Breaking the Aging Dilemma: A Study on High-Quality Development Models for Pension Tourism Industry Driven by New Quality Productive Forces

Breaking the Aging Dilemma: A Study on High-Quality Development Models for Pension Tourism Industry Driven by New Quality Productive Forces | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Breaking the Aging Dilemma: A Study on High-Quality Development Models for Pension Tourism Industry Driven by New Quality Productive Forces xuejun Chen, junwen Ai, yue Wu, kaiyu Mu, li Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7619668/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract In the context of the strategic response to population aging, the high-quality development of the elderly tourism industry plays a crucial role in addressing the structural contradictions between economic growth and insufficient elderly care. Under the driving force of new-quality productive forces, scientifically selecting development models has become the key to achieving high-quality development in the elderly tourism industry. Based on multiple case studies, a theoretical model for the high-quality development of the elderly tourism industry driven by new-type productive forces has been constructed. Taking China's 30 provinces (regions and municipalities) as the research object, the occurrence of high-quality development models in the elderly tourism industry across provinces has been examined. Additionally, a multiple regression model has been constructed to empirically test the effects of development model influencing factors. The research results show that there are three types of high-quality development models in China's elderly tourism industry: technology innovation-driven, business model upgrading-driven, and talent transformation-driven. The high-quality development model of China's elderly tourism industry exhibits regional differentiation characteristics. The technology innovation-driven model is prevalent in eastern, central, and western regions, the business model upgrade-driven model primarily occurs in economically developed provinces, and the talent transformation-driven model is concentrated in central and western regions. The selection of high-quality development models for the elderly tourism industry is influenced by a combination of internal and external factors, including human capital, industrial efficiency, the fiscal burden of an aging population, industrial structure upgrading, R&D investment, economic development levels, government support, marketization levels, locational conditions, and urban development. It is necessary to comprehensively consider the combined influence of internal and external factors to select an appropriate development model. Business and commerce/Economics Social science/Economics Earth and environmental sciences/Environmental social sciences New quality productivity Pension tourism High-quality development Development model Figures Figure 1 Introduction With the acceleration of the global aging process, the size of China's elderly population continues to expand. By the end of 2024, China's population aged 60 and above will reach 310 million, accounting for 22% of the total population. Population aging has given rise to the rise of "silver hair economy"; and pension tourism industry, as one of the important forms of silver hair economy, has gradually become a new growth point to promote consumption upgrading and optimize the industrial structure. 2024 General Office of the State Council issued "Opinions on the Development of Silver Hair Economy and Enhancement of Well-Being of the Elderly", which puts forward the development of a new type of pension industry, namely, residential pension. The new quality productivity is the key to high quality economy in the new era. New quality productivity is the core kinetic energy for high-quality economic development in the new era, and its essence is a new type of productivity pattern led by scientific and technological innovation and characterized by a leap in total factor productivity. The report of the 20th CPC National Congress clearly pointed out that "opening up new fields and new tracks for development, shaping new kinetic energy and new advantages for development", and took the new quality productivity as the strategic pivot point for building a modernized industrial system. The "Overall Layout Plan for the Construction of Digital China" released by the State Council in 2023 emphasized the need to build a digital economy through " digital technology to empower the real economy and promote the development of new industries". Digital technology empowers the real economy and promotes changes in the mode of production, lifestyle and governance", the core of which lies in reconfiguring the way factors of production are combined - expanding from new types of factors such as traditional labor, capital, algorithms, and green technology. In September 2023, General Secretary Xi Jinping proposed for the first time during his visit to Heilongjiang, and emphasized "integrating scientific and technological innovation resources, leading the development of strategic emerging industries and future industries, and accelerating the formation of new quality productivity". This concept provides a new paradigm for the high-quality development of the pension and tourism industry. The new quality productivity promotes the change of social production mode and industrial operation mode, and brings subversive changes to the development mode of pension tourism industry. The new quality productivity centered on artificial intelligence, Internet of Things, and big data is reshaping the pension tourism service industry, giving rise to new forms of business such as intelligent recreation communities and digital residence platforms. However, there are significant differences in resource endowment, technological innovation and policy support among provinces in China. How to scientifically choose a high-quality development model for the pension tourism industry that suits the actual situation has become a key proposition to crack the contradiction between the upgrading of the demand for pension tourism and the lagging of the industrial supply. Based on this, firstly, a qualitative exploratory study is conducted using the rooting theory to establish a theoretical model of the high-quality development mode of the pension tourism industry driven by the new quality productivity; secondly, the occurrence of the high-quality development mode of the pension tourism industry in 30 provinces (cities and districts) in China from 2014 to 2023 is empirically analyzed with 30 provinces (cities and districts) as the object of the study and a multiple regression model is constructed to test the development mode of the pension tourism industry in the 30 provinces (cities and districts) in China. construct a multiple regression model to test the effect of the influencing factors of the development mode. The article aims to answer four core questions: (1) What are the high-quality development patterns of the senior care tourism industry driven by new quality productivity? (2) What are the high-quality development modes chosen by the senior care tourism industry in each province (city and district)? (3) What factors affect the selection of high-quality development models for the elderly tourism industry? (4) How to choose the high-quality development model of senior care tourism industry according to regional realities? Literature review 1.1 Studies on the high-quality development model of senior citizen tourism industry driven by new quality productivity As the core driving force for industrial change, the impact of new quality productivity on the high-quality development model of the pension and tourism industry has become a new area of concern in the academic community. Existing researches have explored the three dimensions, namely, industrial integration perspective, empowerment mechanism and mode selection, which provide multiple perspectives for understanding this topic. First of all, in terms of industrial integration research, scholars at home and abroad generally take the perspective of "+tourism" research to explore the empowerment path of new quality productivity to the segmented areas. Research involves "senior + tourism" [ 1 ] , "sports + tourism" [ 2 ] , "culture + tourism" [ 3 ] , "digital + tourism" [ 4 ] , "Rural + Tourism" [ 5 ] and other fields, systematically sorting out the mechanism of new quality productivity in factor allocation, industry innovation and other aspects. Foreign studies focus on medical tourism [ 6 ] , cultural tourism [ 7 ] , digital tourism [ 8 ] and other fields; at the same time, the innovative development mode of digitization-driven pension and tourism industry [ 9 ][ 10 ] is studied. Elzbieta Szymaska constructs a model of health tourism innovation system and proposes three modes of technological innovation empowerment [ 11 ] . The above studies reveal the role of new quality productivity in driving the high-quality development of the senior tourism industry, but there is a lack of systematic research on how new quality productivity drives the high-quality development model of the senior tourism industry. Second, in terms of the research methodology of the enabling mechanism, the academic community has formed a complementary qualitative and quantitative research. Qualitative research has verified the enabling effect of new technology on eco-health tourism [ 12 ] and explained the key mechanisms such as innovation-driven factor allocation and structural optimization of digital technology [ 13 ][ 14 ] ; quantitative research has empirically verified the enabling effect of new technology on eco-health tourism through action research [ 15 ] , spatial modeling [ 16 ] , geometrical analysis [ 17 ] and other methods. and other methods to empirically verify the impact of digital innovation on industrial performance. Meanwhile, the research on the senior care industry proposes a smart senior care model [ 18 ] and identifies internal and external driving factors [ 19 ] , which provides a reference for the research on senior care tourism model, but has not yet formed a systematic framework applicable to the integration scenario of "senior care + tourism". Finally, regarding the research on mode selection, the existing studies present multiple perspectives to explore. First is the integrated development model. This includes the “tourism innovation + public welfare elderly care” integrated development model [ 20 ] , the integrated development model of traditional Chinese medicine culture and elderly care tourism industry [ 21 ] , and the rural tourism elderly care model [ 22 ] . Second is the travel-residence elderly care model. This includes the rural travel-residence elderly care model [ 23 ] , the “medical care and travel-residence” combined elderly care model [ 24 ] , and the smart travel-residence elderly care model [ 25 ] . Third, other models. These include the medical wellness tourism development model [ 26 ] and the tourism-oriented retirement town development model [ 27 ] . However, studies on the selection of high-quality development models for the pension tourism industry driven by new quality productivity are still very limited. Therefore, it is of great significance to systematically study the high-quality development mode of China's elderly tourism industry and its choice from the perspective of new productivity empowerment. 1.2 Studies on the influencing factors of the high-quality development mode choice of the senior care tourism industry Research on the influencing factors of the selection of high-quality development models for the elderly tourism industry has evolved from a single-factor approach to a multi-dimensional approach. Early studies focused on single factors, and foreign scholars explored the influence of political system [ 28 ] , organizational innovation [ 29 ] , infrastructure [ 30 ] , information technology [ 31 ] , etc., on the tourism industry; while domestic studies focused on the influence of governmental behaviors [ 33 ] , environmental system [ 33 ] , digital economy [ 34 ] , personal characteristics [ 35 ] ,industry structure [ 36 ] and other factors on the tourism industry. This type of research reveals the independent influence of key elements, but neglects the interaction between multidimensional elements. With the depth of research, the multidimensional factor integration perspective gradually becomes the mainstream of research. Based on the multidimensional analysis framework, some scholars proposed the synergistic mechanism of grassroots power, market power and potential power [ 37 ] , revealing the synergistic mechanism among the power sources, which provides a reference to understand the endogenous development logic of the elderly tourism industry. Refining the influencing factors based on the four dimensions of supply, demand, innovation and policy [ 38 ] highlights the interaction between policy and market in the senior tourism industry. Meanwhile, some scholars have studied the influence of six factors, namely, formal system, entrepreneurial environment, population base, medical level, regional economic development level, and openness to the outside world, on the development model of the pension tourism industry [ 39 ][ 40 ][ 41 ] foreign scholars have formed a consensus that multiple factors jointly influence the high-quality development of the pension tourism industry, but there are still different understandings of the key influencing factors. There are different understandings of the key influencing factors. Some scholars emphasize the influence of factors such as health, culture, and medical care [ 42 ] ; some scholars believe that the destination environment is central to senior tourism, and that infrastructure, workforce training, and so on, are more important [ 43 ] ; Hu analyzes the influence on the tourism industry, such as tourism resources, facilities, and transportation, from the perspective of spatial heterogeneity [ 44 ] . In summary, although research on the selection of high-quality development mode for the elderly tourism industry at home and abroad has made great progress, there are still many shortcomings: firstly, there is a lack of research on high-quality development models for the elderly tourism industry from the perspective of new productive forces; secondly, there is a lack of research results on the selection of high-quality development models for the elderly tourism industry; thirdly, there is a lack of empirical research on the factors influencing model selection. Therefore, from the perspective of new productive forces, researching the models and selection of high-quality development for the elderly tourism industry has important research value. Research overview A mixed research method is adopted, including rooted theory (Study 1) and empirical analysis (Study 2). Study 1 uses qualitative exploratory analysis in order to identify three new qualitative productivity-driven high-quality development modes of the pension tourism industry and establish a theoretical model of high-quality development modes of the pension tourism industry. Study 2 is designed to examine the occurrence of high-quality development modes of the senior care tourism industry in each province of China based on panel data of 30 provinces (cities and districts) in China from 2014–2023, and constructs a multiple regression model to test the effects of the influencing factors of mode selection. The two studies build on and support each other in an incremental manner. The combination of qualitative and quantitative methods strengthens the internal and external validity of the study and ensures its rigor [ 45 ] . Study 1: Exploratory theoretical modeling Study 1 aims to conduct exploratory analysis and refine the typical model of the high-quality development of the elderly tourism industry, in order to establish a theoretical model of the high-quality development model of the elderly tourism industry driven by the new quality productivity. 3.1 Data collection In the data collection stage, information is obtained from multiple data sources to ensure the comprehensiveness and accuracy of the data. First of all, the primary data mainly came from telephone interviews with the main persons in charge of the case enterprises, online consultation and field research. Among them, the six interviewees are all responsible for the elderly tourism business, and the interviews focus on the application of technology, product upgrading, talent management and development mode of the elderly tourism enterprises, etc. The interviews lasted from 20 to 40 minutes, and the total length of the interviews amounted to 3.5 hours, and the number of words in the audio recordings and translations amounted to 32,000 words. Secondly, based on the principles of typical representativeness and data availability, 10 pension tourism enterprises were screened as research samples (see Table 1 ); the case enterprises were divided into 7 modeling groups and 3 testing groups, which can not only refine the differentiated development mode, but also verify the theoretical saturation of the theoretical model through comparison to ensure the research credibility. The enterprise case materials are mainly derived from public interview records, enterprise publicity documentaries, enterprise official websites, enterprise official website case database, enterprise annual reports, news special reports, academic papers and industry reports. By organizing and filtering the relevant information, the secondary information of nearly 50,000 words was finally formed. Table 1 Sample cases of pension tourism enterprises serial number company identification Areas covered Enterprise size Development model Case Usage A Taikang Home Medical Recreation, Intelligent Elderly Care, Cultural and Tourism Integration mega Closed-loop model of "insurance-healthcare-cultural tourism". modelling B Greentown Wuzhen Yayuan Cultural tourism property, education and retirement, eco-community mega Ecological Integration Model of "Culture, Education, Tourism and Nutrition" modelling C Kaurau City Group Community Aged Care, Intelligent Platform, Ageing Supply Chain, Travelling Services mega The "four-level grid + digital centre" model modelling D green pine health care IoT technology, AI health monitoring, insurance data services, travel safety medium-sized "IoT data capitalisation" model modelling E source of affinity Membership-based retirement, financialised benefits, blockchain deposits, inter-regional healthcare medium-sized "Membership financialisation + blockchain trust" model modelling F Chengdu Global International Travel Service Senior speciality tours, high-end customised tours medium-sized "Online + offline" integration model modelling G Sichuan Huayun International Travel Service silver haired train medium-sized "Resource + Channel" dual-drive model modelling H Ankangtong Intelligent Elderly Care IoT security monitoring, subscription-based services, inclusive ageing, emergency response medium-sized The "cellular safety net" model inspect I Hainan Puren Residential Retirement Base Climate medicine, Chinese medicine and health care, cross-border data flow, intellectual property operation medium-sized "Climate Healthcare IP + Data Across Borders" Model inspect J Beijing Golden Cane International Retirement Residence Film and TV IP development, immersive recreation, extended reality technology, cultural derivation medium-sized "Film and TV IP Immersion Recreation" Model inspect 3.2 Data analysis The 35,000-word interviews with six interviewees were analyzed for patterns using the three-level coding procedure of procedural rooting theory. First, the researcher reviewed all interviews to ensure a comprehensive understanding of the data. Second, open coding was conducted, using Nvivo software to initially conceptualize the raw data as labels, and a total of 91 core concepts and 17 initial categories were extracted. Again, on the basis of the 17 initial categories, the categories were subjected to principal axial coding to further generalize and extract the main categories, and finally three main categories were summarized. Finally, through further summarization and abstraction of the main categories and sub-categories, a core category, i.e., "high-quality development model of the pension and tourism industry driven by new quality productivity", was formed, and a theoretical model describing the conceptual connotation of each development model was formed. In order to ensure the validity of the qualitative results, the concepts and categories were extracted by labeling the three case studies of the modeling group, open coding was performed to refine the concepts and categories, and the concepts and categories were compared with those of the modeling group to verify the degree of theoretical saturation. In the end, 42 core concepts and 8 initial categories were extracted, and all of them were among the categories summarized by the modeling group, with no other new categories or logical connections. Accordingly, it can be judged that the theoretical saturation degree of "the theoretical model of the high-quality development mode of pension tourism industry driven by new quality productivity" is high. 3.3 Research results 3.3.1 The model of high-quality development of pension tourism industry driven by new quality productivity Based on the above analysis, the model of high-quality development of senior care tourism industry driven by new quality productivity (see Fig. 1 ) is concluded, i.e., technological innovation-driven development model, industry upgrading-driven development model and talent change-driven development model. The three modes show the dynamic evolution path of "technological innovation provides tools→industrial upgrading creates value→talent change enhances effectiveness". 3.3.1.1 Technological innovation-driven development mode The technology innovation-driven development mode takes the triple technology promotion of "intelligent technology - digital technology - green technology" as the core orientation, and reconstructs the value network of the pension tourism industry through technological breakthroughs, integration and application. Its essence lies in: relying on the dynamic synergistic relationship between intelligent hardware and data elements under the leadership of digital intelligence technology, breaking through the boundaries of traditional pension tourism services, driving system integration through technological iteration, realizing the pension service scenario from unitary to intelligent, ecological leap, and constructing a whole-area interconnected intelligent pension tourism ecosystem. At the same time, the technology innovation-driven development model is dominated by three characteristics: technology dominance, intelligent penetration, and dynamic supply and demand matching. Technology-driven is to take technology as the core driving force to realize the transformation of service scenes to "intelligent senior care tourism" with high-end technology; intelligent penetration is that deeply embed technology into the whole process of service, covering health data management, intelligent service response, upgrading of ageing facilities, etc., and forming an all-round technical support system through intelligent monitoring and digital technology. Intelligent penetration is the deep embedding of technology into the whole process of service, covering health data management, intelligent service response, upgrading of aging facilities, etc., and forming an all-round technical support system through intelligent monitoring and digital technology. Dynamic supply and demand matching is based on the ability of technology integration, integrating fragmented technology modules into an interconnected intelligent senior care tourism platform, relying on digital platforms to realize the dynamic equipping of medical resources, senior care tourism products and user demand, and forming a technology-driven dynamic matching network of supply and demand. 3.3.1.2 Industry upgrade-driven development mode The industry upgrading-driven development mode takes the triple element drive of "new industry - new products - new facilities" as the core orientation, and extends the value chain of the pension tourism industry through product reorganization and industry innovation. This model focuses on the upgrading of the whole industry of pension tourism, supported by resource allocation capacity, with the core logic of industry integration driven by product innovation, and realizing the transformation of hardware and facilities and the construction of product matrix through the integration of emerging industries, so as to promote the transformation of the pension tourism industry from a single service to a differentiated product system. The industry upgrade-driven development mode are characterized by three features: resource integration, product aging, and industry integration. Resource integration is the pension tourism industry through the integration of pension resources, tourism resources, medical resources, social resources, etc., to optimize the efficiency of resource allocation. Product aging is oriented toward the high-quality elderly tourism needs of the elderly, developing low-intensity, high-experience differentiated products to meet the diverse needs of the elderly. Business integration refers to promoting the integration of “cultural tourism,” “health and wellness,” “medical care,” and other businesses through chain operations and cross-industry cooperation, forming a new diversified elderly tourism business. 3.3.1.3 Talent change-driven development mode The talent change-driven development model takes the triple upgrade of "skill enhancement, service innovation and management innovation" as the core orientation, and enhances the competitiveness of the industry by strengthening the ability of talents and additional services. The model emphasizes the core of professional service supply and humane management, and the synergistic innovation of "talent-service-management" as the main line of logic, promoting the leap from standardized service to personalized service through the skill training and optimization of the management mechanism under the leadership of talent echelon construction, in order to build the matrix of high value-added service capacity. The talent-driven development model is characterized by three key features: service specialization, skill-driven innovation, and capability matrixing. Service specialization refers to providing precise services through professional teams specializing in elderly care, tourism, healthcare, and wellness. Skill-driven innovation involves enhancing the service skills of staff through aging-friendly service training, shifting the focus from service quality alone to a balance between service quality and emotional support. Capability matrixing involves restructuring the diverse capabilities possessed by individual employees or teams, and constructing a service capability matrix centered on core elements such as talent pipelines, service standards, and management mechanisms. 3.3.2 Comparison of high-quality development models of new quality productivity-driven pension tourism industry Driven by the new quality of productivity, the three models of high-quality development of the pension tourism industry have certain links, that is, all of them take the improvement of the high-quality development of the pension tourism industry as the core objective, and unfold with the logical main line of "strategic motivation→capability base→development elements→development channels", and the three models show a spiral interaction; at the same time, there are differences in terms of the applicable. At the same time, there are differences in application, driving core and value creation path (see Table 2 ). Table 2 Comparison of the characteristics of high-quality development modes of pension tourism industry driven by new quality productivity Development Mode Applicable subject Driving core Value creation path Typical Practice Technology Innovation Driven Technology-intensive organizations, large pension groups with R&D capabilities Digital Intelligence Technology Tool upgrading → system integration → ecological reconstruction Taikang Home Powerback Rehabilitation System, Philips EPIQ5 Medical Data Integration Industry Upgrade Driven Resource-intensive regions, small and medium-sized senior living communities requiring product differentiation Industry Integration Resource optimization → product design → industry extension Yueyuan community "natural oxygen bar" culture and tourism scene, summer recreation tour product matrix Talent change-driven Service-oriented institutions, senior care service enterprises that require both standardization and humanization High-quality talents Capacity building → standardization → experience upgrading "Nine division team" precision care, silver-haired tour guide and geriatric academy Study 2: Empirical Analysis 4.1 Variable selection Panel data of 30 provinces in China (excluding Tibet Autonomous Region, Taiwan Province, Hong Kong and Macao Special Administrative Regions) from 2014–2023 are used as the research sample. The data mainly come from China Statistical Yearbook, China Science and Technology Statistical Yearbook, China Tertiary Industry Statistical Yearbook, China Culture and Tourism Statistical Yearbook, China Civil Affairs Statistical Yearbook, China Social Statistical Yearbook, the official web site of the National Bureau of Statistics, and the official statistical yearbooks of provinces and cities, etc., where some of the missing data are handled by using analogical or interpolation methods. 4.1.1 Explained variables The occurrence of the high-quality development mode of the pension tourism industry is the explanatory variable. It includes the occurrence of technological innovation-driven development mode, the occurrence of industry upgrading-driven development mode and the occurrence of talent change-driven development mode. The specific measurements are as follows: (1) Technological innovation-driven mode measurement index - Technology Driven Index (TDI) In formula (1), PA represents the number of tourism patents authorized, RD represents the number of enterprises carrying out innovation activities, DT represents the level of digital transformation, expressed as the Internet penetration rate, and E represents the economic impact factor, which is the ratio of the income of the pension and tourism industry to GDP. \(\:\frac{PA}{RD}\) represents the efficiency of R&D investment.1+ \(\:\text{D}\text{T}\) represents the impact factor of the level of digital transformation, reflecting the promotion effect of digital transformation on technology-driven; the higher the level of digitization, the more widely the technology is applied, and the technology-driven index will be increased accordingly.E reflects the importance of the senior care tourism industry in the economy. If the industry's contribution to the economy is greater, the more significant the impact of technology drive on its development. (2) Industry upgrade-driven mode measurement indicator–New Industry Driven Index (NEDI) The New Industry Driving Index (NEDI) is used to measure the impact of the integration of new industries with the tourism industry on the development of the pension and tourism industry. Characterized by the health industry and tourism industry integration index, the specific measurement index system is shown in Table 3 . Table 3 Evaluation index system of integration between health industry and tourism industry Target layer The criteria level Indicator layer weight Health industry development index Industrial base Number of medical and health institutions 22.12% Number of beds per 1,000 people in medical and health institutions 11.91% Number of nursing homes 19.39% industrial development Number of old-age insurance participants (10,000) 22.96% Total revenue of medical institutions 23.63% Tourism industry development index Industrial base Number of star hotels 26.10% Number of travel agencies 20.70% Number of A-level scenic spots 25.77% industrial development Total tourism revenue 27.43% Calculate the development of the health industry and tourism industry separately, and use formula (2) to calculate their comprehensive integration degree [ 46 ] . NEDI= \(\:\frac{{\text{H}\text{I}}_{\text{H}\text{e}\text{a}\text{l}\text{t}\text{h}\:\text{i}\text{n}\text{d}\text{u}\text{s}\text{t}\text{r}\text{y}}}{{\text{T}\text{I}}_{\text{T}\text{o}\text{u}\text{r}\text{i}\text{s}\text{m}\:\text{i}\text{n}\text{d}\text{u}\text{s}\text{t}\text{r}\text{y}}}\) (2) (3) Talent change-driven mode measure - Talent Concentration Degree (TCD) TCD = \(\:{Ln（（EPC}_{\text{R}}+{TP}_{\text{R}}）\times\:\frac{{EP}_{R}}{{EDL}_{R}}）\) (3) In Eq. (3), EPC stands for elderly care practitioners, TP stands for tourism practitioners, EDL stands for educational attainment, and EP stands for the proportion of the elderly population to the total population. The calculation step is divided into two steps, the first part \(\:{EPC}_{R}+{TP}_{R}\) represents the region's employees in the field of elderly care and tourism. The second part \(\:\frac{{EP}_{R}}{{EDL}_{R}}\) represents the ratio of the educational level of the region relative to the aging population, reflecting the relationship between the quality of the talent in the region and the pressure of aging. The final result, TCD , is the product of the two parts taken as a logarithm, which comprehensively reflects the concentration of high-quality talent in the region. 4.1.2 Explanatory variables The study identifies ten internal and external factors that influence the selection of high-quality development models for the elderly tourism industry driven by new productive forces. The internal factors include human capital (HCM), industrial efficiency (IE), aging fiscal burden (AFB), industrial structure upgrading (ISU), and research and development investment (RDI). The external factors include economic development level (EDL), government support (GS), marketization degree (MD), locational conditions (LC), and urban development (UC). The specific indicators selected are shown in Table 4 . Table 4 Indicator system of influencing factors for the selection of high-quality development mode of pension tourism industry driven by new quality productivity Influencing Factor Variable Symbol Metric Internal influencing factors Human capital HCM The proportion of the number of people with a bachelor's degree or above in the total employment Industrial efficiency IE Total revenue of elderly care / fixed asset investment of elderly care institutions (take logarithm) Aging fiscal burden AFB (Local financial expenditure on science and technology + local financial expenditure on education)/local financial general budget expenditure Upgrading of an industrial structure ISU Industrial structure upgrading = (the added value of the primary industry *1 + the added value of the secondary industry *2 + the added value of the tertiary \(\:-\sum\:_{\text{m}=1}^{3}（{\text{Y}}_{\text{m}}/\text{Y}){\text{Y}}_{\text{m}}{\text{L}}_{\text{m}}）/(\text{Y}/\text{L})-1\) industry *3)/GDP; Industrial structure rationalization index = |(|. Among them, Y and L represent output and labor input, and m = 1,2,3 distribution represents the primary, secondary and tertiary industries. Research input RDI The ratio of R&D investment intensity to total regional tourism revenue to GDP External influencing factors Level of economic development EDL Regional GDP per capita Government support GS Expenditure on elderly welfare in the Civil Affairs sector (logarithm) Marketization degree MD Marketization index Location conditions LC Passenger turnover (logarithm) Urban construction UC Green coverage rate of built-up areas 4.1.3 Control variables Based on the consideration of the robustness of the regression analysis results, the following control variables are introduced: ①Retirement Tourism Industry Agglomeration (RTAC), with "the ratio of the total income of regional retirement tourism to the national total income of retirement tourism" as the proxy variable; ②Openness to the outside world (OPEN), represented by "the proportion of total import and export trade to GDP by region"; ③Transportation infrastructure level (TIL), represented by "the proportion of total import and export trade to GDP by region", in order to eliminate data heteroskedasticity and linearize the relationship between variables, the "total freight volume" is treated as a natural logarithm. 4.2 Measurement of the occurrence of high-quality development mode of the pension tourism industry 4.2.1 Occurrence of technological innovation-driven development mode Based on formula (1), the technology-driven index of China's 30 provinces (cities and districts) in the senior care tourism industry from 2014 to 2023 is calculated. It is set that if the increase of a province (city or region) exceeds the average increase of the whole country in the examination period, it is recognized that a technological innovation-driven development mode has occurred in that province. As shown in Table 5 of the calculation results, the average increase of the country during the period of 2014–2023 is 25.79%; among them, there are 16 provinces (municipalities and districts) exceeding the average increase, then the technological innovation-driven development mode has occurred in the senior care tourism industry of 16 provinces (municipalities and districts). On the whole, the occurrence of technological innovation-driven development mode nationwide presents significant regional differentiation characteristics. Relying on the strong economic foundation and industrial resource advantages, the eastern region (e.g., Jiangsu, Tianjin, etc.) empowers the high-quality development of the pension tourism industry with industrial technology through the application of intelligent pension technology, digital tourism platform and other innovative means. Central region (such as Anhui, Jiangxi, etc.) relying on resource integration to form a latecomer competitiveness, and actively undertake the transfer of industries in the east, the use of regional ecological resources to develop intelligent recreation and tourism. Western regions (e.g. Chongqing, Sichuan, Ningxia, etc.) rely on policy support and digital upgrading of cultural and tourism resources, with significant technology-driven effects. Table 5 Changes in provinces with technological innovation-driven development mode Order number Province 2014 Maximum value during the period Amplification 1 Tianjin 1.1512 1.4998 30.28% 2 Jiangsu 1.1848 1.5581 31.50% 3 Zhejiang 1.2177 1.5451 26.89% 4 Anhui 1.0978 1.4830 35.09% 5 Jiangxi 1.1064 1.4664 32.53% 6 Henan 1.1178 1.4355 28.42% 7 Hunan 1.1174 1.4189 26.99% 8 Guangxi 1.1449 1.4693 28.33% 9 Hainan 1.2361 1.6084 30.12% 10 Chongqing 1.1668 1.4907 27.75% 11 Sichuan 1.1174 1.4527 30.02% 12 Shaanxi Province 1.1577 1.4918 28.86% 13 Gansu 1.1091 1.4971 25.92% 14 Qinghai 1.2514 1.5878 26.88% 15 Ningxia 1.1648 1.5295 31.31% 16 Xinjiang 1.1798 1.5200 28.83% 4.2.2 Occurrence of industry upgrade-driven development mode Based on formula (2), the new mode-driven index of China's pension tourism industry in 30 provinces (cities and regions) from 2014 to 2023 can be calculated. It is set that if the increase of a province (city or region) exceeds the average increase of the whole country in the examination period, it is recognized that the industry upgrade-driven development mode has occurred in that province. Table 6 shows that the national average increase during 2014–2023 is 23.6%; among them, there are 9 provinces (cities and districts) exceeding the national average increase, and 9 provinces (cities and districts) have experienced the industry upgrading-driven development mode in the senior care tourism industry The 9 provinces (cities and districts) show significant regional differentiation characteristics. High growth rate areas concentrated in economically developed provinces (such as Tianjin, Beijing, Shanghai), which rely on the advantages of talent, capital and technology to realize the transformation of the elderly tourism industry into a high-end industry. Medium growth rate provinces such as Jilin, Fujian, Hainan, etc. achieve differentiated development through the development of special resources. In contrast, the growth rate of traditional tourism provinces such as Liaoning, Zhejiang and Guangdong is on the low side, reflecting their gradual exploration of new market segments and gradual optimization of industry structure in the traditional path of dependence. Table 6 Changes in provinces with industry upgrading-driven development mode Order number Province 2014 Maximum value during the period Amplification 1 Beijing 0.2830 0.5762 103.61% 2 Tianjin 0.4881 1.3098 168.36% 3 Liaoning 0.9354 1.1594 23.95% 4 Jilin 1.1594 1.9888 71.54% 5 Shanghai 0.3415 0.6716 96.68% 6 Zhejiang 0.6033 0.7928 31.42% 7 Fujian 0.8712 1.3939 60.00% 8 Guangdong 0.8319 1.1069 33.06% 9 Hainan 0.5325 0.7722 45.01% 4.2.3 Occurrence of talent change-driven development model Based on formula (3), the talent concentration of the senior care tourism industry in 30 provinces (cities and districts) in China from 2014 to 2023 can be calculated. It is set that if the increase of a province (city or region) exceeds the average increase of the whole country in the examination period, it is recognized that the talent change-driven development mode has occurred in that province. As shown in Table 7 of the calculation results, the national average increase during the period of 2014–2023 is 14.80%; among them, there are 14 provinces (municipalities and districts) exceeding the national average increase, and the talent change-driven development mode has occurred in the senior care tourism industry in 14 provinces (municipalities and districts). The talent change-driven development mode in central and western regions showed strong growth potential; relying on the strategy of the rise of central China and the development of western China, accelerating the pace of talent introduction has promoted the high-quality development of the senior care tourism industry. In addition, Yunnan, Guizhou and Sichuan are rich in recreational and cultural tourism resources, attracting a large number of elderly tourists and professionals to gather, forming a favorable ecological environment for the development of the senior tourism industry. Table 7 Changes in provinces with talent change-driven development model Order number Province 2014 Maximum value during the period Amplification 1 Hebei 6.8322 7.9886 16.93% 2 Liaoning 6.7630 7.9060 16.90% 3 Heilongjiang 5.7303 7.1846 25.38% 4 Anhui 6.7089 7.7149 14.99% 5 Jiangxi 6.3151 7.4961 18.70% 6 Henan 6.5923 7.8279 18.74% 7 Hubei 6.8750 7.9996 16.36% 8 Hunan 7.0227 8.3746 19.25% 9 Sichuan 7.2434 8.8836 22.64% 10 Guizhou 6.0041 7.2522 20.79% 11 Yunnan 6.7035 8.1393 21.42% 12 Shaanxi 6.6060 7.6244 15.42% 13 Qinghai 4.5562 5.6546 24.11% 14 Ningxia 4.6518 5.4577 17.32% 4.3 Analysis of influencing factors of the high-quality development model of the pension tourism industry The fixed effect model is used to test the effect of the above influencing factors on the high-quality development mode of the pension tourism industry. The introduction of fixed effects can effectively control the endogeneity problem, thus enhancing the accuracy of causality estimation. 4.3.1 Analysis of the results of the influencing factors of the technological innovation-driven development model Based on a study of provinces with technology innovation-driven development model, the 16 provinces whose technology-driven index (TDI) exceeds the national average increase are selected as a sub-sample to form a panel data composed of 16 provinces during the 10-year period of 2014–2023, and the explanatory variable is set to be the TDI for model estimation. First, the samples are tested for multicollinearity; the correlation coefficients among the explanatory variables are basically not greater than 0.8, indicating that the correlation among the explanatory variables is weak and there is no highly linear correlation. For the consideration of the robustness of the estimation results, the three control variables were used as the basis for the fitting process, and the core explanatory variables were added one by one (the results are shown in Table 8 ). The results show that the model works well and the R² value climbs steadily from 0.8282 to 0.9480 gradually, implying that the explanatory power of the model for the changes in TDI is increasing. The improvement of TDI is the result of the synergistic effect of internal and external factors, but there are significant differences in the paths and effect strengths of different factors. In terms of model effects and variable impacts (see Table 8 ), human capital, industrial structure upgrading, level of economic development, government support, urban construction and level of transportation infrastructure have significant positive impacts on the technology-driven index, while the degree of marketization, industrial efficiency, aging financial burden, and R&D investment do not reach significant impacts, location conditions negatively affect the technology-driven index, and the impact of the degree of openness to the outside world fluctuates with the The influence of openness to the outside world fluctuates positively and negatively with the inclusion of model variables. This indicates that it is necessary to focus on optimizing industrial structure, improving the quality of economic and urbanization development, and improving transportation infrastructure to strengthen the drive for technological innovation. Table 8 Regression results of technological innovation driving factors (1) TDI (2) TDI (3) TDI (4) TDI (5) TDI (6) TDI (7) TDI (8) TDI (9) TDI (10) TDI HCM 0.0374 *** (15.73) 0.0381 *** (16.05) 0.0373 *** (15.30) 0.0318 *** (12.03) 0.0303 *** (11.48) 0.0147*** (7.11) 0.0142 *** (6.93) 0.0145 *** (7.04) 0.0140 *** (6.84) 0.0130 *** (6.35) IE 0.0155** (2.07) 0.0167** (2.22) 0.0146** (2.05) 0.0154** (2.22) 0.0006 (0.13) 0.0004 (0.09) 0.0009 (0.20) 0.0085 (1.46) 0.0084 (1.47) AFB 0.6302 (1.36) 0.7489* (1.70) 0.6707 (1.56) -0.0346 (-0.12) -0.726 (-0.26) -0.0591 (-0.21) -0.1016 (-0.36) 0.0334 (0.12) ISU 0.3493 *** (4.20) 0.3359 *** (4.12) 0.1947 *** (3.60) 0.1976 *** (3.68) 0.1993 *** (3.73) 0.1868 (3.52) 0.1820 *** (3.48) RDI 0.6472 *** (2.75) -0.0651 (-0.40) -0.0544 (-0.34) -0.0654 (-0.41) -0.1217 (-0.76) -0.0882 (-0.56) EDL 0.3244 *** (13.60) 0.3167 *** (13.20) 0.2981 *** (10.88) 0.2771 *** (9.61) 0.2899 *** (10.03) GS 0.0053 * (1.87) 0.0052 * (1.85) 0.0053 * (1.90) 0.0050 * (1.83) MD 0.0070 (1.39) 0.0065 (1.30) 0.0039 (0.78) LC -0.0259 ** (-2.11) -0.0257 ** (-2.13) UC 0.0002 ** (2.29) RTAC 0.3692 (0.255) 0.1291 (0.38) 0.0823 (0.24) -0.0292 (-0.09) -0.4361 (-1.25) -0.1111 (-0.49) -0.1063 (-0.47) -0.0954 (-0.42) -0.1698 (-0.75) -0.1406 (-0.63) OPEN 0.3335 *** (2.76) 0.3954 *** (3.21) 0.3333 ** (2.54) 0.2197 * (1.73) 0.1479 (1.17) -0.2031 ** (-2.35) -0.2174 ** (-2.53) -0.2152 ** (-2.51) -0.2058 ** (-2.43) -0.2920 *** (-3.19) TIL 0.2224 *** (5.66) 0.2069 *** (5.23) 0.2043 ** (5.17) 0.2135 *** (5.71) 0.2137 *** (5.85) 0.0879 *** (3.44) 0.0870 *** (3.44) 0.0804 *** (3.13) 0.0903 *** (3.50) 0.0999 *** (3.89) _cons -1.7160 *** (-3.95) 1.186 *** (7.92) 1.367 *** (8.94) 1.262 *** (8.55) 1.382 *** (9.21) -1.952 *** (-5.15) -1.798 *** (-4.81) -1.970 *** (-4.87) -1.384 *** (-3.53) -1.390 *** (-3.56) N 160 160 160 160 160 160 160 160 160 160 R 2 0.8282 0.8334 0.8355 0.8543 0.8620 0.9418 0.9432 0.9440 0.9459 0.9480 Note: The numbers in parentheses are t-statistics, and *, ** and *** indicate the significance levels of 10%,5% and 1% for variable 1. 4.3.2 Analysis of the results of the influencing factors the industry upgrade-driven development model Based on a study of provinces with industry upgrade-driven development model, the nine provinces whose New Industry Driving Index (NEDI) exceeds the national average increase are selected as a sub-sample to form a panel data composed of nine provinces during the 10-year period of 2014–2023, and the explanatory variables are set as NEDI for model estimation. In order to avoid excessive correlation between variables affecting the reliability of the empirical analysis results, the article first analyzes the correlation of each variable and finds that the correlation coefficient between the explanatory variables is basically less than 0.8, of which only one higher value of 0.8005 exists. In order to ensure that the possible effects of multicollinearity are excluded, the VIF multicollinearity test is further conducted on the main variables, and the results show that Mean VIF = 5.6 < 10, i.e., there is no multicollinearity problem among the explanatory variables. Meanwhile, for the consideration of the robustness of the estimation results, the three control variables were used as the basis for the fitting process, and the core explanatory variables were added one by one. The results show (see Table 9 ): the overall performance of the model is good, and the R² value rises from the initial 0.3630 to 0.6694, indicating that the explanatory power of the model on the changes of the New Industry Driving Index (NEDI) is significantly improved with the gradual addition of variables, and the industry upgrading-driven development mode of the pension and tourism industry is affected by the differentiation of internal and external factors. In terms of model effects and variable influences (see Table 9 ), factors such as human capital, degree of marketization and urban construction have a significant positive influence on the NEDI, industrial efficiency, financial burden of the elderly and government support negatively influence the NEDI, and industrial structure upgrading, R&D investment, economic development level, and location conditions do not reach a significant influence. This suggests that the high-quality development of pension tourism industry driven by industry upgrading needs to take human capital and market-oriented reform as the core driving force, pay attention to alleviating the crowding out effect of the burden of the elderly, and balance the efficiency enhancement and innovation inputs; at the same time, avoid falling into the "efficiency trap" of the traditional industry. Table 9 Regression results of industry upgrading-driven drivers (1) NEDI (2) NEDI (3) NEDI (4) NEDI (5) NEDI (6) NEDI (7) NEDI (8) NEDI (9) NEDI (10) NEDI HCM 0.0375 *** 0.0401 *** 0.0432 *** 0.0367 *** 0.0387 *** 0.0355 *** 0.0360 *** 0.0308 *** 0.0303 *** 0.0271 *** (5.20 ) (6.22) (6.99) (5.47) (5.82) (4.44) (4.51) (3.85) (3.77) (3.37) IE -0.1329 *** -0.1620 *** -0.1579 *** -0.1812 *** -0.1880 *** -0.1842 *** -0.1877 *** -0.1751 *** -0.1826 *** (-4.58) (-5.59) (-5.57) (-6.01) (-5.93) (-5.82) (-6.12) (-5.09) (-5.38) AFB -3.7446 *** -3.6248 *** -4.1787 *** -4.7090 *** -4.6335 *** -4.8904 *** -4.7271 *** -4.0094 *** (-3.15) (-3.12) (-3.56) (-3.40) (-3.36) (-3.65) (-3.48) (-2.90) ISU 1.2949 ** 0.9810 1.0716 * 1.0865 * 1.4999 ** 1.3184 ** 0.7563 (2.18) (1.63) (1.73) (1.77) (2.42) (2.00) (1.07) RDI 1.9470 * 2.0669 ** 2.1477** 1.3693 1.4641 1.1301 (1.99) (2.08) (2.16) (1.35) (1.43) (1.11) EDL 0.0957 0.1317 0.0165 0.0021 -0.0593 (0.72) (0.98) (0.12) (0.01) (-0.42) GS -0.0266 -0.0280 -0.0286 -0.0332 * (-1.30) (-1.42) (-1.44) (-1.69) MD 0.0867 ** 0.0748 * 0.0748 * (2.39) (1.92) (1.95) LC -0.0443 -0.0166 (-0.83) (-0.30) UC 0.0298 * (1.94) RTAC -2.5961 -1.3160 -2.1088 -1.8674 -6.1188 ** -6.5251 ** -6.7892 ** -3.1335 -3.4929 -2.3862 ( -1.14 ) (-0.64) (-1.08) (-0.98) (-2.15) (-2.25) (-2.34) (-0.98) (-1.08) (-0.74) OPEN 0.3354 0.1654 0.3195 0.3351 0.3476 0.3715 0.4014 * 0.3048 0.3121 0.2349 (1.26) (0.69) (1.37) (1.48) (1.56) (1.64) (1.78) (1.37) (1.40) (1.06) TIL 0.0001 * 0.0001 ** 0.0001 ** 0.0000 * 0.0000 * 0.0000 * 0.0000 0.0000 0.0000 0.0000 (1.73) (2.31) (2.52) (1.77) (1.81) (1.91) (1.30) (1.03) (1.04) (0.20) _cons -0.1085 0.4345 * 1.1584 *** 0.7011 * 0.9476 ** -0.0030 -0.1700 0.3057 0.8514 0.4260 (-0.49) (1.87) (3.64) (1.87) (2.45) (-0.00) (-0.12) (0.23) (0.57) (0.29) N 90 90 90 90 90 90 90 90 90 90 R 2 0.3630 0.5006 0.5588 0.5854 0.6068 0.6096 0.6188 0.6476 0.6510 0.6694 Note: The numbers in parentheses are t-statistics, and *, ** and *** indicate the significance levels of 10%,5% and 1% for variable 1. 4.3.3 Analysis of the results of the factors influencing the talent change-driven development model Based on a study of provinces with talent change-driven development model, the 14 provinces whose talent concentration degree (TCD) exceeds the national average increase are selected as a sub-sample to form a panel data composed of 14 provinces during the 10-year period from 2014–2023, and the explanatory variable is set as TCD for model estimation. First, the sample is tested for multicollinearity, and the correlation coefficients between the explanatory variables are basically no greater than 0.8, and the VIF values of the variables are all less than 10, so there is no problem of multicollinearity; out of the consideration of the robustness of the estimation results, the three control variables are used as the basis for the fitting process, and the core explanatory variables are added one by one. The results show (see Table 10 ): the model overall performance is good, and the R² value is significantly improved from the initial 0.1051 to 0.7139, which indicates that the explanatory power of the model on the changes of talent concentration degree (TCD) is significantly enhanced with the gradual addition of variables. In terms of model effects and variable impacts (see Table 10 ), the four factors of internal influences of industrial efficiency, aging fiscal burden, industrial structure upgrading and R&D investment have a significant impact on talent change-driven development model. The external factors of economic development level, marketization degree and location conditions have a significant impact. Among them, aging financial burden, marketization degree and location conditions have negative influence. Table 10 Regression results of talent change-driven drivers (1) TCD (2) TCD (3) TCD (4) TCD (5) TCD (6) TCD (7) TCD (8) TCD (9) TCD (10) TCD HCM 0.0172 *** 0.0166 *** 0.0168 *** 0.0068 * 0.0041 0.0023 0.0021 0.0028 0.0015 0.0014 (3.51) (3.52) (3.57) (1.68) (1.10) (0.71) (0.64) (0.89) (0.47) (0.46) IE 0.2060 *** 0.2096 *** 0.1597 *** 0.1138 ** 0.0864 ** 0.0837 ** 0.0735 * 0.1234 *** 0.1256 *** (3.40) (3.45) (3.20) (2.44) (2.09) (2.03) (1.85) (2.91) (2.93) AFB 3.6772 -0.0676 -2.3691 -5.1679 ** -5.2052 ** -6.2407 *** -5.2763 ** -5.1870 ** (1.07) (-0.02) (-0.90) (-2.18) (-2.20) (-2.73) (-2.35) (-2.29) ISU 3.9080 *** 3.3074 *** 1.1551 ** 1.2027 ** 1.5479 *** 1.5222 *** 1.4822 *** (7.82) (7.00) (2.10) (2.18) (2.87) (2.91) (2.77) RDI 9.2354 *** 4.6690 ** 4.7551 *** 5.3364 *** 5.0255 *** 4.9264 *** (4.94) (2.57) (2.62) (3.05) (2.95) (2.86) EDL 1.0041 *** 0.9250 *** 1.2823 *** 1.0860 *** 1.0391 *** (5.96) (5.04) (6.22) (5.13) (4.33) GS 0.0290 0.0323 0.0295 0.0283 (1.08) (1.25) (1.18) (1.11 MD -0.1523 *** -0.1588 *** -0.1594 *** (-3.33) (-3.58) (-3.57) LC -0.2104 *** -0.2081 *** (-2.84) (-2.79) UC 0.0088 (0.42) RTAC 5.6198 2.3998 1.4299 -6.6543 * -16.7996 *** -13.4723 *** -13.3893 *** -15.2602 *** -13.7875 *** -13.7130 *** (1.34) (0.58) (0.34) (-1.85) (-4.33) (-3.90) (-3.87) (-4.54) (-4.17) (2.93) OPEN -0.2788 1.1520 1.0838 1.1222 -0.3318 -1.8551 * -1.8794 * -2.1923 ** -2.1859 ** -2.0998 ** (-0.19) (0.80) (0.75) (0.95) (-0.30) (-1.83) (-1.85) (-2.25) (-2.31) (-2.29) TIL 0.0243 0.0020 0.0015 0.0330 0.0435 0.0272 0.0300 0.0373 0.0438 * 0.0439 * (0.60) (0.05) (0.04) (1.01) (1.46) (1.03) (1.13) (1.46) (1.76) (2.77) _cons 6.4759 *** 5.9155 *** 5.2979 *** 4.8193 *** 5.5008 *** -3.5444** -3.0385 * -5.6337 *** -2.5370 -2.3977 (12.93) (11.64) (6.90) (7.66) (9.30) (-2.21) -1.82) (-3.16) (-1.24) (-1.15) N 140 140 140 140 140 140 140 140 140 140 R 2 0.1051 0.1830 0.1907 0.4655 0.5571 0.6602 0.6636 0.6932 0.7134 0.7139 Note: The numbers in parentheses are t-statistics, and *, ** and *** indicate the significance levels of 10%,5% and 1% for variable 1. Conclusion and discussion 5.1 Research conclusion First, three high-quality models of the pension tourism industry are refined. Based on the rooted theoretical analysis of 10 cases of senior care tourism enterprises, three high-quality development modes, namely, technological innovation-driven, industry upgrading-driven and talent change-driven, are identified. The three modes show a dynamic evolutionary logic chain of "technological innovation provides tools→industrial upgrading creates value→talent change enhances effectiveness"; the three modes differ in terms of the applicable subject, the driving core, and the path of value creation, etc. The study finds that, for the first time, the senior care tourism industry has been recognized as a high-quality development mode from the perspective of new quality productivity. The study finds that the first high-quality development model of pension tourism industry is refined from the perspective of new quality productivity, which meets the real needs of the development of pension tourism industry under the background of digital intelligence technology, and breaks through the traditional research perspective of industrial economy. At the same time, it reveals the internal logic of the high-quality development of the industry driven by the new quality productivity, and enriches the theoretical research on the intersection of pension tourism and the new quality productivity. Second, it reveals the pattern of high-quality development mode selection of China's pension tourism industry in various provinces.The occurrence of high-quality development modes of China's pension tourism industry in 30 provinces in 2014–2023 shows that: the technological innovation-driven development mode occurs in the eastern, middle and western regions; the industry upgrading-driven development mode is mainly concentrated in economically developed provinces such as Beijing, Shanghai and Guangdong; the talent change-driven development mode occurs in the middle and western regions; and the talent change-driven development mode occurs in the middle and western provinces. The potential of talent change-driven development mode is outstanding in the central and western regions. This study finds that for the first time, quantitative research scientifically reveals the law of high-quality development mode selection of China's pension tourism industry in various provinces, which makes up for the shortcomings of most of the existing studies that are based on qualitative descriptions, and provides empirical guidance for the scientific decision-making of pension tourism industry in various regions. Meanwhile, the combination of rooted theory and panel data analysis realizes the complementarity of qualitative exploration and quantitative verification, and enhances the scientific and persuasive nature of the research conclusions. Thirdly, the influencing factors of high-quality mode selection in the elderly tourism industry are analyzed. Technological innovation-driven development mode is positively influenced by human capital, industrial structure upgrading, economic development level, government support and transportation infrastructure, while location conditions play a negative role; industry upgrading-driven development mode is driven by high-quality talents and the degree of marketization, while efficiency improvement of the traditional industry and the pressure of public finances inhibit its development; talent change-driven development mode relies on internal industrial efficiency, R&D investment and external economic development level; and talent change-driven development mode relies on internal industrial efficiency, R&D investment and external economic development level. The talent change-driven development model relies on internal industrial efficiency, R&D investment and external economic development level, while the degree of marketization and location conditions have a negative influence. This study reveals the internal and external influencing factors and their heterogeneity in the selection of high-quality models for the pension and tourism industry in the digital age, especially examining the special mechanisms such as the "traditional efficiency trap" and the "fiscal pressure crowding out effect", which makes up for the lack of attention to the practical suitability of the models in the previous studies. In particular, it examines the special mechanisms such as the "traditional efficiency trap" and the "financial pressure crowding out effect", which makes up for the shortcomings of the previous studies that have paid insufficient attention to the adaptability of the model practice, enriches and expands the research on the influencing factors of the selection of high-quality models of the pension and tourism industry, and provides new perspectives for the understanding of the differentiation of the development of the pension and tourism industry in the region. 5.2 Practical implications Based on the above conclusions, the main initiatives to empower the high-quality development of the tourism and pension industry with new productivity include: first, for the technological innovation-driven model, the "East, Central and West Technology Collaboration Network" should be established, with the eastern region exporting digitalization and intelligent technology experience, and the central and western regions relying on the characteristic resources to carry out the adaptive technological transformation, and at the same time, strengthening the transportation infrastructure and regional technology platform. At the same time, we should strengthen the connection between transportation infrastructure and regional technology platforms, promote cross-regional transformation of technological achievements, and break down regional barriers to technology application. Secondly, for the mode driven by industry upgrading, a "special fund for cultivating new industries" can be set up, focusing on supporting the integration projects of "tourism + medical care", "culture + recreation", etc., and reducing the pressure on public finance through market-oriented reforms. At the same time, through market-oriented reforms to reduce the crowding out effect of public financial pressure on innovation, encourage enterprises to set up innovation teams with high-quality talents as the core to break through the efficiency bottleneck of the traditional industry. Finally, around the talent change-driven model, we need to build a "school-enterprise-land" linkage training mechanism, universities add interdisciplinary major in elderly care tourism services and management, local governments to introduce talent subsidies and career development policies, and enterprises to improve the skills upgrading and incentive system, forming a "cultivation-introduction-retention" talent closed loop. This will form a closed loop of "cultivation-introduction-retention" and help release the potential of talent drive in the central and western regions. 5.3 Limitations and prospects Although this study reveals the mode selection mechanism of new quality productivity driving the high-quality development of the pension tourism industry, there are certain limitations. For one thing, based on 10 typical cases of senior care tourism enterprises to refine the model type, the number of cases is limited and concentrated in the head enterprises, which is difficult to reflect the practice characteristics of small and medium-sized micro-organizations and characteristic counties of senior care tourism, which may affect the universality of the model. In the future, the breadth of cases and data can be expanded to include cases of small and medium-sized micro-enterprises and counties with special characteristics, so as to improve the refinement of the study by combining micro and macro data. Second, the empirical analysis identifies the independent role of each factor, but does not fully explore the interaction mechanism between variables, and does not sufficiently study the specific path of policy tools. In the future, we can analyze the role of variable combinations through the moderating and mediating effect models, and quantify the impact of different policy tools by combining policy evaluation methods, so as to provide the basis for precise policy implementation. Declarations Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Chongqing Jiaotong University (Approval Numbers：2025Q0285-003). Informed consent Informed consent has been obtained from all participants and/or their legal guardians. Interviews were conducted on March 11, March 24, March 25, and April 8, 2025.Prior to the interview, informed consent was obtained from participants, who voluntarily agreed to answer questions. Before conducting the semi-structured interview, the purpose was explained, and participants were informed that all content would be anonymized for academic research only. Personal information will be strictly confidential. Data Availability The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request. Declarations of competing interest None. [Funding] This study was funded by Research Project of Humanities and Social Sciences of Chongqing Municipal Education Commission in 2025(Grant number:K24YD2070038);Chongqing's Education Science "14th Five-Year Plan Project"（Grant number:K24YD2070038） References Huang JX, Zhao XY (2023) Research on key factors for the high-quality development of elderly health and wellness tourism bases based on the DEMATEL-ISM-MICMAC method. Tourism Sci 37(2):60–76 Ma Z, Yang X (2024) Research on the Empowerment of Folk Sports Tourism by New Quality Productivity. 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Acta Geogr Sin 78(6):1553–1572 You YW (2014) Reflections on the Medical Care, Elderly Care, and Travel Integrated Retirement Model. Chin Party Government Cadres Forum, (9), 96–98 Liu D, Tang B, Zhao K, Chen L, Qiu C, Fu P (2022) Research on the Needs of Public Space for Elderly Sojourners in the Context of Internet Plus: A Case Study of Southern Hunan. Advances in Urban Engineering and Management Science Volume 1. CRC, pp 463–472 Zhou YL (2016) Selection of Development Models for Medical Wellness Tourism in Hainan. Open Guide, (2), 109–112 Yiqian YANG, Xiaogang CHEN, Xiaoyun LI (2018) The Development Model of Tourism-Based Retirement Towns. J Landsc Res, 10(4) Yasarata M, Altinay L, Burns P et al (2010) Politics and sustainable tourism development—Can they co-exist? Voices from North Cyprus. Tour Manag 31(3):345–356 Monteiro P, Correia A, Braga V (2019) Factors for Marketing Innovation in Portuguese Firms CIS2014. Math Comput Appl 24(4):99 Kanwal S, Rasheed MI, Pitafi AH et al (2020) Road and transport infrastructure development and community support for tourism: The role of perceived benefits, and community satisfaction. Tour Manag 77:104014 Erol I, Neuhofer IO, Dogru T et al (2022) Improving sustainability in the tourism industry through blockchain technology: Challenges and opportunities. Tour Manag 93:104628 Sun P, Li Y, Li Z (2021) The Impact Mechanism of Local Government Behavior on the Total Factor Productivity of Tourism Industry. J Huaqiao Univ (Philosophy Social Sci Edition), (3), 45–58 Peng C, Shi G, Hu J (2023) An Empirical Study on the Impact of Environmental Regulation Intensity on the Competitiveness of the Tourism Industry. Stat Decis 39(2):78–82 Yang X, Song R (2024) The Mechanism of Digital Economy's Impact on Tourism Industry Development. Progress Geographic Sci 43(10):1943–1955 Yang X, Zhang W, Tian C (2025), May 1 The Impact of Personal Characteristics of Cultural Tourism Administrators on the Development of Regional Tourism Industry. Tourism Science . https://doi.org/10.16323/j.cnki.lykx.20240415.001 Mu H, Fan L (2017) Research on the Impact of Industrial Structure Upgrading on the Space for Reducing Pension Insurance Premiums. J Hebei Univ (Philosophy Social Sci Edition) 42(6):93–101 Xu A (2021) Research on the Evaluation and Influencing Factors of High-quality Development of China's Tourism Industry. Unpublished doctoral dissertation, East China Normal University, Shanghai Liu J, An K, Zhao Q et al (2024) Evolution of China's Tourism Industry Chain Development Pattern and Spatial Effects. Geogr Geographic Inform Sci 40(3):122–134 Zhang R, Sun Y (2023) The Evolution of Rural Tourism Industry in Ethnic Regions: A Different Path? —— Configuration Path Analysis Based on Qualitative Comparative Analysis. Tourism J 38(9):77–90 Li W, Li D, Hu H et al (2024) Research on the Development Level and Influencing Factors of the Elderly Care Industry in the Yangtze River Delta Region. World Geogr Res 33(2):123–135 Yang X, Song R (2024) The Mechanism of the Impact of Digital Economy on Tourism Industry Development. Progress Geographic Sci 43(10):1943–1955 Losada N, Alen E, Cotos-Yanez TR et al (2019) Spatial heterogeneity in Spain for senior travel behavior. Tour Manag 70:444–452 Andrades L, Dimanche F (2017) Destination competitiveness and tourism development in Russia: Issues and challenges. Tour Manag 62:360–376 Hu L, Xu J, Bao C et al (2021) Influential factor detection for tourism on the Qinghai-Tibet Plateau based on social media data. ISPRS Int J Geo-Information 10(9):579 Liu-Lastres B, Wen H, Okumus F (2024) Exploring the impacts of internal crisis communication on tourism employees insights from a mixed-methods study. Tour Manag 100:104796 Liu S, Qu L, Mo X et al (2025) The Impact of the Integration of Two Industries on the Carbon Emission Intensity of Manufacturing —— An Empirical Analysis Based on WIOD Cross-National Panel. Res World, (4), 33–46 Additional Declarations No competing interests reported. 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By the end of 2024, China's population aged 60 and above will reach 310\u0026nbsp;million, accounting for 22% of the total population. Population aging has given rise to the rise of \"silver hair economy\"; and pension tourism industry, as one of the important forms of silver hair economy, has gradually become a new growth point to promote consumption upgrading and optimize the industrial structure. 2024 General Office of the State Council issued \"Opinions on the Development of Silver Hair Economy and Enhancement of Well-Being of the Elderly\", which puts forward the development of a new type of pension industry, namely, residential pension. The new quality productivity is the key to high quality economy in the new era.\u003c/p\u003e \u003cp\u003eNew quality productivity is the core kinetic energy for high-quality economic development in the new era, and its essence is a new type of productivity pattern led by scientific and technological innovation and characterized by a leap in total factor productivity. The report of the 20th CPC National Congress clearly pointed out that \"opening up new fields and new tracks for development, shaping new kinetic energy and new advantages for development\", and took the new quality productivity as the strategic pivot point for building a modernized industrial system. The \"Overall Layout Plan for the Construction of Digital China\" released by the State Council in 2023 emphasized the need to build a digital economy through \" digital technology to empower the real economy and promote the development of new industries\". Digital technology empowers the real economy and promotes changes in the mode of production, lifestyle and governance\", the core of which lies in reconfiguring the way factors of production are combined - expanding from new types of factors such as traditional labor, capital, algorithms, and green technology. In September 2023, General Secretary Xi Jinping proposed for the first time during his visit to Heilongjiang, and emphasized \"integrating scientific and technological innovation resources, leading the development of strategic emerging industries and future industries, and accelerating the formation of new quality productivity\". This concept provides a new paradigm for the high-quality development of the pension and tourism industry. The new quality productivity promotes the change of social production mode and industrial operation mode, and brings subversive changes to the development mode of pension tourism industry. The new quality productivity centered on artificial intelligence, Internet of Things, and big data is reshaping the pension tourism service industry, giving rise to new forms of business such as intelligent recreation communities and digital residence platforms. However, there are significant differences in resource endowment, technological innovation and policy support among provinces in China. How to scientifically choose a high-quality development model for the pension tourism industry that suits the actual situation has become a key proposition to crack the contradiction between the upgrading of the demand for pension tourism and the lagging of the industrial supply. Based on this, firstly, a qualitative exploratory study is conducted using the rooting theory to establish a theoretical model of the high-quality development mode of the pension tourism industry driven by the new quality productivity; secondly, the occurrence of the high-quality development mode of the pension tourism industry in 30 provinces (cities and districts) in China from 2014 to 2023 is empirically analyzed with 30 provinces (cities and districts) as the object of the study and a multiple regression model is constructed to test the development mode of the pension tourism industry in the 30 provinces (cities and districts) in China. construct a multiple regression model to test the effect of the influencing factors of the development mode. The article aims to answer four core questions: (1) What are the high-quality development patterns of the senior care tourism industry driven by new quality productivity? (2) What are the high-quality development modes chosen by the senior care tourism industry in each province (city and district)? (3) What factors affect the selection of high-quality development models for the elderly tourism industry? (4) How to choose the high-quality development model of senior care tourism industry according to regional realities?\u003c/p\u003e"},{"header":"Literature review","content":"\u003cp\u003e \u003cb\u003e1.1 Studies on the high-quality development model of senior citizen tourism industry driven by new quality productivity\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAs the core driving force for industrial change, the impact of new quality productivity on the high-quality development model of the pension and tourism industry has become a new area of concern in the academic community. Existing researches have explored the three dimensions, namely, industrial integration perspective, empowerment mechanism and mode selection, which provide multiple perspectives for understanding this topic. First of all, in terms of industrial integration research, scholars at home and abroad generally take the perspective of \"+tourism\" research to explore the empowerment path of new quality productivity to the segmented areas. Research involves \"senior\u0026thinsp;+\u0026thinsp;tourism\"\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e, \"sports\u0026thinsp;+\u0026thinsp;tourism\"\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, \"culture\u0026thinsp;+\u0026thinsp;tourism\"\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, \"digital\u0026thinsp;+\u0026thinsp;tourism\"\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, \"Rural\u0026thinsp;+\u0026thinsp;Tourism\"\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e and other fields, systematically sorting out the mechanism of new quality productivity in factor allocation, industry innovation and other aspects. Foreign studies focus on medical tourism\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, cultural tourism\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, digital tourism\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e and other fields; at the same time, the innovative development mode of digitization-driven pension and tourism industry\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e is studied. Elzbieta Szymaska constructs a model of health tourism innovation system and proposes three modes of technological innovation empowerment\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. The above studies reveal the role of new quality productivity in driving the high-quality development of the senior tourism industry, but there is a lack of systematic research on how new quality productivity drives the high-quality development model of the senior tourism industry. Second, in terms of the research methodology of the enabling mechanism, the academic community has formed a complementary qualitative and quantitative research. Qualitative research has verified the enabling effect of new technology on eco-health tourism\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e and explained the key mechanisms such as innovation-driven factor allocation and structural optimization of digital technology\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e; quantitative research has empirically verified the enabling effect of new technology on eco-health tourism through action research\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, spatial modeling\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, geometrical analysis\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e and other methods. and other methods to empirically verify the impact of digital innovation on industrial performance. Meanwhile, the research on the senior care industry proposes a smart senior care model\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e and identifies internal and external driving factors\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, which provides a reference for the research on senior care tourism model, but has not yet formed a systematic framework applicable to the integration scenario of \"senior care\u0026thinsp;+\u0026thinsp;tourism\". Finally, regarding the research on mode selection, the existing studies present multiple perspectives to explore. First is the integrated development model. This includes the \u0026ldquo;tourism innovation\u0026thinsp;+\u0026thinsp;public welfare elderly care\u0026rdquo; integrated development model\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e, the integrated development model of traditional Chinese medicine culture and elderly care tourism industry\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e, and the rural tourism elderly care model\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Second is the travel-residence elderly care model. This includes the rural travel-residence elderly care model\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e, the \u0026ldquo;medical care and travel-residence\u0026rdquo; combined elderly care model\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, and the smart travel-residence elderly care model\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Third, other models. These include the medical wellness tourism development model\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e and the tourism-oriented retirement town development model\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. However, studies on the selection of high-quality development models for the pension tourism industry driven by new quality productivity are still very limited. Therefore, it is of great significance to systematically study the high-quality development mode of China's elderly tourism industry and its choice from the perspective of new productivity empowerment.\u003c/p\u003e \u003cp\u003e \u003cb\u003e1.2 Studies on the influencing factors of the high-quality development mode choice of the senior care tourism industry\u003c/b\u003e \u003c/p\u003e \u003cp\u003eResearch on the influencing factors of the selection of high-quality development models for the elderly tourism industry has evolved from a single-factor approach to a multi-dimensional approach. Early studies focused on single factors, and foreign scholars explored the influence of political system\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, organizational innovation\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, infrastructure\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, information technology\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e, etc., on the tourism industry; while domestic studies focused on the influence of governmental behaviors\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, environmental system\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, digital economy\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e, personal characteristics\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e ,industry structure\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e and other factors on the tourism industry. This type of research reveals the independent influence of key elements, but neglects the interaction between multidimensional elements. With the depth of research, the multidimensional factor integration perspective gradually becomes the mainstream of research. Based on the multidimensional analysis framework, some scholars proposed the synergistic mechanism of grassroots power, market power and potential power\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e, revealing the synergistic mechanism among the power sources, which provides a reference to understand the endogenous development logic of the elderly tourism industry. Refining the influencing factors based on the four dimensions of supply, demand, innovation and policy\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e highlights the interaction between policy and market in the senior tourism industry. Meanwhile, some scholars have studied the influence of six factors, namely, formal system, entrepreneurial environment, population base, medical level, regional economic development level, and openness to the outside world, on the development model of the pension tourism industry\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e][\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e][\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e foreign scholars have formed a consensus that multiple factors jointly influence the high-quality development of the pension tourism industry, but there are still different understandings of the key influencing factors. There are different understandings of the key influencing factors. Some scholars emphasize the influence of factors such as health, culture, and medical care\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e; some scholars believe that the destination environment is central to senior tourism, and that infrastructure, workforce training, and so on, are more important\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e; Hu analyzes the influence on the tourism industry, such as tourism resources, facilities, and transportation, from the perspective of spatial heterogeneity\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn summary, although research on the selection of high-quality development mode for the elderly tourism industry at home and abroad has made great progress, there are still many shortcomings: firstly, there is a lack of research on high-quality development models for the elderly tourism industry from the perspective of new productive forces; secondly, there is a lack of research results on the selection of high-quality development models for the elderly tourism industry; thirdly, there is a lack of empirical research on the factors influencing model selection. Therefore, from the perspective of new productive forces, researching the models and selection of high-quality development for the elderly tourism industry has important research value.\u003c/p\u003e"},{"header":"Research overview","content":"\u003cp\u003eA mixed research method is adopted, including rooted theory (Study 1) and empirical analysis (Study 2). Study 1 uses qualitative exploratory analysis in order to identify three new qualitative productivity-driven high-quality development modes of the pension tourism industry and establish a theoretical model of high-quality development modes of the pension tourism industry. Study 2 is designed to examine the occurrence of high-quality development modes of the senior care tourism industry in each province of China based on panel data of 30 provinces (cities and districts) in China from 2014\u0026ndash;2023, and constructs a multiple regression model to test the effects of the influencing factors of mode selection. The two studies build on and support each other in an incremental manner. The combination of qualitative and quantitative methods strengthens the internal and external validity of the study and ensures its rigor\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Study 1: Exploratory theoretical modeling","content":"\u003cp\u003eStudy 1 aims to conduct exploratory analysis and refine the typical model of the high-quality development of the elderly tourism industry, in order to establish a theoretical model of the high-quality development model of the elderly tourism industry driven by the new quality productivity.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Data collection\u003c/h2\u003e \u003cp\u003eIn the data collection stage, information is obtained from multiple data sources to ensure the comprehensiveness and accuracy of the data. First of all, the primary data mainly came from telephone interviews with the main persons in charge of the case enterprises, online consultation and field research. Among them, the six interviewees are all responsible for the elderly tourism business, and the interviews focus on the application of technology, product upgrading, talent management and development mode of the elderly tourism enterprises, etc. The interviews lasted from 20 to 40 minutes, and the total length of the interviews amounted to 3.5 hours, and the number of words in the audio recordings and translations amounted to 32,000 words. Secondly, based on the principles of typical representativeness and data availability, 10 pension tourism enterprises were screened as research samples (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e); the case enterprises were divided into 7 modeling groups and 3 testing groups, which can not only refine the differentiated development mode, but also verify the theoretical saturation of the theoretical model through comparison to ensure the research credibility. The enterprise case materials are mainly derived from public interview records, enterprise publicity documentaries, enterprise official websites, enterprise official website case database, enterprise annual reports, news special reports, academic papers and industry reports. By organizing and filtering the relevant information, the secondary information of nearly 50,000 words was finally formed.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample cases of pension tourism enterprises\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eserial number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecompany identification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAreas covered\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnterprise size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDevelopment model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCase Usage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTaikang Home\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedical Recreation, Intelligent Elderly Care, Cultural and Tourism Integration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emega\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClosed-loop model of \"insurance-healthcare-cultural tourism\".\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGreentown Wuzhen Yayuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCultural tourism property, education and retirement, eco-community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emega\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEcological Integration Model of \"Culture, Education, Tourism and Nutrition\"\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaurau City Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCommunity Aged Care, Intelligent Platform, Ageing Supply Chain, Travelling Services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emega\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe \"four-level grid\u0026thinsp;+\u0026thinsp;digital centre\" model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egreen pine health care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIoT technology, AI health monitoring, insurance data services, travel safety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"IoT data capitalisation\" model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esource of affinity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMembership-based retirement, financialised benefits, blockchain deposits, inter-regional healthcare\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"Membership financialisation\u0026thinsp;+\u0026thinsp;blockchain trust\" model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChengdu Global International Travel Service\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSenior speciality tours, high-end customised tours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"Online\u0026thinsp;+\u0026thinsp;offline\" integration model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSichuan Huayun International Travel Service\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003esilver haired train\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"Resource\u0026thinsp;+\u0026thinsp;Channel\" dual-drive model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emodelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnkangtong Intelligent Elderly Care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIoT security monitoring, subscription-based services, inclusive ageing, emergency response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe \"cellular safety net\" model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003einspect\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHainan Puren Residential Retirement Base\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClimate medicine, Chinese medicine and health care, cross-border data flow, intellectual property operation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"Climate Healthcare IP\u0026thinsp;+\u0026thinsp;Data Across Borders\" Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003einspect\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeijing Golden Cane International Retirement Residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFilm and TV IP development, immersive recreation, extended reality technology, cultural derivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emedium-sized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"Film and TV IP Immersion Recreation\" Model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003einspect\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Data analysis\u003c/h2\u003e \u003cp\u003eThe 35,000-word interviews with six interviewees were analyzed for patterns using the three-level coding procedure of procedural rooting theory. First, the researcher reviewed all interviews to ensure a comprehensive understanding of the data. Second, open coding was conducted, using Nvivo software to initially conceptualize the raw data as labels, and a total of 91 core concepts and 17 initial categories were extracted. Again, on the basis of the 17 initial categories, the categories were subjected to principal axial coding to further generalize and extract the main categories, and finally three main categories were summarized. Finally, through further summarization and abstraction of the main categories and sub-categories, a core category, i.e., \"high-quality development model of the pension and tourism industry driven by new quality productivity\", was formed, and a theoretical model describing the conceptual connotation of each development model was formed.\u003c/p\u003e \u003cp\u003eIn order to ensure the validity of the qualitative results, the concepts and categories were extracted by labeling the three case studies of the modeling group, open coding was performed to refine the concepts and categories, and the concepts and categories were compared with those of the modeling group to verify the degree of theoretical saturation. In the end, 42 core concepts and 8 initial categories were extracted, and all of them were among the categories summarized by the modeling group, with no other new categories or logical connections. Accordingly, it can be judged that the theoretical saturation degree of \"the theoretical model of the high-quality development mode of pension tourism industry driven by new quality productivity\" is high.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Research results\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 The model of high-quality development of pension tourism industry driven by new quality productivity\u003c/h2\u003e \u003cp\u003eBased on the above analysis, the model of high-quality development of senior care tourism industry driven by new quality productivity (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is concluded, i.e., technological innovation-driven development model, industry upgrading-driven development model and talent change-driven development model. The three modes show the dynamic evolution path of \"technological innovation provides tools\u0026rarr;industrial upgrading creates value\u0026rarr;talent change enhances effectiveness\".\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section4\"\u003e \u003ch2\u003e3.3.1.1 Technological innovation-driven development mode\u003c/h2\u003e \u003cp\u003eThe technology innovation-driven development mode takes the triple technology promotion of \"intelligent technology - digital technology - green technology\" as the core orientation, and reconstructs the value network of the pension tourism industry through technological breakthroughs, integration and application. Its essence lies in: relying on the dynamic synergistic relationship between intelligent hardware and data elements under the leadership of digital intelligence technology, breaking through the boundaries of traditional pension tourism services, driving system integration through technological iteration, realizing the pension service scenario from unitary to intelligent, ecological leap, and constructing a whole-area interconnected intelligent pension tourism ecosystem. At the same time, the technology innovation-driven development model is dominated by three characteristics: technology dominance, intelligent penetration, and dynamic supply and demand matching. Technology-driven is to take technology as the core driving force to realize the transformation of service scenes to \"intelligent senior care tourism\" with high-end technology; intelligent penetration is that deeply embed technology into the whole process of service, covering health data management, intelligent service response, upgrading of ageing facilities, etc., and forming an all-round technical support system through intelligent monitoring and digital technology. Intelligent penetration is the deep embedding of technology into the whole process of service, covering health data management, intelligent service response, upgrading of aging facilities, etc., and forming an all-round technical support system through intelligent monitoring and digital technology. Dynamic supply and demand matching is based on the ability of technology integration, integrating fragmented technology modules into an interconnected intelligent senior care tourism platform, relying on digital platforms to realize the dynamic equipping of medical resources, senior care tourism products and user demand, and forming a technology-driven dynamic matching network of supply and demand.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section4\"\u003e \u003ch2\u003e3.3.1.2 Industry upgrade-driven development mode\u003c/h2\u003e \u003cp\u003eThe industry upgrading-driven development mode takes the triple element drive of \"new industry - new products - new facilities\" as the core orientation, and extends the value chain of the pension tourism industry through product reorganization and industry innovation. This model focuses on the upgrading of the whole industry of pension tourism, supported by resource allocation capacity, with the core logic of industry integration driven by product innovation, and realizing the transformation of hardware and facilities and the construction of product matrix through the integration of emerging industries, so as to promote the transformation of the pension tourism industry from a single service to a differentiated product system. The industry upgrade-driven development mode are characterized by three features: resource integration, product aging, and industry integration. Resource integration is the pension tourism industry through the integration of pension resources, tourism resources, medical resources, social resources, etc., to optimize the efficiency of resource allocation. Product aging is oriented toward the high-quality elderly tourism needs of the elderly, developing low-intensity, high-experience differentiated products to meet the diverse needs of the elderly. Business integration refers to promoting the integration of \u0026ldquo;cultural tourism,\u0026rdquo; \u0026ldquo;health and wellness,\u0026rdquo; \u0026ldquo;medical care,\u0026rdquo; and other businesses through chain operations and cross-industry cooperation, forming a new diversified elderly tourism business.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section4\"\u003e \u003ch2\u003e3.3.1.3 Talent change-driven development mode\u003c/h2\u003e \u003cp\u003eThe talent change-driven development model takes the triple upgrade of \"skill enhancement, service innovation and management innovation\" as the core orientation, and enhances the competitiveness of the industry by strengthening the ability of talents and additional services. The model emphasizes the core of professional service supply and humane management, and the synergistic innovation of \"talent-service-management\" as the main line of logic, promoting the leap from standardized service to personalized service through the skill training and optimization of the management mechanism under the leadership of talent echelon construction, in order to build the matrix of high value-added service capacity. The talent-driven development model is characterized by three key features: service specialization, skill-driven innovation, and capability matrixing. Service specialization refers to providing precise services through professional teams specializing in elderly care, tourism, healthcare, and wellness. Skill-driven innovation involves enhancing the service skills of staff through aging-friendly service training, shifting the focus from service quality alone to a balance between service quality and emotional support. Capability matrixing involves restructuring the diverse capabilities possessed by individual employees or teams, and constructing a service capability matrix centered on core elements such as talent pipelines, service standards, and management mechanisms.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Comparison of high-quality development models of new quality productivity-driven pension tourism industry\u003c/h2\u003e \u003cp\u003eDriven by the new quality of productivity, the three models of high-quality development of the pension tourism industry have certain links, that is, all of them take the improvement of the high-quality development of the pension tourism industry as the core objective, and unfold with the logical main line of \"strategic motivation\u0026rarr;capability base\u0026rarr;development elements\u0026rarr;development channels\", and the three models show a spiral interaction; at the same time, there are differences in terms of the applicable. At the same time, there are differences in application, driving core and value creation path (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the characteristics of high-quality development modes of pension tourism industry driven by new quality productivity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDevelopment Mode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApplicable subject\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDriving core\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValue creation path\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTypical Practice\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTechnology Innovation Driven\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTechnology-intensive organizations, large pension groups with R\u0026amp;D capabilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDigital Intelligence Technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTool upgrading \u0026rarr; system integration \u0026rarr; ecological reconstruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTaikang Home Powerback Rehabilitation System, Philips EPIQ5 Medical Data Integration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndustry Upgrade Driven\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResource-intensive regions, small and medium-sized senior living communities requiring product differentiation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndustry Integration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eResource optimization \u0026rarr; product design \u0026rarr; industry extension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYueyuan community \"natural oxygen bar\" culture and tourism scene, summer recreation tour product matrix\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTalent change-driven\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eService-oriented institutions, senior care service enterprises that require both standardization and humanization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh-quality talents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCapacity building \u0026rarr; standardization \u0026rarr; experience upgrading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\"Nine division team\" precision care, silver-haired tour guide and geriatric academy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Study 2: Empirical Analysis","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e4.1 Variable selection\u003c/h2\u003e\n \u003cp\u003ePanel data of 30 provinces in China (excluding Tibet Autonomous Region, Taiwan Province, Hong Kong and Macao Special Administrative Regions) from 2014\u0026ndash;2023 are used as the research sample. The data mainly come from China Statistical Yearbook, China Science and Technology Statistical Yearbook, China Tertiary Industry Statistical Yearbook, China Culture and Tourism Statistical Yearbook, China Civil Affairs Statistical Yearbook, China Social Statistical Yearbook, the official web site of the National Bureau of Statistics, and the official statistical yearbooks of provinces and cities, etc., where some of the missing data are handled by using analogical or interpolation methods.\u003c/p\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e4.1.1 Explained variables\u003c/h2\u003e\n \u003cp\u003eThe occurrence of the high-quality development mode of the pension tourism industry is the explanatory variable. It includes the occurrence of technological innovation-driven development mode, the occurrence of industry upgrading-driven development mode and the occurrence of talent change-driven development mode. The specific measurements are as follows:\u003c/p\u003e\n \u003cp\u003e(1) Technological innovation-driven mode measurement index - Technology Driven Index (TDI)\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e \u003cp\u003eIn formula (1), PA represents the number of tourism patents authorized, RD represents the number of enterprises carrying out innovation activities, DT represents the level of digital transformation, expressed as the Internet penetration rate, and E represents the economic impact factor, which is the ratio of the income of the pension and tourism industry to GDP. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{PA}{RD}\\)\u003c/span\u003e\u003c/span\u003erepresents the efficiency of R\u0026amp;D investment.1+\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{D}\\text{T}\\)\u003c/span\u003e\u003c/span\u003e represents the impact factor of the level of digital transformation, reflecting the promotion effect of digital transformation on technology-driven; the higher the level of digitization, the more widely the technology is applied, and the technology-driven index will be increased accordingly.E reflects the importance of the senior care tourism industry in the economy. If the industry's contribution to the economy is greater, the more significant the impact of technology drive on its development.\u003c/p\u003e \u003cp\u003e(2) Industry upgrade-driven mode measurement indicator\u0026ndash;New Industry Driven Index (NEDI)\u003c/p\u003e \u003cp\u003eThe New Industry Driving Index (NEDI) is used to measure the impact of the integration of new industries with the tourism industry on the development of the pension and tourism industry. Characterized by the health industry and tourism industry integration index, the specific measurement index system is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvaluation index system of integration between health industry and tourism industry\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarget layer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe criteria level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndicator layer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eweight\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eHealth industry development index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndustrial base\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of medical and health institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of beds per 1,000 people in medical and health institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of nursing homes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.39%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eindustrial development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of old-age insurance participants (10,000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.96%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal revenue of medical institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.63%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eTourism industry development index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eIndustrial base\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of star hotels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of travel agencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of A-level scenic spots\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eindustrial development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal tourism revenue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCalculate the development of the health industry and tourism industry separately, and use formula (2) to calculate their comprehensive integration degree\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e .\u003c/p\u003e \u003cp\u003eNEDI=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{\\text{H}\\text{I}}_{\\text{H}\\text{e}\\text{a}\\text{l}\\text{t}\\text{h}\\:\\text{i}\\text{n}\\text{d}\\text{u}\\text{s}\\text{t}\\text{r}\\text{y}}}{{\\text{T}\\text{I}}_{\\text{T}\\text{o}\\text{u}\\text{r}\\text{i}\\text{s}\\text{m}\\:\\text{i}\\text{n}\\text{d}\\text{u}\\text{s}\\text{t}\\text{r}\\text{y}}}\\)\u003c/span\u003e\u003c/span\u003e (2)\u003c/p\u003e \u003cp\u003e(3) Talent change-driven mode measure - Talent Concentration Degree (TCD)\u003c/p\u003e \u003cp\u003e \u003cem\u003eTCD\u003c/em\u003e=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Ln（（EPC}_{\\text{R}}+{TP}_{\\text{R}}）\\times\\:\\frac{{EP}_{R}}{{EDL}_{R}}）\\)\u003c/span\u003e\u003c/span\u003e (3)\u003c/p\u003e \u003cp\u003eIn Eq.\u0026nbsp;(3), \u003cem\u003eEPC\u003c/em\u003e stands for elderly care practitioners, \u003cem\u003eTP\u003c/em\u003e stands for tourism practitioners, \u003cem\u003eEDL\u003c/em\u003e stands for educational attainment, and \u003cem\u003eEP\u003c/em\u003e stands for the proportion of the elderly population to the total population. The calculation step is divided into two steps, the first part \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{EPC}_{R}+{TP}_{R}\\)\u003c/span\u003e\u003c/span\u003e represents the region's employees in the field of elderly care and tourism. The second part \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{EP}_{R}}{{EDL}_{R}}\\)\u003c/span\u003e\u003c/span\u003e represents the ratio of the educational level of the region relative to the aging population, reflecting the relationship between the quality of the talent in the region and the pressure of aging. The final result, \u003cem\u003eTCD\u003c/em\u003e, is the product of the two parts taken as a logarithm, which comprehensively reflects the concentration of high-quality talent in the region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e4.1.2 Explanatory variables\u003c/h2\u003e \u003cp\u003eThe study identifies ten internal and external factors that influence the selection of high-quality development models for the elderly tourism industry driven by new productive forces. The internal factors include human capital (HCM), industrial efficiency (IE), aging fiscal burden (AFB), industrial structure upgrading (ISU), and research and development investment (RDI). The external factors include economic development level (EDL), government support (GS), marketization degree (MD), locational conditions (LC), and urban development (UC). The specific indicators selected are shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIndicator system of influencing factors for the selection of high-quality development mode of pension tourism industry driven by new quality productivity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInfluencing Factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSymbol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMetric\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eInternal influencing factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHuman capital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHCM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe proportion of the number of people with a bachelor's degree or above in the total employment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndustrial efficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal revenue of elderly care / fixed asset investment of elderly care institutions (take logarithm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAging fiscal burden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAFB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Local financial expenditure on science and technology\u0026thinsp;+\u0026thinsp;local financial expenditure on education)/local financial general budget expenditure\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpgrading of an industrial structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eISU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndustrial structure upgrading = (the added value of the primary industry *1\u0026thinsp;+\u0026thinsp;the added value of the secondary industry *2\u0026thinsp;+\u0026thinsp;the added value of the tertiary \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:-\\sum\\:_{\\text{m}=1}^{3}（{\\text{Y}}_{\\text{m}}/\\text{Y}){\\text{Y}}_{\\text{m}}{\\text{L}}_{\\text{m}}）/(\\text{Y}/\\text{L})-1\\)\u003c/span\u003e\u003c/span\u003eindustry *3)/GDP; Industrial structure rationalization index = |(|.\u003c/p\u003e \u003cp\u003eAmong them, Y and L represent output and labor input, and m\u0026thinsp;=\u0026thinsp;1,2,3 distribution represents the primary, secondary and tertiary industries.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResearch input\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRDI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe ratio of R\u0026amp;D investment intensity to total regional tourism revenue to GDP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eExternal influencing factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel of economic development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRegional GDP per capita\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGovernment support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExpenditure on elderly welfare in the Civil Affairs sector (logarithm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarketization degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMarketization index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocation conditions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePassenger turnover (logarithm)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban construction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGreen coverage rate of built-up areas\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e4.1.3 Control variables\u003c/h2\u003e \u003cp\u003eBased on the consideration of the robustness of the regression analysis results, the following control variables are introduced: ①Retirement Tourism Industry Agglomeration (RTAC), with \"the ratio of the total income of regional retirement tourism to the national total income of retirement tourism\" as the proxy variable; ②Openness to the outside world (OPEN), represented by \"the proportion of total import and export trade to GDP by region\"; ③Transportation infrastructure level (TIL), represented by \"the proportion of total import and export trade to GDP by region\", in order to eliminate data heteroskedasticity and linearize the relationship between variables, the \"total freight volume\" is treated as a natural logarithm.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Measurement of the occurrence of high-quality development mode of the pension tourism industry\u003c/h2\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1 Occurrence of technological innovation-driven development mode\u003c/h2\u003e \u003cp\u003eBased on formula (1), the technology-driven index of China's 30 provinces (cities and districts) in the senior care tourism industry from 2014 to 2023 is calculated. It is set that if the increase of a province (city or region) exceeds the average increase of the whole country in the examination period, it is recognized that a technological innovation-driven development mode has occurred in that province. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e of the calculation results, the average increase of the country during the period of 2014\u0026ndash;2023 is 25.79%; among them, there are 16 provinces (municipalities and districts) exceeding the average increase, then the technological innovation-driven development mode has occurred in the senior care tourism industry of 16 provinces (municipalities and districts). On the whole, the occurrence of technological innovation-driven development mode nationwide presents significant regional differentiation characteristics. Relying on the strong economic foundation and industrial resource advantages, the eastern region (e.g., Jiangsu, Tianjin, etc.) empowers the high-quality development of the pension tourism industry with industrial technology through the application of intelligent pension technology, digital tourism platform and other innovative means. Central region (such as Anhui, Jiangxi, etc.) relying on resource integration to form a latecomer competitiveness, and actively undertake the transfer of industries in the east, the use of regional ecological resources to develop intelligent recreation and tourism. Western regions (e.g. Chongqing, Sichuan, Ningxia, etc.) rely on policy support and digital upgrading of cultural and tourism resources, with significant technology-driven effects.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in provinces with technological innovation-driven development mode\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrder number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum value during the period\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmplification\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTianjin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.28%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJiangsu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1848\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZhejiang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnhui\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.0978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.09%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJiangxi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHenan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHunan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuangxi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHainan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.6084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChongqing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSichuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4527\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.02%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShaanxi Province\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.86%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGansu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.92%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQinghai\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5878\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNingxia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.31%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eXinjiang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.5200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.83%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e4.2.2 Occurrence of industry upgrade-driven development mode\u003c/h2\u003e \u003cp\u003eBased on formula (2), the new mode-driven index of China's pension tourism industry in 30 provinces (cities and regions) from 2014 to 2023 can be calculated. It is set that if the increase of a province (city or region) exceeds the average increase of the whole country in the examination period, it is recognized that the industry upgrade-driven development mode has occurred in that province. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows that the national average increase during 2014\u0026ndash;2023 is 23.6%; among them, there are 9 provinces (cities and districts) exceeding the national average increase, and 9 provinces (cities and districts) have experienced the industry upgrading-driven development mode in the senior care tourism industry The 9 provinces (cities and districts) show significant regional differentiation characteristics. High growth rate areas concentrated in economically developed provinces (such as Tianjin, Beijing, Shanghai), which rely on the advantages of talent, capital and technology to realize the transformation of the elderly tourism industry into a high-end industry. Medium growth rate provinces such as Jilin, Fujian, Hainan, etc. achieve differentiated development through the development of special resources. In contrast, the growth rate of traditional tourism provinces such as Liaoning, Zhejiang and Guangdong is on the low side, reflecting their gradual exploration of new market segments and gradual optimization of industry structure in the traditional path of dependence.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in provinces with industry upgrading-driven development mode\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrder number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum value during the period\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmplification\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeijing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.5762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e103.61%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTianjin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.3098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e168.36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiaoning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJilin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.9888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.54%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShanghai\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96.68%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZhejiang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFujian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.3939\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuangdong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.06%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHainan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e4.2.3 Occurrence of talent change-driven development model\u003c/h2\u003e \u003cp\u003eBased on formula (3), the talent concentration of the senior care tourism industry in 30 provinces (cities and districts) in China from 2014 to 2023 can be calculated. It is set that if the increase of a province (city or region) exceeds the average increase of the whole country in the examination period, it is recognized that the talent change-driven development mode has occurred in that province. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e of the calculation results, the national average increase during the period of 2014\u0026ndash;2023 is 14.80%; among them, there are 14 provinces (municipalities and districts) exceeding the national average increase, and the talent change-driven development mode has occurred in the senior care tourism industry in 14 provinces (municipalities and districts). The talent change-driven development mode in central and western regions showed strong growth potential; relying on the strategy of the rise of central China and the development of western China, accelerating the pace of talent introduction has promoted the high-quality development of the senior care tourism industry. In addition, Yunnan, Guizhou and Sichuan are rich in recreational and cultural tourism resources, attracting a large number of elderly tourists and professionals to gather, forming a favorable ecological environment for the development of the senior tourism industry.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in provinces with talent change-driven development model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrder number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProvince\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaximum value during the period\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAmplification\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHebei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.8322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.9886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiaoning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.7630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.9060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeilongjiang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.7303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.1846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnhui\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.7089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.7149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.99%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJiangxi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.3151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.4961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHenan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.5923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.8279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.74%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHubei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.8750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.9996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHunan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.0227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.3746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSichuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.2434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.8836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuizhou\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.0041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.2522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.79%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYunnan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.7035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.1393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShaanxi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.6060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.6244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQinghai\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.5562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.6546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNingxia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.6518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.4577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.32%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Analysis of influencing factors of the high-quality development model of the pension tourism industry\u003c/h2\u003e \u003cp\u003eThe fixed effect model is used to test the effect of the above influencing factors on the high-quality development mode of the pension tourism industry. The introduction of fixed effects can effectively control the endogeneity problem, thus enhancing the accuracy of causality estimation.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 Analysis of the results of the influencing factors of the technological innovation-driven development model\u003c/h2\u003e \u003cp\u003eBased on a study of provinces with technology innovation-driven development model, the 16 provinces whose technology-driven index (TDI) exceeds the national average increase are selected as a sub-sample to form a panel data composed of 16 provinces during the 10-year period of 2014\u0026ndash;2023, and the explanatory variable is set to be the TDI for model estimation. First, the samples are tested for multicollinearity; the correlation coefficients among the explanatory variables are basically not greater than 0.8, indicating that the correlation among the explanatory variables is weak and there is no highly linear correlation. For the consideration of the robustness of the estimation results, the three control variables were used as the basis for the fitting process, and the core explanatory variables were added one by one (the results are shown in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe results show that the model works well and the R\u0026sup2; value climbs steadily from 0.8282 to 0.9480 gradually, implying that the explanatory power of the model for the changes in TDI is increasing. The improvement of TDI is the result of the synergistic effect of internal and external factors, but there are significant differences in the paths and effect strengths of different factors. In terms of model effects and variable impacts (see Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), human capital, industrial structure upgrading, level of economic development, government support, urban construction and level of transportation infrastructure have significant positive impacts on the technology-driven index, while the degree of marketization, industrial efficiency, aging financial burden, and R\u0026amp;D investment do not reach significant impacts, location conditions negatively affect the technology-driven index, and the impact of the degree of openness to the outside world fluctuates with the The influence of openness to the outside world fluctuates positively and negatively with the inclusion of model variables. This indicates that it is necessary to focus on optimizing industrial structure, improving the quality of economic and urbanization development, and improving transportation infrastructure to strengthen the drive for technological innovation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression results of technological innovation driving factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003cp\u003eTDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e 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colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0155**\u003c/p\u003e \u003cp\u003e(2.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0167**\u003c/p\u003e \u003cp\u003e(2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0146**\u003c/p\u003e \u003cp\u003e(2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0154**\u003c/p\u003e \u003cp\u003e(2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0006\u003c/p\u003e \u003cp\u003e(0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0009\u003c/p\u003e \u003cp\u003e(0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0053\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0052\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0053\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0050\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0070\u003c/p\u003e \u003cp\u003e(1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0065\u003c/p\u003e \u003cp\u003e(1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0039\u003c/p\u003e \u003cp\u003e(0.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.0259\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.0257\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0002\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRTAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3692\u003c/p\u003e \u003cp\u003e(0.255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1291\u003c/p\u003e \u003cp\u003e(0.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0823\u003c/p\u003e \u003cp\u003e(0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0292\u003c/p\u003e \u003cp\u003e(-0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.4361\u003c/p\u003e \u003cp\u003e(-1.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.1111\u003c/p\u003e \u003cp\u003e(-0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.1063\u003c/p\u003e \u003cp\u003e(-0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.0954\u003c/p\u003e \u003cp\u003e(-0.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.1698\u003c/p\u003e \u003cp\u003e(-0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.1406\u003c/p\u003e \u003cp\u003e(-0.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOPEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3335\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3954\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3333\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(2.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2197\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(1.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1479\u003c/p\u003e \u003cp\u003e(1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.2031\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.2174\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.2152\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.2058\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-2.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.2920\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-3.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2224\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2069\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2043\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2135\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2137\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(5.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0879\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0870\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0804\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0903\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0999\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(3.89)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.7160\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-3.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.186\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(7.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.367\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.262\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(8.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.382\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(9.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.952\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-5.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.798\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.970\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-4.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-1.384\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-3.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.390\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(-3.56)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.9418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.9432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.9440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.9459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.9480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: The numbers in parentheses are t-statistics, and *, ** and *** indicate the significance levels of 10%,5% and 1% for variable 1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Analysis of the results of the influencing factors the industry upgrade-driven development model\u003c/h2\u003e \u003cp\u003eBased on a study of provinces with industry upgrade-driven development model, the nine provinces whose New Industry Driving Index (NEDI) exceeds the national average increase are selected as a sub-sample to form a panel data composed of nine provinces during the 10-year period of 2014\u0026ndash;2023, and the explanatory variables are set as NEDI for model estimation. In order to avoid excessive correlation between variables affecting the reliability of the empirical analysis results, the article first analyzes the correlation of each variable and finds that the correlation coefficient between the explanatory variables is basically less than 0.8, of which only one higher value of 0.8005 exists. In order to ensure that the possible effects of multicollinearity are excluded, the VIF multicollinearity test is further conducted on the main variables, and the results show that Mean VIF\u0026thinsp;=\u0026thinsp;5.6\u0026thinsp;\u0026lt;\u0026thinsp;10, i.e., there is no multicollinearity problem among the explanatory variables. Meanwhile, for the consideration of the robustness of the estimation results, the three control variables were used as the basis for the fitting process, and the core explanatory variables were added one by one.\u003c/p\u003e \u003cp\u003eThe results show (see Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e): the overall performance of the model is good, and the R\u0026sup2; value rises from the initial 0.3630 to 0.6694, indicating that the explanatory power of the model on the changes of the New Industry Driving Index (NEDI) is significantly improved with the gradual addition of variables, and the industry upgrading-driven development mode of the pension and tourism industry is affected by the differentiation of internal and external factors. In terms of model effects and variable influences (see Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e), factors such as human capital, degree of marketization and urban construction have a significant positive influence on the NEDI, industrial efficiency, financial burden of the elderly and government support negatively influence the NEDI, and industrial structure upgrading, R\u0026amp;D investment, economic development level, and location conditions do not reach a significant influence. This suggests that the high-quality development of pension tourism industry driven by industry upgrading needs to take human capital and market-oriented reform as the core driving force, pay attention to alleviating the crowding out effect of the burden of the elderly, and balance the efficiency enhancement and innovation inputs; at the same time, avoid falling into the \"efficiency trap\" of the traditional industry.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression results of industry upgrading-driven drivers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(9)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(10)\u003c/p\u003e \u003cp\u003eNEDI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHCM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0375\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0401\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0432\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0367\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e 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colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.9470\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.0669\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.1477**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.3693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.4641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.1301\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e 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colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.0266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.0280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.0286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.0332\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.0867\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.0748\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0748\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(2.39)\u003c/p\u003e \u003c/td\u003e 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colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(1.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRTAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.5961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.3160\u003c/p\u003e \u003c/td\u003e \u003ctd 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\u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTIL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0000\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e 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align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(0.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e_cons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.1085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4345\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1584\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7011\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.9476\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.0030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.1700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.3057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.8514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.4260\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(-0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(-0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(0.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.6510\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.6694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: The numbers in parentheses are t-statistics, and *, ** and *** indicate the significance levels of 10%,5% and 1% for variable 1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e4.3.3 Analysis of the results of the factors influencing the talent change-driven development model\u003c/h2\u003e \u003cp\u003eBased on a study of provinces with talent change-driven development model, the 14 provinces whose talent concentration degree (TCD) exceeds the national average increase are selected as a sub-sample to form a panel data composed of 14 provinces during the 10-year period from 2014\u0026ndash;2023, and the explanatory variable is set as TCD for model estimation. First, the sample is tested for multicollinearity, and the correlation coefficients between the explanatory variables are basically no greater than 0.8, and the VIF values of the variables are all less than 10, so there is no problem of multicollinearity; out of the consideration of the robustness of the estimation results, the three control variables are used as the basis for the fitting process, and the core explanatory variables are added one by one.\u003c/p\u003e \u003cp\u003eThe results show (see Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e): the model overall performance is good, and the R\u0026sup2; value is significantly improved from the initial 0.1051 to 0.7139, which indicates that the explanatory power of the model on the changes of talent concentration degree (TCD) is significantly enhanced with the gradual addition of variables. In terms of model effects and variable impacts (see Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e), the four factors of internal influences of industrial efficiency, aging fiscal burden, industrial structure upgrading and R\u0026amp;D investment have a significant impact on talent change-driven development model. The external factors of economic development level, marketization degree and location conditions have a significant impact. Among them, aging financial burden, marketization degree and location conditions have negative influence.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRegression results of talent change-driven drivers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv 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align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(2.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(2.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(2.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAFB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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colname=\"c4\"\u003e \u003cp\u003e(1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(-2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(-2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(-2.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(-2.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eISU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.9080\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3074\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.1551\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.2027\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.5479\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.5222\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e 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colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.2104\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.2081\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(-2.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(-2.79)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(0.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRTAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6.6543\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-16.7996\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-13.4723\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-13.3893\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-15.2602\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-13.7875\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-13.7130\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(-1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-4.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-3.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(-3.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(-4.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(-4.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(2.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOPEN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.2788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1520\u003c/p\u003e \u003c/td\u003e 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colname=\"c2\"\u003e \u003cp\u003e(-0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(-0.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-1.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(-1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(-2.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(-2.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(-2.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" 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\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-3.0385\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-5.6337\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.5370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.3977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(12.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(11.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(6.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(7.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(9.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(-2.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(-3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(-1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(-1.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.6602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.6636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.6932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.7134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.7139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote: The numbers in parentheses are t-statistics, and *, ** and *** indicate the significance levels of 10%,5% and 1% for variable 1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion and discussion","content":"\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Research conclusion\u003c/h2\u003e \u003cp\u003eFirst, three high-quality models of the pension tourism industry are refined. Based on the rooted theoretical analysis of 10 cases of senior care tourism enterprises, three high-quality development modes, namely, technological innovation-driven, industry upgrading-driven and talent change-driven, are identified. The three modes show a dynamic evolutionary logic chain of \"technological innovation provides tools\u0026rarr;industrial upgrading creates value\u0026rarr;talent change enhances effectiveness\"; the three modes differ in terms of the applicable subject, the driving core, and the path of value creation, etc. The study finds that, for the first time, the senior care tourism industry has been recognized as a high-quality development mode from the perspective of new quality productivity. The study finds that the first high-quality development model of pension tourism industry is refined from the perspective of new quality productivity, which meets the real needs of the development of pension tourism industry under the background of digital intelligence technology, and breaks through the traditional research perspective of industrial economy. At the same time, it reveals the internal logic of the high-quality development of the industry driven by the new quality productivity, and enriches the theoretical research on the intersection of pension tourism and the new quality productivity.\u003c/p\u003e \u003cp\u003eSecond, it reveals the pattern of high-quality development mode selection of China's pension tourism industry in various provinces.The occurrence of high-quality development modes of China's pension tourism industry in 30 provinces in 2014\u0026ndash;2023 shows that: the technological innovation-driven development mode occurs in the eastern, middle and western regions; the industry upgrading-driven development mode is mainly concentrated in economically developed provinces such as Beijing, Shanghai and Guangdong; the talent change-driven development mode occurs in the middle and western regions; and the talent change-driven development mode occurs in the middle and western provinces. The potential of talent change-driven development mode is outstanding in the central and western regions. This study finds that for the first time, quantitative research scientifically reveals the law of high-quality development mode selection of China's pension tourism industry in various provinces, which makes up for the shortcomings of most of the existing studies that are based on qualitative descriptions, and provides empirical guidance for the scientific decision-making of pension tourism industry in various regions. Meanwhile, the combination of rooted theory and panel data analysis realizes the complementarity of qualitative exploration and quantitative verification, and enhances the scientific and persuasive nature of the research conclusions.\u003c/p\u003e \u003cp\u003eThirdly, the influencing factors of high-quality mode selection in the elderly tourism industry are analyzed. Technological innovation-driven development mode is positively influenced by human capital, industrial structure upgrading, economic development level, government support and transportation infrastructure, while location conditions play a negative role; industry upgrading-driven development mode is driven by high-quality talents and the degree of marketization, while efficiency improvement of the traditional industry and the pressure of public finances inhibit its development; talent change-driven development mode relies on internal industrial efficiency, R\u0026amp;D investment and external economic development level; and talent change-driven development mode relies on internal industrial efficiency, R\u0026amp;D investment and external economic development level. The talent change-driven development model relies on internal industrial efficiency, R\u0026amp;D investment and external economic development level, while the degree of marketization and location conditions have a negative influence. This study reveals the internal and external influencing factors and their heterogeneity in the selection of high-quality models for the pension and tourism industry in the digital age, especially examining the special mechanisms such as the \"traditional efficiency trap\" and the \"fiscal pressure crowding out effect\", which makes up for the lack of attention to the practical suitability of the models in the previous studies. In particular, it examines the special mechanisms such as the \"traditional efficiency trap\" and the \"financial pressure crowding out effect\", which makes up for the shortcomings of the previous studies that have paid insufficient attention to the adaptability of the model practice, enriches and expands the research on the influencing factors of the selection of high-quality models of the pension and tourism industry, and provides new perspectives for the understanding of the differentiation of the development of the pension and tourism industry in the region.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Practical implications\u003c/h2\u003e \u003cp\u003eBased on the above conclusions, the main initiatives to empower the high-quality development of the tourism and pension industry with new productivity include: first, for the technological innovation-driven model, the \"East, Central and West Technology Collaboration Network\" should be established, with the eastern region exporting digitalization and intelligent technology experience, and the central and western regions relying on the characteristic resources to carry out the adaptive technological transformation, and at the same time, strengthening the transportation infrastructure and regional technology platform. At the same time, we should strengthen the connection between transportation infrastructure and regional technology platforms, promote cross-regional transformation of technological achievements, and break down regional barriers to technology application. Secondly, for the mode driven by industry upgrading, a \"special fund for cultivating new industries\" can be set up, focusing on supporting the integration projects of \"tourism\u0026thinsp;+\u0026thinsp;medical care\", \"culture\u0026thinsp;+\u0026thinsp;recreation\", etc., and reducing the pressure on public finance through market-oriented reforms. At the same time, through market-oriented reforms to reduce the crowding out effect of public financial pressure on innovation, encourage enterprises to set up innovation teams with high-quality talents as the core to break through the efficiency bottleneck of the traditional industry. Finally, around the talent change-driven model, we need to build a \"school-enterprise-land\" linkage training mechanism, universities add interdisciplinary major in elderly care tourism services and management, local governments to introduce talent subsidies and career development policies, and enterprises to improve the skills upgrading and incentive system, forming a \"cultivation-introduction-retention\" talent closed loop. This will form a closed loop of \"cultivation-introduction-retention\" and help release the potential of talent drive in the central and western regions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Limitations and prospects\u003c/h2\u003e \u003cp\u003eAlthough this study reveals the mode selection mechanism of new quality productivity driving the high-quality development of the pension tourism industry, there are certain limitations. For one thing, based on 10 typical cases of senior care tourism enterprises to refine the model type, the number of cases is limited and concentrated in the head enterprises, which is difficult to reflect the practice characteristics of small and medium-sized micro-organizations and characteristic counties of senior care tourism, which may affect the universality of the model. In the future, the breadth of cases and data can be expanded to include cases of small and medium-sized micro-enterprises and counties with special characteristics, so as to improve the refinement of the study by combining micro and macro data. Second, the empirical analysis identifies the independent role of each factor, but does not fully explore the interaction mechanism between variables, and does not sufficiently study the specific path of policy tools. In the future, we can analyze the role of variable combinations through the moderating and mediating effect models, and quantify the impact of different policy tools by combining policy evaluation methods, so as to provide the basis for precise policy implementation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Chongqing Jiaotong University (Approval Numbers：2025Q0285-003).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent has been obtained from all participants and/or their legal guardians. Interviews were conducted on March 11, March 24, March 25, and April 8, 2025.Prior to the interview, informed consent was obtained from participants, who voluntarily agreed to answer questions. Before conducting the semi-structured interview, the purpose was explained, and participants were informed that all content would be anonymized for academic research only. Personal information will be strictly confidential.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eDeclarations of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e[Funding]\u003c/strong\u003e This study was funded by Research Project of Humanities and Social Sciences of Chongqing Municipal Education Commission in 2025(Grant number:K24YD2070038);Chongqing\u0026apos;s Education Science \u0026quot;14th Five-Year Plan Project\u0026quot;（Grant number:K24YD2070038）\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHuang JX, Zhao XY (2023) Research on key factors for the high-quality development of elderly health and wellness tourism bases based on the DEMATEL-ISM-MICMAC method. 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Res World, (4), 33\u0026ndash;46\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"New quality productivity, Pension tourism, High-quality development, Development model","lastPublishedDoi":"10.21203/rs.3.rs-7619668/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7619668/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn the context of the strategic response to population aging, the high-quality development of the elderly tourism industry plays a crucial role in addressing the structural contradictions between economic growth and insufficient elderly care. Under the driving force of new-quality productive forces, scientifically selecting development models has become the key to achieving high-quality development in the elderly tourism industry. Based on multiple case studies, a theoretical model for the high-quality development of the elderly tourism industry driven by new-type productive forces has been constructed. Taking China's 30 provinces (regions and municipalities) as the research object, the occurrence of high-quality development models in the elderly tourism industry across provinces has been examined. Additionally, a multiple regression model has been constructed to empirically test the effects of development model influencing factors. The research results show that there are three types of high-quality development models in China's elderly tourism industry: technology innovation-driven, business model upgrading-driven, and talent transformation-driven. The high-quality development model of China's elderly tourism industry exhibits regional differentiation characteristics. The technology innovation-driven model is prevalent in eastern, central, and western regions, the business model upgrade-driven model primarily occurs in economically developed provinces, and the talent transformation-driven model is concentrated in central and western regions. The selection of high-quality development models for the elderly tourism industry is influenced by a combination of internal and external factors, including human capital, industrial efficiency, the fiscal burden of an aging population, industrial structure upgrading, R\u0026amp;D investment, economic development levels, government support, marketization levels, locational conditions, and urban development. It is necessary to comprehensively consider the combined influence of internal and external factors to select an appropriate development model.\u003c/p\u003e","manuscriptTitle":"Breaking the Aging Dilemma: A Study on High-Quality Development Models for Pension Tourism Industry Driven by New Quality Productive Forces","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-22 12:56:45","doi":"10.21203/rs.3.rs-7619668/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-09T06:13:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T13:26:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-23T03:06:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164812915860934110612610481069021420592","date":"2026-04-19T01:15:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"70366437267237954143459212267352363989","date":"2026-04-14T10:07:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-24T14:19:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53065806049654892737076083434829315277","date":"2026-03-05T00:31:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-17T15:32:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-29T04:59:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T09:47:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-12T13:04:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-11-12T12:59:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"49fc9e97-fc5b-4ef5-bf20-8389e8f6d1a0","owner":[],"postedDate":"February 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-09T06:13:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T13:26:23+00:00","index":144,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":63081304,"name":"Business and commerce/Economics"},{"id":63081305,"name":"Social science/Economics"},{"id":63081306,"name":"Earth and environmental sciences/Environmental social sciences"}],"tags":[],"updatedAt":"2026-05-15T13:53:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-22 12:56:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7619668","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7619668","identity":"rs-7619668","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}