As a typical application of fintech, the robo-advisor has increasingly gained attention over the last decade. However, most research regarding the robo-advisor has focused on its development issues such as performance improvement and regulation, while limited research has paid attention to trust. This research extends the literature by investigating the trust influencing mechanism of robo-advisors by a mixed method approach. Specifically, we identified six salient trust influencing factors by qualitative interviews and proposed the research model based on trust transfer theory. This model was tested via a survey of 230 investors. Our study finds the significant influencing role of supervisory control and validates the relationships among trust influencing factors, trust in technologies, trust in vendor and trust in robo-advisor. Moreover, several differences between junior investors and senior investors are also found in our research. This study examines trust transfer theory in the new context of the robo-advisor and contributes to further development of this increasingly utilized service.

Small and medium enterprises (SMEs) play an important role in promoting the national economy and providing employment opportunities. E-commerce platforms may facilitate transactions between these enterprises. However, transactions on the e-commerce platform are non-face-to-face, strongly virtual, and variable, resulting in SMEs often facing moral hazards and opportunistic behaviors. Blockchain is a distributed ledger consisting of an encryption algorithm, consensus mechanism, and smart contracts, having the characteristics of authenticity, security, transparency, and unforgeability. Thus, the problems faced by SMEs can be resolved by combining e-commerce platforms and blockchain technology. In this study, we first provide a conceptual framework for blockchain-supported e-commerce platforms for SMEs. Second, based on this conceptual framework, we build a total business architecture. Finally, we propose three key applications to illustrate how the platform facilitates SMEs in solving financing and trading problems. This study provides significant guidance for the operation and management of blockchain-supported e-commerce platforms for these enterprises.

As a disruptive tool, blockchain technology can eradicate the product-counterfeiting problem in supply chains. However, a blockchain-supported platform charges an operating fee to legitimate manufacturers and retailers for product traceability and authentication. In this study, we employ enterprise profit-driven analytical models using Stackelberg equilibrium theory and highlight the values of blockchain-supported e-commerce platforms in addressing the product-counterfeiting problem. To measure the actual benefits of blockchain technology, we compare the profits of all agents in two different supply chains, traditional and blockchain-supported. Results show that the application of blockchain technology is not always beneficial to manufacturers, retailers, and customers. However, when the manufacturing cost of a legitimate manufacturer is sufficiently high, the manufacturer generates more profits using blockchain technology. Further, for a price-sensitive market, a retailer tends to trade in a blockchain-supported e-commerce platform if the retailer’s qualification in the platform is lower than that in a traditional supply chain, and the manufacturing cost of the counterfeit manufacturer in the platform is higher than that in a traditional supply chain.

The COVID-19 pandemic has severely impacted global tourism, raising the need for sustainable recovery strategies. This study examines how tourists’ confidence in tourism recovery (CTR) influences travel intentions across different pandemic phases—outbreak, stabilization, and conclusion. Positioned within the Theory of Planned Behavior (TPB), the research explores the mediating role of CTR in the relationships between attitude, subjective norms, perceived behavioral control, and travel intention. Using structural equation modeling (SEM), multi-group analysis (MGA), and Importance–Performance Matrix Analysis (IPMA), this study assesses changes in travel behavior during each pandemic phase. Data were collected through three surveys conducted in major Chinese cities between late 2022 and early 2023. The findings reveal that CTR significantly mediates the influence of behavioral factors on travel intention, especially during the stabilization and conclusion phases. The IPMA results highlight key areas for intervention, with CTR, perceived behavioral control, and subjective norms varying in importance across phases. This research underscores the need for adaptive and sustainable strategies to strengthen traveler confidence, offering practical insights for supporting long-term resilience and growth in the tourism industry during and beyond health-related crises.

Predicted price-to-book value ratios (P/BV) are widely used for the valuation of listed common stocks. However, with the application of automated trading system (ATS), the existing indicators that are applied in the method are losing their effectiveness in the Chinese market. Combining qualitative research with the text mining method, this study explores and validates those ignored factors to improve the accuracy of the stock valuation. On the basis of the principal of the existing valuation method, we clarify the scope of the factors that affects the P/BV ratio prediction. Through semi-structured interviews that are designed with six first-level factors which are taken from the literature, we then excavate some second-level factors. After that, with three corpuses including samples form Sina.com.cn, Xueqiu.com, and CSDN.net, four first-level factors and thirteen second-level factors have been verified step by step through the Latent Dirichlet Allocation (LDA) model. In the process, two other new factors and three sub-factors are also found. Furthermore, based on the factor correlation that was found in a data analysis, a factor relationship model was built. The results can be used in a stock valuation in future work as the basis of the indicator system for the prediction of P/BV ratio.