Greater Bay Area Research Articles

Quantifying high-resolution carbon emissions driven by land use change in the Guangdong-Hong Kong-Macao Greater Bay Area

Accurate research on carbon emission spatial distribution is vital for achieving carbon neutrality. Previous studies suffered from scale effects, demanding enhanced resolution. This study collected and computed land use carbon emission data for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). It also introduced a novel method to downscale this data into 30 m raster format using night light and NDVI data. The study showed a consistent annual rise in GBA land use carbon emissions, accompanied by increasing disparities. At the city level, emissions in the highest-ranking cities were 58 times higher than those in the lowest-ranking ones. Impervious land carbon emissions held over 90% sway over total carbon emissions, making them the primary driver of land use-related carbon emissions. Remarkably, high-emission zones, such as coastal cities Guangzhou, Foshan, Dongguan, and Hong Kong, expanded outward, forming multi-tiered, high-density carbon areas, giving rise to an “∩” shape pattern. Carbon emission change rates from cropland were modest, characterized by a pattern of fluctuation. Moreover, spatial autocorrelation and K-means cluster analyses uncovered a noticeable spatial correlation among urban land use carbon emissions in the GBA. Consequently, a compelling case exists for enhancing inter-city cooperation to collectively pursue regional emission reduction objectives.

Hotel Performance in the Guangdong-Hong Kong-Macau Greater Bay Area: A Non-Homogeneous Perspective

Improving upon previous studies on hotel performance evaluation in terms of efficiency, which usually treat different hotels as homogeneous in their product provision, this study examines the performance of 53 hotels in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) during 2015 to 2019, by employing data envelopment analysis with a non-homogeneous decision making units (DMUs) model. The results show that the hotels in GBA were inefficient, and those with high product diversification are generally closer to achieving optimal efficiency levels, particularly those providing rooms, food and beverage, meeting services, and spa services, while those providing only rooms had the worst performance. Among the GBA cities included in this study, the non-homogeneous efficiency scores of the hotels in Guangzhou outperformed those of hotels in the other cities, and the overall hotel efficiency score of the core cities was better than that of the key node cities.

Origins of formaldehyde in a mountainous background atmosphere of southern China

Formaldehyde (HCHO) is one of the key indicators of severe photochemical pollution and strong atmospheric oxidation capacity in southern China. However, current information on the origins of regional HCHO and the impacts of polluted air masses remains scarce and unclear. In this study, an intensive observation of HCHO was conducted at a mountainous background site in southern China during typical photochemical pollution episodes. The concentrations of HCHO reached up to 6.14 ppbv and averaged at 2.68 ± 1.11 ppbv. Source appointment using a photochemical age-based parameterization method revealed significant contributions of secondary formation (50 %) and biomass burning (42 %). Meanwhile, under the influence of the East Asian Winter Monsoon, polluted air masses from central and western China can significantly increase the regional HCHO levels. The simulation results adopting the Rapid Adaptive Optimization Model for Atmospheric Chemistry model further demonstrated that the intrusion of active anthropogenic pollutants (e.g., small-molecule alkenes) can accelerate the net production rate of HCHO, particularly through BVOC-oxidation pathways. This study suggests a potential enhanced mechanism of HCHO production resulting from anthropogenic-biogenic interactions. It highlights that polluted air masses carrying abundant HCHO from upwind areas may facilitate severe photochemical pollution in the Greater Bay Area.

China’s Opening to the World: Models, Stages, and Directions

The article includes four sections: the historical stages of China’s opening-up, the developmental patterns of China’s opening-up, the open policy of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), and the bilateral opening-up developments between China and Russia. Starting with elaboration of the primary processes of China’s opening-up since the era of reform and opening-up, summarizing the distinct historical stages of China’s opening-up and the main features of each developmental phase. Subsequently, it analyzes the characteristics of China’s external development in spatial patterns, and selects two typical cases of China’s external development, namely Hainan Free Trade Port and Chongqing, for further analysis. Furthermore, it meticulously reviews the opening initiatives in key sectors of the GBA’s development and its contributions to China’s high-level external openness. Finally, the article briefly introduces the main measures and outcomes of enhancing bilateral openness between China and Russia under the current international circumstances.

Integrating policy quantification analysis into ecological security pattern construction: A case study of Guangdong–Hong Kong–Macao Greater Bay Area

The construction of an ecological security pattern (ESP) is an important undertaking in ensuring the stability of the ecosystem and the long-term growth of humanity. Existing research, However, existing research often overlooks the quantification of policy implications in ESP development. The objective of this paper was to bridge this gap by integrating policy quantification analysis (PQA) with nature, society and into ESP construction and providing targeted ecological management recommendations. The policy texts were quantified into reusable research data, which served as a foundation for the selection of indicators and the optimization of ecological security patterns, by using machine learning techniques. The methodology “Patch-matrix-corridor” was used to create a spatially correlated ecological security pattern. Through factor analysis and Random Forest (RF), the impact of each indicator on ecological security was thoroughly examined, offering substantial support for policy development and ESP construction planning. The Guangdong-Hong Kong-Macao Greater Bay Area(GBA) was selected as the study area, the study found that: (1) The proposed framework PQA based-ESP could provide a useful eco-management tools. (2) Policy adaptability had a substantial impact on environmental security in the GBA, but the ecosystem service index has the highest impact. (3) Applying the framework, we identified a total of 1,993 km2 of ecological sources, 23 key ecological corridors, 58 general ecological corridors, and 31 ecological nodes. An improved ESP, characterized as “one circle, two bays, three rivers, multiple areas, corridors, and nodes,” was constructed in the GBA. (4) Given the multi-scale analysis, tailored ecological management policy recommendations were proposed for each city in the GBA. The study's findings offer actionable solutions for the international community facing growing ecological challenges.

Resource acquisition strategies of joint‐venture universities in China: Two cases in the Greater Bay Area

AbstractAs cross‐border education continues to evolve, a comprehensive understanding of the latest trends requires an awareness of the behaviours of partner universities and host governments. This case study examines two joint‐venture universities in China and compares their institutional approaches to resource acquisition. It compares their strategies in four dimensions: initial launch, choice of name, capacity building, and strategy in leveraging resources from the local government. The divergent strategies show that both universities use their particular advantages to obtain different resources to sustain their development. This study presents a portrait of a dynamic organisational environment for cross‐border in China. While the government plays a key role in the establishment of the universities, their resource acquisition effectiveness depends on how successfully they integrate their agendas with local needs.

Cross‐border university choice in China's Greater Bay Area

AbstractThis study explored Chinese students' motivations for selecting a cross‐border university in China's Guangdong‐Hong Kong‐Macau Greater Bay Area (GBA) and how they perceive their undergraduate experiences. The GBA was developed as an international economic cluster in China. Despite the vitality of the GBA's international education sector, few studies have focused on individual students' perspectives on cross‐border higher education choices and experiences. We interviewed twenty students and two academics in charge of university admissions about their opinions and reflections concerning a GBA cross‐border university. Students' university choices were linked to different admission profiles, parental influences, institutional features and interactions between students and the institutions. Our study has significant implications for leaders and policymakers in higher education seeking to attract talented university students, improve enrolment and promote students' learning experiences in cross‐border higher education institutions.

Research on Sustainable Urban–Rural Integration Development: Measuring Levels, Influencing Factors, and Exploring Driving Mechanisms—Taking Eight Cities in the Greater Bay Area as Examples

Research on Sustainable Urban–Rural Integration Development: Measuring Levels, Influencing Factors, and Exploring Driving Mechanisms—Taking Eight Cities in the Greater Bay Area as Examples

Spatial network structure and influencing factors of carbon emission intensity in Guangdong-Hong Kong-Macao greater bay area

Introduction: In response to China’s ambitious dual-carbon goals, this study investigates the spatial correlation and influencing factors of carbon emission intensity within the Guangdong-Hong Kong-Macao Great Bay Area (GBA), a region pivotal for the nation’s energy conservation and emission reduction efforts. Through a comprehensive analysis encompassing the period from 2000 to 2020, this research aims to delineate the spatial dynamics of carbon emissions and identify actionable insights for regional low-carbon development.Methods: Utilizing an integrated methodology comprising spatial autocorrelation analysis, Social Network Analysis (SNA), and the Quadratic Assignment Procedure (QAP), the study analyzes carbon emission data alongside socio-economic variables. These methodologies allow for a nuanced exploration of the spatial correlation structure and the determination of factors influencing carbon emission intensity across the GBA.Results: Findings reveal a cyclical fluctuation in the spatial network of carbon emissions from 2000 to 2020, characterized by varying degrees of cohesion among cities, indicating significant opportunities for spatial optimization. A “core-periphery” pattern emerges, with economically robust cities such as Hong Kong and Macao at the core, and less developed cities like Huizhou and Jiangmen on the periphery. Cities like Guangzhou and Shenzhen play crucial mediator roles. The QAP analysis further identifies six major influencing factors: geographic spatial proximity, economic development level, urbanization rate, industrial configuration, level of technological innovation, and environmental protection efforts, with the latter four having a markedly positive impact on spatial relevance.Discussion: The study’s insights underscore the importance of understanding the spatial dynamics of carbon emissions and the role of socioeconomic factors in shaping these patterns. For policymakers and stakeholders in the GBA, these findings highlight the necessity of targeted intervention strategies that consider both the unique position of cities within the spatial network and the broader socio-economic context. This approach can significantly contribute to achieving China’s dual-carbon objectives, promoting energy conservation, and facilitating the transition to a low-carbon economy.

Mapping Annual Tidal Flat Loss and Gain in the Micro-Tidal Area Integrating Dual Full-Time Series Spectral Indices

Tracking long-term tidal flat dynamics is crucial for coastal restoration decision making. Accurately capturing the loss and gain of tidal flats due to human-induced disturbances is challenging in the micro-tidal areas. In this study, we developed an automated method for mapping the annual tidal flat changes in the micro-tidal areas under intense human activities, by integrating spectral harmonization, time series segmentation from dual spectral indices, and the tide-independent hierarchical classification strategy. Our method has two key novelties. First, we adopt flexible temporal segments for each pixel based on the dual full-time series spectral indices, instead of solely using a fixed period window, to help obtain more reliable inundation frequency features. Second, a tide-independent hierarchical classification strategy based on the inundation features and the Otsu algorithm capture the tidal flat changes well. Our method performed well in Guangdong, Hong Kong, and Macao (GHKM), a typical area with micro-tidal range and intense human activities, with overall accuracies of 89% and 92% for conversion types and turning years, respectively. The tidal flats in GHKM decreased by 24% from 1986 to 2021, resulting from the loss of 504.45 km2, partially offset by an accretion of 179.88 km2. Further, 70.9% of the total loss was in the Great Bay Area, concentrated in 1991–1998 and 2001–2016. The historical trajectories of tidal flat loss were driven by various policies implemented by the national, provincial, and local governments. Our method is promising for extension to other micro-tidal areas to provide more scientific support for coastal resource management and restoration.

Climate risk assessment and adaption ability in China's coastal urban agglomerations - A case study of Guangdong-Hong Kong-Macao greater bay area

As climate change intensifies, extreme weather events, especially the coastal flooding is becoming increasingly severe. Carbon emissions exacerbate climate change, leading to increased frequency and intensity of extreme precipitation, which may result in flooding. This study focuses on the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a coastal city cluster in China, and adopts the scenario analysis approach to evaluate flood risks in the different carbon mitigation scenario from the perspectives of dangerousness, and adaption ability. The result shows that the Huizhou in the east of the GBA and the Zhaoqing in the northwest have the highest level of flood disaster risk. However, the central region of the GBA (Guangzhou, Dongguan, Zhongshan, and Foshan) is very vulnerable to disaster-inducing environments and hazard-affected bodies, which means that the flooding risk and the impact of such risk in the GBA display regional differentiation characteristics and the spatial patterns of them are different. According to the carbon neutrality scenario, the flood risk in the GBA peaks in 2030, and decreases during 2030–2090. In contrast, under the uneven development and high carbon pathways, the risk peaks in 2060, and the overall risk by 2090 is roughly the same as that in 2060. In addition, the regions with the highest flood disaster risk are Guangzhou, Foshan, Dongguan and Zhongshan along the Pearl River estuary. Overall, it shows that areas with higher levels of urbanization and more developed economies will face higher flooding risks. The “dangerousness-adaption ability” structure can reflect the spatial distribution pattern of flood disaster risks, identify the priority areas for flood prevention and control, and is conducive to risk management. At the same time, the research results show that ecological protection have a positive effect on reducing flood risk. In addition, corresponding policy recommendations for pre-disaster, mid-disaster and post-disaster have been proposed, providing references for flood risk management in the GBA.

Uncovering the role of urban green infrastructure in carbon neutrality: A novel pathway from the urban green infrastructure and cooling power saving

Cities are crucial in carbon reduction and carbon neutrality. However, the contribution of urban green infrastructure (UGI) to achieve these goals has been underestimated. Here, taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as an example, we develop a methodology incorporating fine-resolution UGI mappings and use the results from 2017 to 2022 to elucidate UGI patterns, trends, and carbon reduction capacity. The results revealed that: 1) Urbanization area increased by scarifying UGI, and the carbon sequestration capacity experienced a decrease and fixed 1.4% carbon emissions in GBA. 2) Based on the climate regulation from UGI, cities in GBA mitigated 29.5% of GBA's carbon emissions. The total carbon reduction from UGI was 193.6 million tons in 2022. 3) By synthesizing global field measurement studies with meta-analysis, we found that the rate of UGI increased by 1%, and the air temperature decreased by 0.01 °C. 4) With consideration of climate changes, we identified that increasing the coverage of UGI is more effective in strengthening the carbon emission reduction capacity than improving UGI quality. This study broadens the capacity of UGI in carbon neutrality, can effectively mitigate urban carbon reduction stress, and provides a novel perspective for urban carbon neutrality in China and elsewhere.

Mitigating flood impacts on road infrastructure and transportation by using multiple information sources

The transportation disruption caused by flood events is occurring more frequently and intensively due to climate change and rapid urbanization. Understanding the deterioration of road infrastructure and transportation caused by surface water floods is crucial to help city authorities alleviate flood consequences. This study aims to provide a framework to mitigate surface water flood damages in road transportation systems, using the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as a case study. An integrated framework linking news media analytics and vulnerability assessment is used to assess floods' effect and severity on road infrastructure and transportation. This study first examined historical news media activities toward flood-related transportation damage. Then, the study explored the potential impacts of surface water floods on road infrastructure and transportation via vulnerability assessment and news media analysis, respectively. The findings from this research offer valuable insights for city authorities to enhance flood mitigation strategies in road transportation systems.

Efficiency of green and low-carbon coordinated development for mega urban agglomerations: an empirical study

As a critical engine for national economic growth, mega urban agglomerations have significant scale effects and economic and environmental spillover effects. This paper aims to study the green and low-carbon coordinated development of mega urban agglomerations to evaluate the country’s level of ecological civilization and its green and low-carbon development. The traditional research on green and low-carbon urban development tends to homogenize the redistribution theme, leading to significant errors in spatial allocation. This results in a lower accuracy of spatial distribution calculations for green development. Additionally, the research is constrained by data precision and methodology, making it challenging to measure the spatial differences in green and low-carbon development within urban clusters at the block level. This limitation hinders the ability to conduct detailed studies on the efficiency variations of green and low-carbon development in urban clusters. To achieve this aim, the study adopts the DPSR framework of the economic, resource, social, and ecological environment complex system and focuses on the Guangdong-Hong Kong-Macao Greater Bay Area in China. The study uses the entropy method, Gini coefficient method, and non-expected output super-efficiency SBM model to analyze the spatial effects and development efficiency of green and low-carbon development in this region from 2006 to 2020. The study results indicate that: (1) the overall level of green and low-carbon development in the Greater Bay Area is on the rise, with Shenzhen, Guangzhou, Foshan, and Zhuhai showing more stable development than other cities. Foreign direct investment and fixed asset investment in science and technology have significantly promoted green and low-carbon development. (2) The spatial differences in the region’s level of green and low-carbon development have narrowed trends, mainly due to differences between regions. However, well-developed cities such as Guangzhou and Shenzhen have taken the initiative to lead the development of other cities, fully leveraging their advantages in science and technology, geographical location, and other resources to promote the improvement of the external orientation of other cities. (3) The overall development efficiency of green and low-carbon in the Greater Bay Area is on the rise, with Guangzhou region showing overall stability, and Shenzhen region and Zhuhai region experiencing multiple ups and downs in their development. The three sub-regions show significant differences, but the balance and coordination of development have significantly improved. Finally, this study provides theoretical support for the future green and low-carbon development of urban clusters. It is advantageous for integrating the mainstream policy analysis framework of environmental economics with the complex adaptive systems of urban clusters. The research expands the boundaries of existing theoretical studies and offers new methodological approaches for interdisciplinary research. The study achieves a balance between the opportunity effects of green and low-carbon development and environmental policy constraints in super large urban clusters, effectively enhancing resource utilization efficiency in these clusters.

SEA for better climate adaptation in the face of the flood risk: Multi-scenario, strategic forecasting, nature-based solutions

Numerous scholars have warned that many cities in the Greater Bay Area (GBA) are threatened by severe flood risk, which is often underestimated. Considering this, we provide a scenario-based Strategic Environmental Assessment (SEA) approach to analyse the roles of adaptation strategies on the environment in response to climate change and flooding risk. Three strategies are proposed including a non-Nature-based Solutions strategy (non-NbS), and two Nature-based Solutions strategies (NbS 1.0 and NbS 2.0). The non-NbS strategy refers to the way of promoting urban development yet no additional environmental concerns. The NbS 1.0 strategy focuses on ensuring arable lands for food security, and the NbS 2.0 strategy acquires further regulations on ecology protection.The analysis consists of two steps. First, this paper simulates the land use scenarios in 2030 and 2050, respectively, following non-NbS and NbS (1.0 & 2.0) strategies. This process is developed based on a patch-generating land use simulation (PLUS) model, which allows users to explore various future land use scenarios on account of different spatial development strategies, environmental conditions, and socio-economic trends. Second, the study overlays the land use scenarios with potential sea flooding scopes to reveal how different landscapes (e.g., forests and wetlands) are affected by carbon emissions in RCP 2.6 and RCP 8.5. Further research is suggested to incorporate the 2020 GDP data to refine the findings of this study and consider the impacts of dykes on flood-prone area mapping.The analysis finds that the NbS (1.0 & 2.0) strategies play an active role in decreasing the future flood risk of built-up areas in the GBA regionally, especially under the high-emission RCP 8.5 projection. However, their impacts vary between cities. (1) The NbS 2.0 strategy is effective in reducing the risk of built-up areas in Shenzhen, Hong Kong, and Macao, while the effectiveness of the NbS 1.0 strategy is not apparent. (2) The NbS 1.0 and 2.0 strategies are both effective in Dongguan, Guangzhou, Huizhou, Jiangmen, Zhuhai, Zhaoqing, and Zhongshan in reducing the flood risk of built-up areas. In addition, the NbS 2.0 strategy is more productive than the NbS 1.0 strategy either in 2030 or 2050. (3) The NbS 1.0 and 2.0 strategies generate subtle different effects in Foshan in 2030 and 2050. The NbS 2.0 strategy is more productive in 2050, while less productive in 2030. This study provides a comprehensive insight into the distributed flood risk following the non-NbS or NbS strategies in the context of climate change, which is useful to policymakers and urban planners.

Heat stress resilience assessment of urban form from physical space dimension: A case study of Guangdong-Hong Kong-Macao Greater Bay Area

Improving urban resilience is crucial to counteract rising high-temperature disasters. This study constructed a framework for a process-based heat stress resilience (HSR_phy) assessment from the urban physical space dimension. Based on the universal thermal climate index (UTCI), the Weather Research and Forecasting (WRF) model, and the Local Climate Zone (LCZ) map generated through WUDAPT, an HSR_phy evaluation method with high spatiotemporal accuracy is proposed. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was studied for heat stress resilience patterns in July 2021. Boosted regression tree (BRT) models analyzed LCZ landscape patterns' impacts on HSR_phy. The results indicated that HSR_phy during the daytime was significantly lower than that at night. The HSR_phy of GBA showed the characteristics of low inland and high periphery. Significant differences in HSR_phy existed among most LCZs. LCZA, LCZC, and LCZ9 showed strong HSR_phy, whereas LCZ2, LCZ8, and LCZ7 were opposite. At the 1500 m scale, the Percentage of Landscape (PLAND), Landscape Shape Index (LSI), and Shannon's Diversity Index (SHDI) of LCZ4, LCZ5, and LCZ6 were the key factors affecting HSR_phy. Our research demonstrates how to quantify heat stress resilience and impact factors of urban physical spaces to provide a basis for developing climate-sensitive urban design strategies.

Optimizing flood disaster management: unraveling the role of social organizations in China’s GBA through social network analysis

This study delves into the efficiency and structure of the social organization network involved in flood disaster management in China’s Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Leveraging the global knowledge graph, we analyzed social media data and news reports to identify the pivotal roles and interactions of various social organization types in flood disaster governance. The empirical findings underscore the central role of national public social organizations, evidenced by their high frequency of news coverage and mentions. Meanwhile, International Social Organizations and Local Public Social Organizations exhibit growing influence and participation. As China shifts toward a comprehensive disaster reduction strategy, the study observes increased diversity and decentralization among these organizations, with non-governmental organizations and volunteer groups playing vital roles in resource mobilization, information dissemination, and disaster coordination. Network analysis unveils evolving interaction patterns and co-occurrence frequencies among social organizations, reflecting the evolving roles of different organization types in disaster relief. This research aims to provide actionable insights to enhance the effectiveness of social organizations in disaster management, contributing to the establishment of a more resilient and efficient disaster management framework in the GBA.

Regulating FinTech in the Greater Bay Area: RegTech and the Role of Regulatory Sandboxes

Abstract In parallel to the growing impacts of various new technologies such as artificial intelligence on societies, the environment, ecosystems, and human lives, financial technologies (FinTech) are playing an increasingly important role in the organization of financial systems and economies worldwide. To verify this claim, the present article takes a closer look at the role of the regulation of FinTech in the context of the regional cooperation in the Greater Bay Area (GBA). The GBA currently comprises the two Special Administrative Regions of Hong Kong and Macao and the nine municipalities in the Guangdong Province of the People’s Republic of China (PRC), which together form one of the world’s most dynamic and innovative regions. Based on each of the GBA members’ unique legal systems, united under the principle of ‘one country, two systems’, the GBA can be regarded as a fertile testing ground, ‘legal laboratory’, or ‘regulatory sandbox’ for the regulation of FinTech worldwide. For this purpose, the article first introduces the existing legal framework, fleshing out the contours of the GBA. Second, it briefly outlines the current scope of FinTech and provides examples of its use in the GBA. The main focus of the article then shifts from FinTech to the regulatory challenges posed by FinTech in the GBA, and the article discusses how these may best be addressed by, for instance, relying on regulatory technology (RegTech) and so-called ‘regulatory sandboxes’. The article concludes by arguing for both an early and a comprehensive discussion about the expected benefits and the potential risks of the rapid implementation and use of FinTech in the GBA and the world at large.

Enhancing Legal Convergence in the GBA through Harmonization of the Digital Dispute Resolution Legal Framework

Abstract This article examines theories of legal convergence and the practice of rule harmonization for online dispute resolution (ODR) in the Greater Bay Area (GBA). The ODR platforms in the GBA employ collaborative mechanisms, institutional alliances, international standards, and multi-jurisdiction remote hearings to promote the convergence of ODR rules. However, to date, the efforts made to promote ODR rule harmonization have not resolved the fundamental issue of a lack of uniform ODR legislation within the GBA. It is posited here that an independent model of legal convergence would be more applicable in the GBA context. The article calls for the GBA Legal Department Joint Conferences to provide general ODR standards and principles, with specific laws and regulations then formulated in the respective jurisdictions. Public and private ODR providers are found to play distinct roles in legal convergence, and specialized procedural rules should be formulated to ensure due process and cybersecurity in remote hearings.

Competitiveness without Competition: The Role of Antitrust Law in the Development of the Guangdong-Hong Kong-Macao Greater Bay Area

Abstract The economic integration of the constituent jurisdictions in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) involves an enhanced market connectivity and an asymmetric opening up for trade in goods and services. The development of the GBA presents a unique case study for understanding the role of the competition law and policy in the context of regional economic integration. In contrast to the regulatory experiences of other economic integration projects around the world, such as, for example, the European Union, where harmonization of competition laws and their coordinated enforcement became the norm, the GBA explicitly abandons this approach. The regulatory framework for the GBA development does not envisage common competition rules or policies. Equally, it does not seek to harmonize the existing divergences in competition laws. This article analyses the specifics of the GBA economic integration in the context of the ‘one country, two systems’ principle and explains the reasons behind the distinct role of the competition law and policy in this process.