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Integrating financial technologies with green initiatives is critical to the sustainable development agenda. This is particularly true for newly developed smart cities like Tongzhou, the sub-city center of Beijing. To assess the adoption of green fintech in Tongzhou, this paper extends the EnergyAugmented Technology Acceptance Model (EA-TAM) to incorporate two green factors – environmental awareness and green knowledge. This paper applies structural equation modeling techniques to analyze data from 403 respondents who live, work, or study in Tongzhou and finds allhypothesized constructs significant. Since green knowledge is significant to the adoption of green fintech, this paper further divides the sample into a high-education group (162 respondents with university-or-above degrees) and a low-education group (251 respondents with post-secondary-orlower degrees) to evaluate the impact of education. All the hypothesized factors are significant to the high-education group,but environmental awareness and perceived usefulness are insignificant to the low- education group. Hence, the results provide evidence that people in the newly developed smart city adopt green fintech due to their environmental sensitivity. The adoption of green fintech is more environmentally sensitive for people with high education levels.
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An increasing number of countries have launched their central bank digital currencies (CBDC) in recent years, but the economic impacts of CBDC adoption are underexplored. To empirically assess how CBDC adoption influences regional economic integration, this paper investigates the Greater Bay Area, where China carried out one of its first digital renminbi pilot programs. The Greater Bay Area provides a good example because the growing acceptance of digital renminbi in the area can potentially mitigate transaction costs and risks due to the exchange rate volatility of the Chinese renminbi, Hong Kong dollar, and Macao pataca. CBDC adoption can lead to greater real and financial integrations by facilitating cross-border trade in goods and services. This paper evaluates deviations from uncovered interest rate parity, purchasing power parity, and real interest rate parity across Guangdong, Hong Kong, and Macao based on monthly interest rate and price data from January 2016 to December 2022. The time series have mean values near zero, which validate the parity conditions and indicate high degrees of financial, real, and economic integrations. The Markov regime-switching regression model identifies three regimes: (1) pre-Covid, (2) post-Covid, and (3) post-CBDC. The Covid-19 outbreak brought lower integration and stability, but the launch of the CBDC restored some of the pre-Covid integration and stability. Regimes 1 and 2 are persistent, and transitions from Regime 3 back to Regime 1 are probable. Hence, this study finds evidence that CBDC adoption improves regional economic integration in the short and long run.
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