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China’s economy has entered a critical period of structural adjustment. The developing green industries and the transforming traditional industries have increasing demand for finance, making ""green finance"" increasingly essential. While China's green finance is in the development stage, some newly developed zones serve as pilots for the launch of green financial products. An example is Tongzhou District of Beijing, which aims to expand Beijing’s space, promote the coordinated development of Beijing-Tianjin-Hebei, and explore the optimal development mode of the densely populated economic areas. This thesis aims to study consumer acceptance of green financial technology (fintech) in the case of Tongzhou District. This thesis extended the commonly applied theoretical model for the problem of study, the Energy Augmented Technology Acceptance Model (EA-TAM), to analyze the impacts of perceived usefulness, perceived ease of use, attitude toward use, intention, usage intention, environmental awareness, and green knowledge on the acceptance of green fintech in Tongzhou District. The survey collected 403 valid responses from people that had been active in Tongzhou District. The quantitative analysis is based on structural equation modeling techniques, including reliability analysis, validity analysis, standard method deviation test, and hypothesis testing. The analytical results show that all the hypothesized factors are significant. In addition, the sample is divided into different gender groups and education groups, so that the impacts of the socio-demographic characteristics can be explored. Males’ environmental awareness and green knowledge are insignificant in determining their acceptance of green fintech. The low-educated group’s acceptance of green fintech does not significantly depend on environmental awareness and perceived usefulness

The development of green financial products like green bonds and industry financing has gained momentum, showing positive impacts on sustainable economic development, renewable energy investment, and greenhouse gas emission reduction. As the research problem is inadequately explored, this dissertation aims to fill the research gap to evaluate the impacts of green finance on economic development. Furthermore, this study assesses the differences between Asian and non-Asian economies in the impacts of green finance on economic development. Two empirical measures are analyzed in this study.Green finance is measured with the Global Green Finance Index (GGFI), a composite index that captures over 100 instrumental variables, covering the business environment, human capital, infrastructure, and sustainability aspects of a financial center. Growth rate of gross domestic product (GDP) per capita reflects economic development. The dataset encompasses 83 international financial centers from 2018 to 2022. The regression model finds a significant negative relationship between growth rates of GGFI and GDP per capita in the full sample, the Asian subgroup, and the non-Asian subgroup. GGFI growth is confirmed to have Granger caused GDP per capita growth, but GDP per capita growth did not Granger cause GGFI growth. Combined with the insights of the previous studies, this study justifies the findings as a short-term negative impact of green finance on economic growth. However, the Asian region, with many emerging economies, could transition faster, so the regression derives a less negative coefficients for Asian financial centers. The policy implication 5 is that continued government support to improve the effectiveness of green finance is necessary for the long-term benefit of green finance to be fully realized

Many sports events have been reopened since the recovery from the global Covid19 epidemic. As countries work toward the third sustainable development goal of good health and well-being, sports events have received increasing support and investments. This study focuses on the Xiamen Marathon, which had reached the platinum level of sustainable development and is a benchmark marathon race in China. To assess the factors that influence the brand image and behavior of consumers of the Xiamen Marathon, this dissertation references the conceptual models in previous studies and hypothesizes that experience, brand image, loyalty, satisfaction, motivation, organization, quality, and trust are the direct influencing factors of brand image and indirect determinants of word of mouth, sport, and behavioral intention. This study surveyed participants of the Xiamen Marathon in 2024 and collected data from a sample of 285 participants. All the respondents were local residents and over 90% were contestants. The largest proportions were 36-to-55-year-old, married, highly educated, and employed, earning monthly income between ¥5000 to ¥15000 and spending over ¥1000 on marathon equipment. IBM SPSS and Amos were used for the quantitative analysis based on structural equation modeling techniques, including reliability test, validity test, and hypothesis testing. The questionnaire quality was good, the scale data were suitable for factor analysis, and the questionnaire data fitted well. However, quality and trust were excluded due to low significance. The results show that experience, loyalty, satisfaction, motivation, and organization have significant and positive impacts on brand image, which in turn has significant and positive impacts word of mouth, sport, and behavioral intention. The results support the eight hypotheses of direct effects and the 15 hypotheses of intermediate effects

This book is a compilation of the best papers presented at the APEF 2019 conference which was held on 25th and 26th July 2019 at the Grand Copthorne Waterfront in Singapore. With a great number of submissions, it presents the latest research findings in economics and finance and discusses relevant issues in today's world. The book is a useful resource for readers who want access to economics, finance and business research focusing on the Asia-Pacific region.

The degree of economic integration in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), as reflected in the mobility of trade and capital flows, has been strengthened by free trade agreements, but obstacles including border effects, capital controls, differences of exchange rate systems and inadequate cross-regional coordination remain. Digital renminbi (e-CNY) has been tested in Shenzhen, a core GBA city since April 2020. If e-CNY is adopted in the GBA, the area will effectively become a single currency zone. Whether the GBA constitutes an “optimum currency area” (OCA) depends on its degree of economic integration. This paper computes real interest rate differential (RID), uncovered interest rate differential (UID) and deviation from purchasing power parity (PPD) of each regional pair based on data of interest rates, exchange rates and price indexes from 2016M2 to 2022M7. All UID, PPD and RID series have means within about 1 percent point from 0, indicating high degrees of financial integration, real integration and economic integration. With the exception of Guangdong-Macau RID, all series are stationary, implying mean-reverting behavior. Hence, the parities are expected to hold both in the short run and in the long run, which is a condition for an OCA in the GBA. Furthermore, the regression analysis finds that the test launch of e-CNY in Shenzhen (adjusted for the COVID-19 outbreak) has significant impacts on all RIDs, Guangdong-Macau PPD and Hong Kong-Macau PPD. With merely two and a half years of test launch, the introduction of e-CNY already had impacts on overall economic integration in the GBA.