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The aim of this paper is to evaluate the kind of evidence and arguments used to support Richard Lynn's increasingly influential doctrine that genetically determined differences in population IQ are the main cause of differences in regional and national levels of socio‐economic development and public health status.

The paper's approach is two‐fold. First, new data on the correlation between regional differences in educational achievement of Italian schoolchildren and regional differences in socio‐economic development are presented in order to test the validity of Lynn's report that there is a progressive North‐to‐South reduction of Italian regional IQ that is highly correlated with a corresponding North‐to‐South reduction in the level of socio‐economic development. Second, a thorough and systematic review of the content of Lynn's article is carried out in order to assess the validity of the data, methods, and arguments normally used to support his socio‐economic doctrine.

Lynn's study uses regional differences in the performance of Italian secondary school children on Organisation for Economic Co‐operation and Development tests of educational achievement to assess regional IQ differences. However, data on Italian regional differences in educational achievement obtained in a much larger INVALSI study of 2,089,829 Italian schoolchildren provide unequivocal evidence that Lynn's educational achievement measure is not a valid index of IQ differences. More generally, the lengthy literature review in Lynn's article reveals uncritical acceptance of reported correlations between any putative index of IQ and socio‐economic variables. Any measure of cognitive performance that is correlated with IQ is considered a measure of IQ, even if there is only a weak correlation. All correlations between such measures and socio‐economic or public health variables are viewed as evidence of direct causal relationships. In all cases, causality is assumed to be in the direction that supports Lynn's doctrine when it would be equally valid to argue that socio‐economic and public health differences cause differences in the performance of IQ tests. In addition to these fundamental logical and statistical errors the present report records numerous other data processing, methodological, and conceptual errors.

The value of the present article is that it demonstrates the flawed manner in which data are interpreted and analysed in order to support Lynn's thesis. Left unchallenged, this pernicious doctrine would promote a socially damaging conception of critically important socio‐economic and public health issues that would discourage the adoption of national policies designed to increase levels of socio‐economic development and improve public health status.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

The aim of this paper is to show that online learning behaviors are dictated by both personal characteristics and regional differences.

Data were collected from 16,133 users in 25 regions of Taiwan. The paper examined usage behaviors by looking at 11 items of categorical variables about online learning. This study implemented a multi‐level latent class model to investigate online learning behavior patterns that exhibit regional differences.

The results showed that online learning patterns do exhibit regional differences, as the regional segments are dictated by the individual segments of different use patterns. For instance, the urban area segment comprised a higher proportion of members who are good at using the internet. The rural area segment made up a higher proportion of members who occasionally use the internet. Interestingly, rural users went online more often than urban users when in search of e‐learning or entertainment. On the other hand, the individual segments are dictated by users' personal characteristics. For instance, younger people are good at employing online learning and entertainment services. Moreover, those who use many types of online applications pay less respect to intellectual property rights than those who only use a few types of applications.

By using a massive amount of survey data to show regional differences in online learning behavior patterns, the findings herein will help internet service providers form an applicable guideline for developing service strategies of higher service satisfaction between products and users' needs.

This paper aims to investigate the patterns of and reasons for regional differences in entrepreneurship among Chinese provinces (excluding Hong Kong and Taiwan).

The paper employs a linear regression model to examine determinants of regional entrepreneurship in China.

Evidence suggests that provincial differences in entrepreneurship were directly related to local business growth, but not to factors such as level of local business development, urbanisation rate, level of market economy, level of salary and ratio of unemployment. The differences among economic growth in various regions contributed directly to differences in entrepreneurship.

There is a need to determine the spatial patterns of entrepreneurship by using panel data in a more sophisticated econometric model. A further investigation of regional entrepreneurship in China is planned for the near future.

Active entrepreneurship in a region can contribute to the economic growth of the region, leading to more active enterprising activities. It is therefore argued that one of the effective ways to boost entrepreneurship and small business development is to advance the economic growth of a region.

The paper adopts an industrial location perspective on determinants of business growth and its links with regional entrepreneurship.

To cope with the severe situation of the global climate, China proposed the “30 60” dual-carbon strategic goal. Based on this background, the purpose of this paper is to investigate scientifically and reasonably the interprovincial pattern of China’s power carbon emission intensity and further explore the causes of differences on this basis.

Considering the principle of “shared but differentiated responsibilities,” this study measures the carbon emissions within the power industry from 1997 to 2019 scientifically, via the panel data of 30 provinces in China. The power carbon emission intensity is chosen as the indicator. Using the Dagum Gini coefficient to explore regional differences and their causes.

The results of this paper show that, first, China’s carbon emission intensity from the power industry overall is significantly different. From the perspective of geospatial distribution, the three regions have unbalanced characteristics. Second, according to the decomposition results of the Gini coefficient, the overall difference in power carbon emission intensity is generally expanding. The geospatial and economic development levels are examined separately. The gaps between the eastern and economically developed regions are the smallest, and the regional differences are the source of the overall disparity.

Further exploring the causes of differences on this basis is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies. This study provides direction for analyzing the green and low carbon development of China’s power industry.

As an economic indicator of green and low-carbon development, CO₂ intensity of power industry can directly reflect the dependence of economic growth on the high emission of electricity and energy. and further exploring the causes of differences on this basis is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies.

For a long time, with the rapid economic development, resulting in the unresolved contradiction between low energy efficiency and high carbon emissions. To this end, scientifically and reasonably investigating the interprovincial pattern of China’s power carbon emission intensity, and further exploring the causes of differences on this basis, is crucial for relevant departments to formulate differentiated energy conservation and emission reduction policies.

Third, considering the influence of spatial factors on the convergence of power carbon emission intensity, a variety of different spatial weight matrices are selected. Based on the β-convergence theory from both absolute and conditional perspectives, we dig deeper into the spatial convergence of electricity carbon emission intensity across the country and the three regions.

The purpose of this paper is to investigate regional impact of macroeconomic and regional policy impulses, using our newly developed multi-regional computable general equilibrium (CGE) model for three, structurally distinctive Polish macro-regions.

In this study, we build an interregional social accounting matrix for Poland and use it to develop a small scale, three-region CGE model, reflecting the size of regional economies and cross-regional differences in industrial structures, while also explicitly accounting for the dynamics of main economic relationships across regions, such as interregional flows in commodities, labor and capital. The model is subsequently use to simulate regional effects of various policy impulses.

We demonstrate important cross-regional differences in the transmission mechanism of macro-level policies, which either affect regional output and its individual components (as in the case of imposing shocks to VAT or PIT rates) or are limited to the components, while preserving a rather uniform impact on output (as in the case of imposing shocks to wages). Furthermore, we contribute to the regional policy equity-efficiency trade-off debate, by illustrating quantitatively how, due to structural differences, spatially targeted expenditure measures might promote either regional convergence or aggregate output growth at the country-level.

Prior to our study, regional CGE models have not been used to simulate spatial distribution of aggregate shocks in Poland or in any other CEE country. Another originality of our study lies in comprehensive evaluation of various policy impulses, from the perspective of their impact on the respective region, spillovers to the other regions and its overall, country-level effect.

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 paper aims to explore two fundamental aspects of branding in emerging markets. First, are there significant differences in product evaluation behaviour between regions within a large emerging market such as China? Second, how important is branding relative to other product cues in the product evaluation among consumers in emerging markets?

Data were collected from a sample of respondents in three Chinese cities (Hong Kong, Shanghai, and Chongqing). Respondents were asked to evaluate combinations of a hypothetical product (domestic air conditioning) varying in brands, prices and country of origin (COO). ANOVA, t‐tests and regression were conducted to test for significant differences in ratings brand, price and COO, perceived product quality and purchase intention.

The results show significant differences between the three regions in product evaluation processes and outcomes. In addition, the study identifies a general preference across regions for global brands over local brand competitors.

While the findings may be due to the particular Chinese locations and/or the product chosen, nevertheless, the differences identified in the product evaluation processes and outcomes point to the importance of considering the potential differences between regions in diverse emerging countries like China. In addition, the general preference for international brands suggests important implications for foreign and local manufacturers.

Managers will develop an improved awareness of the importance of brands in emerging markets and of the regional differences in diverse markets such as China.

By focussing on regional differences within diverse emerging markets (rather than treating such markets as homogeneous), this study extends understanding of the complexities facing international and domestic marketers.