Core Viewpoint - The Chinese cosmetics industry is projected to reach a market size of 1.1 trillion yuan, with domestic brands surpassing international brands in market share and consumer preference [1][2]. Group 1: High-Quality Development and New Productive Forces - The domestic cosmetics market retail sales are expected to reach 470 billion yuan by 2025, indicating a significant growth trajectory for the industry [2]. - New productive forces are essential for the high-quality development of the cosmetics industry, transitioning from traditional manufacturing to intelligent and lean production [4]. - New productive forces enhance production efficiency and product consistency through automation and intelligent equipment, addressing quality control challenges [4]. Group 2: Intelligent Manufacturing Practices of Domestic Brands - The past decade has seen a shift in the cosmetics manufacturing industry from experience-driven to data-driven processes, evolving through three stages: semi-automated, automated, and now data-driven intelligent stages [6]. - Leading brands like Han Shu and Pechoin have made significant investments in intelligent manufacturing, achieving production capacity increases and improved quality control [8][10]. - Domestic brands have made historical advancements in intelligent manufacturing, with automation rates rising from approximately 40% to levels comparable to international brands [10]. Group 3: R&D Innovation and Cost Management - R&D expenditure rates vary across different categories, with skincare products averaging 1.5%-5% and medical beauty products at 2%-5%, reflecting a focus on compliance and clinical data [21][23]. - Domestic brands like Han Shu and Pechoin have R&D personnel ratios comparable to international leaders, indicating strong R&D capabilities [24]. - The production cost rates for various product categories range from 15% to 30%, with domestic brands leveraging self-researched technologies and integrated supply chains to maintain competitive pricing [27][28]. Group 4: International Competitiveness of Domestic Brands - Domestic brands have achieved significant breakthroughs in the cosmetics sector, enhancing core competitiveness through new productive forces [31]. - Intelligent manufacturing has enabled micro-level quality control, establishing trust in product quality [33]. - The integration of AI and 5G technologies in manufacturing processes positions domestic brands at the forefront of global standards, driving high-quality development in the industry [33].

Core Insights - The report focuses on the online variety show industry in China, analyzing user scale, content innovation, and marketing trends for 2024-2025, aiming to provide decision-making references for platforms and brands to transition from traffic competition to quality and sustainability [1] User Scale of Online Video - The overall user base has reached 1 billion, with a slight year-on-year growth of 3.4%, indicating a significant recovery in the industry [2] - In 2024, the online video sector shows signs of recovery, with monthly unique device numbers experiencing a small increase, particularly in Q2 and Q4 [2] User Trends in Online Variety Channels - The variety show market remains stable, with monthly active device numbers reaching 500-600 million, peaking in June and October due to seasonal factors [6] - The influx of student users during summer and the impact of the National Day holiday contributed to the market's performance [6] Audience Profile of Variety Channels - The primary audience for variety channels consists of young people, female viewers, and residents of new first-tier cities, with a TGI index of 122 for the 18-24 age group [7] Content Creation Market Performance - There is a growth in new variety shows and sequels, with 20 new shows launched in 2024, an increase from 19 in 2023, and a notable improvement in their viewership [11] - The willingness to produce sequels has increased, with 32 sequels in 2024, up from 29 in 2023 [11] Performance of Different Content Types - The outdoor experience category remains the highest in market share, while comedy shows have seen a significant increase in viewership, up 143% from 2023 [13] - The emergence of reality game content is noted, indicating a potential new market opportunity [13] Reality Game Content Performance - In 2024, six reality game shows were produced, with Youku leading in both quantity and viewership, contributing 35.5% of the segment's total viewership [16] New Variety Show Overview - The new variety shows in 2024 exhibit diverse themes, with Q2 and Q3 being peak periods for premieres [18] Key Highlights of Reality Game Shows - Reality game shows redefine the genre by offering immersive experiences that engage viewers with real-world issues [20] Key Highlights of Comedy Variety Shows - Comedy shows prioritize emotional value and address social issues through light-hearted expressions, with Tencent and iQIYI leading in this category [25] Innovation in Content Creation - The rise of new IPs and the phenomenon of second seasons indicate a shift towards long-term value driven by content innovation [30] - The integration of film and variety shows enhances fan engagement and extends the life cycle of popular IPs [32] Changes in Sponsorship Trends - The number of sponsorship brands for variety shows has slightly decreased, but the average number of brands for top new shows has increased from 3.3 to 3.9 [40] - Fast-moving consumer goods account for 62.4% of sponsorship frequency, indicating their dominance in the market [45] Marketing Budget Changes - Overall marketing budgets are tightening, with a projected decrease of 7-10% for 2025, varying significantly across industries [50] Evaluation of Sponsorship Effectiveness - The effectiveness of sponsorship is assessed through both basic metrics like viewership and specific business indicators relevant to the industry [57] Ecological Marketing Strategies - The evolution of content monetization has led to the emergence of ecological marketing, integrating brands, content, and ecosystems for mutual benefit [59] Innovative Marketing Strategies - Brands are increasingly co-creating content with variety shows to enhance their image and engage younger audiences [62] - The use of KOLs and multi-platform strategies is becoming common to maximize brand exposure and sales [65]

Core Viewpoint - The article emphasizes that AI technology is fundamentally transforming the internet media industry by enhancing content production, distribution, and consumption processes, leading to a more efficient and innovative media ecosystem [1][2]. Group 1: Industry Overview - The Chinese internet media industry is transitioning into an AI-enabled intelligent ecosystem, with user growth slowing and competition shifting towards existing markets [2][6]. - Generative AI is accelerating the integration of multimodal applications, reshaping the content ecosystem and user experience, and driving the industry towards quality and efficiency [2][4]. Group 2: Deep Empowerment of AI - AI technology is deeply empowering the internet media industry, promoting intelligent transformation across the entire value chain, from production to consumption [2][24]. - Major media and social platforms in China, such as People's Daily and Weibo, are actively applying AI technology to enhance content creation, review, and distribution processes [2][36]. Group 3: Challenges and Opportunities - The internet media industry faces challenges such as content authenticity issues, high technical costs, and privacy risks, which need to be addressed for sustainable growth [3][46][54]. - Opportunities exist for media platforms to build competitive advantages through self-developed technologies, data governance, and intelligent recommendations [3][54]. Group 4: AI's Role in Content Production - Generative AI is reshaping the content production landscape by breaking down professional barriers and enabling user-generated content (UGC) creation [24][28]. - The integration of AI in content review processes enhances efficiency and accuracy, allowing for automated initial screenings and human-AI collaboration [26][28]. Group 5: AI's Impact on Content Distribution and User Engagement - AI technology enhances content distribution efficiency by analyzing user behavior and optimizing recommendation paths, thereby increasing user engagement and retention [28][31]. - The use of AI in user operations allows for personalized content matching and intelligent customer service, further enhancing user experience [28][31]. Group 6: AI's Influence on Content Consumption - The shift from one-way communication to interactive engagement allows consumers to evolve into co-creators, fostering a cycle of creation and consumption [31][46]. - AI technologies facilitate seamless access to content through translation and voice conversion, lowering barriers to information consumption [31][46]. Group 7: AI Applications in Media Platforms - Major platforms like Douyin and Weibo are embedding AI technologies throughout their content lifecycle, from production to marketing, creating a comprehensive ecosystem [40][42]. - Weibo's self-developed multimodal model supports various AI products that enhance the entire content production and distribution chain [42][44]. Group 8: Future Trends and Developments - The generative AI landscape is expected to evolve towards specialized models and applications, focusing on scene-based usage rather than merely scaling up [18][40]. - The industry is exploring cost optimization strategies, including embracing open-source models and developing proprietary vertical models to ensure competitive advantages [51][54].

Core Insights - The report provides a comprehensive analysis of the current state and trends of financial intelligent agents in China, emphasizing their development driven by technological breakthroughs, business innovations, and policy support [1][2]. Group 1: Driving Factors - Technological breakthroughs are addressing the "last mile" challenges in the application of large models, enhancing their task execution capabilities through advancements in tools and frameworks [6]. - Approximately 33% of financial institutions are showing a positive investment attitude towards intelligent agents, indicating market recognition of their practical value [7]. - Policy support is providing clear guidance and target planning for the application and development of intelligent agents in finance, with specific focus areas outlined in various governmental documents [8][10]. Group 2: Current Industry Cycle - The financial intelligent agent industry is in its initial exploration phase, with 96% of applications still in the proof of concept (POC) and pilot stages, while only 4% have moved to agile practice [12]. - The majority of intelligent agent applications are focused on operational functions, such as knowledge Q&A and office assistance, with expectations for these to transition to agile practice within 1-2 years [16]. - Financial institutions are primarily exploring two deployment paths: embedding intelligent agent functions into existing systems and developing independent intelligent agent applications [18]. Group 3: Project Implementation and Challenges - Most projects are progressing according to established plans, with a significant portion still in the delivery phase, particularly those signed in the latter half of 2025 [19]. - There is an anticipated risk of 20%-25% of projects not meeting expectations or failing, influenced by factors such as product capabilities and real-world complexities [22]. - The banking sector is the leading area for intelligent agent applications, accounting for 43% of projects, followed by asset management at 27% and insurance at 15% [25][26]. Group 4: Market Size and Growth - The investment scale for intelligent agent platforms and applications in Chinese financial institutions is projected to reach 950 million yuan in 2025, with an expected compound annual growth rate of 82.6% by 2030 [35]. - The market growth is supported by both existing project expansions and new entrants, driven by policy incentives and successful case demonstrations from leading institutions [36]. Group 5: Customer Expectations and Investment Willingness - Financial institutions are increasingly viewing intelligent agents as core innovation engines for sustainable business growth rather than merely tools for efficiency [53][58]. - The willingness to invest in intelligent agents has risen significantly, with a 27.5% increase in institutions expressing positive investment intentions, driven by peer examples and policy guidance [58][59]. - Institutions are categorized into three investment types: proactive exploration, pragmatic follow-up, and cautious observation, reflecting varying levels of resource allocation and risk tolerance [64]. Group 6: Safety and Compliance - Safety and compliance are paramount for financial institutions when adopting intelligent agents, with a strong consensus on the need for secure operational frameworks [71]. - Key concerns include ensuring the reliability of intelligent agent operations, protecting data privacy, and maintaining compliance with regulatory requirements [72]. Group 7: Value Assessment and Practical Implementation - The definition and measurement of value have become critical decision-making anchors for financial institutions adopting intelligent agents, focusing on maximizing value in specific application scenarios [73]. - Successful implementation of intelligent agents requires a deep understanding of financial business logic, alongside safety and usability considerations [76][80].

Core Insights - The Chinese restaurant food chain franchise industry is undergoing significant transformation, driven by macroeconomic recovery and increasing consumer spending power, leading to market expansion and digital transformation [1][4][12] - The rise of home dining and heightened consumer demand for health, efficiency, and social value are reshaping industry structures, prompting chain brands to accelerate their digital transformation and omnichannel marketing strategies [1][10] - The relationship between brands and franchisees is shifting from extensive expansion to refined operations and mutual selection, with a growing group of experienced "professional franchisees" [1][47] Market Overview - The Chinese restaurant food market reached 12.6 trillion yuan, with a compound annual growth rate (CAGR) of approximately 7.2% from 2020 to 2024, driven by both service and retail sectors [9] - The restaurant service sector is recovering strongly post-pandemic, with an annual growth rate nearing 9%, while food retail is experiencing structural upgrades with high-value subcategories [9][10] - The home dining market is growing rapidly at an annual rate of 18.4%, expected to account for 13.5% of the overall food retail market by 2029, indicating a significant shift towards retailization in the industry [10][36] Consumer Spending Trends - From 2020 to 2024, urban and rural residents' per capita consumption expenditure is showing a recovery trend, with urban growth at 6.4% and rural at 8.9%, reflecting the ongoing vitality of the lower-tier market [6] - Food and beverage spending remains stable and resilient, providing a solid demand foundation for the restaurant food industry [6] Franchise Market Dynamics - The franchise market is dominated by the restaurant sector, which accounts for nearly 50% of the market, indicating its high-frequency consumption and standardization advantages [20] - The chain rate in the restaurant service sector is expected to rise from 15% to 24% between 2020 and 2025, although it still lags behind developed markets like Japan and the U.S. [12] - The competitive environment is shifting towards refined operations, with franchisees focusing on quality site selection and cost structures as market saturation increases [24][48] Investment Considerations - Franchisees are increasingly favoring low-investment, high-profit margin segments, with the home dining sector being particularly attractive due to its lower entry barriers and shorter investment return periods [34][36] - The home dining segment is characterized by a high degree of standardization and flexibility in product offerings, making it appealing for franchisees [32][34] Brand Selection Criteria - Franchisees prioritize brands with clear profit models, operational support, and a proven track record, leading to a dual selection mechanism between brands and franchisees [48] - The leading brand in the home dining sector, Guoquan Shihui, is recognized for its low investment threshold, mature replicable model, and diverse product matrix, making it a preferred choice for franchisees [39][40] Digital Transformation - The industry is witnessing a pressing need for digital transformation to support scale expansion and profitability, with brands leveraging data-driven site selection and standardized operational systems [44] - Digital management of supply chains is enhancing control, reducing waste, and improving efficiency, which is crucial for increasing single-store profitability [44] Conclusion - The Chinese restaurant food chain franchise industry is poised for growth, driven by changing consumer behaviors, digital transformation, and evolving franchisee dynamics, presenting numerous opportunities for investment and expansion [1][9][12]

Core Insights - The global "pet economy" is rapidly growing, with China's pet market transitioning from "basic care" to "quality care," driven by pet tech products that are becoming increasingly "smart, healthy, and personalized" [1][5][60] - The Chinese pet market is projected to reach 345.3 billion yuan in 2024, with the smart pet products market exceeding 10.2 billion yuan, accounting for 20% of the pet products market [1][13] - Key growth segments include smart feeding, health monitoring, and environmental cleaning, with sales of companion robots increasing by 210% year-on-year and smart collars and health devices growing by 180% [1][11] Market Dynamics - The competitive landscape is characterized by "diverse participation and fierce competition," with room for increased concentration among leading brands [2][11] - The trend of "AI + full scene" is emerging, with devices evolving from single-function to multi-modal interactions, such as smart trackers with satellite positioning and AI health analysis feeders [2] - Future expectations include precise identification for multiple pets, device interconnectivity, and AI emotional companionship, indicating a shift from "functional tools" to a "smart ecosystem" [2] Consumer Behavior - Pet owners are increasingly characterized by "high-end, younger, and emotional" traits, with an average annual spending of 4,440 yuan on pets, where smart products account for 50.8% of expenditures [1][17] - The demand for pet tech products is driven by emotional companionship needs, with 55.6% of users spending between 501-2000 yuan annually on smart products [1][34] - Major pain points for pet owners include issues with pet hair odor (42.5%) and lack of care for pets when owners are away (38.4%), highlighting clear demand scenarios for tech solutions [1][31] Product Trends - The pet tech product category is defined by advanced technologies such as IoT, AI, and big data, enhancing pet care and owner interaction [3][5] - The market is witnessing a shift from traditional pet care to a tech-driven era, with a focus on personalized solutions that cater to pets' specific needs based on breed, age, and health status [6][8] - Popular product categories include automatic feeders, health monitoring devices, and pet-friendly home appliances, with high purchase intent for vacuum cleaners and air purifiers [37][58] Future Outlook - The future of pet tech products is expected to focus on self-adaptive devices, understanding pet behavior, and multi-device interconnectivity, with significant consumer interest in these areas [55][60] - AI companion robots are anticipated to become a key segment by 2025, leveraging technologies for effective emotional recognition and interaction [62] - The integration of smart health management and personalized nutrition plans is expected to drive further growth in the pet tech market [64][67]

Core Insights - Embodied intelligence has gained significant traction globally, with Figure achieving a valuation of $39 billion despite zero revenue, while domestic players are securing commercial orders and projecting substantial revenue growth [1][4] - The Chinese market is integrating embodied intelligence into its strategic development plans, indicating a shift towards a trillion-dollar market potential [1][9] Definition and Understanding - Embodied intelligence is recognized as a crucial development in artificial intelligence, characterized by agents that interact with their environment through a physical body, showcasing autonomy and adaptability [2] - It represents a convergence of machine learning, computer vision, and robotics, marking a significant step towards practical AI applications [2] Commercial Scene Classification - Different forms of embodied intelligent robots are evolving to meet diverse needs across retail, dining, manufacturing, logistics, education, and healthcare [4] - Commercial applications focus on enhancing service experiences in dynamic environments, while industrial applications emphasize precision and stability in structured settings [4] Strategic Significance - Embodied intelligence is pivotal in narrowing the technological gap between China and the U.S., driving innovation across various sectors including manufacturing and healthcare [6] - The competition in advanced technology between the two nations highlights the importance of breakthroughs in embodied intelligence for economic and competitive advantages [6] Policy Incentives - The Chinese government is actively promoting the development of embodied intelligence through various policies, funding, and standardization efforts [9] - Local governments are also implementing initiatives to support industry growth, including funding for humanoid robots and establishing collaborative platforms [9] Development Stages - The evolution of embodied intelligence can be categorized into three phases: conceptual development (1950s), technological accumulation (2000-2020), and application expansion driven by large models (2020 onwards) [11] - The current phase sees the U.S. leveraging its advantages in computational power and capital, while China accelerates its catch-up through policy support and industry collaboration [11] Bottlenecks and Challenges - The transition from experimental to commercial applications faces challenges such as data scarcity, high costs, and technical limitations in dexterity and generalization [13][16] - The industry is exploring solutions to overcome these challenges, including the establishment of data collection training grounds and innovative data acquisition methods [19] Model Evolution - The VLA model is emerging as a consensus for the development of embodied intelligence, integrating reasoning capabilities with real-world perception and action [21] - This evolution is expected to lead to a significant leap in capabilities, akin to the breakthroughs seen with large language models [21] Commercialization Breakthroughs - The path to large-scale commercialization of embodied intelligence hinges on advancements in five key dimensions: endurance, latency, execution, reliability, and economic viability [29] - Initial applications are focusing on low-complexity, high-ROI scenarios, with future expansions into more complex environments as technology matures [31] Global Market Predictions - The global market for embodied intelligence is projected to reach 19.2 billion RMB by 2025, with a compound annual growth rate of 73% over the next five years [46] - China's market is expected to experience significant growth, potentially exceeding 280 billion RMB by 2035, driven by a robust industrial ecosystem [50] Competitive Landscape - The competition in the embodied intelligence sector is characterized by three main players: AI-native challengers like Figure, traditional industrial players like ABB, and cross-industry giants like Tesla [55] - The market is anticipated to undergo consolidation as product homogeneity increases, leading to a potential first wave of industry shakeout [57] Initial Player Strategies - Startups in the sector must leverage their agility and innovation capabilities to survive against established giants, focusing on strategic partnerships and long-term value creation [59]

Group 1 - Chinese commercial aerospace companies are actively expanding into overseas markets, utilizing "rideshare launch" models to reduce costs and attract international clients from countries like Egypt, Nepal, and the UAE. The domestic launch cost has decreased to 50,000-60,000 yuan per kilogram, but still lags behind SpaceX, which has a competitive edge due to its high-frequency launches and Starlink project [3][4]. - The home appliance and light manufacturing industries are expected to face pressure on both domestic and foreign sales in 2026, with a potential recovery in overseas sales in the latter half of the year. Emerging markets are anticipated to show stronger demand compared to developed markets, particularly in Latin America and Southeast Asia [5]. - China's automotive exports are projected to reach 5.859 million units in 2024, maintaining the top position globally, with a shift from vehicle exports to a more comprehensive output of technology, brand, and supply chain solutions. This transition reflects a move from "selling products" to "building brands" [6][7]. Group 2 - The development of autonomous driving technology in China is being propelled by high-quality growth initiatives and strategic policies, with companies like Baidu Apollo enhancing safety standards and promoting technology exports. The industry is evolving into a collaborative ecosystem that drives innovation and reliability [7][8]. - The Chinese潮玩 (trendy toy) industry is rapidly globalizing, with brands like Pop Mart and 52TOYS successfully entering overseas markets through localized strategies and partnerships. The market share of Chinese潮玩 in the overseas market is projected to grow from 3% in 2020 to 18% by 2025 [9]. - Chinese companies are increasingly investing in the European market, particularly in renewable energy and high-tech sectors, while facing challenges such as national security reviews and compliance issues. Differentiated strategies and localized investments are essential for success [10]. Group 3 - Amazon's global store initiative aims to cultivate 200 cross-border brands in Shandong over the next three years, focusing on AI-driven strategies and innovative measures to enhance logistics efficiency and support local sellers [11]. - The Chinese commercial vehicle sector is transitioning from product trade to a comprehensive service model, emphasizing lifecycle services and local adaptation. The export of Chinese commercial vehicles to the EU has seen a 42% year-on-year increase [18]. - The digital culture industry in China is experiencing rapid growth, with online games, films, and literature becoming key components of global cultural exchange. The industry is encouraged to enhance IP development and international collaboration to overcome cultural barriers [17].

Core Insights - The automotive industry is undergoing significant transformation, with domestic brands emerging as the primary growth engine, and new energy technologies reshaping value rules and pricing strategies [1][2][4] Group 1: Domestic Brand Growth - Domestic brands have become the sole growth driver in the automotive market, with sales increasing by 20.3% year-on-year, translating to a net increase of 1.855 million vehicles, contributing to a 9.2% overall market growth [2][4] - The share of domestic brands in the market has risen significantly, with their market share increasing from 90% to 97% in the under 100,000 yuan segment [8] Group 2: Pricing and Value Restructuring - The application of new energy technologies has led to a redefinition of pricing standards, where product value now supersedes brand symbolism [4][6] - The competition landscape is shifting towards price tier management, with a focus on cost reduction and efficiency becoming a new operational challenge [9][8] Group 3: Advertising and Marketing Trends - Overall advertising investment in the automotive industry has decreased compared to the previous year, with a notable contraction in the number of advertisers [12][14] - The luxury segment (vehicles priced above 300,000 yuan) accounted for 41.3% of advertising investment, while the mainstream market (10,000-200,000 yuan) represented 38.5% [17] Group 4: AI and User Engagement - Baidu's automotive ecosystem is leveraging AI to enhance user experience and marketing workflows, with a 5.3% increase in automotive search volume and a 34.4% rise in user reading volume [25][21] - AI is transforming the search engine into an AI engine, reshaping user interaction and content consumption patterns [37][39] Group 5: User Behavior and Decision-Making - The average decision-making period for users has shortened, with a 37.5% increase in the number of models compared during the search process [48][53] - Users are increasingly favoring content that provides strong comparative references and purchase recommendations, indicating a shift towards more informed decision-making [53][48]

Core Viewpoint - The trend of socialized employment is expanding, driven by macroeconomic fluctuations, labor shortages, and rising costs, particularly in manufacturing and retail sectors, which are the most receptive to this model [1][2][6]. Group 1: Concept and Environment - Socialized employment refers to various forms of employment outside standard labor relations, including outsourcing, labor dispatch, hourly pay, platform-based flexible employment, and shared employment [1][3]. - The macroeconomic environment is characterized by a decline in the working-age population, leading to dual pressures of labor shortages and rising costs for enterprises [1][16]. - The retail sector utilizes a mix of outsourcing, hourly pay, and platform-based flexible employment to adapt to sales fluctuations and market demands, with high employee turnover being a core pain point [1][29]. Group 2: Trends and Policy - The scale of socialized employment continues to grow, with supportive policies expected to improve further [2][9]. - Socialized employment is becoming a standard for enterprises, with human resource service providers upgrading towards specialization and digitalization [2][9]. - The relationship between individuals and organizations is shifting from dependency to symbiosis, requiring a more diverse skill set from individuals [2]. Group 3: Macro Environment - The digital economy is projected to reach 63.2 trillion yuan by 2024, accounting for 46.8% of GDP, driving high-quality economic development and transforming the employment market [6]. - National policies have been introduced to encourage the development of socialized employment, pushing enterprises to balance efficiency and risk management [9]. Group 4: Industry Penetration - As of 2024, over 240 million flexible employment individuals exist in China, with socialized employment penetrating various industries deeply and qualitatively [19]. - Business outsourcing has a penetration rate exceeding 50%, while labor dispatch accounts for 20%-30%, and platform-based employment is below 20%, indicating a diverse employment landscape [19]. Group 5: Micro Environment - External competition and internal management demands are driving enterprises to adopt socialized employment strategies, allowing for agile organizational structures and flexible cost control [23]. - Socialized employment effectively balances the need for cost efficiency in enterprises with the personal development needs of workers [26]. Group 6: Sector-Specific Characteristics - In the retail sector, socialized employment is characterized by high employee turnover, with rates exceeding 30% for frontline positions, leading to management challenges [37]. - Manufacturing enterprises prefer socialized employment for its flexibility in adjusting workforce size in response to production capacity fluctuations, with outsourcing becoming more common [44][49]. Group 7: Emerging Job Demands - The rise of AI and instant retail is creating new job roles in digital operations and intelligent supply chains, necessitating a workforce skilled in both traditional and emerging technologies [40][54]. - Socialized employment in manufacturing is increasingly requiring cross-disciplinary and composite talents to adapt to technological advancements [54].