Search

Large vessels that call at European ports will have to pay for their CO2 emissions from transporting cargo that enters or goes from a European port since January 2024. The costs will increase with increasing global trade. This results in a higher pollution level, including greenhouse gas (GHG) emissions like CO2. Based on the gravity model embedded in a global supply chain, we developed a model to evaluate maritime transport pollution in case a new, sufficiently large container port becomes operational. Additionally, we consider how lousy railway connections to European customers increase transportation costs and pollution. The approach to the well-connected sequences of gravity models in the intercontinental maritime chains evaluates the differences in quantities of cargo between ports when a new port is opened, and the waiting time does not change. We also highlight that poor rail connections can reduce this positive effect. We showed how it is possible to estimate the optimal capacity of a new port with a multi-level gravity model and how this would affect the pollution around the port and on the routes from the port to the final consumers. [ABSTRACT FROM AUTHOR]

Accurately grasping the spatial network correlation structure of operational efficiency in star-rated hotels and its influencing factors is of great significance for promoting high-quality coordinated development of star-rated hotels and the regional tourism reception industry. Using a comprehensive approach integrating the Super-DEA model, modified gravity model, and social network analysis to explore the evolving characteristics of spatial network structure in operational efficiency of provincial star-rated hotels in China from 2013 to 2022, and their underlying mechanisms. The results indicate that: (1) During the study period, the average operational efficiency of star-rated hotels in China was 0.618, with spatial efficiency values showing a distribution pattern of "Eastern > Central > Western > Northeastern". (2) The spatial correlation network of operational efficiency among provincial star-rated hotels in China overall exhibits characteristics of densification, hierarchical structure, and reinforcement. Provinces such as Beijing, Tianjin, Shanghai, and Jiangsu in the eastern region play central roles as "central actors" in the network, while provinces in the western and northeastern regions such as Heilongjiang, Tibet, and Xinjiang play roles as "passive actors" in the spatial network. (3) Members of the "Net benefit" and "Two-way spillover" are primarily from the eastern and some central provinces, while members of the "Net overflow" are mainly from the northeastern and western provinces. (4) Factors such as economic development level, residents' consumption level, and distance from provincial capital cities collectively drive the evolution and optimization of the spatial network structure of operational efficiency among provincial star-rated hotels in China. This study not only enriches the research findings on hotel operational efficiency but also provides a reference for constructing a cross-regional collaborative mechanism to enhance the operational efficiency of star-rated hotels. [ABSTRACT FROM AUTHOR]

Population mobility between cities significantly affects traffic congestion, disease spread, and societal well-being. As globalization and urbanization accelerate, understanding the dynamics of population mobility becomes increasingly important. Traditional population migration models reveal the factors influencing migration, while machine learning methods provide effective tools for creating data-driven models to handle the nonlinear relationships between origin and destination characteristics and migration. To deepen the understanding of population mobility issues, this study presents GraviGBM, an expandable population mobility simulation model that combines the gravity model with machine learning, significantly enhancing simulation accuracy. By employing SHAPs (SHapley Additive exPlanations), we interpret the modeling results and explore the relationship between urban characteristics and population migration. Additionally, this study includes a case analysis of COVID-19, extending the model's application during public health emergencies and evaluating the contribution of model variables in this context. The results show that GraviGBM performs exceptionally well in simulating inter-city population migration, with an RMSE of 4.28, far lower than the RMSE of the gravity model (45.32). This research indicates that distance emerged as the primary factor affecting mobility before the pandemic, with economic factors and population also playing significant roles. During the pandemic, distance remained dominant, but the significance of short distances gained importance. Pandemic-related indicators became prominent, while economics, population density, and transportation substantially lost their influence. A city-to-city flow analysis shows that when population sizes are comparable, economic factors prevail, but when economic profiles match, living conditions dictate migration. During the pandemic, residents from hard-hit areas moved to more distant cities, seeking normalcy. This research offers a comprehensive perspective on population mobility, yielding valuable insights for future urban planning, pandemic response, and decision-making processes. [ABSTRACT FROM AUTHOR]

This study evaluates the limitations of gravity models in constructing regional association networks, using China's interprovincial economic connections as a case study. Comparison between a gravity-model-based simulated network and an actual network reveals significant topological differences. The gravity model overestimates the influence of larger, inward-oriented provinces and fails to accurately represent external connections. Attempts to refine the model with additional variables proved ineffective. Further theoretical analysis attributes these deficiencies to measurement bias from the model's simplified binary perspective and information loss due to dimensional mismatch between pairwise predictions and complex network structures. These findings underscore the need for cautious application of gravity models and the development of more comprehensive analytical frameworks in regional network analysis. [ABSTRACT FROM AUTHOR]

Satellite altimetry is the main tool for constructing global or regional marine gravity fields. To improve the accuracy and spatial resolution, it is necessary to fuse multi-mission altimeters. How to determine the weights of multi-mission altimeters is a crucial issue, making the conventional calculation process very complex. In addition, traditional satellite inversion methods are often independent of shipborne gravity, which is used only as validation data, thus not take full advantages of high accuracy and resolution of shipborne gravity. In this study, we introduce a convolutional neural network (CNN) to merge the vertical deflections (DOVs) obtained from multi-altimeter missions to construct a marine gravity model in the South China Sea. High-accuracy shipborne gravity and a dataset comprising DOVs and geo-locations are employed as input data for neural network training. For the validation of CNN method, the gravity model is also computed by conventional Inverse Vening Meinesz (IVM) method. Independent shipborne gravity measurements and SIO V32.1, DTU17 models are used as validation data. The evaluation results show that the CNN-derived model achieves a higher level of accuracy, yielding a standard deviation (STD) of 3.21 mGal, with an improvement of 36.56% compared to IVM-derived model. More than 92% of the differences between the CNN-derived model and shipborne gravity are less than 5 mGal. In addition, spectral analysis results further show that the CNN-derived model has stronger energy at short wavelengths (less than 25 km) compared to other models. These findings reveal that CNN method is feasible for marine gravity recovery and the CNN-derived model can achieve higher accuracy. The CNN method can improve the accuracy and spectral characteristics of the constructed gravity model by taking advantage of the high accuracy and high resolution of shipborne gravity. [ABSTRACT FROM AUTHOR]

This study examined the factors affecting Vietnam's rice export value in the transitional period of 2011-2021 using panel data of 45 importers comprising 90% of Vietnam's rice export value. The generalized least square model was used for estimation, and the results reveal that the factors of world rice export prices, importing country's population, membership in the Comprehensive and Progressive Agreement for Trans-Pacific Partnership, European--Vietnam Free Trade Agreement, and multilateral or bilateral relationship positively affect export value. However, the importing country's GDP and self-produced food output and Vietnam's inflation negatively influence rice export turnover. Consequently, several policy recommendations are suggested. [ABSTRACT FROM AUTHOR]

Choice of trade route and destination by cross border traders is an important decision in today's increasingly cross border trade of products including fish. The current study examined the geographical factors influencing choice of informal trade route and destination by fish traders. Both qualitative and quantitative approaches were adopted for the study. These included semi-structured questionnaires through personal interviews and key informant interviews with fish border inspectors. Data was analyzed through various techniques for trader's choice and destination. Specifically, principal component analysis and spearman correlation, and Huff's gravity model were used to identify significant factors influencing choice of trade route and destination, and market attractiveness, respectively. Fish traders bypass official border posts using informal routes connecting the main route before and after the border post. Despite attempts and awareness about formal trade, stringent regulations forced fish traders to use informal trade routes. However, investigations into choice of trade routes and destination found that route distance, presence of alternative destination, mode of transport, demand of the fish product, and personal safety and risks were the factors influencing choice of both trade route and destination by informal fish traders. This geographic analysis provides a basis for addressing challenges in informal cross border trade in Malawi. It is recommended that strategic efforts and investments should be made in the development of transportation infrastructure, such as roads and railways to improve connectivity between secondary routes and one stop border post. The government should also intensify awareness initiatives on COMESA simplified trade regime (STR) to encourage informal traders to transition to the formal sector through use of formal routes. [ABSTRACT FROM AUTHOR]

In the context of the coordinated development of Beijing–Tianjin–Hebei, examining the spatial connections and network structure characteristics of the tourism economy holds substantial theoretical and practical significance. This study constructs a tourism economic quality evaluation index system from four dimensions and optimizes the tourism economic gravity model by incorporating time distance and weight factors to dynamically simulate the intensity of tourism economic spatial connection (ITESC). Based on the new perspective of relational data, social network analysis is employed to investigate the spatial correlation network characteristics and group structure changes in the tourism economy within the Beijing–Tianjin–Hebei urban agglomeration (BTHUA). The results demonstrate a significant improvement in overall tourism economic quality from 2013 to 2022, with the average quality increasing from 0.128 in 2013 to 0.157 in 2022. Tourism economic spatial connections are prevalent among cities, exhibiting heterogeneous characteristics, characterized by density in the north and relatively sparse in the south. The network cohesion of ITESC strengthens, and the network structure evolves from a highly centralized to a multi-centralized configuration, with increasingly frequent cooperation and interaction in tourism between cities. Beijing, Tianjin, and Shijiazhuang occupy central positions in the network, exhibiting strong ITESC and a high degree of connectivity, generating a significant "trickle-down effect" on peripheral cities. Consequently, strengthening ITESC between peripheral cities and core areas, as well as enhancing the bidirectional spillover of tourism development between cities, is crucial for the future sustainable and coordinated development of tourism in the BTHUA. [ABSTRACT FROM AUTHOR]

As China shifts from urbanization to rural revitalization within its rural governance strategy, devising appropriate governance programs becomes crucial for the effective implementation of overarching strategies. This paper explores the policy pathway of the rural revitalization strategy via the lens of village relational governance. This paper builds a relational network of village governance using the Newtonian gravity model and proposes an effective relational governance policy by analyzing the impact of village cluster patterns under different policy rules. Empirical research was conducted in Guiyang County, Hunan Province, China. The findings of this paper are as follows. (1) Rural development in Guiyang County heavily relies on location advantages and natural resources, and there is an urgent need to reinvent the path of rural governance to foster potential rural clusters. (2) A comparative analysis of the relational networks shows that the assignment-based network has more high-clustering groups and fewer low-clustering clusters than the merit-based network, and it has more cluster types, resulting in a more balanced and diverse network structure. In contrast, the merit-based network has fewer cluster types and tends to have a centralized structure. (3) The assignment-type network has greater advantages in terms of agricultural productivity, preserving local culture, and protecting the environment. Simultaneously, its network path has the potential to boost the intrinsic vitality of rural areas and attract more groups to contribute to its development. This path is feasible due to the high level of organization within the Chinese villages. Consequently, this study recommends that the county government should actively decentralize power to villages and grant villages equal development rights to encourage villages to build network clusters with unique competitive advantages. [ABSTRACT FROM AUTHOR]

This study examines the social attitudes towards the Central Najdi dialect among speakers of other Najdi dialects, i.e., Qassimi and Northern dialect. The Central dialect, spoken in the capital city of Riyadh, which has the largest population in the kingdom, is considered representative of Saudi Arabic. Based on the gravity model (Trudgill, 1974), it is hypothesized that other Najdi dialects will gravitate towards the dialect of Central Najd. The social attitudes towards the Central dialect will be assessed using the indirect method known as the verbal-guise test. The test measures individuals' implicit attitudes towards a dialect or a language. Participants listen to authentic short speech excerpts from each of the dialects understudy and rate each speaker based on selected status and solidarity traits. Findings indicate that the Central Najdi dialect is perceived more favorably in terms of status traits such as being civilized, educated, and open-minded compared to Qassimi and Northern dialect. [ABSTRACT FROM AUTHOR]

It is well established that maximizing the information extracted from upcoming and ongoing stage-IV weak-lensing surveys requires higher order summary statistics that complement the standard two-point statistics. In this work, we focus on weak-lensing peak statistics to test two popular modified gravity models, |$f(R)$| and nDGP, using the forge and bridge weak-lensing simulations, respectively. From these simulations, we measure the peak statistics as a function of both cosmological and modified gravity parameters simultaneously. Our findings indicate that the peak abundance is sensitive to the strength of modified gravity, while the peak two-point correlation function is sensitive to the nature of the screening mechanism in a modified gravity model. We combine these simulated statistics with a Gaussian Process Regression emulator and a Gaussian likelihood to generate stage-IV forecast posterior distributions for the modified gravity models. We demonstrate that, assuming small scales can be correctly modelled, peak statistics can be used to distinguish general relativity from |$f(R)$| and nDGP models at the 2σ level with a stage-IV survey area of |$300$| and |$1000 \, \rm {deg}^2$|⁠ , respectively. Finally, we show that peak statistics can constrain |$\log _{10}\left(|f_{R0}|\right) = -6$|  per cent to 2 per cent precision, and |$\log _{10}(H_0 r_c) = 0.5$| per cent to 25 per cent precision. [ABSTRACT FROM AUTHOR]

Clarifying the spatial correlation characteristics and influencing factors of coupling coordination between Foreign Direct Investment (FDI) flow networks and carbon transfer networks in countries along the Belt and Road Initiative is of utmost importance for the formulation of regional carbon governance strategies and the establishment of a high-quality Green Silk Road. This study used a comprehensive approach combining social network analysis and coupling coordination model to measure the coupling coordination degree of FDI flow networks and carbon transfer networks of 67 Belt and Road countries from 2010 to 2016. In addition, a modified gravity model is used to characterize the spatial correlation network structure of coupling coordination between the two networks, and the QAP regression analysis method is applied to investigate the factors influencing the spatial association network. The results are as follows: 1) The spatial correlation network of coupling coordination between the two networks has good accessibility and relatively high overall network stability. 2) Countries such as Qatar and the United Arab Emirates occupy central positions in the network, while Bahrain and Jordan are positioned on the periphery of the network. 3) The spatial correlation network can be divided into three sectors: net outflow, net inflow, and bidirectional overflow sectors. 4) Spatial adjacency, bilateral investment treaties, economic development, and institutional quality have significant positive effects on the spatial association network, while the industrial structure and the level of infrastructure development have a significant negative impact. This study proposes an indicator system for the coupling coordination between FDI flow networks and carbon transfer networks. The aim is to investigate the coupling coordination relationship between FDI flow networks and carbon emission transfer networks in countries along the Belt and Road Initiative, providing important guidance for the formulation of regional cooperative carbon emission reduction strategies in other regions. [ABSTRACT FROM AUTHOR]

This study examines the relative impacts of transport and information and communications technology (ICT) components of trade-related infrastructure on bilateral trade flows between Nigeria and its major trading partners. An augmented standard gravity model that featured variables for the transport infrastructure component and the ICT component was estimated using bilateral trade data on 22 major trading partners of Nigeria for the period 2005–2021. The panel instrumental variables technique, precisely pooled two-stage least squares technique leveraged on fixed and random effects models, was used for the analysis. The findings show that the two components of trade-related infrastructure, transportation and information and communication technology (ICT) have a significant impact on trade flows between Nigeria and its trading partners. In the exports model, the differential impact of the transport infrastructure component is higher than the ICT component, but the differential impact of the ICT component is greater in the imports model. This suggests that the efficient provision of both transport and ICT infrastructure facilitates trade, while the inefficient provision of either or both hinders it. Therefore, greater attention must be placed on improving both components. [ABSTRACT FROM AUTHOR]

Introduction: Creating an ecological space network is essential for safeguarding the core structure of ecological space. Methods: Morphological spatial pattern analysis was used to locate ecological sources in the Kuye River Basin. Using the least cumulative resistance model and gravity model, the resistance surface, ecological corridor, and ecological space management network are determined. Results and discussion: The study revealed that in 2022, the predominant land use types in the Kuye River Basin were wood land and grassland, cultivated land, and construction land. MSPA model software identifies a substantial portion of the landscape pattern as consisting of core and marginal areas, which encompass 30324.05 hm² and 15088.24 hm². High ecological resistance surface factors dominate the socioeconomically vibrant zone and northern regions. Resistance values ranging from 0.02 to 0.87, and high and law resistance zones alternate. The minimal cumulative resistance approach found 171 ecological corridors. And gravity model using the interaction matrix of 19 primary ecological sources discovered 8 first-level ecological corridors with the highest interaction force. There are 137 core and 23 subsidiary ecological corridors with significant affects. Overlying the road factors and ecological corridors of national highways, provincial roads, railways, and high-speed roads creates a total of 38 ecological breakpoints, each characterized by specific barrier effects and legal ecological stability. [ABSTRACT FROM AUTHOR]

The global marine gravity anomaly model is predominantly recovered from along-track radar altimeter data. Despite significant advances in gravity anomaly recovery, the improvement of the gravity anomaly model remains constrained by the absence of cross-track geoid gradients and the reduction in radar altimeter data, especially in coastal and high-latitude regions. ICESat-2 laser altimetry, with a three-pair laser beam configuration, a small footprint, and a near-polar orbit, facilitates the determination of cross-track geoid gradients and provides valid observations in certain regions. We present an ICESat-2 altimeter data processing strategy that includes the determination of cross-track geoid gradients and the combination of along-track and cross-track geoid gradients. Utilizing these methods, we developed a new global marine gravity model, SDUST2022GRA, from radar and laser altimeter data. Different weight determination methods were applied to each type of altimeter datum. The precision and spatial resolution of SDUST2022GRA were assessed against published altimeter-derived global gravity anomaly models (DTU17, V32.1, NSOAS22) and shipborne gravity measurements. SDUST2022GRA achieved a global precision of 4.43 mGal , representing an improvement of approximately 0.22 mGal over existing altimeter-derived models. In local coastal and high-latitude regions, SDUST2022GRA showed an enhancement of 0.16–0.24 mGal compared to the other models. The spatial resolution of SDUST2022GRA is approximately 20 km in certain regions, which is slightly superior to the other models. The percentage contribution of ICESat-2 to the improvement of the gravity anomaly model is 4.3 % in low- to mid-latitude regions by comparing SDUST2022GRA with ICESat-2 to SDUST2021GRA without ICESat-2, and this is increasing in coastal regions. These assessments suggest that SDUST2022GRA is a reliable global marine gravity anomaly model. The SDUST2022GRA data are freely available at https://doi.org/10.5281/zenodo.8337387 (Li et al., 2023). [ABSTRACT FROM AUTHOR]

This paper investigates whether and how export growth to China varies following shocks in bilateral political relations between China and six Southeast Asian countries—Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam—between 2000 and 2019. High‐frequency news data is used to quantify bilateral political relations between each of the six countries and China. Then, a net cooperation index, plus separate indices of political cooperation and conflict, are placed in an augmented gravity model of trade situated in a vector autoregression framework alongside real exchange rate and industrial production variables to examine the short‐ (months) and long‐run (years) effects of shocks to bilateral political relations on each countryʼs exports growth to China. The results reveal that political relations with China played a role in Thailandʼs and Vietnamʼs exports growth to China but not in Indonesiaʼs, Malaysiaʼs, the Philippinesʼ and Singaporeʼs, and contribute new findings to the literature on politics and trade. Code and data for the analysis is available at: https://github.com/tradepolsrepository/tradepols.git. [ABSTRACT FROM AUTHOR]

The gravity model, which is applied to international trade, explains the conceptual models of international business. It has been used in various areas of the global economy, such as trade, foreign direct investment, and even the determinants of tourist demand at the level of countries and sectors of economic activity. In terms of the methodology, this study of the gravity model followed the PRISMA requirements and bibliometric analysis (co-occurrence of keywords and network of co-authorship), which were applied to the Scopus database. In terms of the results, economic, geographical distance, and location variables are essential in explaining international trade. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Pekinensis is the property of Editorial Office of Acta Scientiarum Naturalium Universitatis Pekinensis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present paper seeks to conceptualise the notion of complementarity with the help of rail-based commodity flow data in one of the most prominent railway towns in India i.e. PanditDeenDayalUpadhyaya Nagar (Mughal Sarai). Referring to the theoretical notion of 'complementarity' and a modified form of 'gravity model' from the 'Family of Spatial Interaction Models', this research puts an intensive discussion forward on the existing nature of spatial interaction of PanditDeenDayalUpadhyaya Nagar (Mughal Sarai) with its complementary areas and a comparison of these areas in terms of their relative complementarity with the town concerned. The resultant outcome in the form of a Complementarity Index, portrays a different, if not entirely contradictory picture from the crude values of material shipments to PanditDeenDayalUpadhyaya Nagar (Mughal Sarai). This analysis thus well-indicates that merely supplying greater amount of commodities of any kind does not necessarily reflect greater complementarity and vice versa. Therefore, a more comprehensive analysis of commodity flows is imperative to have a deeper insight into the notion of spatial interaction. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study examines the current state of China's agricultural exports to ASEAN countries using a segmented export structure analysis via a stochastic frontier gravity model, based on panel data from 2007 to 2020. The results indicate that: (1) China's primary agricultural exports to ASEAN countries include plant products, food and beverages, and tobacco, with animal products mainly exported to Thailand, plant products mainly exported to Vietnam, and animal and plant fats, food, beverages, and tobacco mainly exported to Malaysia. (2) The economic scale and population size of China and ASEAN countries have differing impacts on various markets, while distance significantly negatively affects the exports of animal products, plant products, food, beverages, and tobacco. Additionally, ASEAN countries' per capita carbon emissions positively influence the exports of these product categories. (3) The liner shipping connectivity index is significantly negatively correlated with trade inefficiency. The influences of financial freedom, trade freedom, investment freedom, and government expenditure on trade inefficiency vary across ASEAN countries. (4) China's export efficiency for animal products, plant products, food, beverages, and tobacco has increased rapidly to Thailand and Vietnam, with Malaysia and Singapore showing high export efficiency, while that to Cambodia lags. (5) China exhibits significant export potential to Thailand, Indonesia, and Vietnam, with substantial expansion opportunities in Indonesia. Moreover, China's export potential and opportunities in Cambodia are steadily increasing. [ABSTRACT FROM AUTHOR]

This study evaluates the new urbanization (NU) quality and the ecological resilience (ER) of 33 districts and counties in the Urban Agglomeration of Central Guizhou from 2010 to 2020. For this purpose, we used a modified coupled coordination degree (CCD) model, spatial autocorrelation analysis, and trend surface analysis to analyze the spatiotemporal evolutionary characteristics of the CCD of NU and ER. Meanwhile, we used a modified gravity model and social network analysis to investigate the spatial connection network (SCN) characteristics of the CCD of NU and ER. The results show that (1) the general NU quality has increased significantly in the Urban Agglomeration of Central Guizhou. There is, however, a downward trend in ER. (2) For the CCD of NU and ER in the Urban Agglomeration of Central Guizhou, there is coupling dissonance, with a double U-shaped arc, characterized by west > north > south > east > central. (3) The network density increases and then decreases. Network connectivity is 1, and network efficiency decreases and then increases. (4) During the study period, the SCN is characterized by significant core–edge characteristics; there are no "island nodes" in the SCN. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Economics & Social Sciences is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Agricultural water productivity is crucial for sustainability amidst the escalating demand for food. Cereals are pivotal in providing nutritious food at affordable prices. This study was based on Ghanaian data spanning from 1992 to 2021 to evaluate water usage in the cultivation of major cereals. It also examined the virtual water losses or gains in cereal trade alongside influencing factors. The analysis utilized secondary data encompassing the virtual water content, production quantity, export and import quantities, distance, GDP per capita, population, and land per capita of Ghana and its 75 trade partners. In the last 5 years, crop water use (CWU) reached an average of 7.08 billion m3/yr for maize, 3.48 billion m3/yr for rice, 1.08 billion m3/yr for sorghum, and 0.63 billion m3/yr for millet production. Ghana's major partners for exported virtual water (EVW) were Niger, Burkina Faso, South Africa, and Togo. Major partners for imported virtual water (IVW) were Argentina, South Africa, Ukraine, Togo, Russia, Burkina Faso, Canada, Senegal, Nigeria, Portugal, UK, Niger, and the USA. The Panel Least Squares Method of regression was used to apply the Gravity Model principle in assessing influencing factors. The findings indicate that Ghana is a net importer of virtual water in the cereal trade, with significant influences from geographical distance, GDP per capita, population, land per capita, and cereal water use. [ABSTRACT FROM AUTHOR]

Improving the green electricity efficiency (GEE), is an important issue for China's high-quality economic development. This study presents a spatial correlation network of urban GEE in the Yellow River Basin from 2012 to 2021, constructed using an improved gravity model. Social network analysis and the quadratic assignment procedure method are employed to analyze the spatial correlation characteristics and influencing factors. The findings indicate that urban GEE in the Yellow River Basin exhibits complex and stable network characteristics. The spatial network analysis reveals that Jiayuguan City, Dongying City, Dingxi City, Zibo City, and Shizuishan City occupy central positions within the network. The results indicate that spatial adjacency, GDP per capita, industrial structure, and the level of science and technology expenditure are positively related to urban GEE, while environmental regulation and average temperature are negatively related. The findings of the study have led to policy recommendations aimed at enhancing urban GEE in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Research on the marine science and technology innovation efficiency (MSTE) from the perspective of innovation value chain is not only an inevitable requirement for in-depth exploration of Marine science and technology innovation activities, but also an important guidance for the sustainable development and optimization of marine economy. Based on the innovation value chain perspective, the marine science and technology innovation process is divided into three phases: basic innovation, applied research and development, and gainful transformation, and the chain network DEA model is used to measure the MSTE of 11 provinces and municipalities along the coast of China from 2007 to 2021; the modified gravity model and social network analysis are used to examine the spatial correlation network characteristics of the marine MSTE at different phases and their influencing factors. The results show that the spatial correlation of China marine MSTE gradually develops from a sparse and dispersed state to a close trend, and the three phases gradually show a development pattern from unicentre, polycentre and networked. There is no strict hierarchical structure in the spatial correlation network of marine MSTE, the applied research and development and revenue transformation phases are more relevant than the basic innovation phase, and the cross-regional collaborative innovation needs to be improved. The high-efficiency provinces have a strong ability to radiate the MSTE to other provinces, and can absorb a large amount of innovation resources. The spatial correlation network of MSTE development has formed four plates of two-way spillover, broker, net spillover and net benefit in all three phases, and the transmission of kinetic energy of regional MSTE development has obvious gradient characteristics. The strength of government support, marine industry structure, and marine management services are conducive to enhancing the spatial correlation of the three phases of innovation development. Through this study, we can not only grasp the overall pattern and development dynamics of China Marine science and technology innovation, but also deeply analyze the internal logic and formation mechanism of its spatial correlation network structure, so as to provide scientific basis for optimizing resource allocation and improving innovation efficiency. [ABSTRACT FROM AUTHOR]

With the vigorous development of digital technologies, digital economy has become a brand economic model, providing a strong driving force for improving the matching of supply and demand, enhancing the allocation of resources, and promoting economic transformation and upgrading. To comprehensively analyze the overall situation of the development of digital economy and the spatial relationship, firstly, the digital economy evaluation index system was established for 31 provinces (municipalities and autonomous regions) in China, and the gravity value was calculated by the revised gravity model to build the spatial network. Secondly, the spatial dependence of regions was explored through the global Moran indexes. Finally, the space-time fixed Durbin model was established to analyze the influence of explanatory variables effected on the development of digital economy and their spatial spillover. The results are as follows: China's digital economy development spatial network is not compact enough. The difference among regions is obvious and neighboring regions depend on each other. The improvement of urbanization level not only promotes the development of digital economy in the province involved, but also indirectly drives the improvement of neighboring provinces, which is a strong spatial spillover effect, while the human capital level has a restraining effect. [ABSTRACT FROM AUTHOR]

This paper examines the impact of access to finance on intra-Africa trade efficiency using a panel dataset comprising 44 African exporters. Between 2008 and 2021, a stochastic frontier version of the gravity model finds intra-Africa trade to have been lower than its full potential by $1.1 billion on average. Exporters with better access to finance such as South Africa, Morrocco and Mauritius operated closer to their full potential. The effect of access to finance on intra-Africa trade is found to have been stronger between distant trading partners. This suggests that access to finance largely promotes intra-Africa trade through financing transportation and logistics. In view of these results, the analysis recommends policy efforts to improve access to finance in order to maximize trade between African countries. [ABSTRACT FROM AUTHOR]

This study examines the empirical validity of the Linder hypothesis for India's service sector exports from 2005 to 2021, focusing on 35 major importing countries. We use a gravity model trade, applying Feasible Generalised Least Squares (FGLS) and two-step system generalised method of moments (GMM), incorporating country- and time-fixed effects. Our results confirm that the Linder hypothesis does not hold for Indian service exports, revealing an increase in trade intensity between countries with dissimilar income levels. The study finds that distance has a positive and significant impact on Indian service exports. Exchange rates have a negative and significant impact on India's service exports, while the results for the RTA dummy variable are inconclusive. Sharing a common border, a common colony, and a language has a positive and significant effect on Indian service exports. [ABSTRACT FROM AUTHOR]

Urban land is the primary location for manufacturing and services, facilitating the expansion and interconnectedness of economic activities and factor flows to shape various urban land-use performances (ULUP). Exploring these spatial linkages of urban land-use performance can play a crucial role in fostering cohesive urban development. Taking 109 prefecture-level cities as research samples, this paper explores the characteristics and influencing factors of the spatial network associated with ULUP in the Yangtze River Economic Belt through modified gravity model, network analysis and QAP analysis. The analysis shows that ULUP has shown an N-shaped trend over the past two decades. It has formed a network of correlations, with Chongqing, Shanghai, and Wuhan emerging as central nodes. Notably, the correlation predominantly occurs between geographically adjacent cities, with weaker links between the Yangtze River Economic Belt's upstream, midstream, and downstream regions. The network can be divided into four distinct types: main inflow plate, main outflow plate, agent plate, and bidirectional spillover plate. Geographic location is the most significant factor influencing network formation, followed by resource mismatch, economic development, and openness. The study provides theoretical guidance and empirical support for improving the utilisation of urban land and promoting coordinated development. [ABSTRACT FROM AUTHOR]

Land disputes have significantly disrupted legal order, production, and social harmony, and has been regarded as a quintessential challenge in public governance, attracting worldwide attentions from scholars. As an emblematic feature of China's latest reform and opening-up strategy, the Yangtze River Economic Belt (YREB) in China has experienced rapid development after entering the new era (2012–2021) alongside substantial risks and challenges, particularly regarding land disputes. Better understanding of the manifestation and formation mechanism of new characteristics of land disputes is beneficial for contemporary public governance and for achieving a high-quality development of the YREB, whose Gross Domestic Product (GDP) accounted for 46.3% of the national GDP in 2023. A total of 325,105 land dispute cases in 11 provinces or municipalities of the YREB from 2012 to 2021 were collected and analyzed. On this basis, an evaluation index system of the new characteristics of land disputes, named the overall land dispute (OLD) index, was constructed according to measurement theory by coupling the interactions of quantity, claim amounts, duration periods, and the appeal rate of land dispute. Then, the OLD index was evaluated by descriptive statistical methods, a geographic information system (GIS) spatial analysis, a center of gravity model, kernel density estimation, and Theil index methods, to reveal the new characteristics and formation mechanisms of land disputes in the YREB from 2012 to 2021. The results indicated that: (1) The OLD index exhibited a trend of an initial increase followed by a decline, indicating that land disputes in the YREB showed signs of alleviation. (2) The government's capacity for resolving land disputes was significantly improved, as evidenced by the decline in the OLD index from 0.59 in 2018 to 0.51 in 2021. This improvement could be attributed to the effectiveness of enhanced governmental working mechanisms, regulatory standards, and the integration of digital technologies. (3) The analysis of the center of gravity model indicated that the focus of land disputes shifted westward, propelled by national policy support for upstream regions of the YREB and the need for land ecological protection. (4) The analysis of kernel density estimation indicated that regional disparities in land disputes within the YREB had declined, driven by a positive trend toward balanced regional development and rural governance. This study provides scientific insights into the new characteristics of land disputes in the YREB and guidance for policy decision making on effective land dispute management. [ABSTRACT FROM AUTHOR]

To unravel the general relationship between bus travel and land use around bus stops and along bus routes and to promote their coordinated development, this paper explores a method to estimate passenger flow volumes from and to bus stops based on land use types, intensities, and spatial distributions around bus stops and along bus routes. Firstly, following the principle of the gravity model, which considers traffic volumes analogous to gravity based on trip generation and distance impedance between traffic analysis zones (TAZs), a gravitational logic estimation method for passenger flow volumes from and to bus stops was constructed with land use elements between bus stop TAZs and the upstream and downstream collections of bus stop TAZs. Building upon this, the passenger flow volumes from and to 38 bus stops in the Xueyuan Square area of Dalian during weekday morning peak hours were taken as the experimental objects. The basic estimation models of two gravity sets corresponding to passenger flow volumes from and to bus stops were constructed using the bus travel generation based on the aggregation of area-based origin unit method and the bus travel distance impedance based on the probability density method. Finally, the reliability of the estimation method of passenger flow volumes from and to bus stops was verified by regression fitting between the surveyed values of passenger flow volume and the estimated values of the basic models. The results indicate that the fuzzy estimation and transformation of bus travel based on land use elements, which serves as a crucial lever for facilitating strategic alignment in transit-oriented development (TOD), can be effectively achieved by using the area-based origin unit method to aggregate bus travel generation and the probability density method to evaluate the bus travel distance impedance. [ABSTRACT FROM AUTHOR]

OpenStreetMap (OSM) is one of the most successful and wellknown projects in the field of Volunteered Geographic Information (VGI). It has not only become supplement to basic mapping services and professional surveying data, but also a popular free spatial dataset in urban analysis. However, the completeness of OSM building data in China was relatively low in the past. As a result, there is a relatively small number of studies on OSM building data in China, especially in terms of spatial patterns and evolution of OSM building data. In response to this research gap, this article proposes an OSM building data evolution model that combines gravity model and tree model. The spatial distribution pattern and evolution trend of OSM building data in the Yangtze River Delta region of China from 2014 to 2020 were systematically studied, providing insights and references for the future development of OSM building data in China. The research results indicate: (1) From 2014 to 2020, OSM building data in various cities in the Yangtze River Delta region grew rapidly, with an average annual growth rate of 30%, but there were significant spatial differences; (2) In terms of space, due to the influence of urban economy, population, and education level, OSM buildings mainly evolve and develop along large cities, forming a local radial development structure around large cities. Shanghai-Suzhou-Wuxi-Nanjing-Xuzhou/Hefei is the main evolutionary path of OSM building data in the Yangtze River Delta region; (3) In terms of time series, the gap between cities gradually decreases with the development of time, and OSM buildings gradually expand and develop from large cities to small and medium-sized cities, with spatial differences gradually narrowing. However, when OSM buildings have a certain scale, the city size will limit the development of OSM buildings to some extent. [ABSTRACT FROM AUTHOR]

In the post-epidemic era, the restart of China's inbound tourism is imminent. However, there are gaps in our current understanding of how distance perception dynamically affects inbound tourism in China. In order to understand the past patterns of inbound tourism in China, we mapped the data of 61 countries of origin from 2004 to 2018 into a dynamic expanding gravity model to understand the effects of cultural distance, institutional distance, geographical distance, and economic distance on inbound tourism in China and revealed the dynamic interaction mechanism of non-economic distance perception on inbound tourism in China. Our research results show that cultural distance has a positive impact on China's inbound tourism, while institutional distance has a negative impact. The significant finding is that the dynamic interaction of the above two kinds of perceived distance can still have a positive impact on China's inbound tourism. Its practical significance is that it can counteract the influence of institutional distance by strengthening the cultural distance. Generally speaking, geographical distance and institutional distance restrict China's inbound tourism flow, while cultural distance, economic distance, and interactive perceptual distance promote China's inbound tourism flow. [ABSTRACT FROM AUTHOR]

Tis study elucidates the factors impacting China’s apple trade, its efciency, and opportunities for increased revenue. Tis study adopts a stochastic frontier gravity model on China’s apple exports data, covering the period from 1997 to 2022 across 38 signifcant trading partners. Te fnding demonstrates that the economic growth of China and its trading partners substantially boosts apple export volumes, with a positive correlation between GDP growth and export fows. Te research also highlights the deterrent efect of geographical distance on exports and reveals a complex negative relationship between the per capita GDP of importing nations and export efciency, shedding light on the nuanced nature of trade dynamics. Furthermore, the study fnds that the appreciation of China’s currency plays a crucial role in enhancing export efciency by lowering transaction costs. Meanwhile, increased agricultural land in importing countries presents competitive challenges, impacting export performance negatively. Geographical proximity and infrastructural features, such as shared borders and lack of access to seaport, are identifed as signifcant factors in export efciency. Te analysis unveils considerable untapped export potential in various countries, suggesting a strategic avenue for market expansion. To optimize China’s apple export strategy, policymakers are advised to consider currency management, negotiate trade agreements that mitigate distance and per capita GDP efects, and target markets with high untapped potential, thereby facilitating sustainable growth in China’s apple export sector. [ABSTRACT FROM AUTHOR]

Historically, India has been a great investment opportunity for foreigners. However, in the last several decades, the country has experienced a substantial increase in its foreign direct investment (FDI) owing to several reforms made by the government. This study analyzes the determining factors behind Indian FDI inflows from its top source countries using the augmented gravity model. The sample period of this study ranges from 2000 to 2019, thus providing an updated analysis regarding FDI inflows. To attain the objective of this paper, we employ several econometric techniques such as Poisson pseudo maximum likelihood (PPML), feasible generalized least square (FGLS), and Newey-West standard error models. The findings show that the source country's per capita GDP is a negative determinant of FDI inflows in India from selected countries of the world. Moreover, FDI openness, gross fixed capital formation, and exports are found as the positive determinants of FDI inflows in India. The results imply that more export-oriented sectors can be identified for the selected nations, encouraging inflows. The country should look forward to incorporating new elements in old bilateral investment treaties as per the new conditions of the world economy. [ABSTRACT FROM AUTHOR]

We employ mobile network data referred to the area of Lombardy in Italy to investigate alternative touristic behaviours, such as same-day visits and overnight stays in Italy. We show that larger availability of tourism accommodations, cultural and natural endowments are relevant factors explaining overnight stays. Conversely, temporary entertainment and transportation facilities increase municipalities attractiveness for same-day visits. The results also highlight a trade-off in the capability of municipalities of being attractive in connection to both the tourism behaviours. For instance, higher tourists arrivals are observed in areas receiving limited visitors, coming from municipalities with low same-day visits outflows. We highlight mobile data offer an adequate level of spatial and temporal granularity and can be thus employed to support policy makers in the design of effective tourist management strategies. [ABSTRACT FROM AUTHOR]

The aim of this study is to comprehensively evaluate the economic network patterns and their influencing factors of the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) in China, considering population scale, economic development level, and land-resource endowment. By employing a modified gravity model and a social-network method, we quantitatively analyzed urban agglomeration integrity indices, such as network density, edge–core structure, cohesive-subgroup index, and urban individual index (e.g., centrality degree) of this region, encompassing nine cities in Guangdong Province and two special administrative regions. The results revealed significant changes in the economic network patterns within the GHMGBA over time. Furthermore, the quadratic assignment procedure correlation analysis index was used to identify the various factors affecting the strength of the economic interaction. The findings demonstrated an annual increase in the strength of economic interaction between cities and regions within the GHMGBA over the past 20 years, along with the emergence of a polycentric economic development pattern. The results also suggest that the spatial location and level of economic development are key determinants influencing the strength of economic linkages in this area. This study supports the conclusion that deepening exchanges and cooperation among core cities, bolstering economic development in sub-core cities, and facilitating the construction of an integrated regional transportation network will expedite the process of economic integration. [ABSTRACT FROM AUTHOR]

The purpose of this study is to use an extended gravity model to examine the factors that influence the demand for tourism from origin nations to Vietnam. Data from eleven major marketplaces were gathered for the study between 2005 and 2020. The research employs stepwise regression techniques to choose variables and testing procedures to identify the most suitable model among Ordinary Least Squares (OLS), Random Effects Model (REM), Fixed Effects Model (FEM), and Feasible Generalized Least Squares (FGLS) models. The gravity model comprises variables associated with geographic features, tourism supply capacity, demand attributes, and interconnected variables. Surprisingly, geographical distance holds no statistical significance in the international tourist demand model based on the gravity model, a phenomenon bolstered by globalization. Conversely, the emerging investment factor in restaurants and hotels emerges as the most pivotal determinant influencing tourism demand. Hence, the tourism sector must devise nation-specific policies that target key influencing factors and actively appeal to potential source markets to attract visitors. [ABSTRACT FROM AUTHOR]

As the hot spot and key topic in landscape ecology, the construction of ecological security pattern strives to maintain the integrity of landscape patterns and the continuity of the ecological process, and achieve sustainable development of the region. Taking Hefei City in China as a study area, according to the basal ecological features of Hefei City, the InVEST model was used to select three key indicators of ecosystem service importance (biodiversity, water yield, and carbon storage) to identify ecological sources; the resistance surface based on land use types was modified by the nighttime light (NTL) data; the potential ecological corridors were identified using minimal cumulative resistance model; lastly, the key ecological corridors were extracted using the gravity model. The results showed that: By combining 14 ecological sources, 91 potential ecological corridors, 16 key corridors, and ecological nodes, the ecological security pattern of Hefei City was constructed. Hefei's ecological source area is 1911.7 km2, accounting for 16.68% of the city's total area. It was dominated by water and woodland, which was distributed in the city's eastern and southern regions. The potential ecological corridor was 926.71 km long, while the key ecological corridor was 56.7 km long. Finally, A "One vertical and three horizontal" Hefei City ecological security pattern was built on this foundation. Our research results had important guiding significance for the sustainable utilization of ecological resources in Hefei City and could provide theoretical basis and technical support for ecological protection in Hefei City. [ABSTRACT FROM AUTHOR]

In the backdrop of criticism that the China-Pakistan Free Trade Agreement has disproportionately favored China, particularly in agricultural trade, there has been a surge in Pakistan's imports, leading to a trade deficit. This study attempts to evaluate the impact of CPFTA 1&2 on the vegetable exports of Pakistan which is an important sector of the agricultural industry. A panel data set of Pakistan's vegetable exports to its trading partners from 2003 to 2021 was analyzed with the extensively used gravity model of trade. The vegetable export data was sourced from the International Trade Centre (ITC) which is based on the Pakistan Bureau of Statistics. The results suggest that the China-Pakistan Free Trade Agreement (CPFTA-I) has a positive association with Pakistan's vegetable exports to China. However, trade liberalization with Afghanistan, Sri Lanka, and Malaysia plays a more substantial role in driving Pakistan's vegetable exports. CPFTA-II has not had a measurable or statistically significant impact on the vegetable exports of Pakistan as this period was highly influenced by COVID-19. The results of colonialism variables show that Pakistan is exporting more to countries with the same colonial history. Moreover, the results of the geographical variable suggest that Pakistan should explore more close markets to expand vegetable exports. Policy implications suggest the need to reduce trade costs, leverage CPEC infrastructure, enrich trade relations with neighboring countries, and involve business professionals in policy negotiations. [ABSTRACT FROM AUTHOR]

Despite numerous attempts to remove tariff and non-tariff barriers, the average number of barriers in the agricultural sector, particularly in the palm oil sector, is rising. Non-tariff effects are subjective, which makes them challenging to quantify. A new palm oil trade restrictiveness index that considers each trade barrier imposed on palm oil exports, such as tariff and non-tariff measures, is necessary to facilitate the sector's exports. Hence, this study aims to calculate the trade restrictiveness index (TRI) of palm oil and analyse its impact on Malaysia's and Indonesia's palm oil exports. This study uses a gravity model with Poisson pseudo-maximum likelihood (PPML) estimation to analyse the impact of trade barriers on world palm oil export for a sample of 59 major palm oil importing countries from 2009 to 2019. The study revealed that each importing country imposes different restrictions on Malaysia and Indonesia. The TRI showed a negative and significant relationship influencing palm oil exports in the case of Malaysia, while a positive and significant relationship for Indonesia. The policy implications of this study suggest that policymakers in both Malaysia and Indonesia should take proactive steps to comply with every criterion demanded by the importing country. [ABSTRACT FROM AUTHOR]

We examined how the unprecedented rise in freight rates in 2021 affected US containerized agricultural trade. We considered alternative measures of trade (value, volume, container numbers), as well as product, port, and partner‐country characteristics, and conducted separate analyses for exports and imports. Overall, we find that shipping costs have a substantial trade‐reducing effect. On average, 10% higher shipping costs reduce US agricultural export values by 0.58% and import values by 1.72%. For exports, we find a significant negative impact for several product categories. Our results suggest that policies addressing port congestion and shipping rate issues will have heterogenous outcomes. [ABSTRACT FROM AUTHOR]

The optimization of a tourism economic network is critical in the promotion of the high-quality development of a regional tourism economy. In order to explore the spatial network structure of the tourism economy of the Yangtze River Delta urban agglomeration and its influencing factors, this study used a modified gravity model and social network analysis methods for evaluation and analysis. The results show the following: (1) the spatial network of the tourism economy in the Yangtze River Delta urban agglomeration in 2016–2021 was characterized by significant non-equilibrium; however, that trend has weakened, and the tourism connections are now stronger in economically developed regions. (2) The density of the network structure was slightly strengthened. The structure of the tourism economy network shows an obvious core–periphery distribution pattern. The external radiation of the center city was enhanced, and the core area of the network expanded. (3) The concept of the "small world" is characterized by a significant evolution from five major associations to four major associations during the study period. (4) The quadratic assignment method (QAP) of regression analysis showed that tourism service reception capacity, tourism information flow, tourism resource endowments and transportation convenience make a significant contribution to the formation of the spatial network of inter-city tourism economic connections. The results of this study can provide a theoretical basis for the optimization of the tourism economic network of urban agglomerations and the scientific decision-making underpinning tourism economic cooperation. [ABSTRACT FROM AUTHOR]

Modern height systems are based on the combination of satellite positioning and gravity field models of high resolution. However, in many regions, especially developing or newly industrializing countries, there is no (reliable) regional gravity model at all, due to challenges such as limited data availability, unknown/low data quality, and missing metadata. This paper addresses this issue in a case study of Colombia, where eight decades of historical terrestrial and airborne gravity measurements are available but widely contain systematic errors, outliers, and biases. Correspondingly, processing strategies and structures are proposed and applied to validate and improve the quality of old gravity datasets. A novel method is developed based on spherical radial basis functions (SRBFs) for estimating biases, which are found in different airborne surveys with values exceeding 40 mGal. The validity of this bias estimation method is demonstrated both by a simulation test and by the evaluation of the airborne data in comparison to the SATOP (SAtellite-TOPography) model, which merges the satellite-only global gravity model GOCO06s with the Earth2014 topography model. The terrestrial and airborne data are then combined with a global gravity model (GGM), ultra-high-resolution topography models, as well as altimetry-derived gravity anomalies from DTU21GRA for the offshore areas. The results are presented in terms of height anomalies (QGeoidCOL2023), and they are thoroughly validated using GPS/leveling data both in the absolute and relative manner. The standard deviation in comparison to the GPS/leveling data after applying a correction surface to account for the datum inconsistencies amounts to 15.76 cm, which is 27% smaller compared to the mean standard deviation value given by five recent high-resolution GGMs, and 36% smaller than the one delivered by the latest South American quasi-geoid model QGEOID2021. The relative validation results show that QGeoidCOL2023 performs better, i.e., delivers lower RMS errors than the GGMs and QGEOID2021 in all the baseline length groups. These results indicate the validity and benefits of the developed methods and procedures, which can be used for other data-challenging areas to facilitate the realization of geopotential-based height systems. [ABSTRACT FROM AUTHOR]

Regional integration in Africa is deepening, and the existing regional groupings are making frantic efforts to remove barriers to trade. One way in which trade among countries can be promoted is through the establishment of free trade areas with member-states. However, regulatory quality that supports international trade in most African countries is exceptionally low. This study investigates the effect of the Common Market for Eastern and Southern Africa (COMESA) free trade area (FTA) on the bilateral export efficiency of member-states over the period 1997–2021. The results obtained using a stochastic frontier specification of the gravity model and panel data of 16 exporting COMESA member-states show a positive effect of the COMESA free trade area on export efficiency. In addition, the study finds regulatory quality to have a positive impact on export efficiency. Controlling for regulatory quality, the results also show that the FTA stimulates export efficiency. Hence, non-FTA COMESA members ought to contemplate joining the FTA in order to expand their respective exports with other member-states to their maximum potential. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and the resulting economic recession negatively affected many people's physical, social, and psychological health and has been shown to change population-level mobility, but little attention has been given to park visitations as an indicator. Estimating the frequency of park visitations from aggregated mobility data of all the parks in Washington State (USA), we study trends in park use one year prior to and two years during the COVID-19 pandemic. Our findings indicate that the gravity model is a robust model for the park visitation behavior in different spatial resolutions of city level and state level and different socio-economical classes. Incorporating network structure, our detailed analysis highlights that high-income level residents changed their recreational behavior by visiting their local parks more and a broader recreational options outside of their local census area; whereas the low-income residents changed their visitation behavior by reducing their recreational choices. While it is renown that the COVID-19 pandemic affected the population mobility, little attention has been given to modeling the structural patterns of park visitations, and how these patterns have changed. The authors perform such analysis via gravity model as well as network structure analysis, and link the recreational propensity to socio-economical status of the population. [ABSTRACT FROM AUTHOR]

Cross-border mergers and acquisitions (M&As) have grown rapidly in recent years and are a major part of foreign direct investment (FDI). However, M&A distribution is highly skewed, with most of the activity concentrated in certain countries and even in certain cities. The fact that only a handful of cities account for most M&As raises a research question as to what city attributes attract foreign investment. Unlike many previous studies that have relied on a gravity model approach using the bilateral volume of FDI, this study examines the determinants of cross-border M&As by applying an FDI gravity model to inter-city investment flows. The results based on panel data of M&A flow across 44 major cities in the world from 2010 to 2017, reveal that the gravity model fits well for even the inter-city data, and show that besides the basic attributes used in conventional gravity models, such as market size and distance between origin city and destination city, and urban-specific attributes such as the agglomeration of the world's top-ranked firms and international accessibility are positively associated with cross-border inward M&As. [ABSTRACT FROM AUTHOR]

The improved gravity model was used to determine the spatial correlation of carbon emission efficiency (CEE) among cities, and then the spatial correlation network of CEE of 284 Chinese cities from 2006 to 2019 was constructed for the first time. Based on the social network analysis method, the structural characteristics and influencing factors of the network were analyzed. It was found that: (1) The spatial correlation of CEE at city level is obvious, the overall correlation intensity is increasing, and the aggregation of correlation is significant. (2) The network shows a core–edge structure, cities with high economic development, such as Shenzhen, Beijing, Nanjing, Guangzhou and Shanghai, occupying the center of the network, while cities with relatively weak development such as Heihe, Jiuquan, Baotou and Baoshan are at the edge. (3) The network can be divided into four plates, with sparse association within the plate and the strong spillover effect between the plates. (4) Spatial adjacency relationship, differences in economic development, industrial development, green technology innovation and energy consumption have significant positive effects on establishing a spatial network, while geographical distance has significant negative effects on it. The results can help governments to clearly realize the correlation of CEE between cities and identify the role that each city can play in improving the overall CEE, so as to provide guidance for governments to further formulate accurate carbon emission reduction policies. [ABSTRACT FROM AUTHOR]