Journal of Digital Economy最新文献

Digital technologies reshape the distribution of value added through global value chains (GVCs). Based on the GVC decomposition method, we calculate the digital technology-related value added implied in GVCs. We find that digital technology-related value added share in service industries is higher and growing more rapidly than overall industries. The share of digital technology-related value added of three trade paths in service industries is higher than its share in overall industries. In service industries, simple and complex value chains have a higher share of digital technology-related value added than traditional value chains. Digital technology-related value added in China's service industries grows faster than overall industries, and digital technology-related value added in China's service industries trade grows faster than in overall industries trade. The share of digital technology-related value added in trade is higher and grows faster than its in domestic demand. The share of digital technology-related value added in China's service industries is higher than that in overall industries. This paper offers new interpretations of digital GVCs.

With the rapid advancement of mobile internet, UGC video platforms have become integral to the daily lives of young generations. For content creators on these platforms, sharing videos sponsored by corporations is the primary method to monetize their work. This research delves into the impact of video content sponsorship and sponsorship disclosure on consumer engagement by analyzing nearly 30,000 videos on the Bilibili platform. The results indicate that video sponsorships have a significantly negative impact on consumer engagement. However, comprehensive disclosure of sponsorship beforehand can improve consumer engagement. Additionally, our study demonstrates that followers of top-tier content creators are more sensitive to video sponsorships. This paper presents a critical empirical investigation of the sponsorship issue within the context of UGC platforms, making valuable contributions to the theories of advertisements' externalities in two-sided markets and information asymmetry.

Through the application of discrete choice and machine learning models, the primary objective of this study is to assess the impact of NGA networks coverage on reducing the risk of contagion during the first wave of COVID-19 across 278 municipalities in mainland Portugal, while controlling for other domains under the tutelage of the local public administration. Benchmark estimations reveal that, while holding everything else constant, each spatial unit is 2.4 p.p. more likely to become a high-risk municipality with additional 10 ​000 cabled houses with NGA networks. In a multinomial discrete choice model setting, the technical novelty of this study lies in providing graphical visualization and economic interpretation of coefficients and average marginal effects as a function of the number of classes used to define the dependent variable, while ensuring the satisfaction of the IIA assumption. The positive and significant coefficients of NGA indicate that additional coverage of NGA networks increases the likelihood of municipalities becoming high-risk for increasing number of spatial units not belonging to the low-risk efficiency frontier. The significant, negative, and decreasing average marginal effects of NGA suggest that the ability to remain a low-risk municipality diminishes with increasing NGA networks coverage as the number of municipalities belonging to the low-risk efficiency frontier decreases. The analysis also confirms that the effect of NGA networks coverage on COVID-19 is statistically significant in the indirect channel. This impact persists due to the mediation of population density, which is directly influenced by NGA networks coverage. All these findings can be explained by the fact that benefits related to productive activities do not outweigh costs associated with leisure time. Hence, this research emphasizes the need for a normative discussion on the intended purpose of digital technologies built on top of NGA networks to ensure a level playing field in the post-pandemic era.

With the growth of the social economy and technology, innovation networks have emerged as one of the most significant methods for analyzing the evolution of industrial innovation. Yet, there is a shortage of studies analyzing the components that influence network creation. By highly integrating digital technology with the traditional medical industry chain, the smart medical industry has become one of the important sectors of the digital economy. With the advent of internet-based diagnosis and treatment technologies, innovation inside the smart medical industry has taken the form of a network. This study aims to construct an innovation network by organizing and analyzing patent data from China's smart medical industry cooperation, covering the period from 2005 to 2022. The data is sourced from the IncoPat database. The analysis utilizes the Exponential Random Graph Model (ERGM) approach to conduct regression analysis on various factors. These factors include endogenous structural characteristics, node feature variables such as node emergence time and institutional attributes, as well as the distance network and IPC attribute network. By examining the driving mechanism and influence mechanism that influence the innovation network, this study contributes to the smart medical industry research by gaining a better understanding of the current status of innovation network, which can be advantageous for businesses in this field to accurately recognize and actively promote their innovation practices.

Marxist land rent theory has unveiled the nature and source of land rent, providing the rationale for discussing the distribution of total social products among wages, profits, and land rents. This paper has systematically summarized the development of Marxist land rent theory and its application in the field of digital platform research by constructing the mathematical-political economic model on this basis, we divide digital platform enterprises' revenues obtained into average profit, differential rent, and monopoly rent, and then discuss the source and impact of each part of the revenues respectively. Our study finds that: First, digital platform enterprises need to obtain average profit to compensate for the investment in providing digital space, products, and services, satisfying the fundamental requirement for an equal amount of capital to obtain an equal amount of profit. Second, on the premise of improving production efficiency, digital platform enterprises transfer surplus-profit from the general productive departments in the form of differential rent, whereas having no influence on the average profit of the general productive department. Third, digital platform enterprises can redistribute social revenues by collecting monopoly rent, and the excessive expansion of the scale of monopoly rent will inevitably squeeze the average profit of the general productive department, affecting the requirements of capital accumulation for reproduction on an extended scale and the proportional relationship between departments in social reproduction. Therefore, in order to guide the healthy development of digital platform enterprises, we should meticulously examine the role of digital platform enterprises from the change of overall social-economic efficiency, understand the nature of different types of rents, and evaluate the dynamic impact of digital platform enterprises' overall revenues on the change of the whole society's average profit rate.

The product-service system (PSS), in which customers pay for a product's functionality, is the common business model in a circular economy (CE). Digital technology (DT) is considered to be a crucial enabler of a PSS that facilitates CE integration in businesses. While discussions concerning the capacity of DT to overcome the main challenges posed by CE are growing, the specific evolution path of a PSS that can evolve to the level required by a CE and for the development of DT for each PSS type have not been widely explored. This paper reviewed a multiple-case study involving three manufacturing firms that each used PSS in business evolution projects and proposes guiding principles that can be used to support an effective approach to using the PSS to facilitate a CE at the business evolution stage. Moreover, in this systematic approach, DT impacts PSS deployment by acting as an enabler. The results contribute to theory by advancing the discussion exploring the potential relation between business evolution and circular principles through the mapping of PSS types. Explicit knowledge of the design principles behind PSS approaches can be obtained by analyzing this relationship. In addition, precise DT adaptation has been found in this study to be able to integrate toolsets that satisfy a variety of product demands and productivity plans by using specific technology to develop iterations for increasing service quality. From a practical perspective, this paper can help practitioners navigate the evolution of their businesses through the PSS model to enable a CE that is based on their existing digital and business capabilities.

This study examines the impact of technology and network externalities on exchange-listed Initial Coin Offerings (ICOs). Utilising an online database comprising of self-reported ICO characteristics, measures of post-ICO performance, along with information on business social networks, higher fundraising figures are found to contribute positively to the ICOs long-term success. This positive impact is multiplied by six times when fundraising is conducted to an existing, proprietary blockchain. This is explained by the network effect. The modified information ratio measure is used to approximate the quality signalling of ICO organisations using price time series and benchmarking these to already functioning blockchain technology, e.g. ethereum in the long term. The ICO sample's mean trading period on an exchange is 1.5 years and is used for long-period asset analysis. Additionally, the cointegration to the market technology benchmark is found to have a large, significant negative effect on long-term ICO organisational success as this indicates lower ICO intrinsic value.

The present study intends to provide a comprehensive overview based on existing literature related to social media analytics and digital economy using bibliometric analysis from Scopus database, particularly from the year 1996–2022. The studies that have discussed social media analytics and digital economy on a global scale using bibliometric analysis are very less in numbers. Therefore, this study determines the trends and maps in the digital economy and social media analytics using VOSviewer. The present study analyses 1539 articles collected from the Scopus database and uses VOSviewer that creates a visual representation of the data. Analyses of co-occurrence of keywords, co-citation, journals, and co-authorship have been employed in the study. The findings of the study reveal the most prominent trends in terms of influence, most prolific journals, articles, authors, topics, keywords, and countries. Content analysis has been employed using the bibliographic coupling of documents to identify the broad themes of the clusters. Further, a conceptual quadrant model has been devised to examine the outcomes of the interrelation between social media analytics and digital economy. This study further reveals that research on digital economy and social media analytics has shifted from the developed world to the developing nations. Now, more and more research is being conducted in the countries like China, Pakistan, Bangladesh, Ukraine and India. Through the density visualization of keywords analysis, it is revealed that keywords like “digitalization”, “artificial intelligence”, “blockchain”, “cryptocurrency”, and “bitcoin” are in trends of research in the subject matter.

Using a four-country North-South trade model with two identical countries in each region, this paper studies two types of bilateral free trade agreements: symmetric free trade agreements between countries in the same region, and asymmetric free trade agreements between countries from different regions. It first shows that a symmetric free trade agreement is always beneficial to its members and characterizes when it will increase or decrease the welfare of all countries. It then characterizes when an asymmetric free trade agreement is beneficial to its members and when it is beneficial to all countries.

Results of this paper provide a digital technology perspective for international trade agreements. In particular, they imply that countries with less advanced digital technologies in general have incentives to catch up to the more advanced countries and that in some instances it is also in the interest of the digitally more advanced countries to help the digitally less advanced countries shrink the technology gap.