Journal of Digital Economy最新文献

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.

In the era of digital economy, the data has increasingly become one important production factor. Taking Guiyang Global Big Data Exchange (GBDEx) as an empirical case, this paper first proposes a SEED model for constructing the data factor market which mainly consists of four components: S for System rules designing which refers to the design of rules, standards, policies and laws on data transaction process; E for Exchange platform building which should be credible, controllable, reliable and traceable; E for Ecosystem nurturing that refer to diverse data suppliers, customers for data demand, data intermediaries, data regulators, and other data trading alliances should be nurtured; and D for Data convergence and co-governance refers to the convergence and co-governance of various types of data trading subjects. The SEED can also be interpreted as a process of constructing the data factor market, with the data exchange as the core, igniting the vitality of the whole data factor market like a seed. We believe this paper can make contributions to the digital economy literature: first, it contributes to extant literature on data marketplaces and data ecosystem; second, it provides practical suggestions for constructing the data factor market; third, relevant policy makers and higher-level managers will likely achieve much enlightenment from this paper.

Despite their growing significance in the digital economy, some sharing platforms struggle to achieve sufficient scale, while others fail entirely. By extending the focus beyond network effects and trust-building mechanisms, this paper seeks to identify factors that impact platform growth and to analyze their implications for governance mechanisms and the strategic management of sharing platforms. We center our analysis on transaction costs economics (TCE) and its three key related variables: transaction frequency, transaction uncertainty, and transaction-dedicated investments. Our aim is to examine how these variables determine transaction costs at the platform level and how these costs shape member participation and hence platform growth. To explore our hypotheses, we surveyed a community of members of a digital, peer-to-peer (P2P) sharing platform. Our empirical findings confirm that a platform's growth is significantly affected by transaction features and that, alongside other theoretical approaches, TCE represents an appropriate and complementary lens with which to explore the growth dynamics of sharing platforms, as well as to consider appropriate actions platform owners can take at the organizational, governance, and strategic design levels.

Firms providing virtual platforms that connect buyers with sellers of goods and services are increasingly venturing abroad, sometimes from or near inception. However, these platform multinational companies (PMNCs) seem to struggle more against local competitors in foreign markets compared to more traditional MNCs when it comes to capturing market share and generating profits. In this study, we explore the underlying causes of these patterns. We first flesh out several stylized facts from a longitudinal case study of the mobile phone industry in China, and then we use these facts as input for formal economic modelling and simulations to derive generalized propositions. We find that informal institutional distance (IID) at the macro business system and micro product market levels poses challenges to all MNCs. Yet, whereas traditional MNCs can overcome IID by leveraging their product quality advantage, PMNCs are usually unable to do so and are, thus, more likely to underperform. We explicate that this pattern is likely underpinned by network effects that exacerbate the role of IID for the foreign PMNC. We discuss implications of these results for theory of the PMNC, particularly focusing on the need for research examining how this unique form of MNC can overcome internationalization challenges associated with IID.

With the process of digitalization, digital trade has become the primary pattern of international trade, and digital platforms and data have become two essential ingredients in digital trade. Meanwhile, the governance of digital trade has been a critical issue in international cooperation and domestic regulation. The governance system on digital trade is fragmented, and the governance approaches of the leading economies show divergences and conflicts. With the aim to explore the factors for the policy conflicts, this article selects the United States, the European Union, China, and India as typical cases to analyze their trade development strategies and digital trade rules comparatively. We find that the four economies adopt differentiated digital trade policies and data governance approaches on the basis of digital industrial benefits. We concluded that the government implements trade policies strategically to influence the distribution of digital trade gains and increase the share of the digital industry by intervening in cross-border data flows. This article contributes to current research by keeping up with the latest progress in digital trade governance and making theoretical analyses on strategic digital trade policies and governance approaches.