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- Language: English
Description
Under the new generation of technological and industrial revolutions, digital economy enterprises are increasingly becoming major contributors to socio-economic development. Their scale effect and marginal cost effect are different from traditional enterprises, which also raises concern and discussion on whether digital economy enterprises can promote more equitable and sustainable development of society. The participation of digital economy enterprises in the common wealth is an important source of legitimacy for their development. This thesis investigates the mechanism of the impact of their common wealth inputs on corporate financial performance by using a sample of digital economy firms among Chinese listed companies as a case study. It is found that, overall, the mechanism of the effect of firms' common affluence model on their financial performance has a positive effect. The main source of this positive effect is the secondary distribution of the firm, i.e., the legitimacy of tax contributions. Other legitimacy such as employee and shareholder legitimacy are not significantly associated with financial performance, while social philanthropic input from tertiary distribution participation has a significant negative effect. In the association of redistribution on firm performance, there is a positive facilitating effect on firms' R&D efficiency and a negative moderating effect of economic policy uncertainty. It suggests that there are differences in the impact of firms' legitimacy initiatives, such as tax contributions, on performance under different firm development expectations. Whereas in the third distribution, firms' R&D efficiency has a crowding-out effect on the economic gains from the legitimacy of common wealth participation, economic policy uncertainty has a reinforcing effect in the third distribution of firms. The above suggests that the development of digital economy firms is more positively facilitated by official legitimacy and currently lacks the constraints of industrial ecology from internal and public scrutiny.
ContributorsZhou, Guangyi (Author) / Wu, Shin-Yi (Thesis advisor) / Hu, Jie (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2023
Description
With the rapid development of information technology and the rise of the Internet+ era, the sharing economy has fundamentally changed people's lives and consumption patterns, and has also reshaped the process of value co-creation between enterprises and customers. In the sharing economy, enterprises no longer play the dominant role; instead, they have evolved into platforms that provide support and services for users. In this economy, users not only determine the profitability and reputation of enterprises but also create substantial value through the exchange of usage rights to idle resources and interactions both online and offline. Therefore, studying the value co-creation behavior of bilateral users on sharing service platforms is of significant necessity for enterprise development. This research aims to explore the impact mechanism of bilateral user value co-creation on customer value in sharing service platforms. Through the analysis and summarization of literature, a theoretical model of bilateral user value co-creation and customer value in the context of the sharing economy has been established. The research subjects include users of the homestay/inn platform on Ctrip, as well as users of other types of sharing platforms, such as Lazy Housekeeping, LoveChef, Didi and Airbnb.
In the empirical part, questionnaires were designed and sample data was collected through the Questionnaire Star platform. SPSS 25 and AMOS 23 data analysis software were used to perform reliability and validity analysis and correlation analysis of the scales. Multivariate regression analysis was employed to investigate the impact of bilateral user value co-creation on various aspects of customer value. Additionally, the Bootstrap method was used to test the mediating roles of relevant factors.
Through the above research methods, we will be able to have an in-depth understanding of the impact mechanism of two-sided user value co-creation on customer value of the shared service platform and obtain more comprehensive and concrete research findings. I believe that the findings of this study will have important implications for the theory and practice in the domain of sharing economy. Key words: sharing economy, sharing service platform, two-sided users, value co-creation, customer value
ContributorsLou, Wen (Author) / Shao, Benjamon (Thesis advisor) / Hu, Jie (Thesis advisor) / Dong, Xiaodan (Committee member) / Arizona State University (Publisher)
Created2024
Description
In recent years, the decentralized exchange (DEX) has shown an explosive growth trend in recent years. Uniswap, as one of the largest decentralized exchanges, invented Uniswap, a decentralized financial protocol of the same name based on exchanging cryptocurrencies. Automated transactions between cryptocurrency tokens on the Ethereum blockchain. Currency trading participants create a liquidity pool based on this agreement, and this paper mainly studies the factors that affect the liquidity of currency trading.Specifically, this paper explores the factors that affect monetary liquidity through three hypotheses. The first is the impact of rates on liquidity, exploring the differences in liquidity under various rates. Then, the impact of differences in Uniswap protocol versions on liquidity was studied. Compared with the V2 version, the Uniswap V3 version added centralized liquidity，which changed the unpaid loss. . This feature makes Uniswap V3 the most flexible and efficient protocol. Finally, the influence of different active users on liquidity is compared, and the change trend of liquidity under different numbers of users is explored.
Based on the above three assumptions, this paper adopts GARCH and OLS regression analysis to explore and analyze the collected currency transaction data, and draws the following conclusions for the three assumptions:
(1) Researcher may conclude that rates are correlated with trading volume, and volume growth impacts liquidity capacity and increases rates. Therefore, the fee rate has a significant impact on liquidity.
(2) Compared with V2, V3， quantitative analysis was carried out using unpaid loss. It was found that impermanent loss has a more significant impact on the liquidity of the V3 version but has little correlation with the V2 version.
(3) According to the analysis and comparison of the model, there is no obvious ARCH phenomenon among active users, so it is believed that there is no significant correlation between the two.
(4) Combining conclusions 1 and 3, researcher further analyzed the impact of several independent variables on liquidity and found that the fee rate has a more significant influence than active users
ContributorsWu, Jiawei (Author) / Chen, Pei-Yu (Thesis advisor) / Hu, Jie (Thesis advisor) / Zheng, Zhiqiang (Committee member) / Arizona State University (Publisher)
Created2023
Description
With the continuous development of the Chinese capital market over the past thirty years, the securities analyst industry has experienced a process of transformation from a reckless period to a golden time. One of the most important signals is that securities analysts are increasingly conducting research report providing long-term earnings forecasts for the company. However, current research on analysts is limited to their short-term forecasting behavior, and there is little on analysts' long-term earnings forecasts. Therefore, this article takes the research on analysts' long-term forecast reports issued by analysts on A-share listed companies, and conducts an empirical study on the analysts' forecasts accuracy and its influencing factors. First, the author combed the research literature related to analyst forecasts and selected variables from three dimensions, including company characteristics (financial indicators and non-financial indicators), analyst characteristics and affiliated institution characteristics; secondly, considering the high-dimensionality of the influencing factors, this paper uses the method of combining machine learning and traditional regression to conduct empirical research; finally, the research tested the heterogeneity of influencing factors from two perspectives, including time and industry.The results of this article show that the long-term profit forecasts of analysts in China have advantages over traditional statistical models. More than 60% of analysts
provide profit forecasts that are better than statistical models. Afterwards, when examining the factors that affected the accuracy of analysts’ forecasts, it found that although analyst and institutional characteristics affected analysts’ predictions to a certain extent, company characteristics are the most important variables among them all. As the time goes by, the influence of non-financial factors on forecast accuracy gradually decreasing, but analyst characteristics continue to strengthen. In addition, cyclical industries are more difficult to predict than companies in non-cyclical industries, and the difficulty of prediction will not be reduced with the analyst efforts. This research can help analysts optimizing their forecasting behavior and prompts investors to understand analysts' reports more deeply, which makes them using analyst forecast data to make investment decisions in a rationally ways, and it can also help to promote the securities pricing efficiency and development of Chinese capital market.
ContributorsRao, Gang (Author) / Shen, Wei (Thesis advisor) / Yan, Hong (Thesis advisor) / Hu, Jie (Committee member) / Arizona State University (Publisher)
Created2024
Description
NFT market have developed into an annual sales scale of nearly $60 billion. After the crazy blockchain investment myth, how can the rational trading market grasp consumer demand? As the main platform of marketing for 21st century, social media is widely used by both traditional artists and NFT creator. When artworks are combined with NFT in social media marketing, how do they affect the willingness to purchase digital collectibles? In the hot era of GPT, how will artificial intelligence-generated content (AIGC) affect people's purchasing behavior? This article measures the impact on consumer purchasing willingness from the activity level of social media accounts (number of posts), creator attributes (human vs. artificial intelligence), published content (diversity, content tendency), etc. Through experiments, this article verifies that consumers' demand for uniqueness will positively affect the willingness to purchase digital collectibles and payment prices; artificial intelligence generated content(AIGC) will reduce consumers' willingness to purchase and payment prices, but as the diversity and quantity of published content increases, the negative impact is significantly weakened; compared with emotionally inclined content, the negative impact of artificial intelligence generated content is greater on technology-oriented content.
ContributorsSong, Kai (Author) / Chen, Pei-Yu (Thesis advisor) / Hu, Jie (Thesis advisor) / Hong, Yili (Committee member) / Arizona State University (Publisher)
Created2024
Description
China’s digital economy has developed rapidly after the 19th National Congress of the Communist Party of China. As an important part of the digital economy, the application and development of digital finance has provided a better path for financial institutions about services innovation and business development. Small and medium-sized enterprises (SMEs) account for a large proportion of the number of enterprises in China. They affected the society deeply on various aspects such as economic growth, employment, and innovation. However, financing constraints characterized by “difficult requirements” and “high cost” have long restricted the development of small and medium-sized enterprises. In recent years, the growth rate of the international economy has slowed down in an all-round way due to the impact of the epidemic. The SMEs have become more severe in this environment with stronger demands for funds. The rapid development of digital finance provides a technical environment for substantially improving the availability of loans for SMEs. As the main source of financing for small and medium-sized enterprises, commercial banks can deal with the problem of information asymmetry between them and SMEs easily through comprehensive digital transformation. Furthermore, the digital transformation of commercial banks could alleviate the financing constraints of SMEs and allocate more credit resources for SMEs. This study uses Peking University’s digital financial inclusive index and the SMEs’ loan data from the specific commercial bank for empirical analysis. The results demonstrate that the development of digital finance can alleviate the financing constraints of SMEs and reduce the information asymmetry between banks and enterprises. Moreover, the digital finance could also improve the overall business efficiency of commercial banks. In addition, SMEs with relatively in-depth digital transformation are easier for taking advantage of the opportunity of digital financial development to alleviate their own financing constraints. This study provides effective suggestions for the administrative department to formulate relevant guiding policies for digital financial development, commercial banks’ digital business strategy formulation, and more financial resource allocation for SMEs with development prospects based on the research conclusions.
ContributorsOu, Hong (Author) / Zhu, David (Thesis advisor) / Li, Xianglin (Thesis advisor) / Hu, Jie (Committee member) / Arizona State University (Publisher)
Created2024