摘要 : While scholars and managers have long queried how a review message can be useful, the e-word-of-mouth (eWOM) literature yields inconclusive findings. Our study approaches this classic research question from the novel angle of diversity and investigate how topic diversity of online reviews affect review usefulness. Specifically, topic diversity manifests in both topic variety, the extent to which different topics are discussed in a review message, and content distribution across topics, the extent to which content is distributed across different topics. We leverage the aspect-based topic modeling technique to uncover the extent of different topics discussed in individual review messages as the nested subunits and operationalize topic variety and content distribution as two main unit-level predictors of review usefulness. This text-based approach helps analyze about 200k restaurant reviews from Yelp.com and generates six different topics relating to restaurant reviews. Results reveal that (1) on average, topic variety positively affected review usefulness, while content distribution across topics did not; (2) however, when topic variety is high (low), the impact of content distribution on review usefulness is significant and positive (significant and negative). Our study contributes to the e-WOM literature by offering new knowledge regarding topic diversity and review usefulness.

摘要 : Objective The current study aimed to explore the effectiveness and mechanisms of mindfulness on alleviating both immediate and delayed negative interpretation biases (NIB). Method A total of 105 college students (female: 84.62 %, age: 17–23) with high levels of depression were randomly assigned to a mindfulness-writing group, a mindfulness-only group and a waiting list group, and completed measures of mindfulness, depression, anxiety, NIB across three points in time (pre-, mid, and post interventions). The two intervention groups underwent two phases, each lasting 21 days, with daily self-guided digital interventions lasting 15–30 min. Results In terms of intervention effects : (1) Both intervention groups significantly improved levels of observing, describing, non-judging, and non-reactivity. While the waiting list showed a significant decline in acting with awareness, both intervention groups remained stable. (2) The mindfulness-only group significantly reduced delayed NIB. (3) In terms of reaction time as an indicator, both interventions did not reduce immediate NIB. However, in terms of frequency as an indicator, the mindfulness-only group effectively alleviated immediate NIB. In terms of mechanisms : (1) Regarding delayed NIB, acting with awareness and non-reactivity significantly mediated the relationship between groups and delayed NIB. (2) For immediate NIB, when measured by frequency, non-judging and non-reactivity significantly mediated the relationship between groups and immediate NIB. Conclusion Acting with awareness and non-judging, as mindfulness sub-dimensions, play unique roles in alleviating delayed and immediate NIB, respectively. The enhancement of non-reactivity contributes to the reduction of both immediate and delayed NIB.

摘要 : As a crucial component of green finance, environmental pollution liability insurance exerts a substantial influence on corporate green innovation globally. Since 2007, China's pilot work in this area has gradually advanced and become a model for other countries. In this study, we examine the panel data of publicly listed companies in China from 2007 to 2023 to analyze the effect of the environmental pollution liability insurance policy pilot on corporate green innovation. The findings reveal that implementing socialized environmental governance through the environmental pollution liability insurance significantly enhances corporate green innovation. These results remain valid after conducting robustness tests. Moreover, we analyze the mechanisms driving this effect. Our findings indicate that the insurance promotes corporate green innovation by improving corporate environmental, social, and governance (ESG) performance' enhancing the quality of internal governance' and mitigating financing constraints. Heterogeneity test results indicate that the positive effects are particularly pronounced and strong in non-state-owned, heavy-polluting, and high-tech companies, as well as in a company's strategic innovation other than substantive innovation.

摘要 : The influence of teachers on the acceptance of educational technologies has been largely highlighted in the literature. However, the way their interpersonal behaviours mediate students' acceptance and adoption of artificial intelligence (AI) technologies has received limited attention. To address the gap, this study drew on the technology acceptance model (TAM) to examine such interplay in the context of China. To do so, 103 Chinese English as a foreign language (EFL) students were interviewed online. The findings, obtained from manual thematic analysis, indicated that teachers' interpersonal behaviours affected Chinese EFL students' AI acceptance and adoption in five ways, namely by showcasing practical values of AI, establishing a positive learning environment, increasing ease of use, reducing negative AI-induced emotions and encouraging autonomy and reflectivity. A comprehensive discussion of the findings is provided along with a list of implications on different grounds for EFL teachers, students and trainers augmenting their familiarity with innovative educational technologies in L2 education.

摘要 : Residential preferences play a crucial role in shaping walking behaviors; however, limited literature has examined how residential preferences for specific built environment characteristics relate to walking for different purposes and the potential mediation effects of built environments in these associations. This study employs a path analysis model with data from 1, 050 adult participants in Shanghai, China, to investigate the interrelationships among residential preferences, objective and perceived built environment characteristics, and walking behaviors across different purposes. After controlling socio-demographics, walking preferences, and the built environment, the findings suggest that preferences for transit accessibility and building density are positively linked to commuting and errand walking, respectively, whereas a preference for street connectivity is negatively related to leisure walking. Moreover, residential preferences influence commuting walking through objective and perceived characteristics of built environments, while their impacts on errand and leisure walking are mediated exclusively by perceived built environment features.

摘要 : The convergence of industries in cities is fundamental yet profound to urbanization. However, existing research on urban industry convergence lacks sufficient spatial inquiries and requires deeper investigation of its effect on urbanization. This study introduces the concept of "spatial synergy" as an enhanced synergy between converging industries in space. A spatial synergy evaluation model is developed and applied to the convergence of the cultural and tourism industries in Hangzhou, China, in 2012, 2017, and 2022. The research offers three main novelties. First, this study extends the conception of industry convergence from economic activities to spatial processes, introducing a spatiotemporal framework for its analysis. Second, the study reveals a positive correlation between spatial synergy and urbanization outcomes of industry convergence, such as vitality and economic performance, through the proposed evaluation model, thereby affirming model's effectiveness in understanding industry convergence. Third, this study elucidates the synergistic promotion of spatial and economic urbanization through spatial reshaping and economic growth facilitated by industry convergence. Fourth, the study shows that variation in industry factors mobility and the absence of value chains can lead to a disconnection between market and technology sectors, hinder coordination between spatial and economic urbanization, and ultimately result in unsustainable urbanization. These important findings reinforce the necessity of integrating industry convergence into urban spatial planning, advocate enhanced synergy among factors, and highlight the promote reconstruction of the value chain as essential for sustainable urbanization in Hangzhou and similar cities in China and beyond.

摘要 : Fiscal decentralization has played an increasingly prominent role in driving China's economic growth, yet its influence on distortions in banking competition remains insufficiently examined. Drawing on data from 250 Chinese banks, we show that increased municipal government fiscal expenditure enhances local banks' market power, primarily by improving the performance of local firms, facilitating industrial upgrading, and driving digital advancements. This effect is especially pronounced for non-central state-owned banks with lower customer concentration and less capital-intensive operations in vibrant and central cities. Additionally, the effects of fiscal reform and the establishment of bankruptcy courts work in tandem to ensure bank market positions. Furthermore, while government expenditure may have a delayed but escalating impact on market power, the long-term influence of fiscal decentralization is more likely to shape banks' risk-weighted lending portfolios, even as improvements in bank efficiency may diminish over time.

摘要 : Current vector map zero-watermarking algorithms primarily rely on features such as angles, distances, or vertex counts, which are highly sensitive to noise. While frequency-domain coefficients offer greater stability and a promising alternative, existing frequency-domain algorithms remain vulnerable to rotation, scaling, and translation attacks. To overcome these limitations, this study proposes a novel zero-watermarking algorithm for vector maps based on the ratio invariance in the discrete wavelet transform (DWT) domain. The proposed algorithm first employs the Douglas–Peucker algorithm to simplify objects, enhancing robustness against changes in the vertex count. Subsequently, the horizontal and vertical coordinates of the feature points are separated, and their DWT high-frequency coefficients are calculated. A rotation- and scale-invariant geometric ratio domain is progressively constructed by leveraging the translation invariance of these coefficients. The ratio sequence is then binarized against its median to enhance resistance to vertex noise. Finally, the resulting binary sequences are superimposed to form the final feature matrix. Experimental results demonstrate that the proposed algorithm maintains significant uniqueness while exhibiting outstanding robustness, enabling stable watermark extraction under various attacks, including vertex simplification, vertex addition, noise perturbation, translation, rotation, and scaling.

摘要 : This study investigates the critical role of government subsidy policy objectives in influencing firms' total factor productivity (TFP) through the lens of conflicting policy goals between equity and efficiency. Utilizing panel data from Chinese manufacturing listed companies spanning 2010–2022, the research employs heterogeneous policy analysis to demonstrate that employment subsidies (targeting social equity) and R&D subsidies (focusing on economic efficiency) both achieve their intended objectives — expanding labor employment for the former and stimulating R&D investment for the latter — yet exhibit divergent effects on TFP. Specifically, employment subsidies create labor redundancy systematically depressing TFP growth. In contrast, R&D subsidies significantly boost TFP. The findings reveal an inherent trade-off in government subsidy design: employment-oriented policies may undermine productivity, whereas innovation-driven initiatives struggle to address employment absorption. This research provides theoretical and practical guidance for optimizing government subsidy policies, emphasizing the diversity and complexity of policy goals, and revealing the challenges in achieving both fairness and efficiency.

摘要 : As global urbanization shifts from expansive growth to focused regeneration, assessing how various regeneration models impact urban vitality becomes crucial. Historic districts, marked by deep-rooted identities and rising development pressure, demand nuanced regeneration strategies that align preservation with modernization, and serve as testing grounds for these contrasting approaches. However, the comparative efficacy of government-led and market-driven approaches remains underexplored. This study assesses how divergent regeneration models shape urban vitality, using Weibo_Expressed Sentiment (WESI) and Weibo_Check-in density (WCDI) as key indicators. Focusing on Suzhou's Jianjin Qiao Alley (government-led) and Shiquan Street (market-driven), the research evaluates the spatial-temporal impacts of regeneration. Its mixed-methods framework uses a quasi-experimental Difference-in-Differences (DID) design for robust causal identification, complemented by the machine learning-based Extreme Gradient Boosting (XGBoost) model to handle non-linear prediction and feature analysis. The study draws on geotagged social media check-ins and Points of Interest (POI) data from 2020 to 2024. It quantifies how built-environment elements influence regeneration performance and sentiment expression. Findings reveal a distinct trade-off: (1) the Market-Driven model was superior for improving public perception, causing a significant 0.029% increase in the WESI. (2) In contrast, the Government-Led model excelled at drawing public presence, driving a 0.303% increase in the WCDI, an impact of a much larger magnitude. (3) The predictive XGBoost analysis uncovers a non-monotonic effect where WESI peaks when the catering density index (PCDI) is in the 0.5 to 1.5 range, but turns negative after its value surpasses a threshold of 2. This study challenges conventional regeneration paradigms, uncovering temporal trade-offs between market efficiency and cultural sustainability. By introducing an integrated DID-XGBoost assessment framework, it quantifies the externalities of historic district regeneration, providing a diagnostic tool for optimizing heritage-compatible development.