A digital transformation and consumption patterns of the “New older adults” in China: a systematic review of technological adaptation and learning mechanisms.

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Learn more: PMC Disclaimer | PMC Copyright Notice Front Public Health . 2026 Mar 30;13:1717508. doi: 10.3389/fpubh.2025.1717508 Search in PMC Search in PubMed View in NLM Catalog Add to search A digital transformation and consumption patterns of the “New older adults” in China: a systematic review of technological adaptation and learning mechanisms Baowen Shao Baowen Shao 1 Shandong Huayu University of Technology, Dezhou, China 2 Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing Find articles by Baowen Shao 1, 2 , Muhammad Inshal Muhammad Inshal 3 Indus Hospital & Health Network, Karachi, Pakistan Conceptualization, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing Find articles by Muhammad Inshal 3 , Mirza Amin ul Haq Mirza Amin ul Haq 4 Ziauddin University, Karachi, Pakistan 5 UCSI University, Cheras, Malaysia Conceptualization, Formal analysis, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing Find articles by Mirza Amin ul Haq 4, 5 , Syed Taha Syed Taha 6 University Canada West, Vancouver, BC, Canada Conceptualization, Data curation, Investigation, Visualization, Writing – original draft, Writing – review & editing Find articles by Syed Taha 6 , Najmonnisa Khan Najmonnisa Khan 7 SZABIST University Pakistan, Karachi, Pakistan Resources, Software, Visualization, Writing – original draft, Writing – review & editing Find articles by Najmonnisa Khan 7 , Jing Wang Jing Wang 8 School of Culture and Communication, Putian University, Putian, China Data curation, Methodology, Resources, Validation, Visualization, Writing – review & editing Find articles by Jing Wang 8, * Author information Article notes Copyright and License information 1 Shandong Huayu University of Technology, Dezhou, China 2 Universiti Pendidikan Sultan Idris, Tanjong Malim, Malaysia 3 Indus Hospital & Health Network, Karachi, Pakistan 4 Ziauddin University, Karachi, Pakistan 5 UCSI University, Cheras, Malaysia 6 University Canada West, Vancouver, BC, Canada 7 SZABIST University Pakistan, Karachi, Pakistan 8 School of Culture and Communication, Putian University, Putian, China * Correspondence: Jing Wang, [email protected] Roles Baowen Shao : Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing Muhammad Inshal : Conceptualization, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing Mirza Amin ul Haq : Conceptualization, Formal analysis, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing Syed Taha : Conceptualization, Data curation, Investigation, Visualization, Writing – original draft, Writing – review & editing Najmonnisa Khan : Resources, Software, Visualization, Writing – original draft, Writing – review & editing Jing Wang : Data curation, Methodology, Resources, Validation, Visualization, Writing – review & editing Received 2025 Oct 4; Revised 2025 Dec 2; Accepted 2025 Dec 15; Collection date 2025. Copyright © 2026 Shao, Inshal, Haq, Taha, Khan and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. PMC Copyright notice PMCID: PMC13070757  PMID: 41983104 Abstract China is experiencing a profound demographic shift which is mainly marked by rapid population aging. This systematic review explores the key domains, market segments, and technological innovations targeting China’s new older adults population, employing thematic analysis to synthesize findings from diverse studies. The review identifies multifaceted market segmentation approaches, including demographic, geographic, psychographic, health, and economic channels, which highlights the heterogeneity of older adults consumers. Technological advancements span health and wellness, living environment safety, social inclusion, data infrastructure, and support services, providing benefits such as enhanced health monitoring, independent living, social connectivity, and resource optimization. But current research is constrained by narrow geographic coverage, limited representation of non-digital users, and reliance on theoretical or macro-level analyses, restricting understanding of real-world adoption and long-term outcomes, and future strategies should focus on user-centered technology design, differentiated market segmentation, inclusive digital literacy initiatives, and integrated, AI-enabled service delivery. Also, robust, multi-sector longitudinal studies are needed to evaluate adoption, effectiveness, and scalability of interventions, and this review provides actionable insights for policymakers, industry, and researchers to develop inclusive, efficient, and sustainable support systems for China’s diverse and evolving older adults population. Keywords: new older adults, aging population, China, technology, market segmentation 1. Introduction China is experiencing a profound demographic shift marked by rapid population aging, in 1999, the country officially entered an aging society, in 2021 entered in an aged society, with the proportion of people aged 60 and above reaching 13.5% in 2020 and projected to rise to nearly 30% by 2050, with similar trends in rural areas ( 1 ). This demographic transformation is occurring at a much faster pace than in developed countries, i.e., China’s older adults share grew from 10 to 20% in just 25 years, compared to 115 years in France and 85 years in Sweden ( 2 ). A distinctive subgroup within this aging population, often termed the “New older adults,” remains relatively active, open to new experiences, and eager to engage socially, with specific demands for personalized and diversified products that meet both practical and emotional needs ( 3 , 4 ), and this burgeoning demographic represents a powerful new market for industries and policymakers aiming to address their unique needs. As China transitions into a moderately aging society. The older adults population continues to rise significantly, and there is a multifaceted opportunity to explore domains and market segments targeting the New older adults, ranging from healthcare and smart homes to leisure and social participation ( 5 , 61 ), and this demographic is characterized by active engagement and evolving consumption patterns, creating diverse market demands ( 3 , 4 , 61 ). With rapid advancements in technology, the role of innovation in serving China’s older adults population has gained prominence. Key technological developments are emerging to address challenges faced by the older adults. These developments include health monitoring devices, eldercare robots, smart home systems, and telemedicine platforms ( 6 , 7 ), which are not only improving the quality of life for older adults individuals by enhancing safety and independence but are also reshaping the ways industries engage with this demographic ( 6 ). In other words, the focus is shifting from basic older adults care to quality senior living via technology and scenario integration, which supports personalized and precise eldercare solutions ( 6 ). There are 60,000 types of older adults products available globally, but China accounts for about 2,000 types of older adults products, highlighting a significant gap in supply tailored to the needs of the older adults ( 8 ). In terms of benefits, beyond convenience, these innovations indeed contribute to improved health outcomes, reduced caregiver burden, enhanced social connectivity, and greater autonomy for seniors ( 9 ). The benefits extend to broader societal gains, such as alleviating pressures on healthcare systems and fostering a more inclusive silver economy ( 10 ). Therefore, identifying the core technological domains and understanding their characteristics is crucial for developing comprehensive strategies to meet the evolving needs of the New older adults, along with assessing the benefits of these technological advancements, is essential to appreciating their impact on the older adults population in China. The purpose of the current systematic literature review is to address existing critical gaps in the current literature by exploring key technological innovations, their key characteristics and benefits, and the market domains they serve through the three key research questions, i.e., What are the key domains and market segments used to target the new older adults market in China? What are the key technological innovations by key domains to serve the new older adults market in China, and what are their core characteristics? What are the key benefits of these technological innovations for China’s new older adults population? Moreover, the research also aims to provide valuable insights by synthesizing the carefully selected studies for businesses, market investors, technology and product developers, elder care institutions, policymakers, and government targeting or serving the Chinese older adults market. The contributions of this paper are as follows: Section 2 of the study deals with the background of the new older adults in China and technological innovations in this context, their key characteristics and benefits. Section 3 of this study deals with research methodology, which includes research questions, search string, screening criteria, study selection process illustrated via PRISMA flowchart, quality assessment (QA) criteria, method for data extraction, keywording-guided screening for full-text analysis, and classification themes. In Section 4, the research results are demonstrated by synthesizing the selected papers and presenting them in the form of tables. In the end, in Sections 5 and 6, a summary of findings and the conclusion of the study are presented. 2. Background The demographic landscape of China has been profoundly shaped by its population policies and rapid economic development. For example, following decades of population control measures such as the one-child policy, which was implemented in 1979 and relaxed in recent years, China faces the unprecedented challenge of a rapidly aging population ( 11 , 63 ) and resulting many seniors having only one child to rely on, contributing to sharp rise in caregiving dependency ratio ( 12 ). The demographic structure is shifting dramatically, with projections indicating the population aged 60 and above will reach approximately 40% by 2050 ( 13 ). In 2023, the population aged 60 and above reached nearly 297 million ( 14 ), and by 2025, it is estimated to reach more than 300 million ( 15 ). This shift creates substantial economic and social pressures, including a shrinking labor force and rising demands for health and social care, constraining economic growth and increasing financial burdens ( 9 , 16 ). Simultaneously, this demographic transition has catalyzed the emergence of the “silver economy.” It covers the economic activities and productivity, catering the needs or requirements of older persons and sectors serving aging population ( 17 ). The New older adults in China differ markedly from prior generations, exhibiting higher education levels, urban residency, and significant engagement with digital technologies, enabling a more active and demanding consumer group ( 3 , 4 ), and the concept of the “new older adults” aligns with Neugarten's ( 18 ) “young-old” and embodies what Laslett ( 19 ) termed the “Third Age,” which is a life stage characterized not by decline but by personal fulfillment, though still shaped by existing social divisions like class and gender ( 20 ). This has led to diverse market segments spanning healthcare, smart housing, mobility, leisure, and financial services, triggered by the changing consumption patterns and lifestyle preferences of the older adults ( 15 , 21 ). Also, the senior economy of China is about 7 trillion yuan (6% of GDP) in 2024, and it is projected to reach 30 trillion yuan (10% of GDP) by 2035 ( 21 ). Despite the growing interest, its scope remains fragmented, and not limited to just healthcare, but spanning housing, transport, wellness, and technology ( 62 ), yet lacking clear boundaries or systematic segmentation that underscores the need for systematic clarification. Technological innovation plays a pivotal role in meeting the complex needs of this population. Eldercare robots, wearable health devices, telehealth, and smart home technologies represent key innovations with core characteristics such as enhancing health monitoring, promoting safety and independence, facilitating social connectivity, and alleviating caregiver burdens ( 22 , 23 ). However, scholarly understanding of these technologies’ deployment, characteristics, and uptake in China’s unique socio-economic context is fragmented across various domains. Moreover, evidence about the tangible benefits these innovations provide to the New older adults, such as, social and health-related economic, remains scattered ( 7 , 24 ), necessitating a comprehensive synthesis. Given these significant knowledge gaps, this systematic literature review seeks to identify and clarify the key domains and market segments that target China’s New older adults population firstly, then synthesize evidence on technological innovations within these domains and their defining characteristics, lastly to evaluate the documented benefits arising from these technologies for the older adults population. This inquiry aims to provide clarity and actionable insights to researchers, policymakers, and practitioners engaged in China’s silver economy, supporting more targeted interventions and innovations. 3. Research methodology The current systematic literature review follows a review protocol, and it is illustrated in Figure 1 , which outlines the methods for minimizing any potential biases in the study. Figure 1. Open in a new tab Research protocol. The research questions of this systematic literature review, as in Section 3.2, are derived from the study’s objectives in Section 3.1, and the search strategy is formed through pilot searches to obtain a refined search string in Section 3.3, and in order to identify papers in the relevant category. Then, in order to screen the relevant papers, screening criteria are established in Section 3.4. Section 3.5 deals with the study selection process using the PRISMA flowchart, and in Section 3.6, quality assessment (QA) criteria for included studies are discussed. Section 3.7 deals with a data extraction strategy related to collecting data from included studies is formulated. Furthermore, Sections 3.8 and 3.9 deal with keywording-guided screening for full-text analysis and classification schemes. Finally, forms are created to extract data and present synthesized results in the analysis section. 3.1. Research objectives RO1 : To identify the key domains and market segments used to target the new older adults market strategically in China. RO2 : To identify the key technological innovation domains targeting the new older adults market in China and recognize their core characteristics. RO3 : To identify the key technological innovation domains targeting the new older adults market in China and their benefits. 3.2. Research questions What are the key domains and market segments used to target the new older adults market in China? What are the key technological innovations by key domains to serve the new older adults market in China, and what are their core characteristics? What are the key benefits of these technological innovations for China’s new older adults population? 3.3. Search strings In order to gather relevant studies from a large pool of search results, the selection criteria must meet the objectives of the systematic review. A former study has suggested that a high recall search strategy has the potential to lead to false positives; on the other hand, a precise strategy narrows down the search results ( 25 ). At first, in the pilot phase, search strings were created by using Boolean operators, such as “AND” to narrow search results (i.e., all mandatory terms in the search result) and “OR” to broaden results (i.e., in the search result, any term is acceptable). Also, search modifier, such as “intitle:,” was used to improve search sensitivity while sustaining precision. For search query design, the 256-character limits in the search engine of Google Scholar were considered ( 26 ). Since it is central for optimal results to design search strings with the right keywords ( 25 ). Therefore, to identify appropriate search strings on Google Scholar and Scopus, search strings with the maximum relevant keywords were tested. The final refined search queries obtained are demonstrated in Table 1 . Table 1. Search string (technological innovations for the China’s new older adults market). Source Search string Context Google Scholar “New older adults” AND (intitle:"China” OR intitle:"chinese”) AND (“Technology” OR “Digital”) AND (“Adoption” OR “Learning”) Technology for the new older adults generation in China Scopus TITLE-ABS-KEY (new older adults) AND TITLE-ABS-KEY (China) OR TITLE-ABS-KEY (Chinese) AND TITLE-ABS-KEY (technology) OR TITLE-ABS-KEY (digital) AND TITLE-ABS-KEY (adopting) OR TITLE-ABS-KEY (learning) Open in a new tab The Google search in Table 1 was performed on September 1, 2025, and no publication date restrictions were applied to the timeline. Also, Scopus search was performed on November 11, 2025. 3.4. Screening of relevant papers Not all the studies in the search results returned precise relevance to the research questions of this systematic review, therefore, systematic assessment for actual relevance was performed. Accordingly, the search process for the screening of the relevant studies defined by Dybå and Dingsøyr ( 27 ) was used, and during the first screening phase, studies were selected based on their titles, and studies unrelated to the research area were omitted, such as articles relevant to China’s new older adults in other contexts, with different meanings than those applied in the technological context, and such papers were reasoned entirely out of scope for the systematic review and were excluded. The second screening phase involves the reading of the abstract of each selected study in the first screening phase, and the inclusion and exclusion criteria were also applied. The following four types of studies were excluded: Studies with no relevance to the search string used. Studies not available in the English language. Studies with non-availability of full text. Studies released outside of conferences, journals, technical reports, patents, and academic theses/dissertations. Studies, in the end, were selected based on the above exclusion criteria. 3.5. Study selection process In this systematic review for the selection of eligible studies, focusing on China’s new older adults market in the context of technological innovations, the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) flowchart has been used. Initial electronic searches from Google Scholar and Scopus gave a total of 91 records, of which 10 were non-existent records (n = 10) and 2 were duplicated studies. After this exclusion, a set of 79 studies was available for screening, and after screening, 33 studies were further excluded because of irrelevant titles, keywords, and abstracts. From the remaining 46 studies, 15 studies were eliminated further because of full-text unavailability and eligibility criteria. At the end of this process, a set of 31 studies was included in the qualitative synthesis, and the outcomes of the search and selection process are demonstrated in Figure 2 via the PRISMA flowchart. Figure 2. Open in a new tab PRISMA flowchart for technological innovations for the China’s new older adults market. 3.6. Quality assessment A common practice in Systematic Literature Review (SLR) is to conduct quality assessment (QA) in order to appraise the selected papers for their reliability ( 28 ). In this SLR, a quality assessment tool was adapted, which was employed in previous mapping studies ( 28 , 29 ) to evaluate the quality of the selected studies. The following dimensions were covered by this quality assessment tool: (a) Topic Relevance: Does the selected study discuss the new older adults or other older adults population in China and the characteristics, needs, or preferences of this population group? Yes (+1) or No (0). (b) Context-Fit: Does the study focus on technological innovations for the older adults population in China, including their characteristics or benefits? Yes (+1), Partially (0.5), or No (0). (c) Citation Count: Had the published study been cited by other articles? If the citation count was 1 to 5, it was considered as “Partially (0).” If it had not been cited by any author, it was considered as No (−1). If the citation count was more than five, it was considered as “Yes (+1).” (d) JCR Ranking: What’s the published study’s source? For that, the following Journal Citation Reports (JCR) lists will be taken into consideration while evaluating this (see Table 2 ). Table 2. Quality criteria. Sources Ranking Score Journal Q1 2 Q2 1.5 Q3 1 Q4 1 Study with no JCR ranking 0 Open in a new tab JCR, Journal Citation Reports. Each selected study for this review is assigned a score for each question of quality assessment tool, and a cumulative score for each study ranges from −1 to 5. 3.7. Data extraction method The potential responses to the defined research questions of this systematic review can be obtained by using the following data extraction strategy: RQ1 : The answer to this research question is given by identifying the key domains and market segments used to target the new older adults market strategically in China. RQ2 : The answer to this research question is given by identifying the key technological innovation domains targeting the new older adults market in China and their core characteristics. RQ3 : The answer to this research question is given by identifying the key technological innovation domains targeting the new older adults market in China and their benefits. 3.8. Keywording-guided screening Petersen et al. ( 64 ) used an approach to identify relevant studies by analyzing abstracts with specific keywords. This approach has two stages, i.e., to observe the abstracts first to find the main ideas and keywords that show what the studies were about. In second stage, investigation was done deeper into these keywords to not only understand them better in the context of the research questions but also to organize the reviews in an effective manner by grouping and categorizing the keywords. Further, it was recommended to explore the introduction or conclusion sections in case of a poor-quality abstract ( 64 ). In the case of this systematic review, the full text was analyzed for robust classification themes. 3.9. Classification themes The methodology was adapted from Petersen et al. ( 64 ) for the classification themes of the domain-specific segmentation of China’s new older adults market, technological innovations targeting this market, their key characteristics and benefits as presented below in Tables 3 – 5 . Table 3. Classification themes: segmentation of China’s new older adults market. Research question Classification Themes Sub-themes Sub-sub-themes RQ1 “New older adults” market segmentation Demographic segmentation Age and life stage Individuals born in the 1960s Middle-aged adults Older adults Seniors (50/55+) Older adults (with limitations) Occupation State agency heads Farmers/workers Enterprise employees Private owners Freelancers Income level Income level and purchasing power Low-income Lower-middle-income Middle-income Higher-middle-income High-income Population density Targeting high-density older adults populations Education level Senior universities Different education level Socioeconomic status Lower economic advantage Lower education attainment Special needs groups (disabled and poor older adults, older adults living alone) Geographic segmentation Urban vs. rural Development level Resource access & needs Rural middle-aged/older adults vs. urban older adults Targeting to bridge the urban–rural consumption gap Regional development Economic development level Less-developed vs. commercial cores Remote areas, ethnic areas, backward areas Central urban districts vs. newly developed urban areas Urban core vs. township areas Location type Urban residents vs. Rural residents Urban centers vs. Remote suburbs County-level areas Urban–rural integration zones Accessibility Seniors within a 5 to 15-min walkable life circles Areas with medical service gaps Psychographic segmentation Attitudes and motivation Strong desire for self-improvement and social interaction High intrinsic motivation Forward-looking and self-developing Individuals seeking independence Individuals seeking reduced dependency Constructive user of leisure time, entertainment, and social connection Individuals seeking to improve proficiency Preference for comfort and safety Lifestyle and values Prioritizing travel and connectedness with family/friends Value comfort, convenience and safety Seeking a diversified life choice Individuals interested in lifelong learning Supports “active aging” Self-realization Dignity Mindset Individuals seeking escapism Individuals seeking self-cognition Outlook Attitude toward new things Behavioral segmentation Product usage Preference for “Older adults Mode” apps Preference for family version apps Traditional booking methods (travel agencies/ telephone) Technology adoption and usage Digital literacy Digital self-efficacy Struggling to keep pace Smartphone ownership Travel and consumption Preference for off-season travel Price sensitivity and value-seeking behavior Travel with family/neighbors/friends. Usage preferences Preference for investments and social networking Engagement Users seeking mental health knowledge Users of online courses Users of cognitive tools Users of digital cultural products (online chess, drama, cloud social networking) Users of digital platforms for transactions and financing Engagement frequency Learning frequency Learning motivation Purchasing behavior Budget-consciousness Health and dependency segmentation Health status Disabled older adults (moderate, mild, severe) Disabled and Semi-disabled older adults Dementia older adults Older adults with chronic diseases Older adults with “Sub-healthy” conditions Older adults with disabilities cognitive/physical Individuals needing rehabilitative benefits Cognitive/physical ability Decline in learning skills, visual acuity, memory Mobility limitations Need for medical support and barrier-free facilities Care needs Rehabilitation care Hospice care Post-illness rehabilitation Daily nursing care Dependency level Individuals requiring long-term care Need for integrated medical & pension services Service and product benefit segmentation Service type Smart eldercare Tourism eldercare Medical care integration Daily care Spiritual comfort Parks & fitness centers TCM services Home-based care Emergency, standard and scheduled services Older adults facilities Community dining Corporate catering Technology integration Need for IoT, AI, big data and cloud computing Remote monitoring Telemedicine Wearable devices Experience sought Immersive experiences Leisure and entertainment Learning opportunities Cultural activities Functional need Health products Intelligent health management Mental health knowledge Rehabilitative benefits Intelligent life care Interface simplicity simplified processes Applying XR to improve quality of life Historical and cultural tourism Natural landscape tourism Spiritual, cultural, and material life needs Care model Home-based care Institutional care Community and ecological care Economic and channel segmentation Funding and payment method Long-term care insurance Self-pay Commercial insurance Membership-based model Government-run vs. social-run Collaborative models Partnerships for point accumulation with banks, insurers and merchants Living arrangement Home-based Community-based Institutional Economic capacity Cost-conscious solutions for “working families” High-end, vacation-style retirement models. Channel preference Digital channels for transactions, financing, and social connection Traditional channels like travel agencies, telephone, in-store bookings Family-linked channels for payment assistance Enterprise scale Small business Medium-sized enterprise Large enterprises; Leading enterprises Open in a new tab Table 5. Classification theme: technological innovations targeting the “New older adults” market in China and their benefits. Research question Classification Themes Sub-themes Sub-sub-themes RQ3 Key benefits of technological innovations for China’s older adults market Health and wellness technologies Smart health monitoring and wearable devices Improved safety Independent living Reduced hospitalization Real-time alerts Health tracking Intelligent health monitoring and management systems Dynamic health information Improved quality of life, physical, and mental health. Immediate assistance (e.g., fall detection). Comprehensive health monitoring. Allows ageing in place Enables professional care at home. Reduces hospitalizations and readmission rates through early detection. Enables self-monitoring and management of chronic diseases AI-powered safety and behavior recognition systems Timely detection of abnormal situations (e.g., falls). Enhanced safety and security in everyday life. Aims to ensure the safety of the older adults living alone. High accuracy and speed in recognition. Improved service quality in older adults care. Telemedicine and remote consultation Systems Accessible healthcare Remote diagnosis Accommodates rural service imbalances Reduces travel and cost Intelligent delivery and nutrition management systems Enhanced convenience Better dietary matching Improved nutrition Supports sustainable operation Living environment and safety technologies Smart home and IoT-based care systems Real-time monitoring Risk prevention Improved service quality Remote supervision Enhances independent living AI-driven predictive safety and resource allocation Early warning of resource shortages Optimized resource allocation Supports operational planning Assistive robotics for daily living Assist with activities of daily living Improve gait function Promote independence and convenience Maintain social connections Improve spiritual life Promotes independence Social inclusion & empowerment technologies Mobile and digital learning platforms Continuous self-education Integration into society Social inclusion Sense of accomplishment Digital finance and e-commerce integration Accessible & efficient financial services Easier saving & investing, profitable options Brings convenience Reduces depression by narrowing the urban–rural living standards gap Provides convenience Reduced property security risk Enabling online shopping despite a lack of digital payment confidence Social connection & communication platforms Provides “remote companionship” Reduces loneliness Maintains social connections Improves cognitive ability Offers access to mental health knowledge Online education & lifelong learning platforms Provided access to high-quality educational resources Maintained lifelong learning from home Increases income Enhances sense of career accomplishment Enabled flexible Enabled self-arranged learning time and content Creates new opportunities for the sustainable development of older adults education Helps the older adults learn new knowledge, master new technologies, and integrate into society Provided access to high-quality educational resources Extended reality (XR) & immersive technologies Intuitive and low learning curve Enhanced quality of life Promotes independence and social connection Reduced learning difficulty Reduced risk of musculoskeletal disorders Helps deepen the learning and application of digital cultural products Video communication & social connection systems Remote family connection Emergency detection Mental support Easy access to communication Data infrastructure & platform management Centralized data & information management platforms Better care coordination Accessible anywhere Improves resource matching Enables integrated service delivery Service matching & digital marketplaces Reduces transaction costs Improves purchasing ability Facilitates comparison & selection of services GIS & data-driven spatial planning Objective site selection for care facilities Improved spatial equity Enhanced accessibility Data-driven analytics & smart service integration Analyzes spatial characteristics Predicts optimal sites for older adults care facilities Assesses walkability Precise marketing and personalized travel packages Improved efficiency & quality for industrial chain optimization Optimal resource allocation to efficiently connect caregivers with the older adults Aims to enhance basic healthcare provision in underserved rural areas User-centered & aging-adapted interaction design Accommodates the older adults’s physical and psychological state Natural, easy-to-use, and humanized product interfaces Makes the technology easier to adopt Minimizes physical strain from repetitive use Makes products more suitable for the older adults Support & operational technologies Digital promotion & self-media platforms Increases public awareness Promotes culture & services Boosts engagement Privacy-preserving computing Protects data privacy Foundational digital access infrastructure Provides the foundational access that enables all other digital services Reduces the “digital divide” Improved convenience for the older adults to enter the online world Enhanced usability and reduced complexity Improved learnability and confidence Open in a new tab Table 4. Classification theme: technological innovations targeting the new older adults market in China and their core characteristics. Research question Classification Themes Sub-themes Sub-sub-themes RQ2 Characteristics of technological innovations for China’s older adults market Health and wellness technologies Smart health monitoring and wearable devices Real-time health monitoring User-friendly design Continuous data collection Integration with platforms and third-party devices Intelligent health monitoring & management systems Smart wearable devices Multi-sensor data platforms (ECG, pulse oximeter, EMG) Remote homecare systems AI-powered safety and behavior recognition systems Deep learning-based fall detection (CNNs, transfer learning) Behavior recognition technology (using RGB cameras) Telemedicine and remote consultation systems Video consultations Rapid telephone consultation Chronic disease management Internet medical resources Intelligent delivery and nutrition management systems Smart meal systems Online ordering Nutrition assessment Delivery dispatch Multimodal kitchen-terminal tech Living environment and safety technologies Smart home and IoT-based care systems Sensors Monitoring devices Voice recognition Motion capture Integrates hardware and software AI-driven predictive safety and resource allocation Predictive modeling Spatio-temporal data fusion Dynamic thresholding Graded early warning Assistive robotics for daily living Physical assistance robots Social robots Feeding Assistive Robotics (using HCI) Social inclusion and empowerment technologies Mobile and digital learning platforms Systematic learning content Easy-to-use interface Intuitive UI Voice navigation Features for emotional assurance Digital finance and e-commerce integration Mobile payment Low cost Credibility Digital virtual currency/points Integration with e-commerce and real estate Digital platforms & smart logistics Mobile payment systems (Alipay, WeChat Pay) Payment security features & family account integration Social connection and communication platforms Social communication platforms Use of cell phones, tablets, and communication software Online education and lifelong learning platforms E-learning platforms for older adults Platforms for skills and education Digital devices for learning (TVs, mobile phones) New Media & Multimedia Applications Extended reality (XR) and immersive technologies Gesture Interaction Optimized Gesture Set for the older adults Immersive Learning Environments Video communication and social connection systems Audio-video monitoring Mobile app integration Simplified UI Data infrastructure and platform management Centralized data and information management platforms Cloud-based centralized databases Health data platform Four-level linkage mechanism (city, district, street, community) Role-based access control Service matching and digital marketplaces Digital platforms Online booking Feedback mechanisms GIS and data-driven spatial planning High-resolution spatial data (POI) GIS integration Predictive site selection Data-driven analytics and smart service integration Geospatial modeling and semantic segmentation AI algorithms for tourism (machine learning, NLP) Constrained Clustering Algorithms Care Greeting Network & Matching Model Integrated “micro-clinic + smart pharmacy” networks User-centered and aging-adapted interaction design User-Centered Design Intuitive Human-Computer Interaction High cognitive compatibility & low physiological load Adapted product presentation (fonts, colors) Support and operational technologies Digital promotion and self-media platforms Use of graphics and short videos for promotion Privacy-preserving computing Federated learning Foundational digital access infrastructure Basic connectivity networks Age-suitable terminal products Simplified software interfaces (“Older adults Mode”) Guided tutorials Open in a new tab 4. Analysis In this analysis section, the results associated with the research questions of this review are discussed, and after careful selection of the research studies via the screening process, the responses to each research question have been utilized to provide answers. This section has four main sub-sections: the first sub-section deals with RQ1, which explores the domain-specific segmentation of China’s new older adults market, the second sub-section addresses RQ2 and deals with technological innovations targeting this market, their key characteristics, and the third sub-section addresses RQ3 and deals with the benefits of technological innovations. In the end, the fifth sub-section is about the overall quality assessment score. 4.1. Key domains and market segments targeting China’s new older adults market The adapted method for the classification themes ( 64 ) is applied to 31 extracted articles through the PRISMA method for the identification of key domains and market segments targeting China’s new older adults market, as indicated in Table 6 . Table 6. Classification: domain-specific segmentation of China’s new older adults market. Domain-specific segmentation of China’s new older adults market RQ1 References Domain Demographic segmentation Geographic segmentation Psychographic segmentation Behavioral segmentation Health & dependency segmentation Service & product benefit segmentation Economic & channel segmentation Shao et al. ( 30 ) Older adults Education Technology (EdTech) Age & Generation: Individuals born in the 1960s Education Level: Different Education Level Attitudes & Motivation: Strong desire for self-improvement & social interaction; High intrinsic motivation; Forward-looking and self-developing Outlook: Attitude toward new things Technology Adoption & Usage: Digital literacy; Digital self-efficacy Engagement Frequency: Learning motivation; Learning frequency He et al. ( 36 ) Older adults care services (ECS) Urban vs. Rural: Resource access & needs Service Type: Smart eldercare; Tourism eldercare; Medical care integration Funding & Payment Method: Government-run vs. social-run Shao et al. ( 51 ) Older adults care resource allocation Education Level: Senior Universities Experience Sought: Cultural activities; Learning opportunities Yan ( 37 ) Home older adults care industry Care Needs: Post-illness rehabilitation; Daily nursing care Dependency Level: Need for integrated medical & pension services Service Type: Home-based care Technology Integration Funding & Payment Method: Government-run vs. social-run; Membership-based model Living Arrangement: Home-based; Institutional Zhou and Ye ( 38 ) Digital Inclusive Finance (FinTech) Regional Development: Less-Developed vs. Commercial Cores Technology Adoption & Usage: Struggling to keep pace; Smartphone ownership Usage Preferences: Preference for investments & social networking Wang et al. ( 59 ) Urban Planning Service Type: Parks & fitness centers Sun ( 41 ) Property-based older adults Care Population Density: Targeting high-density older adults populations Location Type: Urban–rural integration zones; County-level areas; Urban centers vs. remote suburbs Service Type: Emergency, standard & scheduled services Yingjie and Huayao ( 42 ) Senior Tourism Industry Lifestyle & Values: Prioritizing travel & connectedness with family/friends; Value comfort, convenience & safety; Seeking a diversified life choice Purchasing Behavior: Budget-consciousness Service Type: TCM services Experience Sought: Immersive experiences; Leisure & entertainment Yichen ( 46 ) Smart Home Care (SHC) Technology Care Needs: Daily nursing care; Rehabilitation care Service Type: Daily care; Rehabilitation; Spiritual comfort Technology Integration: Need for IoT, AI, big data & cloud computing; Remote monitoring; Telemedicine; Wearables Funding & Payment Method: Long-term care insurance; Self-pay; Commercial insurance Living Arrangement: Home-based; Community-based; Institutional Akmal et al. ( 31 ) Older adults Welfare Cottage Industry Income Level: Lower income Urban vs. Rural: Development level; Resource access & needs Location Type: Urban vs. Rural residents Jiang ( 45 ) Integrated Medical and Care Service System Health Status: Disabled & Semi-disabled older adults; Dementia older adults; Older adults with chronic diseases Care Needs: Rehabilitation care; Hospice care Service Type: Home-based care Tan et al. ( 32 ) Social Service Incentive Mechanisms Income Level: Low-income, lower-middle-income, middle-income, higher-middle-income, high-income Location Type: Urban residents vs. Rural residents; Urban vs. Rural residents Collaborative Models: Partnerships for point accumulation with banks, insurers & merchants Zheng et al. ( 39 ) Meal Assistance Service Population Density: Targeting high-density older adults populations Regional Development: Economic Development Level; Less-Developed vs. Commercial Cores Location Type: Urban centers vs. Remote suburbs Service Type: Older adults facilities; Community dining; Corporate catering Wan et al. ( 34 ) Agriculture & Digital Age & Life Stage: Middle-aged adults; Older adults Socioeconomic Status: Rural middle-aged and older adults Urban vs. Rural: Rural middle-aged/older adults vs. urban older adults; targeting to bridge the urban–rural consumption gap Attitudes & Motivation: Individuals seeking to improve proficiency Engagement: Users seeking mental health knowledge; Users of online courses; Users of cognitive tools; Users of digital platforms for transactions and financing Functional Need: Mental health knowledge Channel Preference: Digital Channels for transactions, financing, and social connection Chen and Hu ( 50 ) XR Technology Functional Need: Applying XR to improve quality of life Shen et al. ( 47 ) Healthcare Devices Health Status: Older adults with chronic diseases; Disabled older adults (moderate, mild, severe) Functional Need: Intelligent health management; Intelligent life care Gao et al. ( 40 ) Cultural Technology Income Level: income level and purchasing power Socioeconomic Status: Special needs groups (disabled and poor older adults, older adults living alone) Regional Development: Remote areas, ethnic areas, backward areas Engagement: Users of online courses; Users of cognitive tools; Users of digital cultural products (online chess, drama, cloud social networking) Zhang et al. ( 55 ) Care Monitoring Health Status: Older adults with chronic diseases Disability & Dependency Level: Individuals requiring long-term care Care Model: Home-based Care; Institutional Care Functional Need : Health products Lam and Lee ( 35 ) Social Services Age & Life Stage: Seniors (50/55+) Socioeconomic Status: Lower economic advantage; Lower education attainment Lifestyle & Values: Individuals interested in lifelong learning Attitudes & Motivation: Individuals seeking independence; Individuals seeking reduced dependency; Constructive user of leisure time, entertainment, and social connection Health Status: Individuals needing rehabilitative benefits Functional Need: Rehabilitative benefits Cheng et al. ( 58 ) Education Zhang ( 33 ) Tourism Age & Life Stage : Seniors (50/55+), Older adults (with limitations) Occupation : State agency heads, farmers/workers, enterprise employees, private owners, freelancers Income Level: Income level and purchasing power Attitudes & Motivation : Preference for comfort and safety Product Usage : Preference for traditional booking methods Travel & Consumption : Preference for off-season travel; Price sensitivity and value-seeking behavior; Travel with family/ neighbors/ friends. Cognitive/Physical Ability : Mobility limitations; Need for medical support and barrier-free facilities Functional Need : Historical and cultural tourism; Natural landscape tourism Channel Preference : Traditional Channels like travel agencies, telephone, in-store bookings Yu and Dong ( 48 ) Urban Planning Urban vs. Rural: Urban core vs. township areas; central urban districts vs. newly developed urban areas. Accessibility : Seniors within a 5- to 15-min walkable life circles; Areas with medical service gaps Health Status: Older adults with chronic diseases Functional Need: Health products Economic Capacity: High-end, vacation-style retirement models Cheng ( 57 ) Education An et al. ( 56 ) Older adults-Care Services Huang et al. ( 53 ) Assistive Robotics Hu et al. ( 49 ) Digital Healthcare Health Status: Older adults with chronic diseases; Older adults with “Sub-healthy” conditions; Disabled older adults (moderate, mild, severe) Care Model: Home-based Care; Institutional Care Zhang ( 43 ) Education Lifestyle & Values: Supports “active aging”; self-realization; Dignity Functional Need: Spiritual, cultural, and material life needs Zhao and Gai ( 60 ) Older adults Care Services Care Model: Home-based Care; Institutional Care; Community & Ecological Care Enterprise Scale : Small business; Medium-sized enterprise; Large enterprises; Leading enterprises Wang ( 44 ) New Media Mindset: Individuals seeking escapism; Individuals seeking self-cognition Product Usage: Preference for “older adults Mode” apps; Preference for family version apps Functional Need: Interface simplicity; simplified processes Channel Preference: Family-Linked Channels for payment assistance. Yun ( 52 ) Health & Wellness Technology Socioeconomic Status: Special needs groups (older adults living alone) Health Status: Older adults with chronic diseases; Older adults with disabilities Cognitive/Physical Ability: Decline in learning skills, visual acuity, memory Chen and Chen ( 54 ) Care Technology Care Model: Home-based Care Functional Need: Health products; Intelligent health management; Intelligent life care Economic Capacity: Cost-Conscious Solutions for “working families” Open in a new tab 4.1.1. Assessment of RQ1: what are the key domains and market segments used to target the “new older adults” market in China? The reviewed literature in Table 6 collectively applies a framework to understand the diverse needs or characteristics of China’s new older adults population across various domains, as shown in Figure 3 . Figure 3. Open in a new tab Correlation of technology innovations & market segments targeting China’s new older adults. Demographic Segmentation. Demographic factors are widely used across studies, particularly age, education level, income level, occupation, and socioeconomic status. Shao et al. ( 30 ) classify learners in EdTech based on generational cohorts (1960s-born) and education levels. Studies such as Akmal et al. ( 31 ), Tan et al. ( 32 ), and Zhang ( 33 ) incorporate income and purchasing power to differentiate market opportunities in welfare services, social incentives, and tourism. Other studies, including Wan et al. ( 34 ) and Lam and Lee ( 35 ), segment populations based on life stage, highlighting middle-aged adults transitioning into older adulthood. Geographic Segmentation. Geographic segmentation plays a central role, especially in older adults care and planning. Several studies differentiate users based on urban vs. rural residency ( 31 , 32 , 36 , 37 ), recognizing disparities in resource access and consumption behavior. Others, such as Zhou and Ye ( 38 ), Zheng et al. ( 39 ), and Gao et al. ( 40 ), segment according to regional economic development, targeting less-developed, remote, or ethnic areas. Sun ( 41 ) and Yingjie and Huayao ( 42 ) introduce finer segmentation such as urban–rural integration zones, county-level areas, and high-density older adults clusters, especially relevant to property-based care and tourism. Psychographic Segmentation. Psychographic factors highlight evolving values, motivations, and lifestyles among the new older adults. Shao et al. ( 30 ) emphasize self-improvement, openness to new experiences, and intrinsic motivation among EdTech learners. Yingjie and Huayao ( 42 ) capture the increasing desire for comfort, safety, family connectedness, and diversified lifestyles in senior tourism. Lam and Lee ( 35 ) and Zhang ( 43 ) identify psychographic traits related to lifelong learning, independence, active aging, and self-realization, showing a shift away from passive retirement. Behavioral Segmentation. Behavioral segmentation is prominent across digital, financial, and tourism domains. Shao et al. ( 30 ) and Zhou and Ye ( 38 ) examine technology adoption, digital literacy, smartphone ownership, and engagement patterns, which influence participation in EdTech and FinTech. Yingjie and Huayao ( 42 ) highlight budget-conscious purchasing behavior among older adults tourists. Wang ( 44 ) segments users based on media consumption behaviors, such as preferences for “Older adults Mode” apps or family-linked features for payment support. Health & Dependency Segmentation. Health status, chronic disease presence, disability levels, and dependency needs are critical segmentation criteria. Yan ( 37 ), Jiang ( 45 ), Yichen ( 46 ), and Shen et al. ( 47 ) emphasize chronic disease management, post-illness rehabilitation, dementia care, and varying disability levels, which correspond to differentiated service models (home-based, institutional, hospice). Studies such as Yu and Dong ( 48 ) and Hu et al. ( 49 ) further categorize older adults users by sub-healthy conditions and mobility limitations, which heavily influence service design and accessibility requirements. Service & Product Benefit Segmentation. Across sectors, segmentation involves the benefits or experiences older adults users seek. He et al. ( 36 ) and Yan ( 37 ) distinguish between smart eldercare, tourism eldercare, and integrated medical care. Yichen ( 46 ) and Chen and Hu ( 50 ) identify demand for IoT-enabled home care, telemedicine, rehabilitation, spiritual comfort, and XR-based solutions. Studies in culture and technology ( 40 , 51 ) segment users by desired experiences such as cultural learning, online entertainment, cognitive tools, and immersive activities. Property-based care ( 41 ) and tourism ( 33 ) highlight expectations regarding emergency services, safety, historical or cultural experiences, and leisure amenities. Economic & Channel Segmentation. Economic segmentation appears through analysis of income, funding mechanisms, insurance coverage, and enterprise scale. He et al. ( 36 ) and Yan ( 37 ) differentiate between government-run vs. social-run models. Tan et al. ( 32 ) incorporate income tiers into social incentive mechanisms involving banks and insurers. Yichen ( 46 ) details multiple payment channels including self-pay, long-term care insurance, and commercial plans. Channel segmentation also emerges in studies like Wang ( 44 ) and Zhang ( 33 ), which highlight traditional vs. digital channels, including family-linked payment support, travel agencies, and in-store bookings. To conclude, the reviewed studies collectively demonstrate that China’s new older adults market is deeply heterogeneous. As it is characterized by diverse demographic attributes, like socioeconomic backgrounds, geographic contexts, lifestyle values, digital behaviors, health conditions, and service expectations, and the segmentation patterns reflect a shift toward viewing the older adults not as a uniform group but as multidimensional consumers with evolving needs that cut across technology, healthcare, tourism, education, welfare, digital finance, and property-based services. This multidimensional segmentation highlights the need for tailored, domain-specific strategies in policy, product development, and service delivery, instead of “one-size-fits-all” approaches. The effective interventions for China’s new older adults must account for generational differences, urban–rural disparities, digital readiness, health variations, lifestyle aspirations, and economic capacity, ensuring inclusive and adaptive solutions for an aging society. 4.2. Key domain-specific technological innovations for China’s “New older adults” market and their key characteristics Similarly, the adapted method for the classification themes ( 64 ) is applied to 31 extracted articles through the PRISMA method for the identification of key domain-specific technological innovations targeting China’s new older adults market and their key characteristics, as indicated in Table 7 . Table 7. Classification: domain-specific technological innovations for China’s new older adults market and their key characteristics. Domain-specific technological innovations for China’s new older adults market and their key characteristics RQ2 References Domain Health & wellness technologies Living environment & safety technologies Social inclusion & empowerment technologies Data infrastructure & platform management Support & operational technologies Shao et al. ( 30 ) Older adults Education Technology (EdTech) Mobile & Digital Learning Platforms : Systematic learning content; Easy-to-use interface, Intuitive UI, Voice navigation, Features for emotional assurance He et al. ( 36 ) Older adults Care Services (ECS) Smart Health Monitoring & Wearable Devices: Real-time health monitoring Telemedicine & Remote Consultation Systems: Video consultations Smart Home & IoT-Based Care Systems: Sensors; Monitoring devices Service Matching & Digital Marketplaces: Digital platforms Shao et al. ( 51 ) Older adults Care Resource Allocation Telemedicine & Remote Consultation Systems: Chronic disease management Yan ( 37 ) Home Older adults Care Industry Smart Health Monitoring & Wearable Devices: Real-time health monitoring; User-friendly design; Integration with platforms & third-party devices Smart Home & IoT-Based Care Systems: Monitoring devices Video Communication & Social Connection Systems: Audio-video monitoring; Mobile app integration; Simplified UI Zhou and Ye ( 38 ) Digital Inclusive Finance (FinTech) Digital Finance & E-Commerce Integration: Mobile payment; Low cost; Credibility; Integration with e-commerce and real estate Wang et al. ( 59 ) Urban Planning GIS & Data-Driven Spatial Planning: High-resolution spatial data (POI); GIS integration; Predictive site selection Sun ( 41 ) Property-based Older adults Care AI-Driven Predictive Safety & Resource Allocation: Predictive modeling; Spatio-temporal data fusion; Dynamic thresholding; Graded early warning Privacy-Preserving Computing: Federated learning Yingjie and Huayao ( 42 ) Senior Tourism Industry Smart Health Monitoring & Wearable Devices: Real-time health monitoring Service Matching & Digital Marketplaces: Online booking; Feedback mechanisms Digital Promotion & Self-Media Platforms: Use of graphics and short videos for promotion Yichen ( 46 ) Smart Home Care (SHC) Technology Smart Health Monitoring & Wearable Devices: Real-time health monitoring; User-friendly design; Continuous data collection Smart Home & IoT-Based Care Systems: Sensors, Monitoring devices; Voice recognition; Motion capture; Integrates hardware & software Akmal et al. ( 31 ) Older adults Welfare Cottage Industry Centralized Data & Information Management Platforms: Cloud-based centralized databases; Role-based access control Jiang ( 45 ) Integrated Medical and Care Service System Smart Health Monitoring & Wearable Devices: Real-time health monitoring Telemedicine & Remote Consultation Systems: Rapid telephone consultation; Video consultation; Chronic disease management; Internet medical resources Centralized Data & Information Management Platforms: Health data platform; Four-level linkage mechanism (City, District, Street, Community) Tan et al. ( 32 ) Social Service Incentive Mechanisms Digital Finance & E-Commerce Integration: Digital virtual currency/points Zheng et al. ( 39 ) Meal Assistance Service Intelligent Delivery & Nutrition Management Systems: Smart meal systems; Online ordering; Nutrition assessment; Delivery dispatch; Multimodal kitchen-terminal tech Wan et al. ( 34 ) Agriculture & Digital Social Connection & Communication Platforms: Digital Platforms & Smart Logistics; Social Communication Platforms; Use of Cell Phones, Tablets, and Communication Software Online Education & Lifelong Learning Platforms: Platforms for Skills & Education Foundational Digital Access Infrastructure: Basic Connectivity Networks Chen and Hu ( 50 ) XR Technology Extended Reality (XR) & Immersive Technologies: Gesture Interaction; Optimized Gesture Set for the Older adults User-Centered & Aging-Adapted Interaction Design: High Cognitive Compatibility & Low Physiological Load Shen et al. ( 47 ) Healthcare Devices Intelligent Health Monitoring & Management Systems: Smart Wearable Devices Assistive Robotics for Daily Living : Physical Assistance Robots; Social Robots Gao et al. ( 40 ) Cultural Technology Extended Reality (XR) & Immersive Technologies: Immersive Learning Environments User-Centered & Aging-Adapted Interaction Design: Adapted Product Presentation (fonts, colors) Foundational Digital Access Infrastructure: Age-Suitable Terminal Products Zhang et al. ( 55 ) Care Monitoring AI-Powered Safety & Behavior Recognition Systems: Behavior Recognition Technology (using RGB cameras); Deep Learning-based Fall Detection (CNNs, Transfer Learning) Lam and Lee ( 35 ) Social Services Social Connection & Communication Platforms: Use of Cell Phones, Tablets, and Communication Software; Social Communication Platforms Online Education & Lifelong Learning Platforms: Platforms for Skills & Education Cheng et al. ( 58 ) Education Social Connection & Communication Platforms: Social Communication Platforms Digital Finance & E-Commerce Integration: Mobile Payment Systems (Alipay, WeChat Pay) Foundational Digital Access Infrastructure : Age-Suitable Terminal Products Zhang ( 33 ) Tourism Online Education & Lifelong Learning Platforms: E-Learning Platforms for Older Adults Data-Driven Analytics & Smart Service Integration: AI Algorithms for Tourism (Machine Learning, NLP) Yu and Dong ( 48 ) Urban Planning Data-Driven Analytics & Smart Service Integration: Geospatial Modeling & Semantic Segmentation; Integrated “micro-clinic + smart pharmacy” networks Cheng ( 57 ) Education Online Education & Lifelong Learning Platforms: E-Learning Platforms for Older Adults; Digital Devices for Learning (TVs, mobile phones) An et al. ( 56 ) Older adults-Care Services Social Connection & Communication Platforms: Social Communication Platforms Digital Finance & E-Commerce Integration: Digital Platforms & Smart Logistics Huang et al. ( 53 ) Assistive Robotics Assistive Robotics for Daily Living: Feeding Assistive Robotics (using HCI) Hu et al. ( 49 ) Digital Healthcare Intelligent Health Monitoring & Management Systems: Remote Homecare Systems Zhang ( 43 ) Education Online Education & Lifelong Learning Platforms: New Media & Multimedia Applications Zhao and Gai ( 60 ) Older adults Care Services Data-Driven Analytics & Smart Service Integration: Constrained Clustering Algorithms Wang ( 44 ) New Media Digital Finance & E-Commerce Integration: Payment Security Features & Family Account Integration Foundational Digital Access Infrastructure: Simplified Software Interfaces (“Older adults Mode”); Guided Tutorials Yun ( 52 ) Health & Wellness Technology Intelligent Health Monitoring & Management Systems: Smart Wearable Devices; Multi-Sensor Data Platforms (ECG, pulse oximeter, EMG) User-Centered & Aging-Adapted Interaction Design: User-Centered Design; Intuitive Human-Computer Interaction Chen and Chen ( 54 ) Care Technology AI-Powered Safety & Behavior Recognition Systems : Deep Learning-based Fall Detection (CNNs, Transfer Learning) Open in a new tab 4.2.1. Assessment of RQ2: what are the key technological innovations by key industry sectors to serve the “New older adults” market in China, and what are their core characteristics? The literature, mapped in Table 7 , highlights diverse technological innovations tailored to meet the multifaceted needs of China’s new older adults population, also it highlights the key characteristics of these innovations in domains: health and wellness, living environment and safety, social inclusion and empowerment, data infrastructure and platform management, and support and operational technologies. Health & Wellness Technologies. Health-related technologies remain the most dominant category. Multiple studies ( 36 , 37 , 42 , 45–47 , 52 ) emphasize: Smart health monitoring and wearable devices with real-time tracking, multi-sensor platforms (ECG, EMG, pulse oximetry), and older adults-friendly interfaces. Telemedicine and remote consultation systems supporting video consultations, chronic disease management, rapid telephone consultations, and internet medical resources ( 36 , 45 , 51 ). Intelligent health management platforms, including remote homecare systems ( 49 ). These innovations prioritize continuous monitoring, accessibility, and early detection, addressing chronic conditions and mobility limitations prevalent among older adults populations. Living Environment & Safety Technologies. Studies highlight rapidly advancing smart home safety and environmental monitoring innovations. These include, IoT-based smart home systems with sensors, motion capture, voice recognition, and integrated hardware-software ecosystems ( 36 , 37 , 46 ), AI-driven predictive safety systems, spatio-temporal fusion, dynamic thresholding, and graded early warning models ( 41 ), assistive robotics providing physical and social assistance, improving daily living functions ( 47 , 53 ), and AI-powered fall detection and behavior recognition through deep learning, CNNs, transfer learning, and RGB camera technology ( 54 , 55 ). This domain reflects a transition from passive to proactive safety ecosystems, improving risk detection and supporting independent living. Social Inclusion & Empowerment Technologies. A significant body of literature now focuses on technologies that enhance social connectivity, lifelong learning, and digital participation, like social communication platforms using smartphones, tablets, communication software, and simplified interfaces ( 35 , 37 , 56 ), digital learning and EdTech platforms with intuitive UI, voice navigation, emotion-support features, and accessible e-learning environments ( 30 , 43 , 57 , 58 ), XR and immersive learning technologies enabling realistic interactions, gesture-based input, and older adults-optimized cognitive load ( 40 , 50 ), digital promotion, graphics-led media, and short videos for senior tourism engagement ( 42 ). These technologies support active aging , enabling seniors to learn, connect, and participate socially and culturally. 4. Data Infrastructure & Platform Management. A strong digital backbone underlies most older adults-oriented innovations, like centralized data and cloud-based information systems ( 31 ), multi-level health data platforms linked across city–district–street–community levels ( 45 ), digital finance ecosystems, including mobile payments, secure transactions, virtual currency/points, older adults-mode interfaces, and integration with e-commerce and real estate ( 32 , 38 , 44 ), GIS-based urban planning, geospatial modeling, semantic segmentation, and predictive site selection for older adults-friendly development ( 48 , 59 ), and foundational digital access infrastructure, including older adults-friendly devices and simplified software interfaces ( 34 , 40 , 58 ). This domain shows a movement toward data-driven policymaking, integrated care networks, and inclusive digital finance. 5. Support & Operational Technologies. Operational innovations aim to improve service delivery, logistics, and backend efficiency, such as service matching platforms connecting older adults users with care or tourism services ( 36 , 42 , 56 ), intelligent meal assistance and nutrition management systems, including multimodal technologies from ordering to dispatch ( 39 ), smart logistics and digital platforms for communication, social support, and product delivery ( 34 , 56 ), and privacy-preserving computing (federated learning) to ensure secure AI-driven services ( 41 ). These technologies enhance efficiency, personalization, and secure delivery of community services. The technological landscape for China’s “new older adults” market is characterized by an integrated ecosystem of health monitoring, smart living environments, tools related to social, educational, and immersive XR, sophisticated data management platforms, and operational support systems. This multi-domain innovations cater to the comprehensive needs of older adults users, balancing health, safety, empowerment, financial inclusion, mobility and quality of life with advanced data-driven management and service delivery models. 4.3. Key domain-specific technological innovations for China’s “New older adults” market and their key benefits Likewise, the adapted method for the classification themes ( 64 ) is applied to 31 extracted articles through the PRISMA method for the identification of key domain-specific technological innovations targeting China’s new older adults market and their key benefits, as indicated in Table 8 . Table 8. Classification: domain-specific technological innovations for China’s “New older adults” market and their key benefits. Industry-specific technological innovations for China’s ‘New older adults’ market and their key benefits RQ3 References Domain Health & wellness technologies Living environment & safety technologies Social inclusion & empowerment technologies Data infrastructure & platform management Support & operational technologies Shao et al. ( 30 ) Older adults Education Technology (EdTech) Mobile & Digital Learning Platforms: Continuous self-education; Integration into society; Social inclusion; Sense of accomplishment He et al. ( 36 ) Older adults Care Services (ECS) Smart Health Monitoring & Wearable Devices: Health tracking Telemedicine & Remote Consultation Systems: Accessible healthcare; Remote diagnosis Smart Home & IoT-Based Care Systems: Real-time monitoring Service Matching & Digital Marketplaces: Reduces transaction costs Shao et al. ( 51 ) Older adults Care Resource Allocation Centralized Data & Information Management Platforms: Improves resource matching Yan ( 37 ) Home Older adults Care Industry Smart Health Monitoring & Wearable Devices: Improved safety; Independent living; Real-time alerts; Health tracking Smart Home & IoT-Based Care Systems: Real-time monitoring; Risk prevention; Improved service quality; Remote supervision; Enhances independent living Video Communication & Social Connection Systems: Remote family connection; Emergency detection; Mental support; Easy access to communication Centralized Data & Information Management Platforms: Enables integrated service delivery Zhou and Ye ( 38 ) Digital Inclusive Finance (FinTech) Digital Finance & E-Commerce Integration: Accessible & efficient financial services; Easier saving & investing, profitable options Wang et al. ( 59 ) Urban Planning GIS & Data-Driven Spatial Planning: Objective site selection for care facilities; Improved spatial equity; Enhanced accessibility Sun ( 41 ) Property-based Older adults Care AI-Driven Predictive Safety & Resource Allocation: Early warning of resource shortages; Optimized resource allocation; Supports operational planning Privacy-Preserving Computing: Protects data privacy Yingjie and Huayao ( 42 ) Senior Tourism Industry Centralized Data & Information Management Platforms: Improves resource matching; Enables integrated service delivery Service Matching & Digital Marketplaces: Facilitates comparison & selection of services Digital Promotion & Self-Media Platforms: Increases public awareness; Promotes culture & services; Boosts engagement Yichen ( 46 ) Smart Home Care (SHC) Technology Smart Health Monitoring & Wearable Devices: Improved safety; Independent living; Reduced hospitalization Smart Home & IoT-Based Care Systems: Real-time monitoring; Risk prevention; Improved service quality; Remote supervision; Enhances independent living Akmal et al. ( 31 ) Older adults Welfare Cottage Industry Telemedicine & Remote Consultation Systems: Accommodates rural service imbalances Centralized Data & Information Management Platforms: Better care coordination; Accessible anywhere Jiang ( 45 ) Integrated Medical and Care Service System Smart Health Monitoring & Wearable Devices: Real-time alerts; Health tracking Telemedicine & Remote Consultation Systems: Accessible healthcare; Remote diagnosis; Reduces travel & cost Centralized Data & Information Management Platforms: Improves resource matching; Enables integrated service delivery Tan et al. ( 32 ) Social Service Incentive Mechanisms Service Matching & Digital Marketplaces: Improves purchasing ability; Facilitates comparison & selection of services Zheng et al. ( 39 ) Meal Assistance Service Intelligent Delivery & Nutrition Management Systems: Enhanced convenience; Better dietary matching; Improved nutrition; Supports sustainable operation Wan et al. ( 34 ) Agriculture & Digital Social Connection & Communication Platforms: Brings convenience; Reduces depression by narrowing the urban–rural living standards gap; provides “remote companionship”; Reduces loneliness; Improves cognitive ability; Offers access to mental health knowledge Online Education & Lifelong Learning Platforms: Increases income; Enhances sense of career accomplishment Foundational Digital Access Infrastructure: Provides the foundational access that enables all other digital services; Reduces the “digital divide” Chen and Hu ( 50 ) XR Technology Extended Reality (XR) & Immersive Technologies: Intuitive and low learning curve; Enhanced quality of life; Promotes independence and social connection; Reduced learning difficulty; Reduced risk of musculoskeletal disorders User-Centered & Aging-Adapted Interaction Design: Makes the technology easier to adopt; Minimizes physical strain from repetitive use Shen et al. ( 47 ) Healthcare Devices Intelligent Health Monitoring & Management Systems: Dynamic health information; Improved quality of life, physical, and mental health; Immediate assistance (e.g., fall detection) Assistive Robotics for Daily Living: Assist with activities of daily living; Improve gait function; Promote independence and convenience; Maintain social connections; improve spiritual life Gao et al. ( 40 ) Cultural Technology Extended Reality (XR) & Immersive Technologies: Helps deepen the learning and application of digital cultural products User-Centered & Aging-Adapted Interaction Design: Makes products more suitable for the older adults Foundational Digital Access Infrastructure: Improved convenience for the older adults to enter the online world Zhang et al. ( 55 ) Care Monitoring AI-Powered Safety & Behavior Recognition Systems: High accuracy and speed in recognition; Improved service quality in older adults care; Timely detection of abnormal situations (e.g., falls); Enhanced safety and security in everyday life Lam and Lee ( 35 ) Social Services Social Connection & Communication Platforms: Improves cognitive ability; Provides “remote companionship”; Reduces loneliness. Online Education & Lifelong Learning Platforms: Enhances sense of career accomplishment Cheng et al. ( 58 ) Education Social Connection & Communication Platforms: Provides “remote companionship”; Reduces loneliness; Maintains social connections E-commerce & Mobile Payment Ecosystems: Mobile Payment Systems (Alipay, WeChat Pay); Provides convenience Foundational Digital Access Infrastructure: Improved convenience for the older adults to enter the online world Zhang ( 33 ) Tourism Online Education & Lifelong Learning Platforms: Maintained lifelong learning from home Data-Driven Analytics & Smart Service Integration: Precise marketing and personalized travel packages Yu and Dong ( 48 ) Urban Planning Data-Driven Analytics & Smart Service Integration: Analyzes spatial characteristics; Predicts optimal sites for older adults care facilities; Assesses walkability; Aims to enhance basic healthcare provision in underserved rural areas Cheng ( 57 ) Education Online Education & Lifelong Learning Platforms: Provided access to high-quality educational resources; Maintained lifelong learning from home; Enabled flexible; Enabled self-arranged learning time and content An et al. ( 56 ) Older adults-Care Services Social Connection & Communication Platforms: Maintains social connections E-commerce & Mobile Payment Ecosystems: Brings convenience Huang et al. ( 53 ) Assistive Robotics Assistive Robotics for Daily Living: Promotes independence Hu et al. ( 49 ) Digital Healthcare Intelligent Health Monitoring & Management Systems: Allows ageing in place; Enables professional care at home; Reduces hospitalizations and readmission rates through early detection; Enables self-monitoring and management of chronic diseases Zhang ( 43 ) Education Online Education & Lifelong Learning Platforms: Creates new opportunities for the sustainable development of older adults education; Helps the older adults learn new knowledge, master new technologies, and integrate into society Zhao and Gai ( 60 ) Older adults Care Services Data-Driven Analytics & Smart Service Integration: Improved efficiency & quality for industrial chain optimization; Optimal resource allocation to efficiently connect caregivers with the older adults Wang ( 44 ) New Media E-commerce & Mobile Payment Ecosystems: Reduced property security risk; Enabling online shopping despite a lack of digital payment confidence Foundational Digital Access Infrastructure: Enhanced usability and reduced complexity; Improved learnability and confidence Yun ( 52 ) Health & Wellness Technology Intelligent Health Monitoring & Management Systems: Dynamic health information Improved quality of life, physical, and mental health; Comprehensive health monitoring User-Centered & Aging-Adapted Interaction Design: Accommodates the older adults’s physical and psychological state; Natural, easy-to-use, and humanized product interfaces Chen and Chen ( 54 ) Care Technology AI-Powered Safety & Behavior Recognition Systems: Timely detection of abnormal situations (e.g., falls); Enhanced safety and security in everyday life; Aims to ensure the safety of the older adults living alone Open in a new tab 4.3.1. Assessment of RQ3: what are the key benefits of these technological innovations for China’s “New older adults” population? The literature, mapped in Table 8 , highlights how technological innovations across various industries provide following tailored benefits to China’s new older adults market. Health & Wellness Technologies . A wide range of studies emphasize how smart health monitoring, wearable devices, and telemedicine strengthen older adults health management. Smart health systems ( 36 , 37 , 45–47 , 49 , 52 ) provide real-time tracking, early alerts, fall detection, and chronic disease management, collectively reducing hospitalization and enabling ageing in place. Telemedicine and remote consultation systems ( 31 , 36 , 45 ) expand access to healthcare by reducing travel costs and supporting remote diagnosis, particularly beneficial for rural older adults facing service shortages. Living Environment & Safety Technologies. Smart home, IoT-based systems, AI-driven predictive safety tools, and assistive robotics significantly enhance older adults safety and independence. Yan ( 37 ), He et al. ( 36 ), Yichen ( 46 ), Sun ( 41 ), and Shen et al. ( 47 ) highlight benefits such as real-time monitoring, risk prevention, remote supervision, and early warning of hazards or resource shortages. Care robotics ( 47 , 53 ) further assist with activities of daily living, improving gait, convenience, and autonomy. These technologies create safe, supportive living environments while improving service quality. Social Inclusion & Empowerment Technologies. Digital platforms supporting lifelong learning, social connection, and communication play a vital role in reducing loneliness, enhancing mental well-being, and empowering the older adults. Studies such as Shao et al. ( 30 ), Yan ( 37 ), Lam and Lee ( 35 ), and Cheng ( 57 , 58 ) show that mobile learning platforms and online education expand access to high-quality content, support digital literacy, and foster a sense of accomplishment. Social communication systems ( 34 , 35 , 42 ) provide remote companionship, reduce depression, and maintain familial or social ties. Meanwhile, digital marketplaces ( 32 , 42 ) enhance empowerment by enabling informed service comparison and better purchasing decisions. Extended Reality (XR) technologies ( 40 , 50 ) further promote social and cultural participation by offering intuitive, immersive experiences suited to older adults users. Data Infrastructure & Platform Management. Centralized, cloud-based, and data-driven platforms facilitate resource integration, care coordination, and efficient service delivery. Shao et al. ( 51 ), Yan ( 37 ), Jiang ( 45 ), Akmal et al. ( 31 ), and Yingjie and Huayao ( 42 ) show that shared health and service data platforms ensure smoother multi-agency collaboration and accurate resource allocation. GIS-based planning tools ( 48 , 59 ) optimize the placement of care facilities, improving accessibility and spatial equity. Digital finance and e-commerce ecosystems ( 38 , 44 , 56 ) provide secure, efficient financial services, fostering economic inclusion for older adults users who may lack digital payment confidence. Support & Operational Technologies . Supportive and operational technologies improve service efficiency, convenience, and trust. Intelligent delivery and nutrition management systems ( 39 ) ensure accurate dietary matching and support sustainable meal services. Privacy-preserving computing ( 41 ) protects sensitive personal data in digitized service environments. Service matching platforms ( 32 , 36 , 42 ) reduce transaction friction, streamline elder-caregiver matching, and lower operational costs. AI-powered behavior recognition systems ( 54 , 55 ) enhance security by detecting risky situations such as falls or abnormal movements in real time. To conclude, domain-specific technological innovations for China’s new older adults market deliver multifaceted benefits that enhance health outcomes, safety, social inclusion, lifelong learning, reduce loneliness, improve social participation, resource integration, and operational efficiency. These innovations are instrumental in supporting independent living, improving care quality, enabling financial and social empowerment, and optimizing service delivery in a rapidly aging society. 4.4. Limitations and quality assessment score It is essential for a PRISMA-compliant Systematic Literature Review (SLR) to evaluate the limitations of studies selected for the review and assess their quality in order to ensure the validity of the findings of the review, transparency in the review process, reducing the risk of bias, and clarifying the scope of the conclusion. Table 9 demonstrates the limitations and quality assessment scores of each of the 31 selected studies. Table 9. Limitations and quality assessment score. Classification Quality assessment References Publication channel Journal/ conference ranking Cited by Limitations a b c d Scores Shao et al. ( 30 ) Conference 0 0 Methodologically, the study is limited by its single-province sample and reliance on self-reported survey data, as a result, its findings have restricted generalizability, particularly regarding mobile learning in education. 1 1 −1 0 1 He et al. ( 36 ) Journal Q1 1 Missing data from certain provinces constrain the regional representation and robustness of the study, and this limits its generalizability and prevents analysis of long-term effects, data privacy, and cross-sector consumption behaviors. 1 1 0 2 4 Shao et al. ( 51 ) Conference 0 0 By focusing only on Dezhou and online respondents, the study’s methodological scope is narrow, as a result, findings cannot be generalized to broader regional older adults-care preferences. 1 1 −1 0 1 Yan ( 37 ) Thesis 0 2 The early-stage exploration lacks mature theoretical frameworks and empirical validation, and its conclusions are limited to pilot projects in two cities and do not reflect broader market segmentation or autonomous older adults behavior. 1 1 0 0 2 Zhou and Ye ( 38 ) Journal Q1 12 RDD estimates are valid only near the cutoff, limiting methodological generalizability, and this constrains insights into broader market segmentation, non-FinTech innovations, and cross-sector older adults consumption. 1 1 1 2 5 Wang et al. ( 59 ) Journal Q1 11 The model does not differentiate older adults-care facility types, reducing predictive precision, as a result, the study offers limited insights beyond GIS-based spatial planning. 1 0.5 1 2 4.5 Sun ( 41 ) Journal Q1 0 Exclusion of rural property data and resident preferences limits the study’s methodological completeness, and this restricts generalizability and the applicability of findings to broader pilot counties or extreme conditions. 1 1 −1 2 3 Yingjie and Huayao ( 42 ) Thesis 0 1 Lack of field validation and empirical support reduces the reliability of conclusions about TCM–tourism integration, and findings are limited by the study’s exclusive macro-level, supply-side focus, omitting older adults behavioral data. 1 0.5 0 0 1.5 Yichen ( 46 ) Dissertation 0 0 The Shanghai-specific sample and short observation window limit methodological robustness, as a result, the findings have constrained generalizability and practical relevance. 1 1 −1 0 1 Akmal et al. ( 31 ) Journal 0 0 Conceptually, the proposed system lacks empirical grounding and cost or technology assessments because it provides no insights into market segmentation, industry practices, or older adults consumption behaviors. 1 1 −1 0 1 Jiang ( 45 ) Journal 0 0 The qualitative, location-specific approach limits methodological applicability to other regions, as a result, policy and institutional findings cannot be generalized to the broader older adults market or technology landscape. 1 1 −1 0 1 Tan et al. ( 32 ) Journal 0 0 Purposive sampling and self-reported measures constrain methodological representativeness, and it focuses narrowly on a points-based system for low-income individuals, ignoring broader sectoral or market insights. 1 1 −1 0 1 Zheng et al. ( 39 ) Journal Q1 0 Omitting key variables reduces the methodological completeness of the model, which limits exploration of consumer technology adaptation or detailed behavioral analysis. 1 0.5 −1 2 2.5 Wan et al. ( 34 ) Journal Q1 2 Lack of theoretical grounding and empirical testing restricts methodological robustness, as a result, rural micro-level findings cannot be generalized nationally, and causation cannot be inferred. 1 1 0 2 4 Chen and Hu ( 50 ) Journal Q2 0 Data-based evaluation without theoretical grounding weakens methodological support, and its XR gesture focus limits insights into other industries, market segmentation, or older adults behaviors. 1 1 −1 1.5 2.5 Shen et al. ( 47 ) Journal Q1 18 Limited indicators and lack of geographic validation reduce methodological robustness, and findings from two nursing homes cannot generalize to diverse older adults populations or sectors. 1 1 1 2 5 Gao et al. ( 40 ) Conference 0 3 Narrow sample scope and insufficient field validation limit methodological reliability, and its focus on digital cultural products lacks cross-sector analysis. 1 1 0 0 2 Zhang et al. ( 55 ) Journal Q3 0 Sparse older adults-behavior data and limited GIS variables reduce methodological accuracy, as a result, findings focus only on technical monitoring and not broader market or behavioral insights. 1 1 −1 1 2 Lam and Lee ( 35 ) Conference Q3 9 Absence of longitudinal data constrains methodological reflection of dynamic needs, and convenience sampling further limits generalizability, focusing only on intention rather than actual use. 1 1 1 1 4 Cheng et al. ( 58 ) Journal Q2 34 Insufficient differentiation between facility types weakens methodological precision, and its single-case focus is not generalizable to industry strategies or older adults market behavior. 1 1 1 1.5 4.5 Zhang ( 33 ) Journal Q3 11 Limited data sources and lack of multi-city validation reduce methodological reliability, and its tourism-sector focus prevents cross-sector or regional insights. 1 1 1 1 4 Yu and Dong ( 48 ) Journal Q2 1 Reliance on selected factors limits predictive completeness, and using GIS and POI data, the study omits socioeconomic and user-experience variables. 1 0.5 0 1.5 3 Cheng ( 57 ) Journal Q1 0 Simulation-based methods with unverified assumptions restrict methodological validity, and small rural samples and education-only focus prevent generalization to broader older adults markets. 1 0.5 −1 2 2.5 An et al. ( 56 ) Journal Q1 0 Incomplete service-quality indicators reduce methodological comprehensiveness, and findings are limited to one community intervention, with no sectoral or commercial relevance. 1 1 −1 2 3 Huang et al. ( 53 ) Conference 0 3 Lack of empirical testing across cities limits methodological generalizability, and focusing on a single robotic device provides no market, adoption, or user behavior insights. 1 1 0 0 2 Hu et al. ( 49 ) Journal Q4 3 Limited urban samples and insufficient model validation constrain methodological robustness, and findings from digital health in nursing homes cannot be extrapolated to other sectors or older adults behaviors. 1 1 0 1 3 Zhang ( 43 ) Conference 0 0 Preliminary indicator framework and limited expert validation weaken methodological reliability, and its education-sector focus excludes cross-sector insights into segmentation or technology adaptation. 1 1 -1 0 1 Zhao and Gai ( 60 ) Journal Q3 2 Use of selected spatial variables oversimplifies methodological complexity, and supply-side, industry-chain focus prevents understanding of older adults behavior or cross-sector differences. 1 1 0 1 3 Wang ( 44 ) Conference 0 0 Failure to incorporate behavioral, social, and psychological factors limits methodological explanatory depth, and urban self-reported sample restricts representativeness and sectoral applicability. 1 1 -1 0 1 Yun ( 52 ) Conference 0 0 Limited geographic scope and lack of cross-regional comparison reduce methodological applicability, and conceptual design without user data prevents insights into market segmentation or broader health technology use. 1 1 -1 0 1 Chen and Chen ( 54 ) Conference 0 0 Omitting dynamic service-allocation factors restricts methodological guidance for policy, and narrow engineering focus on a single fall-detection algorithm provides no broader market, sectoral, or behavioral insights. 1 1 -1 0 1 Open in a new tab 4.4.1. Potential limitations This review is limited by the methodological constraints of the included studies. Many studies focus on specific cities, provinces, or pilot sites, relying on small, localized samples, qualitative case studies, or online surveys, often excluding non-digital users. Additionally, a significant portion of the evidence is derived from theoretical frameworks, macro-level analyses, or models with limited empirical validation. These methodological limitations restrict the generalizability of findings and prevent the review from fully addressing broader market segmentation, cross-sector consumption patterns, long-term effects, and practical implementation challenges in older adults-care research. 4.4.2. Overall quality assessment score According to Farooq et al. ( 28 ), the minimum possible score for the study is −1, and the maximum possible score is 5. The average score is calculated as approximately 2.4 in the case of this review. The results of quality assessment in Table 10 , indicate that most included studies, i.e., 52% of the included studies, scored above the average quality score of 2.4, which indicates a reasonable proportion of methodologically robust research. In contrast, 48% fell below this threshold, highlighting substantial limitations, which are common in developing fields. Overall, these results suggest that the review includes several high-quality studies. This range of scores offers a realistic and comprehensive view, allowing for conclusions that are strengthened by synthesizing diverse perspectives while rightly prioritizing the most rigorous contributions. Table 10. Overall quality assessment score. References Score Total Percentage Shen et al. ( 47 ) and Zhou and Ye ( 38 ) 5 2 6% 52% Cheng et al. ( 58 ) and Wang et al. ( 59 ) 4.5 2 6% He et al. ( 36 ), Lam and Lee ( 35 ), Wan et al. ( 34 ) and Zhang ( 33 ) 4 4 13% An et al. ( 56 ), Hu et al. ( 49 ), Sun ( 41 ), Yu and Dong ( 48 ) and Zhao and Gai ( 60 ) 3 5 16% Chen and Hu ( 50 ), Cheng ( 57 ) and Zheng et al. ( 39 ) 2.5 3 10% Gao et al. ( 40 ), Huang et al. ( 53 ), Yan ( 37 ) and Zhang et al. ( 55 ) 2 4 13% 48% Yingjie and Huayao ( 42 ) 1.5 1 3% Akmal et al. ( 31 ), Chen and Chen ( 54 ), Jiang ( 45 ), Shao et al. ( 30 ), Shao et al. ( 51 ), Tan et al. ( 32 ), Wang ( 44 ), Yichen ( 46 ), Yun ( 52 ) and Zhang ( 43 ) 1 10 32% Open in a new tab 5. Discussion The findings from this systematic review illustrate the complexity and heterogeneity of China’s new older adults market, emphasizing the importance of domain-specific segmentation to effectively engage this rapidly growing demographic. The reviewed studies demonstrate that older adults consumers differ across multiple dimensions, including demographics, geography, psychographics, health status, and economic capacity. This multidimensional segmentation reflects the diversity of needs, preferences, and behaviors among older adults, enabling more tailored offerings such as digital education platforms for lifelong learning, IoT-based home care for independent living, and accessible financial technologies. Recognizing this heterogeneity underscores the necessity of flexible, multi-faceted strategies, rather than “one-size-fits-all” approaches, to address differences in lifestyle, health conditions, digital literacy, and generational attitudes. Technological innovations targeting the new older adults market are both sophisticated and multifaceted, spanning health and wellness, living environment and safety, social inclusion, data infrastructure, and operational support. Examples include wearable health devices, telemedicine platforms, smart home systems, XR-based learning environments, and integrated digital finance and care platforms. These innovations prioritize accessibility and ease of use, accommodating varying levels of digital literacy, while advanced applications of AI, big data, and cloud computing enable predictive care, personalized service delivery, and efficient resource allocation. Collectively, these technologies not only enhance quality of life, independence, and social participation among older adults but also contribute to broader societal objectives such as reducing healthcare system burdens, promoting digital inclusion, and fostering lifelong learning and empowerment. Despite these promising developments and including a reasonable proportion of methodologically robust research, significant challenges remain. The geographic and demographic scope of much existing research is limited, with a predominant focus on urban, digitally literate populations, often overlooking rural, low-income, or digitally marginalized groups. Additionally, many studies rely on theoretical frameworks, macro-level analyses, or small-scale empirical studies, constraining understanding of actual adoption behaviors, long-term outcomes, and real-world impact. Addressing these gaps requires more inclusive, empirical, and longitudinal research to inform scalable, equitable, and context-sensitive interventions capable of meeting the complex and evolving needs of China’s aging population. Overall, this review highlights that China’s new older adults market is not a homogeneous group but a multidimensional population whose health, social, economic, and technological needs are diverse. Effective strategies must integrate domain-specific segmentation, technological innovation, and inclusive service design to support independent living, enhance well-being, and enable active participation in an increasingly digital society. 6. Conclusion This review demonstrates that China’s new older adults market is highly heterogeneous, with diverse needs across demographics, geography, psychographics, health, and economic capacity, and an effective engagement requires domain-specific, technology-enabled solutions, like wearable health devices, smart home systems, telemedicine platforms, and digital learning tools in order to prioritize accessibility, usability, and personalization. The findings highlight the importance of multidimensional segmentation and user-centered design to support independent living, enhance health and safety, foster social participation, and improve overall quality of life, along with tailored interventions that account for generational differences, urban–rural disparities, digital literacy, health status, and lifestyle preferences are essential for developing inclusive, efficient, and sustainable care and engagement systems for older adults. 6.1. Limitations and future recommendations 6.1.1. Limitations This review is subject to several notable limitations, such as the geographic focus of many studies is predominantly urban or region-specific, limiting the generalizability of findings to rural, less-developed, or ethnically diverse areas. Also, a substantial proportion of the literature centers on digitally literate or tech-savvy older adults populations, often excluding non-digital users and thereby potentially skewing insights toward more connected subsets of the older adults, and many studies rely on theoretical frameworks, macro-level analyses, or small-scale case studies, providing limited empirical evidence of actual adoption behaviors, preferences, and long-term outcomes. All of these methodological constraints restrict understanding of cross-sector consumption patterns, real-world effectiveness, and practical implementation challenges, and lastly the heterogeneity of China’s new older adults population, in terms of health status, lifestyle, generational differences, and economic capacity, remains underexplored in many studies, highlighting the need for more inclusive, longitudinal, and context-sensitive research to inform scalable and equitable interventions. 6.1.2. Future recommendations Future efforts should focus on actionable strategies aligned with market segmentation and technological innovation, and businesses and service providers should develop differentiated offerings targeting subgroups with distinct motivations, such as self-improvement versus comfort-focused older adults, while considering urban–rural and income-based differences. On the other hand, technology developers should prioritize user-friendly designs, including simplified interfaces, voice navigation, and adaptive settings, ensuring accessibility for all older adults users. In the same way, policymakers should incentivize inclusive solutions, promote digital literacy, and support integration across health, social, financial, and educational domains. In the end, longitudinal and empirical research, particularly among rural and digitally marginalized populations, is needed to evaluate real-world adoption, long-term outcomes, and cross-sector integration, while co-design approaches involving older adults users can ensure innovations are aligned with actual needs and preferences. Funding Statement The author(s) declared that financial support was received for this work and/or its publication. Research on the Concepts and Behaviors of Filial Piety and Aging among the New older adults from the Perspective of Active Aging (23YJAZH120), a general project funded by the Humanities and Social Science Fund of Ministry of Education of China. Footnotes Edited by: Matthew Aplin-Houtz , Brooklyn College, United States Reviewed by: Tifeng Liu , Hohai University, China Yue Ming , Hubei University of Technology, China Data availability statement The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author. Author contributions BWS: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. MI: Conceptualization, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing. MH: Conceptualization, Formal analysis, Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. ST: Conceptualization, Data curation, Investigation, Visualization, Writing – original draft, Writing – review & editing. NK: Resources, Software, Visualization, Writing – original draft, Writing – review & editing. JW: Data curation, Methodology, Resources, Validation, Visualization, Writing – review & editing. Conflict of interest The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Generative AI statement The author(s) declared that Generative AI was not used in the creation of this manuscript. 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