We analyzed the formation mechanism of digital economic gap (DEG), measured the DEGs at four levels (the gaps in information and communication technology accessibility, application skill, digital economic outcome, and efficiency), and explored its spatiotemporal evolution in China by using DEA–Malmquist index method, Gini Coefficent method, Kernel density, and Geodetector. Data from 263 cities in China between 2011 and 2019 were collected. The results demonstrated that (1) The four levels of DEGs showed different trends. The first-, second- and third- level DEGs showed ceiling effects, and the fourth-level DEG oscillated upward. (2) The distribution location of the four levels of DEGs varied. The first- and second-level DEGs shifted at a stable low degree. The third-level DEG increased steadily and polarized. The fourth-level DEG increased steadily and formed a multi-polarization trend, with one strong polar. (3) The long-term transfer trend of the DEGs at four levels changed little, an..., A total of 263 cities in 30 provinces (cities or regions) in China were selected as the study subjects. Data were obtained from the China Statistical Yearbook, China Science and Technology Statistical Yearbook, Provincial and City Statistical Yearbooks, White Paper on China City DE Index, and the Mark Data website (https://www.macrodatas.cn/). The expedition period for this study was from 2011 to 2019. , , The dataset -- data.dta (city = 263, year = 8) -- was compiled from the peer-reviewed literature. This was from study sites in 263 cities, China.

The dataset was compiled by co-authors Shujuan Wu (jane333444@126.com), Jinting Li (1311028217@qq.com), Daqian Huang (1953836900@qq.com), Jianhua Xiao (1312655857@qq.com) of Wuyi University.

For any questions regarding the dataset, please send an email to Shujuan Wu (jane333444@126.com)Â and Jinting Li (1311028217@qq.com).

Filename: data.dta

â—ˆyear: The year of the data

â—ˆcity: City No.

â—ˆregion: The No. Of the region

◈rndexp: R&D expenditure (10000 Yuan)

◈exgebudget:Total financial expenditure (10000 Yuan)

â—ˆfixass: Â Fixed asset investment (10000 Yuan)

◈fstdeg: First-level of digital economy (/)

◈library: The collection of books in public libraries per capi...

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Tradeweb Markets: Navigating the Digital Evolution of Fixed Income (TW)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

China’s manufacturing industry faces the multiple goals of balanced, coordinated and sustainable development. This paper clarifies the connotation of balanced, coordinated and sustainable development of the manufacturing industry from regional structure, industrial structure and development structure. The level of balanced, coordinated and sustainable development of the manufacturing industry is measured using various methods such as index construction model, coupled coordination model and objective assignment method. The temporal and spatial evolution characteristics of the balanced, coordinated and sustainable development of the manufacturing industry are analysed. The following conclusions were obtained: the overall level of manufacturing equilibrium in the east is high, and the level of manufacturing equilibrium in the west and northeast is low. Therefore, it is necessary to promote the level of manufacturing development in the central and western regions through industrial transfer and other means. The overall coordination level of manufacturing industry shows a clear upward trend. The coordination level of manufacturing industry in the east ranks first among the four regions, and the coordination level of manufacturing industry in the west has made the most obvious progress. The overall level of sustainable development of the manufacturing industry is on an upward trend, with the highest level of sustainable development of the manufacturing industry in the east and a relatively low level of sustainable development in the west. There is a need to achieve sustainable development of the manufacturing industry by promoting the integration and development of the digital economy and the manufacturing industry.

Fashion Token Index Market Outlook

According to our latest research, the global Fashion Token Index market size reached USD 1.28 billion in 2024, reflecting a robust expansion driven by the digital transformation in the fashion and retail sectors. The market is projected to grow at a compelling CAGR of 22.7% from 2025 to 2033, reaching an estimated value of USD 9.02 billion by the end of the forecast period. This remarkable growth trajectory is primarily fueled by increased adoption of blockchain technology, rising consumer interest in digital assets, and the proliferation of virtual fashion experiences. As per the latest research, the Fashion Token Index market is witnessing rapid evolution, with both established fashion houses and emerging digital-native brands leveraging tokenization to enhance customer engagement, drive loyalty, and unlock new revenue streams.

One of the key growth factors propelling the Fashion Token Index market is the increasing convergence of fashion and technology. The integration of blockchain-based tokens within the fashion industry enables brands to offer unique digital experiences, authenticate products, and facilitate transparent supply chains. Utility tokens and NFTs are being utilized to provide exclusive access to digital fashion shows, limited-edition collections, and immersive virtual environments. This trend is particularly pronounced among Gen Z and millennial consumers, who are highly receptive to digital ownership and the gamification of brand interactions. The ability to tokenize fashion assets not only enhances consumer engagement but also opens up innovative monetization pathways for designers and brands, further accelerating market growth.

Another significant driver of the Fashion Token Index market is the rise of virtual goods and digital fashion. The burgeoning popularity of the metaverse and online gaming platforms has created a thriving market for digital apparel and accessories, which can be bought, sold, and traded using fashion tokens. Non-fungible tokens (NFTs) are at the forefront of this movement, allowing consumers to own verifiable, scarce digital fashion items. As virtual environments become increasingly sophisticated, brands are investing in NFT collaborations, digital runway events, and avatar customization, thereby expanding the utility and appeal of fashion tokens. The seamless integration of payment and loyalty tokens into these ecosystems further incentivizes consumer participation and fosters brand loyalty.

Furthermore, the Fashion Token Index market is benefiting from the growing emphasis on sustainability and transparency within the fashion industry. Blockchain-powered tokens facilitate traceability, enabling consumers to verify the provenance and ethical credentials of their purchases. Security tokens are being leveraged to fractionalize ownership of high-value fashion assets, democratizing investment opportunities and fostering greater inclusivity. Additionally, the adoption of tokenized loyalty programs is streamlining customer rewards and enhancing the overall shopping experience. As regulatory frameworks around digital assets mature, institutional adoption is expected to rise, paving the way for sustained market expansion.

Regionally, North America and Europe are leading the Fashion Token Index market, driven by advanced digital infrastructure, high consumer awareness, and a vibrant ecosystem of fashion-tech startups. The Asia Pacific region is emerging as a high-growth market, fueled by rapid urbanization, a burgeoning middle class, and widespread adoption of mobile payment solutions. Latin America and the Middle East & Africa are also witnessing increasing interest, with local brands experimenting with tokenization to differentiate their offerings and tap into global audiences. While regional dynamics vary, the overarching trend is clear: the fusion of blockchain technology and fashion is transforming industry paradigms, creating new value propositions for stakeholders across the value chain.

Token Type Analysis

Rachmad, Yoesoep Edhie. 2023. Digital Peer Influence Theory. Tehran Azadi Ketab Nashriyat, Mahsoos Nashriyat 2023. https://doi.org/10.17605/osf.io/nbpkj

The Digital Peer Influence Theory, formulated by Yoesoep Edhie Rachmad and detailed in his 2023 publication "Tehran Azadi Ketab Nashriyat, Mahsoos Nashriyat," explores the mechanisms and effects of peer influence within digital environments, particularly focusing on how individuals' behaviors, preferences, and decisions are shaped by their online social circles. Rachmad's research, initiated in 2016, investigates the profound impact of digital interactions on consumer choices, highlighting how modern connectivity transforms traditional peer influence dynamics. This theory emerges from an understanding that, in the digital age, peer influence extends far beyond physical interactions. Social media platforms, online forums, and digital communities have expanded the scope and scale of peer influence, enabling individuals to be impacted by not only close friends and family but also by broader networks that can span the globe. The Digital Peer Influence Theory posits that digital peer influence operates through several key channels, including social media interactions, user-generated content, online reviews, and shared online experiences. These channels facilitate a complex web of influence that significantly affects individuals' attitudes and behaviors. Rachmad argues that digital peer influence is not just about direct recommendations or overt pressures; it also encompasses the subtle cues and signals that individuals absorb from their online networks, such as likes, shares, and comments. Rachmad concludes that the digital peer influence is powerful because it combines the wide reach of traditional media with the personal relevance of close social interactions. This influence is potent in shaping consumer behaviors, political opinions, and even personal identities. He suggests that understanding this can help businesses and organizations to more effectively harness the power of social networks for marketing, customer engagement, and behavior change initiatives. He recommends that entities seeking to leverage digital peer influence develop strategies that genuinely engage communities, foster authentic interactions, and provide value that encourages sharing and discussion. Additionally, Rachmad emphasizes the importance of monitoring and analyzing social media trends and interactions to gain insights into consumer preferences and behaviors, allowing for more targeted and effective engagement strategies. Overall, the Digital Peer Influence Theory provides a nuanced perspective on how digital environments amplify peer influence and shape modern social dynamics. It offers critical insights for anyone looking to understand or influence trends, behaviors, and decisions within digital communities.   Table of Contents Rachmad, Yoesoep Edhie. 2023. "Digital Peer Influence Theory." Tehran Azadi Ketab Nashriyat, Mahsoos Nashriyat. [DOI: https://doi.org/10.17605/osf.io/nbpkj]

Chapter 1: Introduction to Digital Peer Influence Exploring the Evolution of Peer Influence in the Digital Age............3 The Impact of Connectivity on Social Dynamics............................21 Why Digital Peer Influence Matters...........................................39 Chapter 2: Channels of Digital Peer Influence Social Media as a Platform for Peer Influence................................57 The Role of User-Generated Content and Online Reviews.............75 Shared Online Experiences and Their Influence.............................93 Chapter 3: Mechanisms of Influence in Digital Spaces Direct vs. Indirect Peer Influence Online....................................111 Subtle Cues: Likes, Shares, Comments, and Their Impact...........129 The Spread of Trends and Viral Content......................................147 Chapter 4: Digital Peer Influence on Consumer Behavior How Peer Influence Shapes Buying Decisions............................165 Case Studies in Influential Online Reviews..................................183 Social Proof and Its Role in Modern Marketing............................201 Chapter 5: Digital Peer Influence Beyond Consumerism Influence on Political Opinions and Social Movements................219 The Shaping of Personal Identities Through Digital Interactions...237 The Power of Online Communities in Health and Wellness...........255 Chapter 6: Harnessing Digital Peer Influence in Marketing Strategies for Leveraging Peer Influence in Campaigns...............273 Engaging Communities for Organic Reach................................291 Building Authentic Interactions to Foster Sharing.........................309 Chapter 7: Measuring and Analyzing Digital Peer Influence Tools for Tracking Online Trends and Engagement.....................327 Social Media Analytics: Understanding Peer Networks................345 Interpreting Data to Drive Effective Strategies..............................363 Chapter 8: Challenges and Limitations of Digital Peer Influence Addressing Misinformation and Digital Echo Chambers...............381 Navigating Privacy Concerns in Peer Influence Strategies............399 The Risks of Manipulating Peer Influence...................................417 Chapter 9: Case Studies in Effective Digital Peer Influence Successful Examples from Various Industries...............................435 Learning from Campaigns That Went Viral...................................453 When Peer Influence Backfires: Lessons from Failed Efforts..........471 Chapter 10: The Future of Digital Peer Influence Emerging Trends in Digital Connectivity.....................................489 The Role of Artificial Intelligence in Peer Influence........................507 Predictions for the Evolution of Peer Influence Online....................525

Appendices Appendix A: Glossary of Key Terms in Digital Peer Influence............543 Appendix B: Framework for Developing Peer Influence Strategies....561 Appendix C: Sample Social Media Analytics Report Template..........579 References Selected Bibliography on Digital Influence and Social Media...........597 Index Comprehensive Index of Terms and Topics Covered.......................617

AUTHOR PROFILE
In 2016, the author earned the title of Doctor of Humanity, hold a Ph.D. in Information Technology and a DBA in General Management. Since 2016, the author has been teaching at international universities in Malaysia, Singapore, Thailand, and the USA. In 1999, the author founded the Education Training Centre (ETC), an organization dedicated to providing educational services and social support for the underprivileged. This organization offers shelter homes for children in need of a safe place to live and drop-in schools for those who need to continue their education. The ETC is also involved in research aimed at advancing science, which led to the author earning the title of Professor and joining the WPF. Additionally, the author is actively involved in global social development programs through the United Nations. They are a member of the UN Global Compact (id-137635), the UN Global Market (id-709131), and the UN ECOSOC (id-677556). The author has served as a reviewer for several international journals and book chapters, and has written numerous books and articles on a wide range of topics including Philosophy, Economics, Management, Arts and Culture, Anthropology, Law, Psychology, Education, Sociology, Health, Technology, Tourism, and Communication.

Short Overview of the Project: Unfolding a Global Market in Difficult Times – The British Chamber of Commerce for Switzerland 1920 – 1950

By the end of 1919, as the economy began to recover from the impact of the First World War, J.R. Cahill, the Commercial Secretary of the British Legation in Bern, traveled through Switzerland. His journey was not an ordinary task but a step towards addressing post-war economic challenges. Meeting with British nationals such as bankers, merchants, businessmen, and transport agents across various cities, Cahill laid the groundwork for what would later become the British Chamber of Commerce for Switzerland, or the BSCC in short. Chambers of commerce operate on regional, national, and international levels, each defining its own scope, focus, structure, and function, making a universal definition difficult. Generally, they are privately organized cross-sector collaborations, which can adapt rapidly to changing political, economic, and social environments. Therefore, the BSCC was an ideal vessel for Cahill’s envisioned network, providing the adaptability needed to build a strong economic actor in Switzerland for supporting and rebuilding the economic ties between Britain and Switzerland after World War I. The BSCC was officially founded in Basel in 1920, with a branch office in Lausanne. This was relatively late, as many foreign chambers were already operating in Switzerland, and British Chambers had been expanding abroad since the late 19th century. The post-war conditions and economic crisis made it difficult to build a robust institution. However, the BSCC navigated this period, expanded its network, and continued its services without interruption. Over time, it became an integral part of Anglo-Swiss relations, a role it still plays today. The BSCC’s unexpected success during such difficult times challenges earlier assessments of chambers of commerce. The BSCC did not generate material or financial capital in a traditional sense, but relied on networking power at regional, national and global levels, which proved valuable to businessmen and governments. Throughout the interwar period, the BSCC built a network that developed an unexpected sustainability in view of the many crises that foreshadowed the Second World War. This unexpected and underinvestigated sustainability is at the core of my interest.

In my analysis, I combine micro-global history, institutional economics, and digital humanities to explore the BSCC’s evolution and its ability to sustain itself amid external pressures. I argue that its significance goes beyond traditional institutional history and must be understood in the context of the global networks it built, particularly during crises. A central part of my approach is using digital methods such as text mining, database construction, and network analysis to enhance traditional historical sources. These tools provide both quantitative and qualitative insights, enabling a deeper exploration of fragmented sources like the British-Swiss trade indices. They allow us to investigate the BSCC from a different perspective and gain insights into global trade from a privately organized institutional point of view rather than traditional governmental views. Digital humanities methods allow for the visualization of historical networks and source material, revealing connections and developments across time and space that complement and expand upon traditional archival research. By focusing on often-overlooked smaller actors, my research highlights how the BSCC’s global network facilitated critical links between economic actors in Britain, Switzerland, and beyond. This micro-global perspective offers a more nuanced understanding of global economic relations and the impact of actors on broader political and economic developments. Ultimately, this interdisciplinary approach provides new insights into the BSCC’s role in global capitalism and demonstrates the potential of digital methods to enrich our understanding of global networks and economic infrastructures.

Evaluation index system of the RR-NU-DE composite system.

Level of sustainable development in manufacturing.

Criteria for the evaluation of the level of harmonization.

Composite index of digital economy development (selected years).

Evaluation indicator system for sustainable development in manufacturing.

Ranking of main obstacle factors in the index layer of selected provinces(cities).

Annual averages and annual growth rates of the comprehensive development index for the digital economy and ecotourism.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, β-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of “club convergence”. (3) A convergence analysis shows that there are significant σ-convergence, absolute β-convergence, and conditional β-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

The high-quality development of tourism is crucial to the sustainable development of regional economy. To evaluate high-quality tourism development, this paper has developed an index system with 6 second-level indicators and 24 third-level indicators and used methods of entropy-weight, AHP, and TOPSIS to empirically assess the high-quality tourism development of 9 cities in Fujian Province. According to the results, there are obvious regional differences in the development of high-quality tourism in Fujian Province. From 2016 to 2019, the overall development trend of cities in Fujian Province was consistent, showing a steady upward trend. Green development in tourism has the best performance, which was less affected by the COVID-19. Fuzhou and Xiamen contribute most to the tourism development of Fujian Province, while other cities are lagging behind for various reasons and the lack of innovation and shared development are two of them. Based on the results of the research, we put forward the following suggestions: Fujian should coordinate the planning of the province’s green eco-tourism resources to maximize the use of resources. It should combine the advantages of the primary, secondary and tertiary industries and fully develop both advanced regions and under-developed regions. It should also explore areas of potential growth in the tourism sector, such as Sanming, Longyan, and Nanpin, by strengthening digital innovation and sharing resources with Xiamen, Fuzhou, Quanzhou and other highly-developed tourism regions.

Composite index of ecotourism development (selected years).

Close Degree of Progress (CDP) (spatial differences).

The convergence of China’s digital economy and green finance holds great significance for fostering a sustainable and high-quality developmental path. However, existing studies have not explored the coupling coordination development between these two crucial subsystems. To bridge this gap, this paper employs a modified coupling coordination degree (CCD) model to assess and affirm the coupling coordination degree between the digital economy and green finance across 30 provinces in China from 2015–2021. Based on degree results, provinces are classified into three clusters by using K-means and hierarchical clustering algorithm. Our findings unveil that the current level of coupling coordination development in China is at a primary coordination stage. Although regional disparities significantly exist, the overall level of coordination remains steadily increasing, with the eastern region outperforming the western region. Additionally, we determine that the COVID-19 pandemic’s disruption on the coupling coordination development of these systems has been limited. This research sheds light on the evolution of coupling systems and offers practical recommendations for strengthening the coordinated development of the digital economy and green finance.

With the rapid development of technology and the evolution of the global financial system, digital inclusive finance has become a new way to promote rural revitalization and rural residents’ consumption with the power of financial technology. This study explores the relationship between digitally inclusive finance, rural revitalization, and rural residents’ consumption. Based on the panel data of 30 provinces and cities in China from 2011 to 2021, this study empirically examines the impact of digitally inclusive finance on rural residents’ consumption and the mediating and threshold effects of rural revitalization. The results reveal that digitally inclusive finance is conducive to the enhancement of rural residents’ consumption, and rural revitalization acts as a mediator. Meanwhile, there is a nonlinear positive correlation between the impact of digitally inclusive finance and rural revitalization on rural residents’ consumption, in which there is a double-threshold effect of digitally inclusive finance and rural revitalization in the lagged period. Based on the above findings, we believe that while promoting digitally inclusive finance, it is important to promote rural revitalization strategy in a timely manner, improve rural infrastructure, and continuously stimulate the impact of digitally inclusive finance on rural residents’ consumption.