DOI:http://doi.org/10.65281/738364 Yueqi Li1, Chen Yuan 2* 1College of Business,Quzhou University,Quzhou，Zhejiang,324000,China;  40083@qzc.edu.cn 2School of Finance,Nankai University,Tianjin,300350,China; 1120211042@mail.nankai.edu.cn Statements and Declarations Consent to participate: Informed consent to participate in the research was obtained from all participants in written form. Consent for publication: Not applicable. This study does not include any data from individual persons, such as images or videos, requiring consent for publication. Declaration of conflicting interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Data availability: The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. Data sharing is subject to ethical and legal restrictions to protect participant confidentiality. Author Note: Correspondence concerning this article should be addressed to Chen Yuan 2* Email: 1120211042@mail.nankai.edu.cn Abstract In the rapidly growing and competitive global market landscape, only those businesses can survive which adapt the latest technological (e.g., big data) tools. Today’s world is going through the digital marketing transformation. Enterprise digital marketing and big data work closely to reach their targeted market segments. Aligning the business strategy with big data digital marketing is the key of today’s successful enterprises in China. Keeping this view, the current study explored the importance of enterprise digital marketing strategy for business performance based on big data. The study sample was represented by 390 experts from the various Chinese enterprises. Study design was cross-sectional and the instruments were adopted from the existing research, and standardized questionnaire was formed to collect the survey data. To empirically validate the model, statistical data was analyzed by using Smart PLS and SPSS. Enterprise digital marketing strategy and big data were studied with business performance through mediation of customer relationship management (CRM). Results showed that enterprise digital marketing strategy, big data and CRM have significantly positive impact on business performance. Similarly, customer relationship management mediates the relationship between enterprise digital marketing and business performance. Contrary to this, customer relationship management has no impact between the relationship of big data analytics competency (BDAC) and business performance. The research findings proved that enterprise digital marketing based on the big data is the need of the time and essential for the survival of the enterprises in China. Furthermore, the findings are aligned with the previous researches that has revealed the fact that higher big data analytics competencies result in higher firm performance. Keywords: Enterprise Digital Marketing Strategy; Big Data; Customer Relationship Management; Business Performance. Introduction Nowadays due to rapid advances in technology and an ever-expanding range of digital applications, China has entered the big data era. In light of these recent developments, the marketing strategy employed by businesses across all sectors has experienced major changes. The enterprises are one of China’s fastest growing traditional industries (Jun, Yoo, & Choi, 2018). The impact of the digital marketing approach on the traditional enterprises has been un-precedent. Traditional marketing ideas have gradually lost their competitive advantage. If we do not modify the ideas that we use for marketing and continue to implement old marketing techniques, then the local business will not be able to maintain its competitive advantage in the market competition. Thus, in order to establish the basic capabilities necessary for core competitiveness, it is vital to examine the specific marketing of businesses (Parkin, 2016). So, the rise of digital marketing has changed the way of the world’s economy works and given consumers more power. Competition among businesses has become more competitive as a result of the expansion of digital technology (Dastane, 2020). The use of digital technologies (e.g., big data) has resulted in significant changes to the communication between corporations, audiences, and a variety of other organizations (Suleiman, Muhammad, Yahaya, Adamu, & Sabo, 2020). The term “digital technology” refers to the utilization of new technology for the purpose of achieving marketing goals (Ghobakhloo,2020). In a similar manner, the use of digital technology requires an entirely new range of knowledge and skill. When working in an atmosphere that is dominated by digital technology, it is difficult for marketers to successfully apply traditional marketing strategies (Biletska, Paladieva, Avchinnikova, & Kazak, 2021). The rapid growth of digital marketing is occurring in tandem with the general expansion of digital technology, such as smartphones, intelligent products, the internet of things, and artificial intelligence (AI) (Jianjun et al., 2021; Berg, Burg, Gombovi, & Puri, 2020). This has a significant impact on the performance of businesses, and it is also helping to reshape the future marketing strategy (Buttle & Maklan, 2019). Smartphones offer additional benefits to users in the form of instant access to services, in comparison to the traditional services offered by the organization (Algharabat, Rana, Alalwan, Baabdullah, & Gupta, 2020). The expansion of digital technology has made it easier for customers to gain access to services whenever and wherever they want by logging in to the website of the company, which features a background filled with information about the services offered and graphs (Su, Lin, & Wang, 2022). The expansion of digital technology has made it possible for businesses to cut their spending on traditional forms of marketing through the integration of social media, which presents a possibility for cost savings. However, it can be difficult for marketers to select the optimal combination of digital marketing strategies to increase brand recognition and successfully achieve the appropriate level of business performance through the collection of 296 different opinions from customers continuously (Tamrakar, Pyo, & Gruca, 2018). Furthermore, digital marketing can encourage a diverse variety of clients to establish an effective relationship with the company via digital media in order to direct them in the procurement process (Kurdi, Alshurideh, Akour,Alzoubi, Obeidat, & Alhamad,2022). Sharing ideas, perspectives, and experiences of customers through digital marketing helps to establish the value of the brand in an effective manner, which ultimately results in improved business performance and a better relationship with customer’s enterprises are becoming extremely advanced and efficient, which has led to the development of customer relationship management (CRM) (Wai, Dastane, Johari, & Ismail, 2019). CRM was

DOI:https://doi-xx0.org/6812/17738278534223 Yun Zhao1,2,a  Peihua Shi1,b  Sijia Cheng3*,c （1.College of Tourism and Service, Nankai University, Tianjin, 300350, Tianjin, China； 2.College of Tourism Management, Guilin Institute of Tourism, Guilin, 541006, Guangxi, China； 3.College of Accounting and Auditing, Guangxi University of Finance and Economics, Nanning, 530003, Guangxi, China） a Email:15878398705@mail.nankai.edu.cn b Email:gl5878@126.com *Corresponding Author: Sijia Cheng ，dionysus_417@163.com   Abstract: Under the background of the digital economy, smart tourism technologies are gradually becoming a key driver of the travel industry’s digital transition, and the mechanisms through which it affects tourism operational efficiency warrant further exploration. This paper examines Chinese listed tourism companies on the A-share market from 2010 to 2023, constructs a panel data model, and eempirically examines the effect of wisdom tourism on tourism management efficiency, and tests the intermediary effect of information integration capabilities as well as the moderating effect of digital capabilities. The research results show that smart tourism technology can significantly improve tourism management efficiency; information integration capabilities serve as a partial mediating factor linking smart tourism tech and tourism management efficiency; and corporate digital capability can strengthen the promoting effect of smart tourism technology on management efficiency. The study indicates that smart tourism technology not only improves management efficiency by enhancing information processing and resource integration capabilities, but also exhibits more significant management effects in enterprises with stronger digital capabilities. This paper reveals the path of how smart tourism technology influences management efficiency from the perspective of tourism management, enriches related research on smart tourism, and provides references for the digital transformation of tourism enterprises and tourism management decision-making. Key words: Smart tourism technology; Tourism management efficiency; Information integration capability; Digital capability   1 Introduction As digital economy continues to develop with the help of digital,information and communication technology slowly start changing the digital transformation of traditional industry. During this period the tourism business has been growing through a different manner, there was this new growth consisting of digital things. In recent years, big data, artifical intelligences, data centers and so on are also widely used in the fields of tourism service and travel management which promote the tourism industry towards more digital and smarter operation. According to relevant research, digital technologies such as collecting tourism-related data, sharing information among different stakeholders, conducting intelligent analyses of data, and sharing information among different stakeholders have the ability to improve the digital level of tourism industry so as to promote innovation in tourism management models. (Gretzel et al., 2021)[1]. Under such circumstances, smart tourism has become a very important way for scenic spots to improve their management efficiency and competitiveness. The role of digital platforms and data systems for tourism management is growing. Based on the research, digital technologies enable Tourism Authorities to access real-time tourist behavior data, market demands, which give decision-making data for the tourism industry (Xiang et al., 2022)[2]. At the same time, digital platforms promote the exchange of information and resource integration, and can promote the coordinated development of tourism service systems and tourism management systems (Huang et al., 2023) [3]. Thus, smart tourism technologies change both how tourists get info as well as give dests man technologies. Although the academic research of smart tourism is more now, but most of them focus on tourism experience, service innovation, and destination competitiveness. Take as an example, there are studies analyzing digital technologies impact on tourist satisfaction and experience from a behavior aspect (Neuhofer et al., 2021)[4], others are exploring digital technologies impact on smart tourism ecosystem development from industry aspects (Gretzel et al., 2021)[5]. However, the research on the influence of wisdom-based tourism on operational efficiency from a tourism management perspective is still quite little. In particular, with regard to tourism management, there is still no theoretical analysis and practical research on the application of digital technology to improve management efficiency through information integration and data analysis. At the same time, with the continuous progress of digitization, integration of information is also one of the factors that influence the organizational management efficiency. Relevant studies indicate that digital technologies can improve organizational performance by integrating dispersed information resources and enhancing information utilization efficiency (Verhoef et al., 2021)[6]. In the tourism industry, smart tourism technologies achieve data integration and sharing through digital platforms and information systems, which not only contributes to more scientific decision-making in tourism management but may also further improve management efficiency. Therefore, analyzing the effect of wise tourism on tourism operation efficiency from the perspective of information integration holds significant theoretical importance. Based on the above background, the present study examines the mechanisms through which smart tourism technologies influence the efficiency of tourism management and further analyzes the role played by information integration capabilities in this process. By conducting an empirical study using data from Chinese tourism-related listed firms, this paper aims to reveal how smart tourism technology affects tourism management efficiency, and provides theoretical references and practical insights for the digital governance of tourism destinations. At the same time, this study helps enrich theoretical perspectives on wisdom-based tourism while providing new research evidence to support the digital transformation of the tourism sector.   2 Literature Review 2.1 Research on Smart Tourism Technology The concept of smart tourism was first proposed by Gretzel (2015) [7], who believed that smart tourism is a tourism ecosystem driven by information technology. The swift advancement of information and communication systems has made digital-driven travel an increasingly vital model for driving the digital transformation within the industry. In recent years, it is widely recognized in academic circles that intelligent tourism is a novel development model in the tourism industry that leverages foundational data such as large data, the interconnection of objects, advanced artificial intellect, and data cloud computing, which integrates tourism information resources and service systems to achieve intelligent tourism services, management, and decision-making (Shasha et al., 2025)[8]. Against the backdrop of the rise of smarter cities in the digital economy, smart tourism has not only changed the way tourists travel, but also promoted innovation in destination management models. In recent

https://doi-xx0.org/6812/17671051479640 Shiying Zhang1,a, Hui Wang2,b, Yanhong Lu3,c, Haoxin Xiu4,d,*  1Business School of Nankai University, Tianjin, 300071, Tianjin, China; 2Institute of Economics, Shandong Academy of Social Sciences, Jinan, 250002, Shandong, China 3School of Economics and Management, Hebei University of Technology,Tianjin, 300401 ,Tianjin,China 4Qingdao Hospital, University of Health and Rehabilitation Sciences（Qingdao Municipal Hospital), Qingdao, 266011, Shandong, China aEmail: shiying.zhang@mail.nankai.edu.cn bEmail: ouc_wanghui@163.com cEmail: luyanhong2015@163.com dEmail: xhx19931011@163.com *Corresponding Author Abstract Amidst concurrent internal and external economic pressures, Chinese firms confront a critical challenge: the allocation of scarce resources. This study addresses this dilemma by introducing a leverage point framework. Utilizing firm-level data, our approach employs interpretable machine learning. The goal is to algorithmically discern the pivotal drivers of corporate sustainability within a severely resource-constrained environment. The empirical basis for our framework is a substantial dataset. It comprises 19,518 firm-year observations of Chinese A-share companies from 2010 to 2022. We deploy high-dimensional predictive models, specifically advanced ensemble algorithms like Random Forest and XGBoost. Sustainable operation is defined through two key metrics: the Sustainable Growth Rate (SGR) and Profit Volatility (PV). Following model construction, we examined feature importance and created Partial Dependence Plots (PDPs) to interpret the model, revealing key determinants and significant non-linear relationships. The results offer compelling insights. Financial Performance and Green Development emerged as the highest-ranking determinants of corporate sustainability overall. Our modeling also uncovered critical non-linear thresholds. An optimal range for R&D investment was identified between a ratio of 0.125 and 0.20. Similarly, a supplier concentration level around 20% was found to maximize sustainable performance. Furthermore, the analysis exposed a variety of significant interaction effects, notably between the ROE growth rate and the adoption of green management practices. This research significantly advances the understanding of corporate sustainability drivers. It presents a novel, interpretable, and data-driven framework for strategic resource allocation. This framework is particularly valuable for firms navigating competing demands during periods of economic strain. Ultimately, the study provides actionable, evidence-based guidance. This advice aims to ensure firms not only capture value generation but also cultivate the resilience necessary for long-term growth. Keywords: Financial Performance, Green Development, R&D Investment, Supply Chain Management, Machine Learning 1 Introduction Modern Chinese businesses are facing a collision of serious external and internal pressures that undermine their underlying operational viability and potential for long-term sustainability. Externally, geopolitical tensions have manifested as strategic technology embargoes related to access to important semiconductors, and imposition of tariffs on significant exports like new energy vehicles. Internally, the economy is dealing with the repercussions of a severe real estate slump. Collapsing builders, such as Evergrande Group, have created a domino effect for upstream construction suppliers in terms of capital flow, not to mention that downstream home buyers have properties that they likely will never get. This has tightened liquidity across the economy, with firms in every industry being forced to either reduce salaries or lay-off staff, exacerbating corporate instability in every sector and lack of resources. In this “economic winter”, the businesses are in a strategic conundrum. On the one hand, firms must urgently restrict costs and remain focused on core activities for short-term survival and, on the other, national policy requires firms to make major forward-looking investments. The government’s “dual carbon” targets are forcing firms to transition to green development and requiring significant capital expenditures for environmental protection and energy-saving initiatives. The ideological thrust for innovation-based growth from the strategic directions outlined in the 20th National Congress requires firms to commit substantial funds to R&D. These long-term implications are critical to developing national competitiveness and accountability for ecological well-being, yet firms may not have the financial means to support this longer-term focus.The most notable effect of this resource constraint is the broken capital chain and disrupted supply chain activities that make it extremely challenging for managers to finance green initiatives and R&D in addition to making sure they stay financially solvent and their supply chains resilient. Therefore, how to make the best use of severely constrained resources has become the biggest issue for corporate viability and sustainable development. Existing literature on resource constraints has some valuable suggestions to offer. For example, it is found that firms following a ‘balanced’ strategy, allocating constrained resources to functions like marketing and R&D, perform better than firms allocating in only one function [1]. Another body of literature suggests that resource constraints can paradoxically spur innovation because firms must think creatively and make good use of resource constraints [2]. However, much of this literature has significant limitations in light of today’s complicated crisis. First, the studies tend to lack multi-dimensional analyses examining the role of the constraints on a single domain, say innovation, without consideration of the fact that green development, supply chain management and financial health are all now connected. Second, the type of analytical models used are often linear models which examine how investments, say in R&D, affect financial performance without consideration of the reciprocal and synergetic nature of these domains [3]. Scholarly literature, in general, does not allow for a unified framework of the relational, and at times conflicting, relationships among these three investment areas. This is important when thinking about the complexities faced in today’s environment. In order to move forward in a way that rejects the path of standard linear analysis, this study takes a machine learning (ML) approach. We have selected reasoning for a computational perspective because ML will allow for modelling of the complex, non-linear and bidirectional relationships that comprise corporate investment systems. Standard econometric approaches encounter endogeneity and multi-collinearity among variables and therefore routinely cannot model the multilayered complex interactions. Management uses simultaneous ML algorithms to simulate and forecast outcomes. Rather than limiting the analytical approach to cause and effect analysis pursued in traditional economics, the focus of the current research uses a whole-portfolio effect of a combination of investments that create the necessary green development, innovation and supply chain mix to achieve a baseline financial objectives as well as enable sustainable operation. ML model, by estimating prior data, identifies baseline variables and index points that would

https://doi-xx0.org/6812/17670800716792 Abstract Zailan Tian1* 1Guangdong Polytechnic Normal University *Corresponding author:Zailan Tian Email: hrtian2017@126.com ABSTRACT Based on 412 teacher questionnaires from S University, a moderated mediation model was constructed to examine the impact mechanism of digital leadership on higher education technology adoption. The results showed that digital leadership significantly predicts technology acceptance, with digital organizational culture partially mediating this path. Resource endowment positively moderates mediation strength, with the indirect effect reaching 0.38 in high-resource groups and 0.18 in low-resource groups (Δ=0.20). The bootstrap 95%CI [0.10,0.30] excludes zero. The study confirms that resource abundance amplifies the leadership-culture-technology chain, providing contextual boundary explanations for university digital transformation. Keywords Digital leadership; digital organizational culture; technology acceptance; resource endowment; moderated mediation model Introduction Under the impetus of China’s national digital education strategy, universities commonly face the dilemma of “policy enthusiasm but implementation stagnation” in technology adoption. The case of S University’s “Smart Teaching 2.0” demonstrates that platform login rates remain below 40%, indicating that mere technical provision cannot drive behavioral changes among faculty. While existing research predominantly focuses on individual perceptions or system characteristics, it overlooks the critical absence of leadership and cultural influence in the loosely coupled context of higher education. Systematic validation remains lacking regarding whether digital leadership can enhance technology adoption through shared norms, and how resource conditions such as funding, infrastructure, and literacy amplify this process. Clarifying these mechanisms not only fills gaps in technology acceptance theories within higher education contexts but also provides evidence-based foundations for developing differentiated governance strategies. Building on transformational leadership and social information processing theories, this study constructs a mediation model where “digital leadership → digital organizational culture → technology acceptance” is moderated by resource endowment. Through structural equation modeling and bootstrap methods, empirical testing was conducted on 412 faculty members across 18 departments to reveal the internal logic and boundary conditions of technology diffusion in higher education institutions. 1 Background and Problem Definition During the overlapping period of the “Double First-Class” initiative and national education digitalization strategy, higher education institutions are expected to leverage technology to drive pedagogical innovation. S University’s 2021 “Smart Teaching 2.0” five-year plan, built on three pillars—5G Plus campus networks, big data platforms, and immersive smart classrooms—aims to achieve real-time classroom data collection, instant learning analytics feedback, and dynamic teaching optimization. However, a significant gap exists between policy requirements and actual implementation: by the third semester, platform login rates remained at 38.6%, with less than 15% of faculty using it routinely. Existing research attributes this gap to technological maturity or individual acceptance, while overlooking the unique governance context of universities as loosely coupled organizations. Digital leadership is seen as the key to overcoming the “last mile” challenge, as its ability to shape digital visions, orchestrate resources, and provide institutional support directly influences technology adoption trajectories. Meanwhile, digital organizational culture—through shared cognitive frameworks, collaborative norms, and data-driven discourse—provides teachers with sustained meaning in technology use. When digital leadership is absent and vision signals weaken, faculty struggle to develop collective recognition of technological value. When digital organizational culture remains thin and data-driven practices are not yet established, even skilled teachers may revert to traditional approaches. Thus, the core logic explaining technological stagnation in higher education lies in the interplay between digital leadership, digital organizational culture, and technology adoption. Furthermore, universities exhibit significant inter-institutional disparities in funding availability, infrastructure completeness, and faculty digital literacy. The endowment of resources may amplify or suppress these transmission pathways, thereby creating a moderated mediating context. By focusing on University S as a single case study, we can not only conduct in-depth tracking of policy implementation processes but also capture marginal differences in resource regulation through departmental heterogeneity. This approach provides reusable mechanism explanations and governance paradigms for the digital transformation of higher education. 2. Theoretical Framework and Research Hypotheses 2.1 Direct effects of digital leadership on technology adoption In loosely coupled university governance contexts, digital leadership is conceptualized as a direct driving force exerted by university presidents and IT directors on faculty technology adoption through digital vision building, empowerment, and institutional incentives. Empirical evidence from S University’s “Smart Teaching 2.0” initiative demonstrates that when leadership frequently articulates transformational visions, presents clear roadmaps, and quantifies performance metrics to demonstrate necessity, faculty perceived usefulness of smart classrooms and big data platforms significantly increases, thereby driving adoption willingness. Transformational leadership theory posits that leaders can reduce teachers’ uncertainty avoidance toward new technologies through idealized influence and personalized care. The technology acceptance model further defines perceived usefulness and perceived ease of use as pre-cognitive factors shaping willingness. In higher education settings, digital leadership directly enhances perceived usefulness through strategic alignment communication, prioritized resource allocation, and risk mitigation commitments, bypassing the indirect path of perceived ease of use in traditional Technology Acceptance Model (TAM). Specifically, presidents consistently incorporate “data-driven decision-making” into departmental evaluation metrics during annual teaching conferences, while IT offices simultaneously publish platform usage white papers and offer early adopters class hour reductions and research credits. These signals reinforce faculty’s understanding of the instrumental connection between technological tools and career rewards. Consequently, the impact of digital leadership on technology acceptance can be abstracted into a single-path structural equation, highlighting its independent main effect. Among them, represents the teachers’ willingness to use the intelligent teaching system, represents the digital leadership intensity of principals and information managers, represents the path coefficient, and represents the error term. 2.2 The Mediating Mechanism of Digital Organizational Culture In higher education institutions, digital organizational culture manifests as a three-dimensional interactive system of group norms characterized by collaboration, data-driven practices, and continuous learning. Its formation and reinforcement rely on sustained leadership signals. During the implementation of S University’s “Smart Teaching 2.0” initiative, the president and IT director established a governance framework for data sharing, created cross-departmental teaching innovation communities, and incorporated learning analytics into faculty promotion criteria. These measures conveyed expectations of “collaborative lesson planning, data-driven decision-making, and lifelong professional development,” transforming individual cognition into collective action. The collaboration dimension reduces transaction costs for resource complementarity, the data-driven

Authors:  Li Fan Affiliations:Yu lin University First author email: Fanli741@163.com Abstract Background: In Northern Shaanxi Province, China, the Yangko heritage is being revived against the backdrop of contemporary problems and cultural progress. Aim: The goal of this research is to thoroughly examine the historical foundations, current issues, and creative solutions for Yangko preservation. Method: The study synthesizes previous research using a literature-centric method, providing insight into the effects of community dynamics, economic developments, and urbanisation on Yangko transmission. Results: The findings point to a variety of popularisation tactics that prioritize community involvement, digital platforms, and festivals. Despite the absence of primary data, the study offers insightful information about the difficulties this traditional folk dance faces. Conclusion: The necessity of cultural sensitivity, community cooperation, and adaptation techniques is emphasised in the conclusion as a means of guaranteeing Yangko’s lasting legacy in Northern Shaanxi. Keywords: Yangko, cultural preservation, traditional dance, Northern Shaanxi, community engagement, urbanisation, economic changes, cultural heritage. Introduction Background The ancient folk dance known as Yangko is the focal point of the Northern Shaanxi Province’s cultural mosaic, which is carefully intertwined with threads of history. With centuries-old roots, Yangko has been an integral part of the community and regional festivities. Its roots are in agricultural practices and Lunar New Year celebrations; thus, it is a live example of the mutually beneficial interaction that exists between the people of Northern Shaanxi and their rural environment (Lichao, and Jirajarupat, 2023). The dance itself is a colorful, energetic performance that features sophisticated hand moves, rhythmic footwork, and colourful costumes. In addition to being a medium for artistic expression, yangko promotes social cohesiveness through a sense of shared history and community identity. It has historically been passed down through the generations, with seniors teaching younger community members the subtleties of the dance, therefore maintaining the existence of this live culture (Nian, 2023). However, the Yangko tradition faces several obstacles that endanger its survival in the twenty-first century. The ancient customs that have shaped Northern Shaanxi’s cultural landscape are under threat from the quick speed of globalization and the incursion of technology. The younger generation is becoming more and more cut off from Yangko’s cultural heritage as they become more and more integrated into the digital age and urban lifestyle. Festivals and public meetings, which used to be the lively venues for Yangko performances, are becoming less and less common as other kinds of entertainment take the lead (Jing, and Sensai, 2022). In addition, the traditional rural way of life has been upended by the economic changes sweeping Northern Shaanxi, which has resulted in movement patterns that scatter communities and weaken the links that bind them together—communities that are crucial to the spread of Yangko. The dance is susceptible to the effects of increasing urbanisation since it is entwined with rural communities and agricultural cycles. It becomes harder and harder to transmit Yangko from one generation to the next as the old communal organisations crumble (Wang, and Yi, 2023). The Yangko tradition must be revived and preserved in light of these difficulties. Beyond its aesthetic and cultural significance, Yangko captures the tenacity, cohesion, and individuality of the people in Northern Shaanxi. In addition to documenting the historical significance of Yangko, this research aims to explore the multiple facets of this cultural endeavour and develop workable solutions for its resurrection in the modern era (Xiabin, 2020). Understanding Yangko’s evolution and the crucial part it played in people’s lives is made possible by its historical context. Yangko has been a living manifestation of the tight ties that the people of Northern Shaanxi have with their land, from its agricultural roots, which are closely related to planting and harvesting cycles, to its participation in the celebration of the lunar New Year and other important communal events (Hou, 2021). One important component of the research backdrop is the effect of globalisation on Yangko. The rise of outside influences frequently eclipses traditional customs as the world grows more interconnected. Yangko may seem outdated or unimportant to the younger generation, which is growing up in a time of digital entertainment and globalised trends. Developing tactics that unite tradition with modernity requires an understanding of the dynamics of globalisation and how they affect cultural practices (Gao, and Shi, 2023). The environment for Yangko is made more difficult by the urbanisation and economic changes that are sweeping through Northern Shaanxi. Yangko flourished in traditional rural communities, which are currently experiencing tremendous change. Younger people move to cities in pursuit of other ways to make a living, which breaks the generational transfer of Yangko in close-knit villages. The purpose of the research backdrop is to provide context for the urbanisation and economic changes that have transformed Northern Shaanxi’s social structure and impacted the region’s traditional means of cultural transmission (Jia, 2020). The research backdrop essentially lays the groundwork for a thorough investigation of the difficulties and possibilities related to Yangko revitalisation and preservation. It establishes the foundation for a concentrated examination into the popularisation, use, and instruction of this traditional folk dance in Northern Shaanxi Province by offering a comprehensive knowledge of the historical, cultural, and modern elements that define the milieu in which Yangko exists. Problem Statement The Yangko tradition in Northern Shaanxi Province is threatened by several factors that undermine its vitality and continuity, despite its rich historical value. The cultural transformations brought about by modernisation and globalisation have put a shadow over this age-old folk dance, jeopardising its continued existence as a vital component of the region’s cultural identity. The main issue is that newer generations, who are becoming more and more estranged from their cultural heritage, are becoming less and less familiar with Yangko. Traditional forms of cultural expression, like Yangko, are being pushed to the margins as urbanisation picks up speed and millennials become more interested in digital entertainment, potentially ending up in the annals of history. In addition, the transfer of Yangko across generations has been hampered by changes in the economy and changing work patterns, as

DOI:https://doi-xx0.org/6812/17707151636243 Abstract Future travel trends are significantly influenced by big data technologies. The current study explored the effect of tourist’s destination perceptions on tourism online content management information system in the context of big data. The present study hypothesized that big data has a moderating function in the development of tourist’s behavioral intentions. Moreover, the present study also analyzed the mediating role of tourism online content management information system in the relationship between tourist’s destination perceptions and tourist’s behavioral intentions. The information was gathered from 511 tourists in China’s Shanghai and Beijing cities. PLS-SEM results revealed a direct association between tourist’s destination perceptions and tourism online content management information system. The findings also confirmed the underlying role of big data as a moderating variable. Moreover, the results highlighted the implications of tourism online content management information system using big data technologies in the global tourism industry. Keywords: Tourist’s destination perceptions, tourism online content management information system, tourist’s behavioral intentions, big data. Introduction Before booking a trip, most tourists begin planning stage by doing internet research on the finest vacation spots and hotels (Not, 2021). For many years now, the internet has been the go-to resource for gathering details on fun activities to do in one’s spare time. Tourists’ access to ICT gadgets like computers, tablets, iPads, and smartphones has increased worldwide internet usage for tourism-related purposes including research, advertising, and consumption (Torres, 2022). Information on popular tourist destinations may be accessible through many online resources including social media, search engines, websites, and weblogs thanks to the meteoric rise of online shopping and booking in the hospitality sector. This has helped spread the word about the tourist and hospitality industries all across the globe. Tourists may now easily find, communicate with, compare, and decide to buy online tourism and hospitality bargains thanks to cutting-edge ICT and the internet (Liu, Wang, & Gretzel, 2022; Ravi & Vairavasundaram, 2016; Zhang, Wu, & Fan, 2019). Because consumers’ online search habits can be used to predict what they will buy from virtual markets, smart business technologies focus on collecting information about users’ online browsing history to influence their purchase decisions, satisfaction, happiness, and spreading behaviors (Silaban, Chen, Nababan, Eunike, & Silalahi, 2022). Organizations promoting tourist destinations hope that establishing a strong online presence will attract curious travelers looking for information online, and that providing such travelers with up-to-date and reliable data will prompt their current customers to leave positive reviews that can be easily accessed with a few mouse clicks (Mapanga, 2022; Sun, Liu, & Zhang, 2021). Positive feelings and plans to act, like wanting to go to a tourist spot, can come from using the internet in a good way (Jiménez-Barreto, Rubio, Campo, & Molinillo, 2020). Tourists’ experiences with tourism online content management information systems, such as the quality of online information and how easy it is to access, may have a big impact on their plans to travel (Lee, Lee, Jeong, & Oh, 2020). The rise of virtual markets for online shopping, on the other hand, often makes people worry about how safe and reliable online platforms are (Majeed, Zhou, Lu, & Ramkissoon, 2020b). Threats in the online business environment, like the possibility of losing personal information and payment identity information, may make customers less likely to shop online. This could help find out what travelers like and dislike about buying tourism and hospitality services online (Yu, Moon, Chua, & Han, 2022). The literature on tourism also investigates the link between satisfaction and tourists’ behavioral goals (Chen & Chen, 2010). But in the online tourism industry, the role of the tourism online content management information system as a link between how tourists feel about a destination and what they plan to do there hasn’t been studied yet. In recent years, the modern information society has moved into the age of “big data.” “Big data” has grown quickly into a well-known field that academics and businesses value, and it has been used in many ways (Chen & Li, 2022; Zhao, Zhou, & Mu, 2021). In recent years, artificial intelligence technology has grown quickly. The technology in the field of artificial intelligence has a lot of things that make it unique and complicated (Samala, Katkam, Bellamkonda, & Rodriguez, 2020). Teradata uses “big data” to help people plan their trip to the 2021 London Olympics through a dedicated website. It does this by sifting through the data and sending out emails that are more specific. This helped people avoid the crowds during the games, which affected about 35% of people’s travel decisions (Xie & He, 2022). With big data as the background, it is a great chance for the tourism industry to grow (Xu, 2020). But tourist marketing has several flaws: the idea is old, the techniques are old, and the methods are old. All of these things make it harder for tourism to grow in a sustainable way (Florek & Gazda, 2021; Richards, 2003; Xie & He, 2022). So, the goal of this study was to find out how it affects the link between a tourism online content management information system and tourists’ plans for how they will behave. This study tried to figure out how these things happened in China, which was one of the first places to have smart tourism. Also, the active growth of smart tourism in China is being driven by the following (Guo & Gu, 2022). China thinks that smart tourism is important for the country as a whole. At the beginning of 2011, China’s National Tourism Administration (CNTA) announced that it would start a smart tourism initiative. The goal of this initiative is to make China’s tourism more information-based within 10 years. Since then, China has made a lot of progress in smart tourism (Wang, Zhen, Tang, Shen, & Liu, 2021). In November 2013, the CNTA made the tourism theme “Beautiful China-2014 Year of Smart Travel” official. Smart tourism is a big part of the country’s plan to grow tourism (Jia et al., 2022). So, the main goal

Zhixin Yang1 Hao Deng1 Xiuyuan Shen2 Nan Jiang1* 1School of Management Guangxi Minzu UniversityAbstract 2Guangxi Medical College *Corresponding author: Nan Jiang Email: yangzhixin97@126.com Zhixin Yang Email:yzx121047@163.com Hao Deng Email:denghao188@163.com Xiuyuan Shen Email:18677053297@163.com This study examines the cultivation of entrepreneurial competencies among university students through the lens of innovation and entrepreneurship education. By analyzing corporate requirements for entrepreneurial talents—including market insight, resource integration, risk resilience, and innovative thinking—the research evaluates the alignment between current university programs ‘objectives, content, methodologies, and evaluation systems and enterprise needs. The paper proposes four strategic approaches: 1) aligning educational goals with corporate demands, 2) restructuring curricula to match industry requirements, 3) innovating implementation methods through enterprise integration, and 4) refining evaluation mechanisms based on business needs. These strategies aim to achieve precise alignment between entrepreneurial education systems and corporate requirements, enhance students’ entrepreneurial capabilities, provide enterprises with demand-aligned talent, and foster collaborative development between innovation education and industry needs. Keywords Innovation and entrepreneurship education; enterprise needs; entrepreneurial competence; training system; competency development Introduction As a pivotal direction in higher education reform, innovation and entrepreneurship education primarily aims to cultivate talents with entrepreneurial spirit and capabilities to meet the growing demand for such professionals in economic and social development. However, current practices in some universities fail to adequately align with corporate needs, resulting in issues like overly generalized training objectives, disconnect between theoretical content and practical application, methods that inadequately enhance practical skills, and evaluation systems that miss key industry requirements. These shortcomings hinder both the development of students ‘entrepreneurial competencies and the fulfillment of enterprises’ talent needs. Establishing a student entrepreneurship training framework through a corporate demand-oriented approach can not only optimize the effectiveness of innovation education, boost students’ entrepreneurial capabilities and market competitiveness, but also provide enterprises with well-prepared talent. This strategy promotes deeper integration between higher education and socioeconomic development, carrying significant theoretical and practical implications. The connotation reconstruction of college students’ entrepreneurial ability from the perspective of enterprise demand Decomposition of entrepreneurial competence components in the dimension of enterprise needs In the actual operation of enterprises, market expansion, resource allocation, risk management, and innovation-driven development are core requirements that directly shape the competency framework of entrepreneurial talents. When recruiting such professionals, HR departments typically prioritize market sensitivity, resource integration capabilities, risk resilience, and innovative thinking as key evaluation criteria. Through systematic analysis of entrepreneurial education literature and in-depth interviews with HR managers from 10 small and medium-sized enterprises (SMEs), we have established an element framework for college students’ entrepreneurial competencies. Market sensitivity encompasses accurate industry trend analysis and deep user demand exploration—such as identifying new market opportunities from policy adjustments or uncovering unmet needs through behavioral analytics. Resource integration capabilities refer to effectively consolidating dispersed assets like capital, talent, technology, and distribution channels, exemplified by combining university research with corporate market resources for entrepreneurial projects. Risk resilience involves managing uncertainties during startup phases, including timely strategy adjustments when projects face setbacks or securing alternative funding sources during cash flow constraints. Innovative thinking emphasizes unconventional approaches, such as drawing inspiration from cross-industry business models to develop competitive products or services. These elements are valued by enterprises because market sensitivity helps steer development direction, resource integration enhances operational efficiency, risk resilience reduces startup failure probabilities, and innovative thinking delivers sustainable competitive advantages. Analysis of the logical convergence between innovation and entrepreneurship education and enterprise needs The essence of innovation and entrepreneurship education lies in cultivating talents with entrepreneurial spirit and capabilities, which aligns closely with the human capital theory’s core perspective that education enhances talent competencies. Given that enterprises’ demand for entrepreneurial talents serves as a critical support for their operational development, innovation and entrepreneurship education precisely provides enterprises with talent resources that meet their needs by nurturing students ‘entrepreneurial abilities. The hierarchy of needs theory further explains that enterprises’ talent demands encompass basic execution capabilities, core innovation capabilities, and advanced strategic capabilities. The curriculum system of innovation and entrepreneurship education (such as entrepreneurship fundamentals, business model design, and risk management) precisely covers these levels, forming a precise alignment between capability cultivation and enterprise demands. In a university-local tech enterprise collaboration project, students participated in real enterprise operations throughout the process—from market research to product prototype development and resource integration. The enhanced market sensitivity, resource integration capabilities, and risk resistance demonstrated by students perfectly match the needs of entrepreneurial talents in enterprises. This practical case fully validates the logical congruence between innovation and entrepreneurship education and enterprise demands in reality. The practical representation of integrating enterprise needs into the cultivation of college students’ entrepreneurial ability Analysis of enterprise demand responsiveness at the level of training objectives A review of educational objectives in university entrepreneurship programs (including training plans and syllabi) reveals that while most institutions mention entrepreneurial spirit and innovation capabilities, they fail to clearly define specific competencies required by enterprises, such as market insight and resource integration. Interviews with university administrators and faculty indicate that objective formulation primarily follows guidelines from education authorities and institutional talent development strategies, with enterprise feedback often remaining superficial rather than being genuinely incorporated into goal-setting. When comparing these objectives with corporate requirements for entrepreneurial talent, significant gaps emerge. Some universities overgeneralize their objectives by emphasizing abstract entrepreneurial traits without addressing practical operational needs, while others deviate from industry demands by prioritizing theoretical knowledge over practical skill development. Assess the degree of enterprise demand matching at the cultivation level An analysis of the curriculum system for innovation and entrepreneurship education in higher education institutions (covering core courses and practical courses) reveals that while most universities include foundational entrepreneurship and innovation management in their core courses, they inadequately address practical operational aspects such as business model design and market research. Practical courses predominantly focus on entrepreneurship competitions and simulation training, with insufficient integration of real-world corporate scenarios. Examination of textbook content shows that some materials still prioritize traditional entrepreneurship models, lagging in introducing emerging business models like live-streaming e-commerce and the sharing economy under the digital economy context, failing

https://doi-xx0.org/6812/17651843533908 第一作者英文名1 ,a , Yuan Gao Department： Keyboard discipline University：Shenyang Conservatory of Music City：Shenyang Country：China（英文单位）   *Corresponding author:gao13700046969@hotmail.com   13700046969@163.com   Funding（基金项目）   Abstract— This study rigorously interrogates the differential impacts of Augmented Reality (AR) and Virtual Reality (VR) on piano pedagogy and performance anxiety regulation through a stratified randomized controlled trial involving 60 intermediate-level pianists across three experimental arms: conventional instruction (control), AR-enhanced learning, and VR-based performance simulation. Quantitative analysis revealed that AR yielded the most pronounced improvement in motoric accuracy (Δ = +11 pp; Pre: 73% ± 9, Post: 84% ± 6) by leveraging real-time visuospatial feedback to facilitate proprioceptive calibration and procedural consolidation. Conversely, VR demonstrated superior efficacy in psychophysiological desensitization, reflected in a dramatic reduction in Music Performance Anxiety Inventory scores (Δ = −13; d = 2.29) and minimal vagal withdrawal under recital stress (RMSSD Δ = −1 ms), thereby supporting its application as an immersive exposure-based regulatory intervention. The control group exhibited only marginal gains across cognitive-affective metrics (e.g., accuracy Δ = +3 pp; MPAI Δ = −2), underscoring the limitations of traditional pedagogy in achieving bidirectional neurocognitive optimization. These findings substantiate the theoretical and empirical proposition that immersive AR and VR modalities serve as potent neuropedagogical vectors for synchronously enhancing fine-motor acquisition and affective regulation in high-performance musical contexts. Keywords— Augmented Reality, Virtual Reality, Piano Pedagogy, Performance Anxiety, Motor Learning, Heart Rate Variability, Immersive Technology, Neuropedagogy Introduction The integration of immersive technologies—particularly Augmented Reality (AR) and Virtual Reality (VR)—into educational frameworks has yielded a transformative paradigm in cognitive and sensorimotor training [1]. In the domain of music education, and specifically piano pedagogy, the application of these technologies has not merely introduced novel tools but has also provoked a reconfiguration of conventional instructional modalities [2]. AR overlays have the potential to deliver real-time, spatially contextualized visual feedback during performance, thus engaging learners in a multi-sensory feedback loop that reinforces motor planning and execution through embodied cognition principles. Similarly, VR offers a unique capacity for controlled ecological validity, allowing pianists to engage with hyperrealistic performance environments that simulate the psychophysiological stressors associated with live recital conditions, hence rendering it a promising tool in affective-behavioral desensitization frameworks [3]. Figure 1 Mixed reality strategies for piano education [3] Despite growing enthusiasm in adjacent fields such as medical simulation and engineering education, empirical evidence evaluating the efficacy of AR and VR in structured piano pedagogy remains sparse and methodologically fragmented [4]. Prior studies have largely relied on heuristic metrics or anecdotal practitioner reports, lacking the empirical granularity necessary to establish causality between immersive interventions and improvements in both cognitive–motor integration and performance anxiety regulation [5]. Moreover, the neuropsychological mechanisms through which immersive modalities may influence musical skill acquisition—such as visuomotor entrainment, attentional modulation via dopaminergic salience networks, and sympathetic nervous system attenuation—are only beginning to be elucidated [6]. This study seeks to bridge this lacuna by employing a rigorous experimental protocol with objective and validated psychometric and physiological instrumentation [7]. Central to the theoretical foundation of this investigation is the dual-faceted nature of music performance, which necessitates both the development of fine motor precision and the regulation of performance-related anxiety (PRA), often operationalized through indices such as the Music Performance Anxiety Inventory (MPAI) and autonomic biomarkers including heart-rate variability (HRV). Performance anxiety has been demonstrated to adversely impact procedural memory recall, auditory working memory, and kinaesthetic control, all of which are critical for proficient pianism [8]. Leveraging VR as a controlled exposure environment offers a promising analogue to systematic desensitization techniques, aligning with theories of affective habituation and cognitive reappraisal under the broader umbrella of the psychophysiological model of PRA [9]. Simultaneously, AR-based systems capable of delivering gesture-level feedback through computer vision overlays and haptic-augmented prompts may enhance acquisition of motoric schemas in ways that traditional teacher-led instruction cannot match. This is particularly relevant in the context of skill automatization and chunking theory, where distributed sensory engagement accelerates the consolidation of spatial–temporal mappings [10]. Additionally, AR can induce a state of flow through congruent task-oriented feedback and reduced cognitive load, thus fostering deeper procedural encoding. Such enhancements align with constructivist and enactive learning theories, which posit that skill mastery emerges not solely from observation and repetition, but from active sensorimotor participation in ecologically valid contexts [11]. Accordingly, this research study aims to undertake a tripartite comparative evaluation of traditional instruction, AR-enhanced piano pedagogy, and VR-based exposure therapy to assess their respective impacts on (a) the rate and quality of piano performance accuracy, and (b) the modulation of psychometric and physiological indicators of performance anxiety [12]. Through a randomized controlled trial employing robust within- and between-subject statistical methodologies (e.g., mixed ANOVA with effect size correction), this study contributes not only to applied music education practices but also to the interdisciplinary literature on embodied cognition, digital therapeutic interventions, and neuroeducational engineering [13]. The findings are anticipated to inform both pedagogical praxis and clinical strategies for anxiety mitigation in high-stakes performance domains. Literature Review Augmented Reality (AR) in Sensorimotor Music Training Augmented Reality has increasingly been utilized in fine motor skill training due to its capacity to deliver real-time multimodal feedback overlays that are precisely mapped to anatomical landmarks, thus facilitating the realignment of kinaesthetic errors through immediate perceptual correction. In piano pedagogy, the utilization of AR interfaces—particularly those employing spatially registered note cues and gesture recognition algorithms—has demonstrated efficacy in enhancing visuomotor synchronization and intermanual coordination among novice learners [5]. The underlying computational architecture of AR-based feedback systems enables continuous monitoring of spatial-temporal accuracy, allowing for the dynamic modulation of difficulty parameters, which has been shown to improve cognitive-motor entrainment in domain-specific psychomotor learning [13]. Moreover, evidence from neuroergonomics supports the notion that AR interventions can modulate functional connectivity between the dorsolateral prefrontal cortex and premotor cortices, suggesting that AR may influence not only performance outcomes but also the neurocognitive substrates underpinning musical learning [21]. The pedagogical potential of AR is further supported by findings in embodied cognition, where sensorimotor contingencies are posited as critical variables in the encoding of procedural knowledge. Studies involving digital overlay systems have demonstrated that real-time augmented feedback facilitates the internalization of spatial heuristics—such

https://doi-xx0.org/6812/17651865015813 第一作者英文名1 ,a , Xiaofan Ding 通信作者英文名1,b* Department：College of music education University：Shenyang Conservatory of Music City：Shenyang Country：China（英文单位）   aEmail:ding19880409@hotmail.com   Funding（基金项目） Abstract— This study critically investigates the impact of algorithmically generated musical content on the interpretive, expressive, and motoric dimensions of professional piano performance, with particular emphasis on three core variables: interpretative depth, perceived authenticity, and performative creativity. Utilizing a between-subjects design involving AI-generated and human-composed musical stimuli, the research employed expert evaluation, Delphi-based creativity scoring, self-reported authenticity metrics, and high-resolution MIDI-derived performance fluency analytics. Results indicate that AI-generated music elicits significantly attenuated interpretive engagement, with reduced mean scores across all aesthetic and biomechanical domains, including expert-rated interpretation (–23.6%), perceived creativity (–18.1%), and authenticity (–33.8%). Moreover, quantitative fluency parameters such as note onset deviation, articulation variability, and pedaling efficiency reflected degraded temporal precision and expressive motor output in the AI condition. Effect sizes across all domains ranged from large to extremely large (Cohen’s d > 1.19–2.22), suggesting a systematic and functionally disruptive disconnect between algorithmic compositional structure and the cognitive-embodied mechanisms underpinning expressive human performance. These findings reveal foundational limitations in current generative music systems and challenge the presupposition that algorithmic music can function as an interpretively equivalent substrate within professional performance practice. Keywords— AI-generated music, piano performance, musical interpretation, performance authenticity, computational creativity, expressive fluency, music cognition, algorithmic composition Introduction The exponential evolution of artificial intelligence in creative domains has engendered a paradigmatic shift in music composition, performance, and pedagogy. Algorithmic models such as OpenAI’s MuseNet and AIVA now generate highly structured, stylistically coherent music that is ostensibly indistinguishable from that produced by human composers [1]. These systems utilize deep generative architectures—including transformer-based models and variational autoencoders—to simulate complex harmonic progressions, temporal motifs, and dynamic phrasing [2]. However, despite the sophistication of these generative processes, the ontological status of AI-generated music remains contested in terms of intentionality, emotional valence, and structural teleology [3]. Within the performance domain, pianists serve as an ideal population to assess the cognitive and expressive ramifications of engaging with AI-generated material. Piano performance is deeply embodied and interpretive, involving highly nonlinear mappings between symbolic scores and expressive micro-gestures such as rubato, agogics, pedaling, and articulation [4]. Previous research demonstrates that performers rely not only on the syntactic content of a score but also on inferred composer intentionality and stylistic authenticity to shape interpretive decisions [5]. When such intentionality is obscured—as is often the case with AI-composed works—musicians may experience reduced affective resonance and diminished expressive agency [6]. Unveiling a Pianist’s Expression through AI as shown in Figure 1 Figure 1 Unveiling a Pianist’s Expression through AI The epistemic uncertainty surrounding AI-authored music also intersects with cognitive-affective constructs such as authenticity and creativity. Authenticity in performance is often rooted in the perceived alignment between the score’s idiomaticity and the performer’s interpretive logic, a relationship that may be disrupted by algorithmically constructed outputs lacking embodied musical intention [7]. Moreover, research in creativity studies suggests that AI-generated music may impose cognitive constraints on performers, who often rely on narrative coherence and stylistic norms to scaffold novel yet coherent interpretations [8]. Without a clearly defined expressive grammar or teleological form, performers may default to mechanical rendering, thereby attenuating the spontaneous, emergent features characteristic of creative musicianship [9]. While prior literature has examined the structural attributes of AI-composed music and audience perception of its quality, few empirical studies have investigated how such music directly impacts the pianist’s interpretive behavior, perceived authenticity, and expressive creativity in a performance context [10]. This research aims to fill that lacuna by conducting a comparative analysis between performances of AI-generated and human-composed piano works. Drawing on both quantitative and qualitative metrics—including expert ratings, performance fluency data, and performer self-reports—this study interrogates how AI-authored scores influence not only technical execution but also deeper affective and creative processes [11]. Ultimately, this research contributes to the evolving discourse on human–machine co-creativity, challenging traditional models of authorship and offering critical insight into the embodied dynamics of AI–human musical interaction [12]. Literature Review The Computational Foundations of AI-Generated Music New developments in artificial intelligence have allowed the generation of complicated musical compositions by using deep learning algorithms to imitate stylistic, harmonic and rhythmic patterns. OpenAI MuseNet and Google MusicLM are models based on multi-layered transformer networks that have been trained on large corpora of MIDI and audio data in order to learn to predict note sequences and structure of composition with impressive faithfulness [1]. These architectures learn long-term dependencies and can generate AI systems that can simulate compositional hierarchies, previously believed to only require human cognitive intent [2]. Nevertheless, the syntactic meaningfulness of the works generated by such systems is, in most cases, devoid of semantic purpose, which begs the question of the ontology of algorithmic authorship in the artistic realms [3]. Hybrid systems involving symbolic logic, probabilistic grammar modeling, and variational autoencoders are becoming more commonly used as algorithms to generate music, permitting generative models to produce stylistically rich output that can imitate historical and contemporary styles [4]. However, such systems although can generate notational artifacts that resemble those of canonical composers, are not embodied sensorimotor grounded, but this is a key feature of human music-making [5]. Also, even when stylistic precision is enhanced, the majority of music generated by an AI lacks the telos-driven development and motivic change, which are two characteristics of music written by humans [6]. Interpretation and Expressive Intent in Piano Performance Piano performance interpretation is a multilayered holistic practice through which performers negotiate textual, structural and affective levels of musical score. The mediation is comprised of active micro-decisions, namely, timing inflection, articulation, pedaling, and phrasing, all of which add to an emergent expressive identity [7]. Interpretive approach of the pianist is highly dependent on the perceived composer intent, historical context and familiarity with style which all determine expressive coherence [8]. Ambiguous or algorithmically-determined, without the intentionality of a human being, such cues can lead the performer to expressive disorientation and a lack of ability to participate in the meaning-making process [9]. The cognitive-motor