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This paper examines the impact of livestock environment regulations (LERs) on the location dynamics of the livestock farming industry. Specifically, it tests whether a “pollution haven effect” (PHE) exists in the Chinese livestock industry.

The authors manually collected LERs data based on the frequency of livestock-related vocabulary in government work reports from 279 prefecture-level cities from 2010 to 2017. Using China's implementation of LERs since 2014 as a natural experiment, the authors employed difference-in-difference (DID) to avoid the endogeneity problem.

LERs have led to a decline in livestock production in regulated areas. Moreover, compared with areas with more stringent LERs – southern China and developed areas, areas where LERs are less stringent – northern China and undeveloped areas, attract more livestock industry. As a result, people in northern China and undeveloped areas are exposed to higher livestock pollution.

First, most empirical studies on PHE focus on industrial firms. PHE in the livestock industry has received limited attention. This paper aims to fill this gap. Second, this paper regards LERs as an endogenous process and uses the DID method to generate unbiased results. Third, this paper introduces a novel measurement of LERs based on the frequency of livestock-related vocabulary in government work reports from each prefecture city. Fourth, this paper uses prefecture-level data to analyze the PHE of LERs, and thus obtains more reliable results.

Hong Kong has been a major entrepôt for China for decades and its intermediate role has been enhanced in recent years. With the open door policy of China, Hong Kong manufacturers have relocated extensively their low‐cost operations to the Pearl River Delta in Southern China. Under the outward processing arrangement, raw materials, components and work‐in‐progress are shipped to China for further processing and the finished products are shipped back to Hong Kong for re‐export to other countries. This mode of operation has created tremendous loads on the already congested cross‐border traffic between Hong Kong and the Pearl River Delta. In order to modernize its outdated and inadequate transportation systems, China has embarked on huge infrastructure development programmes in the Pearl River Delta and other fast developing regions. Hong Kong has also launched multi‐billion‐dollar ports and airport development projects scheduled to be completed in 1997/98. On completion of these projects, the strategic position of Hong Kong as an entrepôt of Southern China will be further enhanced, despite increasing competition from neighbouring ports and airports in the medium to long term.

This study aims to propose a refined dynamic network slacks-based measure (DNSBM) to evaluate the efficiency of China's regional green innovation system which consists of basic research, applied research and commercialization stages and explore the influencing factors of the stage efficiency.

A two-step procedure is employed. The first step proposes an improved DNSBM model with flexible settings of stages' input or output efficiency and uses second order cone programming (SOCP) to solve the non-linear problem. In the second step, least absolute shrinkage and selection operator (LASSO) and Tobit models are used to explore the influencing factors of the stage efficiency. Global Dynamic Malmquist Productivity Index (GDMPI) and Dagum Gini coefficient decomposition method are introduced for further discussion of the productivity change and regional differences.

On average, Chinese provincial green innovation efficiency should be improved by 24.11% to become efficient. The commercialization stage outperforms the stages of basic research and applied research. Comparisons between the proposed model and input-oriented, output-oriented and non-oriented DNSBM models show that the proposed model is more advanced because it allows some stages to have output-oriented model characteristics while the other stages have input-oriented model characteristics. The examination of the influencing factors reveals that the three stages of the green innovation system have quite diverse influencing factors. Further discussion reveals that Chinese green innovation productivity has increased by 39.85%, which is driven mainly by technology progress, and the increasing tendency of regional differences between northern and southern China should be paid attention to.

This study proposes an improved dynamic three-stage slacks-based measure (SBM) model that allows calculating output efficiency in some stages and input efficiency in the other stages with the application of SOCP approach. In order to capture productivity change, this study develops a GDMPI based on the DNSBM model. In practice, the efficiency of regional green innovation in China and the factors that influence each stage are examined.

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 chapter focuses on the application of segment reporting under IFRS 8 in the context of the airline industry. It analyses the airlines’ disclosures related to segment reporting considering 11 aspects of segment reporting in the regional and global context. Observations reveal that reporting of segmental disclosures in the airline industry is diverse at different levels. In this regard, the following conclusions were drawn: (1) the nature of segments reported by the airlines is diverse due to methods adopted in preparation of operating segments; (2) factors such as internal reporting system, and nature of business used to identify the airline’s reportable segments were stated by most airlines; (3) types of products and services from which each reportable segment derives its revenues were stated by all airlines; (4) proportion of total revenues represented by separately reportable segments exceeds 75% of the revenue rule of IFRS 8; (5) most segmental performance measures are non-IFRS and diverse; (6) a limited number of airlines use dual reporting currency in segment reporting; (7) most airlines reported segment assets and liabilities for each reportable segment; (8) most airlines reported between 6 and 10 income and expense items in segment reporting; (9) segmental cash flow information is reported by one airline; (10) in terms of entity-wide disclosures, most airlines reported their revenue from major products and services in the revenue disclosures, most airlines reported their revenues on a geographical basis but few airlines reported their non-current assets on a geographical basis; and (11) more than half of the airlines did not declare the identity of the Chief Operating Decision Maker.

In this chapter, we will review the history, deregulation, policy reforms, and airline consolidations and mergers of the Chinese airline industry. The measurement of airline competition in China’s domestic market will also be discussed. Although air deregulation is still ongoing, the Chinese airline industry has become a market-driven business subject to some mild regulations. Then, we will review the impressive development of the high-speed rail (HSR) network in China and its effects on the domestic civil aviation market. In general, previous studies have found that the introduction of HSR services has a significant negative impact on airfare and air travel demand in China. The rapidly expanding network of HSR has important policy implications for Chinese airlines.