The first-hand house price in Beijing, the capital of China, has skyrocketed with 43 percent annual growth from 2005 to 2017, exerting tremendous adverse effects on people’s livelihood and the development of real estate. Thus, exploring the behavioral mechanism and accurate forecasts of house prices is a critical element in making decisions under uncertain conditions and is of great practical significance for both participants and policymakers in real estate. According to the complex features of house price, including nonlinear, nonstationary, and multiscale, and considering the remarkable time and frequency discrimination capability of multiscale analysis in dealing with house price problems, we develop an ensemble empirical mode decomposition- (EEMD-) based multiscale analysis paradigm to investigate the behavioral mechanism and then obtain accurate forecasts of house prices. Specifically, the monthly house price in Beijing over the period January 2005 to November 2018 is first decomposed into several different time-scale intrinsic-mode functions (IMFs) and a residual via EEMD, revealing some interesting characteristics in house price volatility. Then, we compose the IMFs and residual into three components caused by normal market disequilibrium, extreme events, and the economic environment using the fine-to-coarse reconstruction algorithm. Finally, we propose an improved hybrid prediction model for forecasting house prices. Our experimental results show that the proposed multiscale analysis paradigm is able to clearly reveal the behavioral mechanism hidden in the original house price. More importantly, the mean absolute percentage errors (MAPEs) of the proposed EEMD-based hybrid approach are 5.62%, 7.24%, and 8.63% for one-, three-, and six-step-ahead prediction, respectively, consistently lower than the MAPE of the three competitors.

Introduction: This study investigates how the digital economy drives rural revitalization in China through technological progress. With the rapid growth of China’s digital economy, understanding its role in promoting rural revitalization has become increasingly important. This study explores the mechanisms through which digital development contributes to rural revitalization, emphasizing the mediating role of agricultural technological progress.Methods: Using panel data from 281 prefecture-level and above cities from 2011 to 2021, both static and dynamic econometric models are constructed to evaluate the effects of digital economy development. Agricultural technological progress—including general progress, frontier innovation, and pure technical efficiency—is incorporated as both a moderating and threshold variable.Results: The results indicate that the digital economy significantly promotes rural revitalization, exhibiting clear spatial and temporal heterogeneity. Among the three dimensions of technological progress, improvements in pure technical efficiency exert the strongest positive effect. Furthermore, threshold analysis shows that as technical efficiency improves, the positive influence of the digital economy intensifies, whereas the effect weakens when general or frontier technological advancement reaches higher levels.Discussion: These findings highlight the crucial role of agricultural technological efficiency in amplifying the benefits of digitalization for rural development. To maximize the digital dividends, policymakers should focus on strengthening rural digital infrastructure, promoting the integration of digital tools with agricultural technologies, and designing differentiated policy interventions tailored to the stages of technological development.

Introduction: With the rapid progress of urbanization and rising material affluence fostering spiritual needs, balcony agriculture has gradually become a focus of urban residents in China. Based on the Stimulus-Organism-Response theory, this study explores the impact and underlying mechanisms of integrated services on urban residents’ willingness to participate in balcony agriculture. Methods: Theoretical model construction combined with empirical analysis was employed. Data were collected via a structured survey of urban residents to examine the relationships between integrated services, perceived usefulness, perceived ease of use and participation willingness, and analyze the moderating effects of spatial conditions on these links. Results: Integrated services have a significant positive impact on residents’ willingness to engage in balcony agriculture. Perceived usefulness and perceived ease of use mediate the relationship between integrated services and participation willingness. Spatial conditions exert a moderating effect on the links between perceived usefulness, perceived ease of use and participation willingness. Discussion: Integrated services play a pivotal role in fostering residents’ participation in balcony agriculture; strengthening perceived usefulness and ease of use enhances their participation willingness, and optimizing spatial conditions amplifies this effect. Policy implications include encouraging enterprises to focus on customer education and training, optimize supply chain logistics, and provide one-stop shopping and other integrated solutions to support the sustainable development of balcony agriculture.

Background: A rapid increase in food waste has gained global attention, and providing consumers with sustainability information in restaurants is considered an important anti-food waste intervention. However, there is ongoing debate regarding its effectiveness. This study explores whether crowding—a common dining situation in restaurants—has a potential impact on the effectiveness of information-based interventions. Methods: Three experiments were conducted with a total sample of 1,124 participants ( N _total = 1,124) to examine the relationship between restaurant crowding levels and the effectiveness of different types of information-based interventions. Results: The results indicate a matching effect between crowding and information-based intervention types. Specifically, under high crowding conditions, prompt-type interventions (vs. feedback-based interventions) significantly increase consumers’ willingness to pack leftovers and reduce over-ordering behaviors. In contrast, under low crowding conditions, feedback-based interventions (vs. prompt-type interventions) are more effective in mitigating food waste. Furthermore, information processing fluency mediates this matching effect. Discussion: These findings reveal how environmental factors in restaurants influence the effectiveness of information-based interventions and provide practical guidance for marketers to select appropriate information-based intervention types based on the level of restaurant crowding to effectively prevent food waste.