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Scientific and technological innovation and ecological progress are important forces for China's high-quality development. Nevertheless, the current body of research seldom explores the mutual dependence and evolutionary patterns of the two regional systems when considering both historical and future perspectives. This paper aims to enhance the current theoretical research framework by focusing on the coastal region of China. It analyzes and predicts the co-evolution and space–time distribution process of two systems by constructing a coupled model and a gray prediction model. The results show the following: (1) the coupling and coordinated development level of the two coastal systems has basically reached the stage of good coupling and coordinated development, and the level has increased, but the gap has gradually increased, and Jiangsu and Guangdong have reached the leading level; (2) the spatial distribution in coastal areas is uneven, showing a convex spatial pattern of "high in the middle and low at both ends"; (3) during the forecast period, the overall coupling and coordination level of the two systems will continue to improve, but individual cities still cannot jump out of the development state of slow development processes. With the aim of fostering the harmonious growth of both systems at both regional and national levels, this paper proposes practical recommendations concerning the establishment of a sustainable interaction mechanism, the evolution of the industrial structure towards ecological sustainability, and the economic contribution to scientific and technological innovation. Furthermore, this article serves as a valuable reference for advancing the sustainable development of other nations. [ABSTRACT FROM AUTHOR]

This paper investigates the economic development within the Guangdong-Hong Kong-Macao Greater Bay Area from two perspectives--spatial pattern and influencing factors--to promote coordinated development across the area. This paper employs Moran's I test and local Getis-Ord G statistic from spatial statistics. Furthermore, it constructs a hierarchical spatial econometric model to facilitate empirical investigation. It is found that the overall economic development of the Guangdong-Hong Kong-Macao Greater Bay Area exhibits a "mountain-shaped" spatial pattern of the high-level homogeneous regions with "high-high correlation" and the low-level homogeneous regions with "low-low correlation." The internal difference in economic density is moderate, with an obvious trend of decrease year by year. Economic density shows a significant spatial positive correlation, with the expansion of the scope of areas exhibiting "high-high correlation." The differences in economic density between hotspots and sub-hotspots have decreased, but the economic density of cold spots has failed to keep up with the development of other regions. The difference in factor input density among the influencing factors explains most of the differences in economic density among different regions. The results from the R&D capital investment coefficient indicate that in recent years, the effect of investments in urban scientific and technological innovation factors has been more extensive and uniform among the regions under its jurisdiction, but the spatial spillover effect of innovation factors at both layers is not significantly positive. Apart from the city's location within the Greater Bay Area, the relative location of the jurisdictions within the city equally influences the economic development configuration of the Greater Bay Area. Although economic density in regions adjacent to cities outside the Greater Bay Area is notably lower than in other regions, their growth rate and production efficiency remain on par with other regions. T-test and model results underscore the rapid development of the areas encircling the bay. The coefficient of location dummy variables in areas adjacent to cities in the Greater Bay Area varies among cities. At a particular factor input density, some cities have higher output efficiency in areas contiguous to cities in the Greater Bay Area. This study uniquely adopts low-level city jurisdictions and high-level cities to shape a two-tiered hierarchical dataset with nested geographic units. This innovative approach fully leverages insights from distinct layers, delving into spatial interdependence and interplay across layers. This paper aims to explore the spatial pattern and influencing factors steering economic development in the Guangdong-Hong Kong-Macao Greater Bay Area. In doing so, it aims to identify problems and present pertinent policy recommendations. [ABSTRACT FROM AUTHOR]

As development progresses over time and changes in the environment take place, carbon finance development has become a very interesting research topic for many scholars worldwide. This paper proposes a hybrid MCDM method that combines the distance solutions of the TOPSIS and VIKOR methods. The contribution of this paper combines TOPSIS and VIKOR, incorporating AISM models to obtain the development ranking of Chinese carbon finance pilot cities as related to the Chinese carbon finance development pilot provinces and cities. The conclusion notes that Guangdong and Beijing are the most preferred investment locations for carbon investors. In addition, technological innovation, financial sector development, and an active ETS market can effectively drive the level of local carbon finance. Additionally, the MCDM methodology in this paper provides new ideas in environmental and economic development assessment. [ABSTRACT FROM AUTHOR]

Carbon emission trading scheme (ETS) policy is a quota-based market-motivated environmental regulation policy that by transforming environmental responsibility of enterprises into self-consciousness behavior induces green innovation behavior in enterprises and influences the level of regional green innovation. Based on panel data on green patents in 30 Chinese provinces from 2010 to 2019, the paper uses six Chinese pilot provinces for ETS as the treatment group to investigate the induced effects of Chinese ETS policy on the quantity and quality of green technology innovation using difference in difference model and analyzes the effects of Chinese ETS policy on green technology innovation in different pilot regions using a synthetic control method. The findings indicate that (1) compared with non-pilot areas, the carbon emission trading policies in pilot areas can induce green technology innovation activities. (2) In all pilot regions, ETS policies significantly promoted the quantity and quality of green technology innovation, but the quantity promotion effect was significantly better than the quality promotion effect, and the low-quality promotion effect was better than the high-quality promotion effect. (3) In terms of individual pilot region, ETS policies in Guangdong, Hubei and Tianjin significantly promoted the quantity of green technology innovation and low-quality green technology innovation, but significantly inhibited or suppressed high-quality green technology innovation in a short term. This paper not only enriches the research on environmental equity trading policies and green technology innovation theoretically, but also provides empirical evidence for the effectiveness of carbon emission trading schemes pilots program in China. [ABSTRACT FROM AUTHOR]

Innovation platforms can be useful for promoting the diversification of regional industrial paths. Until recently, the literature had depicted such platforms primarily as a tool for enabling local knowledge recombination – and not for anchoring non-local knowledge. In many regions, however, 'smart specialisation strategies' for modernising and transforming industrial structures are difficult to implement without transplantation of non-local knowledge. This paper explores innovation platforms as a tool for anchoring non-local knowledge. We elaborate on recent Chinese experiences by studying diversification-oriented regional innovation policy in Guangdong province. We employ an embedded single-case study design, involving a regionally typical diversification strategy, which we substantiate by tracing platform development with two non-local actors, a university and a technology firm. The paper reveals that non-local actors can play an important role in unlocking regional industrial development potential, especially if platforms enable these actors to relate to local industry by performing desired intermediary functions. [ABSTRACT FROM AUTHOR]

Collaborative innovation can promote scientific productivity and the development of clean technology and thus has a great potential in constraining the ecological footprint. However, current studies on the impact of collaborative innovation on ecological footprint are insufficient, and results remain controversial. To better understand these impacts, this paper took Guangdong-Hong Kong-Macao Greater Bay Area of China as a case, estimated the ecological footprint at the municipal level from 2008 to 2018, measured collaborative innovation both from four dimensions and from a composite approach, then applied threshold regression models to compare the impact of collaborative innovation on the ecological footprint across different economic intervals. The findings showed that: the ecological footprint of the Greater Bay Area displayed an overall upward trend with prominent spatial heterogeneity. The impact of collaborative innovation on the ecological footprint presented a double-threshold effect when examined with different indicators. Among which, the flow of scientific personnel and capital boosted the ecological footprint, which intensified with economic development, while collaboration in technology exerted significant inhibitory effects on ecological footprint, and the influence of inter-city knowledge collaboration was limited. Overall, collaborative innovation inhibited ecological footprint when measured by a composite index. This might inspire policymakers to adopt sustainable strategies depending on the type of collaborative innovation and the economic status of the city to constrain growth of the ecological footprint, thus minimizing the pressures of human activities on the environment and moving towards a more carbon neutral society. [ABSTRACT FROM AUTHOR]

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The scientific and technological innovation ability of the economic free trade zone is crucial to the depth and breadth of its economic development. There are too many subjective factors in the evaluation of the scientific and technological innovation ability of traditional economic free trade zones. In order to objectively evaluate the scientific and technological innovation ability of the free trade zone, this paper uses the random forest weighting method and the weighted linear combination to construct the evaluation index system, designs the evaluation model of the scientific and technological innovation ability of the free trade zone, and makes a specific analysis and evaluation based on the operation data of the economic and technological innovation ability of China's four key free trade zones in 2020. The results show that the scientific and technological innovation ability of Guangdong economic free trade zone is the strongest, followed by Guangdong economic and trade zone, Shanghai economic and trade zone, Zhejiang economic and trade zone, and Tianjin economic and trade zone; Guangdong free trade zone has strong scientific and technological innovation ability. Compared with other free trade zones, Guangdong's main advantages lie in the integration and aggregation ability of the industrial chain, strong policy support, and talent attraction. The scientific and technological innovation ability forms a virtuous circle. The analysis of the model example shows that the introduction of the random forest weighting method into the scientific and technological evaluation of the free trade zone can more objectively compare and analyze the scientific and technological innovation ability of the free trade zone, which is of great significance to help the free trade zone find out the problems and shortcomings in the scientific and technological innovation ability and improve the level of scientific and technological innovation. [ABSTRACT FROM AUTHOR]

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is one of the most active innovation areas in China, but the complex institutional and cultural environment makes innovation cooperation among the cities challenging. Based on 2001–2019 data, this study analyses the spatial pattern and externalities of GBA's knowledge innovation network using a social network method and spatial econometric model. Results show that Guangzhou and Hong Kong have always been the cores of knowledge innovation in network. Shenzhen emerged as an innovation centre after 2012, and other cities have become peripheral areas in the network. Small- and medium-sized cities do not benefit from the innovative development of core cities but are trapped in their agglomeration shadow. Institutional and cultural differences are the main obstacles hindering innovation cooperation between cities. In comparison, distance has fewer limitations on innovation cooperation. The negative externality of knowledge innovation network indicates that this region should narrow the gap of spatial differences, optimise the innovation network pattern to improve the network externalities. [ABSTRACT FROM AUTHOR]

China has limited arable land area, and its output value is increased with enhanced agricultural inputs such as machinery, irrigation, fertilizers, and pesticides. However, this mode is accompanied by an increase in agricultural carbon emissions. With the aim to further examine the driving effect of scientific and technological innovation on economic growth and green agriculture, this study uses the Solow growth model coupled with the Cobb–Douglas production function and vector autoregressive models. Then, the agricultural scientific and technological innovation capacity in Guangdong Province during 2006–2020 is evaluated by using the contribution rate of agricultural scientific and technological progress (ASTP) as the assessment index. In addition, the carbon footprints of green agricultural indexes such as machinery, irrigation, fertilizers, and pesticides are measured to analyze the relationship between green agriculture and agricultural scientific and technological innovation capacity. Results demonstrate the gradual increase in the contribution rate of ASTP in Guangdong Province. During the 11th, 12th, and 13th Five-Year Plan periods, the rates were 65.09%, 65.94%, and 70.40%, respectively, indicating that the agricultural scientific and technological innovation ability constantly improved. Among the indexes of green agriculture, the carbon footprints of machinery have a significant impact on agricultural scientific and technological innovation, which is quickly transformed into machinery. Such innovation requires the driving force of science and technology itself, which have relatively significant and rapid effects. On the basis of the results, corresponding policy suggestions are proposed: increasing investments in scientific and technological innovation in the agricultural field, vigorously developing new energy-saving and emission reduction products and processes for fertilizers, and increasing the research and promotion of agricultural machinery. The proposed method provides good prospects for the development of agricultural production towards mechanization, intelligence, efficiency, and greenness. [ABSTRACT FROM AUTHOR]

The coordinated development of urban quality and technology innovation is an important element of China's technology innovation development strategy in the new era. Based on entropy TOPSIS, coupling coordination models, the gravity center and standard deviation ellipse method, the geographic probe, the GWR, and other methods, we explore the spatial variation and influencing factors of the coupling coordination relationship between urban quality and technology innovation in the Guangdong-Hong Kong-Macao Greater Bay Area from 2011 to 2020. It is found that: (1) the spatial distribution of the coupling coordination shows a characteristic of "high in the middle and low in the surroundings," and (2) the level of benign interaction in the central region is becoming more prominent. The center of gravity of coupling coordination moves toward the northeast, and the standard deviation ellipse shows a contraction trend away from the southwest. (3) Agglomeration capacity, human capital, cultural development, and infrastructure can significantly drive the improvement of the coupling coordination of urban quality and technology innovation, and the two-factor influence is significantly increased after the interaction. (4) The feedback effects of the coupling and coordination states of different cities on each factor have significant spatial differences and show the characteristics of hierarchical band distribution. [ABSTRACT FROM AUTHOR]

With the rapid development of economy, China's urbanization process is accelerated. As major urban cluster center, Guangdong-Hong Kong-Macao Greater Bay Area is regarded as one of the most representative areas with the highest openness and the strongest economic vitality. Under the background of new era, main purpose of making development strategy of the Greater Bay Area is to build a world-class city cluster with great vitality, and establish a world-class science and technology innovation center with great influence. It also lays a good foundation for strengthening the construction of the belt and road initiative in China, and improves quality of life in the cooperation zone between the mainland and Hong Kong and Macao. Under the background, the tourism industry has new challenges, and the tourism spatial structure should be more closely linked. In this paper, tourism spatial structure of 9+2 urban agglomeration in the Greater Bay Area is taken as core research objective, and tourism resource of the urban agglomeration, and development of tourism economy and perfect transportation network in each city are analyzed. According to research results, the targeted suggestions and optimization methods are obtained. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate how Chinese firms' innovation is related to their perceived incentives and pressures from the transitioning institutional environment. Design/methodology/approach: A sample of 166 manufacturing firms located in Guangdong Province (China) is analyzed using binomial and moderated multiple regression models. Findings: The results show that institutional incentives are more effective in promoting incremental innovations than radical ones, whereas institutional pressures are more pronounced in facilitating radical innovations than incremental ones. In addition, the interaction between the two divergent institutional forces is negatively related to innovation performance. Practical implications: The findings inform managers and policy makers in institutional transition environments to consider and balance the effects of institutional forces. Firms should match the institutional incentives and pressures with their own innovation objectives in terms of incremental or radical goals, and take caution to deal with the divergent institutional directions, so as to avoid the negative interaction effects. Policy makers should take a systems approach when considering the incentive-based and/or command-and-control designs of innovation policies and regulations. Originality/value: The study contributes to existing literature on institutions and innovation by disentangling incentive and pressure effects of institutions, regulation and innovation policies, as well as the combined and interaction effects intrinsic within institutional mixes. [ABSTRACT FROM AUTHOR]

With the increase of economic strength and technological advancement, financial and technical issues are becoming less and less constraining for the construction of water conservancy and hydropower projects, and the resettlement of reservoir resettlers has become the most critical factor in determining the success or failure of the construction. This study constructs a risk analysis framework for reservoir resettlers' livelihood strategy transformation from the perspective of "resilient livelihoods", characterizing their risk exposure with a comprehensive risk index and testing the effectiveness of the framework through robustness analysis. The framework was used to analyze the risk of reservoir resettlers in Guangdong Province, from which we found that the degree of risk and the type of vulnerability faced by resettlers with different livelihood strategies differed significantly, and we discussed each of them to help resettlers minimize the possible harm that they might suffer from. Thus, this framework can help reservoir resettlers to achieve sustainable development to a certain extent and also provide useful suggestions for policy makers to ensure the smooth construction of water conservancy and hydropower projects. [ABSTRACT FROM AUTHOR]

When considering the economic growth of the Greater Bay Area, digital transformation stands out as a crucial catalyst. Given its significance, it is imperative to delve into both the theoretical and empirical aspects of how digital transformation affects the region's position in the global value chain. Theoretical hypotheses are put forward regarding the impact and mechanisms of digital transformation on the global value chain position of the Greater Bay Area based on a global value chain perspective. A three-tier nested input–output table that incorporates the Greater Bay Area is constructed, and trade decomposition and global value chain position measurement models specific to the area are developed for analyzing its current state in terms of global value chain position. Empirical testing was conducted to examine how digital transformation impacts this position. Digital transformation will significantly enhance the position of the Greater Bay Area in the division of global value chains, mainly through enhancing technological innovation transformation capabilities and value added by exports from the Greater Bay Area. Digital transformation within the Greater Bay Area has had a more substantial positive impact than the digital transformation in other provinces in China and digital transformation from foreign sources. In terms of city heterogeneity, it is evident that the global value chain from Hong Kong and Macao has experienced a more significant impact from digital transformation compared to cities in the Pearl River Delta. Therefore, the Greater Bay Area should increase the use of both digital transformation and differentiated use of digital transformation. PRD cities should actively learn from Hong Kong and Macao's forms of digital construction and promote the Greater Bay Area's global value chain status. [ABSTRACT FROM AUTHOR]

Environmental regulation has obvious externality on technological innovation. How to protect the environment without exerting negative effects on technological innovation activities carried out by enterprises is an important realistic proposition in economic development. Taking the panel data of 21 cities in Guangdong Province from 2005 to 2018 as the research object, the paper empirically studies the impact of environmental regulation on technological innovation, as well as the moderating effect and threshold effect of the industrial structure upgrading on the relationship between them. The results show that there is an inverted U-shaped effect of environmental regulation on technological innovation, and a moderate intensity of environmental regulation is conducive to promoting the development of technological innovation. The industrial structure upgrading plays a significant negative moderating effect in the inverted U-shaped relationship on the whole, causing the curve of the inverted U-shaped relationship to move to the left. Furthermore, through the threshold regression model, we find that the moderating effect of industrial structure upgrading has significant nonlinear characteristics. The level of upgrading lower than the first threshold or higher than the second threshold is not conducive to the effect of environmental regulation on technological innovation. In the implementation process of environmental regulation, more attention should be paid to promoting the rationalization of industrial structure in combination with industrial policies. [ABSTRACT FROM AUTHOR]

In the context of uncertain economic environments urban agglomerations play a crucial role in economic development, reshaping industrial chains and fostering inter-city cooperation. This study employs the Global Production Network (GPN) theory to enhance our understanding of how cities integrate into regions, emphasizing the often-overlooked governmental influence in strategic coupling processes. In examining the evolution of China's smartphone industry within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) this research categorizes 19,599 smartphone companies into five distinct groups. Through analyzing their spatial distribution and geographical linkage the study identifies four strategic coupling modes based on the localization of assets, considering spatial influence and technological complexity along horizontal and vertical dimensions. Structural and institutional elements within these modes are also explored. The research uncovers unique integration patterns among nine cities in the GBA's mobile industry, revealing distinct spatial clusters rooted in technological, resource and innovation factors. Crucially, local policies play a pivotal role. Cities such as Shenzhen and Dongguan emerge as technology hubs, contrasting with Foshan and Zhongshan, which leverage resource advantages. The spatial impact, contingent on specific assets, underscores the necessity for nuanced top-down coupling methods in regional development. Moreover, the study emphasizes the significance of nurturing innovation links, not only between leading companies but also among midstream and downstream enterprises, enhancing cities' strategic coupling capabilities. [ABSTRACT FROM AUTHOR]

As the primary source sector of carbon emissions, the power industry's green innovation is an indispensable component of China's low-carbon transformation. This paper took China's Carbon Emission Trading Scheme as a quasi-natural experience and adopted the synthetic control method to evaluate the impact of Carbon Emission Trading Scheme pilot policy on power industry's green innovation based on the provincial industrial level data. Furthermore, this paper examined the impact mechanisms of Carbon Emission Trading Scheme on the power industry's green innovation through policy comparison, moderating and mediating effect analyses. The research findings show that: 1) there is heterogeneity in Carbon Emission Trading Scheme's effectiveness in inducing green innovation in China, the power industry only in Beijing and Guangdong has been significantly promoted, while other pilots have not; 2) the success of Beijing and Guangdong can be attributed to distinctive features of their carbon market and power industry, including the refined quota accounting mechanism, the application of paid quota allocation, the larger enterprise scale and more research and development investment; 3) enterprise scale and research and development investment have positive moderating effect and mediating effect in the promotional effect of the Carbon Emission Trading Scheme on green innovation respectively. Finally, some policy recommendations are put forward to promote the power industry's green innovation and carbon market construction. • Evaluate the impact of China's CETS on the power industry's green innovation in each pilot. • The CETS effects among pilots are heterogeneous, only significant in Beijing and Guangdong. • Rational CETS mechanism design could improve the power industry's green innovation. • Enterprise scale and R&D investment positively moderate and mediate the CETS effect. [ABSTRACT FROM AUTHOR]

In recent times, a new wave of scientific and technological advancements has significantly reshaped the global economic structure. This shift has redefined the role of regional innovation, particularly in its contribution to developing the Guangdong–Hong Kong–Macao Greater Bay area (GBA) into a renowned center for science, technology, and innovation. This study constructs a comprehensive evaluation system for the Regional Innovation Ecosystem (RIE). By applying the coupling coordination degree model and social network analysis, we have extensively analyzed the spatial structure and network attributes of the coupled and coordinated innovation ecosystem in the GBA from 2010 to 2019. Our findings reveal several key developments: (1) There has been a noticeable rightward shift in the kernel density curve, indicating an ongoing optimization of the overall coupling coordination level. Notably, the center of gravity for coupling coordination has progressively moved southeast. This shift has led to a reduction in the elliptical area each year, while the trend surface consistently shows a convex orientation toward the center. The most significant development is observed along the 'Guangdong–Shenzhen–Hong Kong–Macao Science and Technology Innovation Corridor', where the level of coupling coordination has become increasingly pronounced. (2) The spatial linkages within the GBA have been strengthening. There are significant spatial transaction costs in the regional innovation ecological network. In the context of the 2019 US-China trade war, the cities of Jiangmen and Zhaoqing experienced a notable decrease in connectivity with other cities, raising concerns about their potential marginalization. (3) Guangzhou, Shenzhen, and Hong Kong have emerged as core nodes within the network. The network exhibits a distinctive "core–edge" spatial structure, characterized by both robustness and vulnerability in various aspects. [ABSTRACT FROM AUTHOR]

Promoting urban green growth necessitates a dual focus on reducing carbon emissions and fostering high-quality development. However, the body of research on the coupling relationship between high-quality urban development and carbon emissions remains remarkably limited. Taking Guangdong province as an example, this study strived to establish a comprehensive evaluation system for high-quality urban development encompassing economic, societal, and ecological dimensions and further conducted an in-depth examination of the spatiotemporal pattern and driving forces of coupling coordination degree between high-quality urban development and carbon emission intensity during 2000–2017. The coupling coordination degree in Guangdong province has shown continuous growth, transitioning from moderate incoordination to moderate coordination. The coupling coordination degree showed the overall spatial distribution characteristics of "high in southeast and low in others", with Zhuhai, Zhongshan, Foshan, Guangzhou, Dongguan, and Shenzhen as the core. Notably, technological advancement, environmental governance, and economic development emerge as pivotal factors that positively affect carbon emission intensity reduction, environmental quality improvement, and coupling coordination enhancement. This research provides valuable insights for achieving harmonized high-quality development in Guangdong province involving policies of regional differences, industrial competitiveness, and new-type urbanization. [ABSTRACT FROM AUTHOR]

Abstract Manufacturing industry is an important part of economic development. Recognizing the sustainable development of regional manufacturing has an important guiding role in the formulation of environmental policies. Based on the meta-frontier Malmquist-Luenberger (MML) productivity index, this paper uses Chinese provincial panel data (2003–2015) to measure the green total factor productivity (TFP) of China's manufacturing. It is decomposed into the following: efficiency change (EC), change of the best practice gap ratio (BPC) and change of technical gap ratio (TGC). We compared the regional differences in green TFP growth in manufacturing in all provinces, analyzed regional and time differences in green TFP and the decomposition of manufacturing between regions and identified innovative regions. The results show that: (1) The average annual growth rate of green TFP in Chinese manufacturing is 0.85% with technological progress playing a key role. (2) There are differences in the causes of the increase in green TFP in all regions. The eastern region and the western region are driven by technological progress while the central region depends on technology catch-up effects. (3) Guangdong and Qinghai are two different types of global innovation regions with Guangdong driven by technological innovation and Qinghai driven by strict environmental protection systems. [ABSTRACT FROM AUTHOR]

This study investigates the interplay between investment, training, and environmental factors in the aquaculture industry in the Guangdong region of China. Using NIPALS regression to address multicollinearity, we identify the factors that significantly impact losses of aquaculture products due to environmental factors. Our findings highlight the importance of targeted training and education for fisherfolks and extension staff to enhance environmental management practices and reduce losses. We also emphasize the need to consider regional variability and challenges in developing universal models. Based on our results, we propose using innovative technology, fostering public–private partnerships, and adapting to regional variability to address environmental challenges. Finally, we suggest establishing a comprehensive monitoring and evaluation system to assess the effectiveness of interventions and promote evidence-based decision-making for sustainable development in the region's aquaculture sector. [ABSTRACT FROM AUTHOR]

Technology transfer is a conscious knowledge transfer and diffusion, which can promote the coordinated configuration and balanced development of technological innovation elements in geographical space. From the perspective of "space of flow", the technology transfer network is constructed. Utilizing patent technology transaction data from 2018, this study analyzes the agglomeration differentiation and spatial polarization patterns of technology transfer from network nodes, network layers, and network partition in Guangdong–Hong Kong–Macao Greater Bay Area. The conclusions are as follows: (1) The agglomeration of technology transfer is remarkable in the network, showing "two poles and two strong" as well as proximity advantages; Shenzhen and Guangzhou have become spatial poles within the network. (2) The Matthew effect is prominent and technology transfer at the spatial level is largely caused by core node interactions, while core‐edge hierarchical transmission mechanisms and geographical proximity contact characteristics are gradually developing. (3) Differences in roles between the plates are pronounced, and there is an agglomeration effect within a plate and between plates, as well as clear spillover effects. [ABSTRACT FROM AUTHOR]

The arrival of the dual-carbon era indicates that it is imperative to reduce industrial carbon emissions with high carbon emissions. The implementation of carbon emission reduction will inevitably have an impact on industrial development. Three different carbon emission scenarios were established. Based on the average annual carbon emission growth rate of the past decade, it is set as a medium carbon scenario. According to the economic development stage and actual social development situation of each region, the corresponding annual average carbon emission growth rate is increased and decreased to set up high carbon and low carbon scenarios. The adjacent accumulation gray multivariate model for industries is established based on different scenarios. The results indicate that the carbon emission scenarios most suitable for industrial development in various regions are different. Heavy industrial provinces and cities such as Beijing, Tianjin and Hebei have the highest industrial output value under high carbon scenarios; Provinces and cities with high levels of industrialization, such as Jiangsu, Shanghai, Guangdong and Chongqing have the highest industrial output value under low-carbon scenarios. The industrial output value of Hebei is expected to grow the fastest under the high carbon scenario, reaching 2.15 trillion yuan by 2030. The industrial output value of Guangdong achieves the greatest improvement under low-carbon scenario. It is expected that the industrial output value of which will reach 6.86 trillion yuan by 2030, ranking first in the country. Therefore, the setting of carbon emission scenarios needs to be tailored to local conditions, increase technological innovation efforts, and further promote industrial development. [ABSTRACT FROM AUTHOR]

To provide a theoretical basis for deepening digital reform in the construction industry and explore the innovation path of the digital construction industry, this research uses patent data for Guangdong Province to carry out explanatory sequence research. First, this research analyzes the dynamic evolution process of networks in the digital construction industry by using social network analysis. Then, grounded theory is used to conduct qualitative research to explore the innovation path of the digital construction industry. The results show that the scale of the innovation network of the digital construction industry is continually expanding and the digital carriers are becoming increasingly diverse. Influenced by the diversification of digital carriers, the research theme of the digital construction industry is beginning to develop in the direction of intelligence. The findings indicate that the use of mixed methods improves the robustness of the results and that the quantitative research results are explained by the qualitative research results. This research not only contributes to information development in the construction industry but also provides a theoretical basis for deepening digital reform in the construction industry. [ABSTRACT FROM AUTHOR]

In the rural areas of China, construction is growing vigorously, and the question of how to realize the creative inheritance and development of these areas in the regional context, as well as the exploration of new construction methods and paths, are important problems. Nowadays, there are two developing trends in terms of research methods. Firstly, the boundaries between various disciplines are becoming increasingly blurred, and interdisciplinary theoretical reference has become an effective means of realizing innovation in this field. The other trend relates to the great development of digital technology, such as parameterization and spatial information technology. This technological innovation sheds new light on rural image construction. This study aims to draw on the montage art concept and organization techniques and to integrate the new technical language into the construction of new aesthetic orientations and context-related inheritance paths of rural historical places in China. Based on the aesthetic relevance of montage aesthetics to rural regional characteristics, the aesthetic cognition of the rural area in Guangdong is analyzed and demonstrated. Then, the strategies and methods used for the construction of rural area are established based on four layers, i.e., the narrative clues, base site pattern, spatial interfaces and monomer construction. The present research expands on the perspectives and methods of rural reconstruction, provides new ideas for the current rural practice, and is conducive to promoting the systematic study of rural construction theory. [ABSTRACT FROM AUTHOR]

With the rapid development of industry 4.0 and the boom of large-scale product customization, the adoption of collaborative robots' innovation becomes a hot topic in research. Previous studies have mainly focused on individuals, but few on enterprises, and in particular, there has been a lack of empirical research on the enterprise level. Based on the combined model of Technology-Organization-Environment Framework (TOE) and Diffusion of Innovations Theory (DOI), this study investigated 373 small and medium-sized enterprises (SMEs) in Guangdong Province, China, to explore the determinants of SMEs' adoption of collaborative robot innovation in technology, organization, and environment. The result shows that the technical factors of relative advantage, compatibility, observability, and trialability have a significant positive correlation with the adoption of collaborative robots, while complexity has a significant negative correlation with the adoption. Among the organizational factors, top management support and organizational readiness have a significant positive correlation with the adoption of collaborative robots. Among the environmental factors, agent support is positively and significantly correlated with adoption. The findings will help practitioners develop appropriate strategies for the adoption of collaborative robot innovation. [ABSTRACT FROM AUTHOR]

Based on the modified gravity model, a spatial correlation network of innovation was constructed among cities in Guangdong, China. Social network analysis was employed to explore their evolution characteristics during 2009–2017. The results indicate that the innovation output of prefecture-level cities in Guangdong Province shows both spatial correlations and differences. Their network shows lower density, higher efficiency, and rigid stratification properties. Based on small cluster analysis, these cities are classified into four blocks, the members of which changed. In 2017, four well-defined subgroups formed, which are "bidirectional spillover plate", "main spillover plate", "net beneficial plate", and "agent plate". With this network, the geographical characteristics of the innovation capabilities and differences among the cities in Guangdong, as well as the different positions and roles of each city in the associated network, can be properly understood. Consequently, the transmission mechanisms and development strategies of innovation in Guangdong Province can be better explored. [ABSTRACT FROM AUTHOR]

This article explores the moderating effects of in-house formal R&D and industrial environment turbulence on the relationship between institutional drivers, in terms of incentives and pressures, and firm innovation. Hypotheses were tested on a sample of manufacturing firms in Guangdong Province of China, where institutional changes and governmental policies play prominent roles in shaping innovation. Results show a positive main effect of institutional incentives, but an insignificant main effect of institutional pressures. In-house formal R&D and industrial turbulence negatively moderate the institutional incentives–innovations relationship, yet positively moderate the institutional pressures–innovations relationship. This study links the innovation systems literature with the institution-based view and deepens the understanding of the joint forces of institutional transitions, industrial changes, and resource heterogeneity in shaping innovation. The findings also inform managers and policymakers in institutional transition environments to better manage institutional drivers of innovation by considering firm- and industry-specific characteristics. [ABSTRACT FROM AUTHOR]

This study aims to investigate the direct relationships of university proximity and research quality with the product innovation performance of Chinese firms engaging in diverse university interaction channels. We collected data on the extent to which a sample of 166 Guangdong manufacturing firms draw from the intra-regional and cross-regional universities, as well as high-quality and average-quality universities. Our results revealed that: (1) interaction with intra-regional universities is more strongly associated with incremental product innovations, whereas interaction with cross-regional universities is more strongly associated with radical product innovations; (2) average-quality university linkages have a stronger relationship with incremental product innovations, while high-quality university linkages have a stronger relationship with radical product innovations; (3) interaction with cross-regional high-quality universities is more strongly associated with radical product innovations, but interaction with intra-regional average-universities is more strongly associated with incremental product innovations. These results furthered our understanding on how firms' product innovations are related to university linkages of different degrees of regional proximity and research quality, and bear direct practical implications for firm strategy and governmental policy. [ABSTRACT FROM AUTHOR]