2024中国科技出行产业10大战略技术趋势展望 亿欧智库 https://www.iyiou.com/research Copyright reserved to EO Intelligence, December 2023 前言 u 以新能源动力、高阶智能网联等科技力量推动的出行载力工具，正在引领当下的大众化用户出行需求，提升出行效率、节约成本、满足用户全新体 验，且绿色可持续发展。亿欧智库在2018年首次提出并定义了"科技出行"这一概念：以新能源、智能网联等汽车科技为载体的大众化出行形态。 u 《中国科技出行产业战略技术趋势展望》报告为亿欧智库针对科技出行产业输出的年度系列报告，亿欧智库希望聚焦智能电动汽车（SEV）、自动 驾驶、出行科技、新能源等出行领域环节，对未来一年的战略技术创新与突破进行趋势预测与展望，探寻市场发展的挑战与机遇，使行业内外人士 直观了解新阶段产业发展的科技想象空间。 《2024中国科技出行产业10大战略技术趋势展望》报告主要围绕科技出行产业生态创新发展、企业降本增效、用户体验升级三个方面展开 2024 中国科技出行 战略技术趋势展望 （二）企业降本增效 （一）生态创新发展 （三）用 ...

2024 THE BRANDX 新消费 品牌力 亿欧智库 hllps:;/ww.iyiou.corn/resealch Copy'ighl ruservec lo EO Inlelliger ce, Decernber 2C24 2024年中国新消费发展洞察 暨品牌力榜单 2024中国新消费发展洞察 InsightsontheDevelopmentof New Consumption in China 2024 目录 Content # 序言 # 第一章 ?亿欧智库 2024中国新消安发展洞察 报告研究范围及评价体系 亿欧智库 # 第二章 # 第三章 2024中国新消 2024中国新消安 时代发展背景 行业司宽及品牌力榜单 第12页 THEBRAND 亿欧智库 新消费·品牌力 2024中国新消费发展洞察 序言 暨品牌力榜单 # 序言 ◆◆◆◆ 时光察，转限，中国新消勇三步入0三为声。这一年，尽兰全经济 以分落挑%，但中回消费小场+辰圳出了非凡的韧性与勃的活力，经济的步 复苏与消或信的整游升，为另营来的不安仅是机遇，泛有史为业的要 与挑货。这片变幻票测的山场中；克争的热化让每一个多与者都率安了口巨 消费小场的法 ...

亿欧智库 https://www.iyiou.com/research Copyright reserved to EO Intelligence, Dec 2024 | 互联网家居发展现状分析 01 1.1 家居行业韧性十足，存量需求占据市场重要份额 1.2 家居全品类融合发展，一站式服务成为核心需求 1.3 互联网家居服务商助力优化全链路业务能力 1.4 互联网家居服务商企业图谱 | 互联网家居服务商观察 02 2.1 售后服务 2.2 仓储物流服务 2.3 营销服务 2.4 渠道平台 2.5 供应链服务 03 2024中国互联网家居合作伙伴TOP5 3.1 2024中国互联网家居合作伙伴评选体系 3.2 2024中国互联网家居合作伙伴TOP5榜单 | 互联网家居发展趋势展望 04 4.1 互联网家居服务商生态化发展趋势愈发显著 01 互联网家居发展现状分析 | 互联网家居发展趋势展望 04 4.1 互联网家居服务商生态化发展趋势愈发显著 家居行业韧性十足，存量需求占据市场重要份额 1.1 家居行业韧性十足，存量需求占据市场重要份额 1.2 家居全品类融合发展，一站式服务成为核心需求 1.3 互联网家居服 ...

〖亿欧智库 2024年未来健康空间生态产业发展自皮书 亿欧智库 https://www.iyiou.com/research Copyright reserved to EO Intelligence, December 2024 :《亿欧智库 l 目录 ar CONTENTS 健康空间生态定义、市场空间及发展驱动因素 01 02 健康空间生态产业价值 03 健康空间生态细分应用场景 04 健康空间生态未来发展趋势 定义-健康空间生态基于智能硬件构建智慧平台，形成健康&节能&舒适空间闭环 ◆ 健康空间概念定义：以安全家装材料、空间智能设备及健康智能设备为基础，采集空间、人体数据，利用40筹法调整空间智能设备参数，以低能耗 为前提提供符合人体最佳生活、工作、出行、休闲、康复等场景的舒适空间状态，并根据人体生命体征指标数据进行反馈，提供健康生活建议与 意见，实现环境与个人健康生活可持续发展的目标。 亿欧智库:健康空间生态定义核心关键词:健康&节能&舒适 健康层面 空间层面 改善生活健康状态的 采集个人健康数据 使用安全材料 管 ஜ 健康空间 分析个人健康行为 使用智能硬件 मेक Hel 健 下 维持良好 缓解亚 ...

刘一苏 美妆个护与母婴赛道撰写 亿欧智库 分析师 Email: liumengyi@iyiou.com 项目支持 特别鸣谢 版权声明 关于亿欧 基于对中国科技、产业和投资的深刻理解，同时凭借国际化视角和高度，亿欧为中外客户提供行业研究、投 资分析、创新咨询、数据产品、品牌公关、国际化落地等服务。已经合作并服务过的客户包括华为、英特尔 、腾讯、百度、一汽解放、理想汽车、京东、微软、安顾集团、统信、中石油-昆仑数智、中电信息、东信 集团等。 基于自身的研究和咨询能力，同时借助亿欧网和亿欧国际网站的传播优势； 亿欧为创业公司、大型企业、政 府机构、机构投资者等客户类型提供有针对性的服务。 ◆ 大型企业 欢迎合作需求方联系我们，一起携手进步；电话 010-53321289，邮箱 hezuo@iyiou.com i " D 0 5 i 扫码添加小助手 加入行业交流群 I *上榜品牌根据首字母排序，排名不分先后。 47 THE BRA 2024中国新消费发展洞察 暨品牌力榜单 零售赛道市场格局进一步分化，即时零售成兵家必争之地 ◆ 2024年前三季度，中国消费市场头部零售商市场份额出现下滑趋势，表示零售赛道的集中度有所下 ...

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Investment Rating - The report indicates a positive outlook for the investment in the new energy vehicle (NEV) industry, particularly focusing on the expansion of the supply chain and international market opportunities. Core Insights - The rapid adoption of new energy smart electric vehicles (EVs) is driving demand for overseas charging stations, presenting opportunities for charging pile suppliers and operators to expand internationally [3]. - China's NEV penetration rate has reached 30%, while Europe stands at 18.5%, indicating significant room for growth in overseas markets [7]. - The report highlights that Chinese NEV companies are evolving from a globalization 2.0 phase to a globalization 3.0 phase, emphasizing local investment and deeper market penetration [12]. Summary by Sections 1. Global NEV Market Overview - The report outlines the global NEV market's growth, with China holding a 32% share and Europe at 11% [4][5]. - It emphasizes the increasing demand for NEVs in regions with low penetration rates, such as South America and other Asian countries [7]. 2. China's NEV Supply Chain Expansion - The report discusses the strategic shift of Chinese NEV companies to establish local manufacturing facilities abroad to mitigate high tariffs and enhance market presence [10]. - It notes that the export scale of Chinese brand smart electric vehicles (SEVs) is expected to reach 6.39 million units by 2030, with significant revenue growth projected [17][28]. 3. Key Export Markets - Major export regions for Chinese NEVs include Southeast Asia, Europe, and Latin America, with a notable increase in exports to South America since 2023 [20][46]. - The report identifies specific countries like Thailand, Malaysia, Germany, and Mexico as key locations for manufacturing and assembly [35][52]. 4. Challenges and Opportunities - The report acknowledges challenges such as varying consumer preferences, low brand recognition of Chinese companies abroad, and insufficient charging infrastructure [95]. - It also highlights the potential for NEV companies to leverage local partnerships and adapt products to meet regional demands [101]. 5. Case Studies of Companies - The report provides examples of companies like BYD, which has established manufacturing plants in multiple countries and focuses on local market integration [89]. - It discusses the strategies of component suppliers like Desay SV and solution providers like Neusoft, which are actively expanding their international presence [40][42][63].

获取更多维度报告数据，请访问亿欧网 (www.iyiou.com) | --- | --- | --- | --- | |-----------------------|---------------------------------|------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | 交易中心名称 | 数据产品供应商 | 产品名称 | 产品内容简介 | | | 汉江智行 | 襄阳市商业健康保险智能核保服务 (API数据) | 利用襄阳市卫健的健康医疗数据，通过整理、分析输出被投保人的健康状况，方便商保公 司对被投保人的健康状况能够及时掌握，进一步提升业的效率和准确性。 | | 北京国 ...

Investment Rating - The report does not explicitly state an investment rating for the smart sanitation industry Core Insights - The smart sanitation industry is driven by urbanization, technological advancements, and the need for efficient waste management solutions. The market is expected to grow significantly, with a projected market size of 231.5 billion yuan by 2025, reflecting a CAGR of approximately 7.86% from 2022 to 2025 [40][41]. Industry Overview and Transformation Background - The smart sanitation sector integrates advanced technologies such as IoT, big data, and AI to enhance waste management efficiency and reduce operational costs. The transition from traditional manual methods to smart solutions is essential for improving urban sanitation services [10][13]. Current Market Status - As of 2023, China's urbanization rate reached 65%, leading to increased demand for sanitation services, particularly in first-tier and new first-tier cities. The number of specialized sanitation vehicles is expected to exceed 480,000 by 2025, with automation and unmanned vehicles playing a crucial role in enhancing operational efficiency [40][42]. Industry Chain Characteristics - The smart sanitation industry comprises various stakeholders, including government agencies, enterprises, and the public. The supply side features a comprehensive management platform that integrates IoT and AI technologies for real-time monitoring and data sharing [23][30]. Demand Side Characteristics - The demand for smart sanitation solutions is driven by the need for improved service quality, efficiency, and public satisfaction. The digital transformation in sanitation management is expected to enhance government service capabilities and public engagement [33][34]. Market Trends and Outlook - The report highlights the increasing penetration of smart sanitation technologies, with an expected market size of 16.2 billion yuan by 2025. The adoption of unmanned cleaning vehicles is anticipated to significantly improve operational efficiency and reduce labor costs [42][40]. Technological Development and Application Gaps - There is a notable gap between the development of smart sanitation technologies and their actual application in smaller cities. While large cities have embraced IoT and AI solutions, smaller cities face challenges in technology adoption due to cost and infrastructure limitations [46]. Transformation Solutions - The report outlines several transformation solutions for the sanitation industry, including automated waste sorting systems, intelligent road cleaning vehicles, and enhanced waste management infrastructure. These solutions aim to optimize resource allocation and improve environmental sustainability [51][55][60].

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The demand for AI large model applications is increasing among enterprises driven by policy support, technological breakthroughs, and digital transformation needs [5][6] - Enterprises face multiple challenges in implementing AI large model applications, including insufficient tools/solutions, diverse model adaptation, and complex end-to-end development processes [14][15] Summary by Sections 1. Demand and Pain Points Analysis - The application of AI large models is becoming crucial for enterprise transformation, with higher demands for accuracy, effectiveness, and deployment efficiency [4][5] - Enterprises are exploring AI's potential to empower their operations while facing challenges in the application process [4][14] 2. Exploration and Successful Pathways - Market attempts to address the pain points of AI large model application include the need for comprehensive solutions and professional capabilities from service providers [20][25] - Successful practices in the industry emphasize the importance of one-stop solutions [20][25] 3. Future Trends and Strategic Recommendations - Enterprises are expected to increasingly focus on the ROI of AI large models, with a significant portion of CIOs planning to increase AI budgets in 2024 [46] - The integration of multi-modal models is seen as a key trend to address complex business problems [47] - Combining Retrieval-Augmented Generation (RAG) with knowledge graphs is anticipated to enhance performance in complex query processing [49] - The development of intelligent agents is moving towards expanding single-agent capabilities and fostering multi-agent collaboration [52] 4. Core Capabilities Required for AI Large Model Application - Service providers need to offer flexible and efficient data processing tools, high-quality data generation capabilities, and robust privacy protection [27][28] - The ability to adapt to diverse computing power and model matching is essential for service providers [28][29] - Full-process service capabilities are necessary to ensure the successful deployment of AI large models [29][30] 5. Best Practices for AI Large Model Deployment - Companies should focus on understanding their business needs and selecting appropriate models for deployment [40][41] - Continuous learning and iteration mechanisms are crucial for optimizing AI model performance [59][60]