, visualization, to the selection of algorithms and evaluation of results, each link is full of difficulties and challenges. Finally, this paper proposes future research directions such as diversifying data sources, strengthening security and privacy protection, developing visualization and analysis tools, accurately using big data to improve the service level of healthcare institutions, semanticizing electronic medical records mining, and improving cancer prevention. At the same time, data mining is deeply integrated with cloud computing, artificial intelligence and other fields to jointly promote scientific and technological progress in the field of health care.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"7 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article explores the application of artificial intelligence (AI) technology in cross-border data flow in international trade and the resulting legal and regulatory issues. With the development of globalization and the digital economy, cross-border data flow has become increasingly important in international trade. The rapid advancement of AI technology has accelerated this trend. However, cross-border data flow involves complex legal and regulatory issues, particularly concerning data privacy protection, security, and sovereignty. This paper aims to explore the current applications of AI technology in cross-border data flow in international trade, identify the legal and regulatory challenges, and propose relevant countermeasures and recommendations. The article points out that the application of AI technology in international trade is mainly reflected in automated production and logistics management, intelligent customer service and user experience, data analysis and decision support, compliance in international trade, and new trade models and innovation. However, cross-border data flow faces multiple challenges, and different countries have different legal requirements, increasing the operational costs and legal risks for enterprises. The article suggests addressing these challenges by strengthening international cooperation, improving domestic laws and regulations, adopting advanced technologies, and enhancing corporate compliance capabilities. By implementing these measures, the security and legality of cross-border data flow can be effectively ensured, promoting the sustainable development of international trade.
{"title":"The Legal and Regulatory Issues of AI Technology in Cross-Border Data Flow in International Trade","authors":"Qirui Chang","doi":"10.62051/cyw9y102","DOIUrl":"https://doi.org/10.62051/cyw9y102","url":null,"abstract":"This article explores the application of artificial intelligence (AI) technology in cross-border data flow in international trade and the resulting legal and regulatory issues. With the development of globalization and the digital economy, cross-border data flow has become increasingly important in international trade. The rapid advancement of AI technology has accelerated this trend. However, cross-border data flow involves complex legal and regulatory issues, particularly concerning data privacy protection, security, and sovereignty. This paper aims to explore the current applications of AI technology in cross-border data flow in international trade, identify the legal and regulatory challenges, and propose relevant countermeasures and recommendations. The article points out that the application of AI technology in international trade is mainly reflected in automated production and logistics management, intelligent customer service and user experience, data analysis and decision support, compliance in international trade, and new trade models and innovation. However, cross-border data flow faces multiple challenges, and different countries have different legal requirements, increasing the operational costs and legal risks for enterprises. The article suggests addressing these challenges by strengthening international cooperation, improving domestic laws and regulations, adopting advanced technologies, and enhancing corporate compliance capabilities. By implementing these measures, the security and legality of cross-border data flow can be effectively ensured, promoting the sustainable development of international trade.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"34 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141924565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Exploring the measurement of the digital economy development level plays a crucial role in analyzing the disparities in digital economy development across China's provinces, formulating differentiated policies, and promoting balanced national digital economy development. This study first constructs an evaluation system for digital economy development levels, comprising 14 tertiary indicators. The weights of each indicator were determined using the Analytic Hierarchy Process (AHP), revealing that the number of domain names, the number of Internet broadband access users, as well as fiber optic cable line length, are significant factors. Subsequently, the TOPSIS method was utilized to measure and compare the digital economy development levels of 31 provinces (autonomous regions and municipalities). The results indicate that coastal provinces such as Guangdong, Jiangsu, and Zhejiang have higher levels of digital economy development, while the development levels in the central and western regions are relatively lagging. The study proposes policy recommendations to narrow the inter-provincial digital economy development gap and promote balanced and sustainable digital economy development nationwide, including strengthening infrastructure construction, implementing differentiated policies, fostering regional coordinated development models, and optimizing the talent cultivation system.
{"title":"A Comprehensive Evaluation of Digital Economy Development Level in China Based on the TOPSIS Method","authors":"Yining Chen","doi":"10.62051/s455dv53","DOIUrl":"https://doi.org/10.62051/s455dv53","url":null,"abstract":"Exploring the measurement of the digital economy development level plays a crucial role in analyzing the disparities in digital economy development across China's provinces, formulating differentiated policies, and promoting balanced national digital economy development. This study first constructs an evaluation system for digital economy development levels, comprising 14 tertiary indicators. The weights of each indicator were determined using the Analytic Hierarchy Process (AHP), revealing that the number of domain names, the number of Internet broadband access users, as well as fiber optic cable line length, are significant factors. Subsequently, the TOPSIS method was utilized to measure and compare the digital economy development levels of 31 provinces (autonomous regions and municipalities). The results indicate that coastal provinces such as Guangdong, Jiangsu, and Zhejiang have higher levels of digital economy development, while the development levels in the central and western regions are relatively lagging. The study proposes policy recommendations to narrow the inter-provincial digital economy development gap and promote balanced and sustainable digital economy development nationwide, including strengthening infrastructure construction, implementing differentiated policies, fostering regional coordinated development models, and optimizing the talent cultivation system.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"14 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141924998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, the auto parts manufacturing industry has been facing multiple challenges, such as economic fluctuations, technological changes, etc. Improving SCR has become an urgent need for the development of the industry. This paper explores how automotive parts manufacturing companies can enhance supply chain resilience by optimizing SCI and analyze how this relationship changes in the context of market turbulence. The study shows that all three dimensions of SCI, namely supplier integration, internal integration and customer integration, can significantly enhance supply chain resilience. Relational capital and supply chain agility play an important role as mediating variables, while MT negatively moderates the supply chain integration and resilience relationship. This study not only deepens the theoretical understanding, but also provides new perspectives for practice, emphasizing that when formulating supply chain strategies, firms need to consider the multidimensional impact of integration to ensure the sustained stability and long-term competitiveness of the supply chain.
{"title":"Study on the Impact Mechanism of Supply Chain Integration on Supply Chain Resilience","authors":"Fuhong Luo","doi":"10.62051/wt7hx264","DOIUrl":"https://doi.org/10.62051/wt7hx264","url":null,"abstract":"In recent years, the auto parts manufacturing industry has been facing multiple challenges, such as economic fluctuations, technological changes, etc. Improving SCR has become an urgent need for the development of the industry. This paper explores how automotive parts manufacturing companies can enhance supply chain resilience by optimizing SCI and analyze how this relationship changes in the context of market turbulence. The study shows that all three dimensions of SCI, namely supplier integration, internal integration and customer integration, can significantly enhance supply chain resilience. Relational capital and supply chain agility play an important role as mediating variables, while MT negatively moderates the supply chain integration and resilience relationship. This study not only deepens the theoretical understanding, but also provides new perspectives for practice, emphasizing that when formulating supply chain strategies, firms need to consider the multidimensional impact of integration to ensure the sustained stability and long-term competitiveness of the supply chain.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"84 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The content and purpose of labor education in higher vocational colleges are highly compatible with ideological and political education. It is of great significance to transform labor education based on skill education into labor education based on comprehensive education, integrate labor education into ideological and political education, and promote the ideological and political construction of labor education courses. This article analyzes the shortcomings and shortcomings of labor education in vocational colleges, and proposes to explore the construction of a "labor ideological and political" model for labor education in vocational colleges from three aspects: "for whom to labor", "what labor to do", and "how to labor". Since the release of the Opinions of the Central Committee of the Communist Party of China and the State Council on Comprehensively Strengthening Labor Education in Primary, Secondary, and Large Schools in the New Era, as well as the Guiding Outline for Labor Education in Primary, Secondary, and Large Schools (Trial) issued by the Ministry of Education, labor education has been widely promoted in vocational colleges. More and more educators have realized that labor education is not only a form of employment education and skill education, but also a form of creative education and holistic education, in order to achieve the organic integration of labor education and ideological and political education. It is also an inevitable requirement for vocational colleges to implement the fundamental task of "cultivating morality and nurturing talents" in the new era.
{"title":"Labor Ideological and Political Education: Promoting the Organic Integration of Labor Education and Ideological and Political Education in Vocational Colleges","authors":"Guohui Su","doi":"10.62051/yb8sw370","DOIUrl":"https://doi.org/10.62051/yb8sw370","url":null,"abstract":"The content and purpose of labor education in higher vocational colleges are highly compatible with ideological and political education. It is of great significance to transform labor education based on skill education into labor education based on comprehensive education, integrate labor education into ideological and political education, and promote the ideological and political construction of labor education courses. This article analyzes the shortcomings and shortcomings of labor education in vocational colleges, and proposes to explore the construction of a \"labor ideological and political\" model for labor education in vocational colleges from three aspects: \"for whom to labor\", \"what labor to do\", and \"how to labor\". Since the release of the Opinions of the Central Committee of the Communist Party of China and the State Council on Comprehensively Strengthening Labor Education in Primary, Secondary, and Large Schools in the New Era, as well as the Guiding Outline for Labor Education in Primary, Secondary, and Large Schools (Trial) issued by the Ministry of Education, labor education has been widely promoted in vocational colleges. More and more educators have realized that labor education is not only a form of employment education and skill education, but also a form of creative education and holistic education, in order to achieve the organic integration of labor education and ideological and political education. It is also an inevitable requirement for vocational colleges to implement the fundamental task of \"cultivating morality and nurturing talents\" in the new era.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"46 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141924079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper discusses the construction and analysis method of user behavioral portrait by the data provided by the electric power platform in the big data environment. Firstly, it introduces the construction and analysis of user profiles based on big data platforms, which covers the construction of user basic attribute profiles, user behavioral characteristics profiles, user product characteristics profiles and user interaction characteristics profiles from different dimensions. Secondly, for the electric power sector, the article discusses the analysis of big data provided by electric power platforms to better understand user behavior and trends in energy consumption. The article proposes a method for constructing a behavioral portrait of power users based on big data analysis, including the construction and management of a user label library and the process of constructing a behavioral portrait of power users based on the improved K-mean algorithm. Finally, the effectiveness and accuracy of the method of this paper are verified by experimental analysis. Overall, this paper provides some guidance and reference for the analysis of user behavior in the field of electric power by exploring the method of user behavior portrait construction with the data provided by the electric power platform in the big data environment.
{"title":"Research on User Profile and User Behavior of Integrating Big Data Platforms","authors":"Yaoxuan Wang","doi":"10.62051/3a6dex21","DOIUrl":"https://doi.org/10.62051/3a6dex21","url":null,"abstract":"This paper discusses the construction and analysis method of user behavioral portrait by the data provided by the electric power platform in the big data environment. Firstly, it introduces the construction and analysis of user profiles based on big data platforms, which covers the construction of user basic attribute profiles, user behavioral characteristics profiles, user product characteristics profiles and user interaction characteristics profiles from different dimensions. Secondly, for the electric power sector, the article discusses the analysis of big data provided by electric power platforms to better understand user behavior and trends in energy consumption. The article proposes a method for constructing a behavioral portrait of power users based on big data analysis, including the construction and management of a user label library and the process of constructing a behavioral portrait of power users based on the improved K-mean algorithm. Finally, the effectiveness and accuracy of the method of this paper are verified by experimental analysis. Overall, this paper provides some guidance and reference for the analysis of user behavior in the field of electric power by exploring the method of user behavior portrait construction with the data provided by the electric power platform in the big data environment.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"36 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141924736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, its application in various fields is increasingly widespread. This study aims to explore how to integrate AIGC into the brand image course to improve teaching effectiveness and cultivate students' innovative practical ability. By analyzing the characteristics and advantages of AIGC, combined with the teaching objectives and contents of the brand image course, specific integration strategies and teaching methods are proposed, and their feasibility and effectiveness are verified through case analysis and teaching practice
{"title":"How to integrate \"Brand image Design\" kecheng into AIGC technology","authors":"Heng Zhu","doi":"10.62051/zw60v325","DOIUrl":"https://doi.org/10.62051/zw60v325","url":null,"abstract":"With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, its application in various fields is increasingly widespread. This study aims to explore how to integrate AIGC into the brand image course to improve teaching effectiveness and cultivate students' innovative practical ability. By analyzing the characteristics and advantages of AIGC, combined with the teaching objectives and contents of the brand image course, specific integration strategies and teaching methods are proposed, and their feasibility and effectiveness are verified through case analysis and teaching practice","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"2 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The organizing Committee of 8th EMEHSS warmly welcomes you to join the 8th International Conference on Economics and Management, Education, Humanities and Social Sciences (EMEHSS 2024), this conference was held in Hong Kong, China during July 29-30, 2024. The aim of the EMEHSS is to provide an interactive platform for the scholars, economists, managers, innovators, entrepreneurs, government agencies and policy-makers etc., from both China and abroad to exchange ideas. EMEHSS 2024 received 125 manuscripts. And the acceptance rate is less than 50%. Articles submitted to the conference should report original, previously unpublished research results, experimental or theoretical and must not be under consideration for publication elsewhere. We firmly believe that ethical conduct is the most essential virtual of any academic. Conference Organizing Committee.
{"title":"Preface: 8th International Conference on Economics and Management, Education, Humanities and Social Sciences (EMEHSS 2024)","authors":"Qin Kang, Caroline Benson","doi":"10.62051/wvcy5z39","DOIUrl":"https://doi.org/10.62051/wvcy5z39","url":null,"abstract":"The organizing Committee of 8th EMEHSS warmly welcomes you to join the 8th International Conference on Economics and Management, Education, Humanities and Social Sciences (EMEHSS 2024), this conference was held in Hong Kong, China during July 29-30, 2024. \u0000The aim of the EMEHSS is to provide an interactive platform for the scholars, economists, managers, innovators, entrepreneurs, government agencies and policy-makers etc., from both China and abroad to exchange ideas. \u0000EMEHSS 2024 received 125 manuscripts. And the acceptance rate is less than 50%. Articles submitted to the conference should report original, previously unpublished research results, experimental or theoretical and must not be under consideration for publication elsewhere. We firmly believe that ethical conduct is the most essential virtual of any academic. \u0000Conference Organizing Committee.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"62 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Songye Wu, Huixin Zheng, Caihong Lv, Jialing Jiang, Shenghong Li
The operational efficiency of information security enterprises is of great significance to China's information security and even economic security. This paper constructs a DEA-GRA model to calculate the BCC efficiency decomposition of 30 listed companies and gives the amount of input redundancy and output insufficiency of non-DEA effective enterprises. This study also explores the grey correlation between the efficiency of super-efficient technologies and the environmental factors of where firms produce and sell. The results of the study show that the vast majority of non-DEA effective decision-making units in 2022 are in a state of decreasing size. The grey correlation analysis shows that the industrial cluster effect and scientific and technological investment in the production place, and the degree of development of the information security industry in the operation place have an important impact on the technical efficiency of information security enterprises.
信息安全企业的运营效率对我国信息安全乃至经济安全具有重要意义。本文构建了DEA-GRA模型，计算了30家上市公司的BCC效率分解，给出了非DEA有效企业的投入冗余量和产出不足量。本研究还探讨了超效率技术的效率与企业生产和销售地环境因素之间的灰色关联。研究结果表明，2022 年绝大多数非 DEA 有效决策单位的规模处于不断缩小的状态。灰色关联分析表明，生产地的产业集群效应和科技投入、经营地的信息安全产业发展程度对信息安全企业的技术效率有重要影响。
{"title":"Study on Information Security Industry Efficiency Measurement Based on DEA-GRA","authors":"Songye Wu, Huixin Zheng, Caihong Lv, Jialing Jiang, Shenghong Li","doi":"10.62051/cnbqs759","DOIUrl":"https://doi.org/10.62051/cnbqs759","url":null,"abstract":"The operational efficiency of information security enterprises is of great significance to China's information security and even economic security. This paper constructs a DEA-GRA model to calculate the BCC efficiency decomposition of 30 listed companies and gives the amount of input redundancy and output insufficiency of non-DEA effective enterprises. This study also explores the grey correlation between the efficiency of super-efficient technologies and the environmental factors of where firms produce and sell. The results of the study show that the vast majority of non-DEA effective decision-making units in 2022 are in a state of decreasing size. The grey correlation analysis shows that the industrial cluster effect and scientific and technological investment in the production place, and the degree of development of the information security industry in the operation place have an important impact on the technical efficiency of information security enterprises.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"57 46","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141923264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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