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The purpose of this paper is to explore the changes of the scale of urban tourists in mainland China under the impact of COVID-19 and, specifically, the following questions: how did the scale of domestic tourists change nationwide and in the seven geographic regions? What are the differences in the changes among the seven geographic regions? What are the changes in the hot spot areas and spatial clustering of domestic tourists across the country?

Using the data of domestic tourist arrivals in 337 cities in mainland China from 2018 to 2021, this research analyzes the absolute differences and relative differences in the scale of domestic tourists nationwide and in seven geographic divisions with the help of indicators such as range analysis, standard deviation, coefficient of variation and Herfindahl–Hirschman Index and explores the changes in the hot spot areas and spatial concentration degree of the spatial scale of domestic tourists nationwide under the influence of the epidemic using kernel density analysis and spatial auto-correlation analysis.

The absolute differences in all seven geographical divisions continue to increase during 2018–2021. The domestic tourism in southwest China is extremely uneven. Absolute differences in the northwest and northeast regions are relatively small, and the development in attracting domestic tourists is more balanced. Relative differences in southwest China are comparatively large, with the trend of uneven development being obvious. The northeast, northwest and eastern regions of China are small, and the development is more balanced. The popularity of domestic tourism in the Beijing–Tianjin–Hebei region, as well as the Yangtze River Delta region, continues to decline and then pick up in 2021. The inland southwest region became a new domestic tourism hot spot in 2021. The size of domestic tourists from 2018 to 2021 in mainland China cities shows a significant positive spatial correlation, and there is a spatial agglomeration phenomenon, but some regional agglomeration types change from 2018 to 2021.

The impact of the epidemic on the number and spatial scale of domestic tourism in China has been clarified, which makes up for the comparison of domestic tourism changes before and after the epidemic. A clear understanding of the changes in the number and spatial scale of domestic tourists in different regions after the epidemic is conducive to the development of domestic tourism revitalization strategies in accordance with the actual situation of each province and promotes the internal circulation of Chinese tourism.

This paper tries to clarify the quantitative scale of domestic tourism in different regions after the epidemic, which is conducive to the development of domestic tourism revitalization strategies in cities in different regions according to regional characteristics and the actual situation of each province and to promote the healthy operation of the internal circulation of tourism in China. This paper also tries to show the changes of domestic tourism market hot spots, agglomeration conditions changes before and after the outbreak and the clarity of tourists’ preference space changes.

Scale of domestic tourists; Absolute difference; Relative difference; Spatial hot spot distribution; Spatial agglomeration change

本文旨在探寻疫情影响下中国大陆城市游客规模演化规律, 具体而言, 疫情影响下, 全国及七大地理分区的国内游客量规模变化如何？七大地理地区的变化有何差异？以及疫情影响下, 全国国内游客空间规模的热点区域和空间集聚程度有何变化？

利用2018-2021年中国大陆337各城市的国内游客量数据, 借助极差、标准差、变异系数、赫芬达尔指等指标分析全国及七大地理分区国内游客规模的绝对差异和相对差异; 借助核密度分析、空间自相关分析等ArcGIS分析工具, 探寻疫情影响下全国国内游客空间规模的热点区域和空间集聚程度的变化情况。

①绝对差异方面, 七大地理分区的绝对差异均持续增大。西南地区的游客量的绝对差异巨大, 国内游发展极不均衡。西北地区、东北地区绝对差异相对较小, 在吸引国内游客方面发展较为均衡。②相对差异方面, 西南地区的国内游发展相对差异较大, 发展不均衡趋势明显; 东北地区、西北地区、华东地区的国内游发展相对差异较小, 发展较为均衡。③热点区域变化方面, 京津冀地区、长三角地区的国内旅游热度持续下降, 在2021年有所回升; 内陆西南地区在2021年成为新的国内游热点区域。④2018年至2021年城市国内游客量规模均呈现出显著的空间正相关的关系, 存在着空间集聚现象, 但部分区域集聚类型在2018到2021年间发生变化。

①理论意义：明晰了疫情对中国国内旅游人次的数量规模和空间规模的影响, 弥补了当前疫情前后国内旅游业变化对比的研究; 阐明了疫情前后中国城市国内游客空间格局的变化, 拓展了研究情景, 丰富了中国旅游业时空变化的相关研究。②实践意义：明晰了疫后不同地区国内旅游人次的数量规模和空间规模变化情况, 以及国内旅游市场热点变化和游客空间偏好变化, 有利于各地区城市对症下药, 制定符合各省份实际情况的国内旅游业振兴策略, 促进中国旅游业内循环。

This study aims to investigate the differences in spatial ability between students with a math learning disability and their normal peers.

To investigate these differences two groups, (60 students with a math learning disability) and (60 normal students) from fifth grade with a mean age (10.6 years) were administered with spatial ability test along with an IQ test. Students with a math learning disability were chosen using measures of the following: math learning disability questionnaire developed from learning disability evaluation scale – renormed second edition (LDES-R²) (McCarney and Arthaud, 2007) and the Quick Neurological Screening Test (Mutti et al., 2012), in addition to their marks in formal math tests in school.

Comparison between the two groups in four aspects of spatial ability resulted in obvious differences in each aspect of spatial ability (spatial relations, mental rotation, spatial visualization and spatial orientation); these differences were clear, especially in mental rotation and spatial visualization.

This paper contributes to gain more insights into the characteristics of pupils with a math learning disability, the nature of spatial abilities and its effect on a math learning disability. Moreover, the results suggest spatial ability to be an important diagnose factor to distinguish and identify students with a math learning disability, and that spatial ability is strongly relevant to math achievement. The results have significant implications for success in the science, technology, engineering and mathematics domain.

The purpose of this article is to explore preference for privacy among people with different demographic and cultural backgrounds. In particular the study aims to investigate the effect of age, gender, previous experience of space and cultural background on people's chosen spatial location for privacy in multi‐bed wards.

A group of 79 subjects were asked to complete a questionnaire on privacy and to select preferred and disliked locations on plans of hospital wards. Spatial data were provided by space syntax analysis (VGA). Possible subgroups in the data were investigated by tests of difference and latent class analysis applied to those spatial attributes which appeared to be relevant to people's preferences on locations for privacy.

The results show that privacy regulation encompasses universal and specific aspects across cultures, age, gender and previous experience of space. Specifically, the results suggest a universal preference for spatial location of privacy across culture, age and gender and a specific significant difference for spatial location of privacy as a result of previous spatial experience. In addition, the VGA integration measure was found to be a highly significant discriminator between preferred and disliked locations for privacy.

There are two particular limitations requiring further study. First, the study investigated only one facet of privacy, i.e. spatial location. More investigation is required to explore the inter‐relationships between spatial location and other facets of privacy, primarily that of intervisibility. Second, only two broader cultures (European and Arabic) were considered.

Ideally it would have been of benefit if a greater number of the people sampled had had direct experience of hospital wards.

At a general level the study supports the notion that there are universal and specific aspects to privacy. At a specific level the research links physical aspects of spatial location (i.e. visibility graph analysis measures) into this discussion.

The authors provide a way to represent spatial and temporal equilibria in terms of error correction models in a panel setting. This requires potentially two different processes for spatial or network dynamics, both of which can be expressed in terms of spatial weights matrices. The first captures strong cross-sectional dependence, so that a spatial difference, suitably defined, is weakly cross-section dependent (granular) but can be non-stationary. The second is a conventional weights matrix that captures short-run spatio-temporal dynamics as stationary and granular processes. In large samples, cross-section averages serve the first purpose and the authors propose the mean group, common correlated effects estimator together with multiple testing of cross-correlations to provide the short-run spatial weights. The authors apply this model to the 324 local authorities of England, and show that our approach is useful for modeling weak and strong cross-section dependence, together with partial adjustments to two long-run equilibrium relationships and short-run spatio-temporal dynamics. This exercise provides new insights on the (spatial) long-run relationship between house prices and income in the UK.

Distinguishing what employers in different areas of Great Britain need to pay to attract and retain labour has been a central component of public-sector resource allocation decisions. This paper examines how changes in the pattern of spatial wage differentials following the global financial crisis have impacted on the formulae which allocate government funding to local government and health providers in the NHS.

Using employer-reported data on earnings, we examine spatial patterns of private-sector wages in Great Britain between 2007 and 2017. The method permits the analysis of finely defined geographical areas and controls for differences in industry and workforce composition to distinguish those differences that are attributable from unmeasured characteristics, such as differences between areas in the cost of living and amenities. These standardised spatial wage differentials (SSWDs) underpin the funding allocation formulae.

The analysis shows that since 2007 private-sector wage dispersion, both within and between regions, has reduced: lower paid areas have experienced a relative increase in wages and higher paid a relative decline. Over the period, there was a significant reduction in the London wage premium.

This paper demonstrates the importance of ensuring established policies are applied using contemporary data. The SSWDs used to distribute government funds have not been re-estimated for some time. As a result, the current resource allocation model has overcompensated the London region and undercompensated others during this period.

Given the inevitable transition to renewable resource utilization and the urgent need to reduce carbon emissions, this study conducted quasi natural experiments to assess the impact of renewable resource utilization on carbon emissions based on the national “urban mining” demonstration bases (NUMDB).

This study uses panel data from 275 prefecture-level cities in China from 2006 to 2019. The paper selects NUMDB as the proxy variable and conducts a quasi-natural experiment using a multi-period differences-in-differences model. We examine the impact of NUMDB on reducing carbon emissions, and then deeply explore its mechanism and spatial spillover effect.

This study found that: (1) the construction of NUMDB can significantly decrease the carbon emission in the host cities; (2) NUMDB’s construction has more significantly reduced the carbon emission in regions with higher levels of circular economy development, green technology innovation, regional environmental pollution, digital economy development and financial development; (3) by means of green technology innovation, optimized energy structure, and high-quality talent aggregation, NUMDB reduces urban carbon emissions; (4) NUMDB construction positively affects the carbon reduction efficiency of neighboring regions.

We propose corresponding policy suggestions to further promote the carbon emission reduction effect of NUMDB and develop the renewable resources industry in China based on the research findings.

The contributions of this paper are as follows. Our study contributes to expanding the research scope on the environmental impact of the renewable resource industry, as there are few quantitative studies in this area.

We further consider the spatial heterogeneity of policies and analyze the carbon reduction effect of the NUMDB from the city level, which is beneficial to exploring more targeted and operable carbon reduction paths.

This study on identifying the causal relationship between renewable resource utilization and carbon emission reduction helps to explore the sustainable development path of renewable resource more comprehensively. Meanwhile, this paper provides a reference for other countries to improve the utilization of renewable resource and effectively reduce carbon emissions.

The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.

In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.

After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.

Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.

Complex environments have a paucity of visual wayfinding information creating a strenuous situation for the new visitors. University campuses situated in the central urban areas with multi-storey structures and complex spatial layouts have poor environmental legibility. International students and visitors with diverse cultural backgrounds feel disoriented during wayfinding in these environments. The purpose of this paper is to investigate the cultural and individual differences affecting wayfinding behaviour.

An online wayfinding survey has been conducted through a questionnaire from 170 university students and visitors from Hong Kong and Pakistan. A five-point bipolar Likert scale has been used to evaluate wayfinding problems and ascribed behaviour.

The results enunciated a substantial influence of culture on the decision-making process and wayfinding behaviour. Critical differences have been documented based on the country of origin and native language. Individual-related differences (age, gender, spatial familiarity, education, etc.) were computed, where age and spatial familiarity being noted as key factors impacting the respondents’ opinion. Future exploration has been discussed for the pivotal elements regarding wayfinding information signage using computer simulations.

The investigation can be further moved towards the other complex environments with fused facilities for a better understanding of wayfinding behaviour.

The findings can be instrumental for improved access to user facilities and can reinforce the user’s trust and dependence on the institutional facility management.

In the wayfinding study, no cross-cultural (individualists vs collectivists) study has been conducted in a university campus to investigate the wayfinding difficulty and ascribed behaviour, especially when the environment is unfamiliar.

Online learning is well-known by its flexibility of learning anytime and anywhere. However, how behavioral patterns tied to learning anytime and anywhere influence learning outcomes are still unknown.

This study proposed concepts of time and location entropy to depict students’ spatial-temporal patterns. A total of 5,221 students with 1,797,677 logs, including 485 on-the-job students and 4,736 full-time students, were analyzed to depict their spatial-temporal learning patterns, including the relationships between identified patterns and students’ learning performance.

Analysis results indicate on-the-job students took more advantage of anytime, anywhere than full-time students. Students with a higher tendency for learning anytime and a lower level of learning anywhere were more likely to have better outcomes. Gender did not show consistent findings on students’ spatial-temporal patterns, but partial findings could be supported by evidence in neural science or by cultural and geographical differences.

A more accurate approach for categorizing position and location might be considered. Some findings need more studies for further validation. Finally, future research can consider connections between other well-known performance predictors (such as financial situation, motivation, personality and major) and the type of learning patterns.

The findings gained from this study can help improve the understandings of students’ learning behavioral patterns and design as well as implement better online education programs.

This study proposed concepts of time and location entropy to identify successful spatial-temporal patterns of on-the-job and full-time students.

This study explored the influence of personalized virtual try-on (PVTO) technology on consumer behavior in the apparel industry, focusing on decision comfort. It investigated how individuals’ spatial processing perception acts as a moderator in this context. Additionally, it examined the ease with which individuals imagine a product within the framework of this psychological mechanism.

Two experimental studies were conducted to evaluate the effects of PVTO technology on consumer decision comfort, with spatial processing perception as a moderating variable. The first experiment (n = 252) explored the impact of PVTO on decision comfort using photo-based simulations across various apparel items. The second experiment (n = 125) further examined these effects using measurement-based PVTO technologies to provide a deeper understanding of the role of spatial processing. Both studies employed a between-subjects design to isolate the influence of PVTO technology from other variables, ensuring a focused analysis of its effects on consumer behavior.

The findings indicated that the effects of PVTO are stronger for consumers with lower spatial perception abilities. Ease of imagining a product was identified as a mediator in the interactive effect between PVTO and spatial perception on decision comfort, demonstrating its pivotal role in online apparel shopping.

The findings indicated that the effects of PVTO are stronger for consumers with lower spatial perception abilities. Ease of imagining a product was identified as a mediator in the relationship between PVTO and decision comfort, demonstrating its pivotal role in online apparel shopping.