Ebook: Modern Management based on Big Data VI

MMBD2025, focusing on the general theme of Big Data and Modern Management along with cutting-edge research topics, has drawn substantial participation from professors and postgraduate students – particularly PhD scholars – from universities worldwide, as well as technicians, policymakers, and senior executives from diverse industries and organizational sectors. The accepted papers primarily address the following key areas: innovation in online education management driven by big data, green supply chain management, big data analytics in supply chains, sustainable development decision-making, digital economy, platform economy, digital innovation, social strategies for human relationship management, total quality management, and modern hospitality and tourism management.

This conference proceedings is structured in three parts:

∙ Part I: Modern Management and Big Data

∙ Part II: Interdisciplinary Field of Modern Management and Big Data

∙ Part III: Special Session on Lifelong Education

All submissions have undergone rigorous and meticulous review by members of the international Technical Program Committee (TPC) and anonymous reviewers, ensuring alignment with MMBD’s research scope in terms of both thematic breadth and analytical depth. From approximately 193 submissions, 58 high-impact contributions representing the most promising advancements in the field and with strong relevance to the series Frontiers in Artificial Intelligence and Applications (FAIA) were selected for inclusion.

We would like to extend our sincere gratitude to all keynote speakers, invited presenters, authors, TPC members, and anonymous reviewers whose dedicated efforts have been instrumental in the success of the conference. We would also like to acknowledge the editorial team and colleagues at IOS Press for their collaborative work in publishing this volume as the sixth edition of the MMBD conference series within the FAIA book series.

Finally, we mourn the unexpected loss of Dr. Einar Fredriksson, founder of IOS Press, who passed away on April 30, 2025. His vision and leadership profoundly impacted the academic publishing community, and his legacy will continue to inspire our work.

July 2025

Antonio J. Tallón-Ballesteros

University of Huelva (Spain)

Huelva City, Spain

As a crucial tool for investors to carry out risk hedging and other investment operations, stock index futures have garnered significant attention and analysis from scholars both domestically and internationally. The article uses EViews software to study the price volatility characteristics of CSI 300 stock index futures. Firstly, the article analyzes the distribution characteristics and trends of its price and yield, and conducts stability test and ARCH effect test on the price and its logarithmic yield. Finally, a GARCH model is constructed to empirically analyze the volatility characteristics of the yield series. The article reveals that the yield series of CSI 300 stock index futures exhibits significant characteristics of volatility aggregation and persistence. This finding offers investors valuable information for pre-investment analysis.

The cryptocurrency market has similar characteristics to the futures market, and trend-following strategies are attractive in this market. This paper uses the spot price data of Bitcoin against the US dollar from January 1, 2013 to September 27, 2023, as well as the daily data of the S & P 500 index and the Shanghai and Shenzhen 300 index in the same period. A trend-following strategy is used to evaluate indicators such as return, Sharpe ratio, Sortino ratio, risk exposure and maximum drawback by optimizing parameters. By analyzing ten years of data on Bitcoin, the research revealed the potential return on investment of the cryptocurrency trend-following strategy, which achieved an annualized return of 112.7%. The results show that the trend tracking strategy of digital currency is more significant under the special conditions of increasing market volatility. Bitcoin shows potential value in investment portfolios, especially when market volatility increases and may become a hedging tool and provide more diversified investment strategies.

This study applies a system dynamics model using 2014–2023 data to examine how digital infrastructure, R&D investment, and software talent affect resource allocation and circulation efficiency in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). The findings reveal that digitalization notably enhances economic quality by boosting circulation efficiency. It is recommended that cross-regional data networks and talent mobility be strengthened to support coordinated regional development.

Budget management is a cornerstone for achieving high-quality and modernized economic development in China. As a critical component of budget systems, budget slack is influenced by multiple factors, among which the intellectual capital formed by executives’ overseas backgrounds has become a focal point for corporate discussion. This study uses data from A-share listed companies in Shanghai and Shenzhen from 2016 to 2022 to examine the impact of executives’ overseas backgrounds on corporate budget slack from the perspective of risk-taking, further exploring the moderating role of environmental uncertainty in this relationship. The results show that executives’ overseas backgrounds can inhibit corporate budget slack by enhancing the level of corporate risk-taking. Environmental uncertainty exhibits a complementary effect in the relationship between executives’ overseas backgrounds and budget slack. Heterogeneity analysis reveals that the impact of executives’ overseas backgrounds on budget slack is more pronounced in non-state-owned enterprises, small-scale enterprises, and enterprises with weaker external oversight.

Innovation is the core driver of China’s high-quality development and a critical support for maintaining the dual-circulation economic security framework. Enhancing corporate innovation capabilities has thus become a pressing issue. This study examines A-share listed companies in Shanghai and Shenzhen stock markets from 2010 to 2022, grounded in behavioral economics theory, using deductive reasoning and empirical research methods, to explore the impact of soft budget constraints (SBC) on corporate innovation and its mechanisms. The findings reveal a positive correlation between SBC and corporate innovation. Mechanism tests indicate that executive risk preferences and overconfidence partially mediate this relationship, with SBC improving innovation through these two behavioral pathways. Additionally, executives’ overseas experience and media attention significantly positively moderate the SBC-innovation relationship. Heterogeneity analysis shows that firm size, technological dependence, and regional factors influence this relationship. Further research demonstrates that SBC enhances corporate innovation resilience. This study provides theoretical support for firms to strategically leverage SBC and gain a competitive edge in innovation markets.

The “Institution Lag” between the demand for cross-border data services and the supply of rules constrains the in-depth development of cross-border data flow. The Guangdong Hong Kong Macao Greater Bay Area, as a strategic region with the highest degree of openness, the most significant institutional differences, and full of vitality and international competitiveness in China, has a particularly prominent internal tension between the autonomy demand for cross-border data flow and institutional standardization. This study takes the offshore data center of the Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone as an example, and combines the theory of ecological niche construction and organizational configuration to propose an analytical framework of “cross-border organizational configuration based on ecological niche construction”. It analyzes the conditional constraints of cross-border data flow in the Guangdong Hong Kong Macao Greater Bay Area and the establishment process of offshore data centers, explores the organizational configuration and institutional innovation mode of the data cross-border service system, and proposes to optimize the ecological niche construction of data cross-border services from the aspects of dislocation development, replenishment development, borrowing development, and expansion and expansion, in order to seek the best balance point between cross-border data flow security and freedom, promote the marketization and globalization of data elements.

The integration of rural secondary and tertiary industries (referred to as “three - industry integration”) is a key pathway to advancing agricultural and rural modernization and an important measure to achieve rural industrial prosperity under the Rural Revitalization Strategy. This study focuses on the level of three - industry integration and its influencing factors in China and its four major economic zones from 2015 to 2024. Using the random effects model and the Oaxaca - Blinder decomposition method for empirical analysis, the study finds that the level of three - industry integration has shown an overall upward trend with fluctuations and exhibits a geographical distribution pattern of “east - west - central” in descending order. From the subsystem perspective, there are significant differences in the development levels of the three - industry integration subsystems across regions, although the overall trend is upward, the development of industrial cycles is relatively slow. Human capital, urbanization, land transfer, and agricultural loans have a significant promoting effect on the integration of the three industries, but they also lead to differences in the level of integrated development across regions to some extent. Based on these findings, it is recommended to continue to focus on the development of rural industrial cycles, guide college students to return to their hometowns to start businesses, promote urbanization and land transfer, to promote high - quality development of the integration of the three rural industries.

The boundaries of economic and social attributes of technology-based platform enterprises are more blurred in the platform ecological field, and the paradigm of social responsibility practice and governance mechanism have produced new changes, which require an in-depth analysis of their logic of origin, practice paradigm and governance mechanism. This paper takes Meituan-Dianping, a widely influential technology-based platform enterprise among platform enterprises, as the research object, and explores the definition of its social responsibility in depth to further explore the issue of social responsibility governance mechanism of technology-based platform enterprises. The study finds that the social responsibility of technology-based platform enterprises can be hierarchically divided according to their roles as ‘independent operating entities’, ‘business operation platforms’ and ‘social resource allocation platforms’. and ‘social resources allocation platform’. A contextualized governance mechanism centered on corporate value, a cross-level network governance mechanism, and an iterative ladder governance mechanism are formed to promote the goodness of science and technology.

Equity incentives, as a key long-term incentive mechanism, are of great significance in solving the prevalent principal-agent problem. This paper takes Enterprise H as the case study object and utilizes the exploratory case study method to explore it in depth. Firstly, we briefly introduce Enterprise H and its shareholding structure, and then analyze the current situation of the implementation of equity incentives in Enterprise H. From the definition of the scope of the incentive target and the setting of the assessment indexes, we present an all-round compendium. Accordingly, the main problems of equity incentives in Enterprise H are summarized, such as the coverage of incentive targets is too small, the performance assessment indexes are defective, and the fixed exercise price is not scientific, etc. Digging deeper into the root cause, it may be due to the lack of science in the internal control mechanism of the enterprise, the market of professional managers is not yet perfect, and the external market environment is still not yet mature and other factors. In the end, for the problems and causes, put forward the corresponding perfect countermeasures, this study not only adds personalized cases for the academic field of equity incentives, enriching the research connotation, but also provides valuable reference for the implementation of equity incentives for China’s listed companies, helping them to build a scientific and efficient incentive system, and promoting the sustainable development of the enterprise and the enhancement of its value.

Traditional museum visitation is evolving from passive observation to technology-driven immersive engagement. This transformation bridges the gap between audiences and cultural artifacts, unleashing the cultural value of artifacts while amplifying museums’ ideological education potential. Through the lens of interactive ritual chains, this study identifies emotional engagement as the critical catalyst for integrating museum immersion with ideological education. The research reveals a three-phase integration mechanism: emotional input through multi-sensory stimulation, physical participation via interactive technologies, and emotional resonance through shared symbolic experiences. We propose a co-creation framework emphasizing collective consciousness-building, emotional alignment, and symbolic meaning-making to optimize museums’ role in contemporary ideological education. Additionally, by taking the “Yunyou Dunhuang” as a case study, this research analyzes the feasibility of integrating museum immersive experiences with “Great Ideological and Political Course”, offering theoretical insights to transcend the limitations of traditional ideological education.

This article analyzes the connotation of the theory of common prosperity from the perspectives of Marxist political economy, welfare economics, and development economics, and proposes three principles for constructing an indicator system, namely multidimensionality, operability, and dynamism. This study focuses on data availability, weight rationality, and dynamic adaptability, distinguishing macro and micro indicators, and proposing an innovative “three-dimensional dynamic adjustment framework” to address the issues of redistribution equity in the eastern coastal areas and the emphasis on economic growth in underdeveloped western regions, thereby implementing differentiated shared prosperity policy paths.

Enhancing the resilience of the high-tech manufacturing industry chain is significant to building a manufacturing powerhouse and promoting high-quality economic development. To quantitatively study the resilience of the high-tech manufacturing industry chain, a comprehensive evaluation index system is constructed from four dimensions: resistance, recovery, reorganization, and renewal. We measured the resilience of the high-tech manufacturing industry chain across 30 provinces in China from 2008 to 2022. The results indicate that while the resilience of this industry chain has been increasing annually, the overall level remains low, and there are significant regional disparities. To strengthen the resilience of the high-tech manufacturing industry chain, it is essential to improve original innovation capacity, promote digital transformation, and achieve coordinated regional development.

Based on the “Syrquin and Chenery Structural Change Model” principle and panel data of the tourism industry in Central China from 2011 to 2020, this study empirically analyzes the structure of tourism talents and its impact on tourism economic development. The industry structure of tourism talents in Central China deviates significantly, yet the overall deviation coefficient fluctuates downward, indicating an annual optimization trend in talent structure across various sectors. Specifically, talent shortages persist in travel agencies due to high turnover rates; the hotel industry has shown a trend towards talent surplus in recent years due to stable talent reserves; and talent gaps in tourism attractions were evident in the first three years since 2011, stabilizing thereafter. The spatial structure of tourism talents among the six provinces in Central China shows an imbalance. Shanxi Province demonstrates a relatively stable talent structure; Jiangxi Province faces relative talent shortages; Henan Province exhibits talent oversupply; and Anhui and Hunan Provinces have transitioned from talent oversupply to demand exceeding supply. (3) The spatial structure of tourism talents in Central China does not significantly impact the tourism economy, whereas the talent structures in the three industries significantly influence tourism economic development, with impacts ranked in the following order: tourism attractions > travel agencies > hotels.

Cross-border trade is an important component of the global economy, and as the scale of cross-border trade continues to expand, container supervision faces many challenges. This paper first clarifies the current status of container supervision in cross-border trade and the existing problems and then discusses in depth the application of AI technology in container supervision, and also analyzes the risks and challenges faced by the application of AI technology and looks forward to the future direction of development of AI technology in container supervision. This study aims to promote the widespread application of AI technology in container supervision, improve supervision level, and facilitate global trade through a combination of qualitative and quantitative research methods, with a large number of examples.

This study focuses on the spatial differentiation characteristics and multidimensional influencing mechanisms of homestays in Hunan Province. Based on data from 6,508 homestays collected from OTA platforms such as Meituan and Ctrip before March 2024, the study uses ArcGIS software combined with spatial analysis methods such as the Nearest Neighbor Index, kernel density estimation, and Lorenz curve. The findings reveal that the spatial distribution of homestays in Hunan presents an overall pattern of “dense in the east and sparse in the west, with agglomeration differentiation.” Key factors influencing the spatial layout of homestays include university agglomeration, transportation accessibility, and the endowment of tourism resources. Notably, the “education-driven” agglomeration effect centered around higher education institutions is a unique spatial feature in Hunan, differentiating it from other regions where transportation or tourist attractions serve as the core drivers of spatial layout. Furthermore, this study identifies the collaborative impact of multiple factors at the regional scale and the dynamic evolution of spatial patterns, shedding light on the inherent logic of cultural-tourism spatial reconstruction. The findings provide significant empirical support and decision-making references for Hunan’s efforts to promote a “university-tourist attraction-transportation” three-dimensional collaborative governance system and formulate cultural tourism integration policies.

This study aims to forecast operating performance of enterprises using ESG reports. First, the textual analysis technique is utilized to analyze the content of ESG reports. Based on the results of content analysis, the genetic algorithm-support vector machine classifier is then used to forecast operating performance of enterprises to provide investors with a reference for decision-making of enterprise investment, thereby increasing their profitability. To achieve the above objective, the following tasks are performed: (i) a process for forecasting enterprise operating performance using ESG reports is designed, (ii) techniques involved in the process of enterprise operating performance forecasting using ESG reports are developed, and (iii) the use of the proposed approach is evaluated.

Under the background of cultural and tourism integration and consumption upgrading of Generation Z, music festival has become an important carrier of urban image communication. This paper takes Strawberry Music Festival as an example, based on the actor network theory (ANT), uses the rooted theory to carry out three-level coding on the interview data of 10 senior participants, and builds a dynamic network model by combining the translation mechanism of “problematization - benefit conferring - recruitment - mobilization”. The research findings are as follows: Music festival, as a cultural translation center, transforms urban cultural capital into a perceptible experience scene for young people through local symbol production such as intangible cultural heritage workshop and dialect interaction; Participants use UGC content creation and ritualized behavior to reconstruct urban cognition and drive the spread of social media; Through the optimization of infrastructure, the city interacts with the music festival to realize the dynamic update of the city image. At the theoretical level, the synergistic logic of human and non-human actors is revealed, and the application boundary of ANT in cultural events is expanded. In practice, strategies such as strengthening the accuracy of local symbol translation and optimizing the service response network are proposed to activate the long-term communication mechanism of urban image.

The dividend distribution policy defined by managers is an important decision for corporate growth and for transmitting information to investors about the future of the business. This article analyzes the impact of dividend distribution announcements on the stock prices of companies listed on the Iberian indices (IBEX35 and PSI) between 2022 and 2023, using the event study methodology. 19 Portuguese and 21 Spanish companies were analyzed. The results show that investors in both markets anticipated dividends below expectations, given the formation of negative abnormal returns even before the distribution was announced. A few days after the announcement, the oscillation of average abnormal returns contracted, suggesting the advantages of diversifying investments in the Iberian markets. However, the significance of the effects does not disappear, suggesting evidence against the semi-strong form of market efficiency. It is therefore important to raise awareness among managers, investors and regulators of the usefulness of resources to support strategic financial decision-making based on digitalization and big data, and to strengthen financial literacy in society.

This paper explores the path of industrial product quality and safety supervision from “point” to “surface,” taking the problematic products and enterprises discovered in supervision as the entry point to identify associated and similar risks. The study excavates key factors influencing quality and safety from the perspectives of supply chains and corporate investment and operation, establishes a quality risk relationship transmission network model (quality relationship network model), and uses big data, artificial intelligence technologies (such as community detection algorithms) to estimate the probability distribution of hidden quality states through limited risk point clues. This realizes the measurement of quality risk correlation between industrial products and enterprises, clarifies the risk association degree and impact degree between identified risk points and industrial products/enterprises to be discovered, and further analyzes risk transmission paths. Different from traditional quality supervision, which discovers isolated quality risk points through methods such as quality sampling and public opinion risk monitoring, supervision based on the quality relationship network constructs networks from two dimensions: supply chains and investment operations. Through this network, it identifies and locates enterprises and products with highly correlated quality risks, achieves cross-product type, cross-enterprise type, and cross-regional quality risk identification, and promotes the leap of quality supervision from “point” to “surface,” enhancing supervision coverage. Additionally, the paper proposes suggestions such as accelerating the interconnection and interoperability of supervision data and improving the efficiency of quality and safety risk management through AI research and development based on the research content.

Based on the unbalanced panel data of Chinese commercial banks from 2014-2023, this paper empirically analyses the impact of commercial banks’ digital transformation on credit supply and its mechanism of action from the perspective of risk-taking by using a two-way fixed effects model. It is found that the digital transformation of commercial banks significantly improves the level of credit supply, and this conclusion still holds after the robustness test. The mechanism test shows that commercial bank risk-taking plays a significant mediating effect between digital transformation and credit supply. The moderating effect test shows that digital financial inclusion negatively moderates the role of digital transformation on credit supply. The study suggests that commercial banks need to build dynamic risk buffer mechanisms to cope with technology spillovers, while regulators can guide classification governance through the construction of data sharing platforms. This paper provides an empirical basis for understanding the risk-return balance mechanism of technology-driven credit expansion.

This study employs a case study methodology to analyze a sample of major food supply chain companies from 2022 to 2024, with Nestlé as a primary focus. It proposes actionable recommendations to enhance the synergistic effects of corporate social responsibility (CSR) in food supply chains. Grounded in stakeholder theory, the paper dissects the content system of CSR, identifies three critical factors (resources, synergy, and systems), and proposes a three-dimensional synergistic promotion mechanism integrating supply chain governance, government regulation, and social supervision. This framework aims to advance supply chain sustainability, foster CSR compliance, and elevate social responsibility standards. In an era of stringent regulations, heightened environmental awareness, and escalating ESG demands, collaborative governance is pivotal for sustainable food industry development.

Taking the data of A-share listed companies in Shanghai and Shenzhen from 2015 to 2023 as a sample, this data was analyzed using empirical methods, fixed-effects, and explicit regression analysis. The findings indicate that dynamic capabilities and the threefold dynamic capabilities promote the intelligent transformation of advanced manufacturing. The findings of this study provide a framework for enterprises to navigate the process of intelligent transformation, address the research gap regarding the role of dynamic capabilities in this field, and demonstrate the differentiated effects of various dimensions of dynamic capabilities, which can inform both managerial practices and industrial policy.

On the basis of constructing a theoretical framework of “four-chain” integration of manufacturing industry empowered by digital technology, the direct and indirect influence mechanisms of digital technology on “four-chain” integration of manufacturing industry are empirically examined by selecting provincial panel data from 2012 to 2022, and the role mechanisms of government and market are further explored. Based on the provincial panel data from 2012 to 2022, we empirically examined the direct and indirect influence mechanisms of digital technology on the integration of the four chains of manufacturing industry, and further explored the role of the government and the market. It is found that digital technology has a significant role in promoting the integration of the four chains of manufacturing industry; the mechanism test finds that digital technology not only directly improves the degree of integration of the four chains of manufacturing industry, but also realizes the integration of the four chains of manufacturing industry through the intermediary path of financial development, which is the most effective way to promote the integration of the four chains of manufacturing industry. The mechanism test finds that digital technology not only directly enhances the degree of integration of the “four chains” of manufacturing industry, but also realizes the systematic empowerment of the integration of the “four chains” through the intermediary path of financial development. Based on the conclusions of the study, it is recommended that efforts be made in three aspects, namely, technological research and development, financial support and institutional synergy: to strengthen key technologies such as artificial intelligence and blockchain, to improve the digital financial support system, and to optimize the synergistic mechanism between policy and market.