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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]

The multi-modal two-step floating catchment area (MM-2SFCA) method is an extension of the two-step floating catchment area (2SFCA) method that incorporates the impact of different transportation modes, thereby facilitating more accurate calculations of the spatial accessibility of public facilities in urban areas. However, the MM-2SFCA method does not account for the impact of distance within the search radius on supply–demand capacities, and it assumes an idealized supply–demand relationship. This paper introduces the gravity model into the MM-2SFCA method, proposing a multi-modal gravity-based 2SFCA (MM-G2SFCA) method to better account for distance decay and supply–demand relationships. Furthermore, a standardized gravity model is proposed based on the traditional gravity model. This model imposes constraints on upper and lower limits for distance decay weights without compromising the fundamental curve characteristics of the gravity model, thereby avoiding extreme weight scenarios. The accessibility of public hospitals in Shenzhen is evaluated through the integration of basic geographic information data, resident travel data, and official statistical data. The findings demonstrate that the standardized gravity model effectively addresses the issue of excessively high local distance weights in the traditional gravity model, making it more suitable as a distance decay function. The MM-G2SFCA method improves the consideration of distance and supply–demand relationships, thereby facilitating a more rational distribution of accessibility on a global scale. This study discovers differences in the spatial allocation of public hospital resources across the Shenzhen's districts. Accessibility within the metropolitan core is significantly higher than that outside the core. Additionally, there is a notable difference in the level of accessibility among the districts. Accessibility is found to be better in district centers and along the main traffic arteries. [ABSTRACT FROM AUTHOR]

AbstractGlobal freight distribution patterns have been affected by trading policies and the pandemic outbreak. The Belt and Road Initiative, trade conflicts, and the COVID-19 pandemic have changed the global logistics flow, shifting cargos from maritime and air transport to railway transport along the countries in the Eurasian Landbridge. Though railway freight emits less carbon than road truck transportation, the increased use of railway freight brings in a higher volume of carbon emissions to cities located along the landbridges. Achieving net zero carbon emission is becoming more important, but there is a lack of literature in assessing the environmental impact of cross-border railway logistics transportation among Belt and Road countries. A novel two-stage multilateral trade-based prediction model is developed, integrating a modified gravity model and nonlinear autoregressive neural network for trade and emission forecasting. The model evaluates railway freight along the landbridge over ten years and forecasts the impact of carbon emissions from trading and logistics along the corridor in the subsequent five years. It further analyses the emissions impact of the proposed Third Eurasian Landbridge and the extended Second Eurasian Landbridge. The findings provide insights for the development of railway freight transport, considering trade and logistics flow, carbon emission mitigation strategies, and sustainability impact between China and other Belt and Road countries. While countries such as India and Kazakhstan were forecast to have significant amounts of carbon emissions in the projected period, the rapid growths in locations with smaller emission amounts such as Kunming and Georgia should draw attention and require continuous monitoring. [ABSTRACT FROM AUTHOR]

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.)

To predict regional freight flow distribution more accurately and depict the connections and interactions between regional economies, a method combining a clustering algorithm and an improved gravity model was proposed. First, Pearson correlation analysis is performed on the influencing factors of freight. The K-means ++ algorithm was then used for node clustering, considering the heterogeneity and similarity between different regions, to study origin-destination (OD) pairs in detail. Next, the traditional gravity model was improved by introducing parameters such as freight influencing factors, social connection strength, and an impedance function constructed from distance and time costs. This makes the model more adaptable to different regional traffic characteristics, enhancing its generality and applicability. Finally, the improved gravity model was used to predict freight flow distribution in Yunnan Province, and the results are compared with those of the traditional gravity model. The results show that the improved gravity model improves prediction accuracy by 57. 75% and stability by 54. 66% compared to the traditional gravity model. This method significantly enhances prediction accuracy, providing a more reliable approach for regional freight flow forecasting. [ABSTRACT FROM AUTHOR]

Green spaces and blue spaces in cities provide a wealth of benefits to the urban social–ecological system. Unfortunately, urban development fragments natural habitats, reducing connectivity and biodiversity. Urban green–blue infrastructure (UGI) networks can mitigate these effects by providing ecological corridors that enhance habitat connectivity. This study examined UGI connectivity for two indicator species in a rapidly developing city in the southern United States. We mapped and analyzed UGI at a high resolution (0.6 m) across the entire city, with a focus on semi-natural areas in private land and residential neighborhoods. Integrating graph theory and a gravity model, we assessed structural UGI networks and ranked them based on their ability to support functional connectivity. Most of the potential habitat corridors we mapped in this project traversed private lands, including 58% of the priority habitat for the Golden-cheeked Warbler and 69% of the priority habitat for the Rio Grande Wild Turkey. Riparian zones and other areas with dense tree cover were critical linkages in these habitat corridors. Our findings illustrate the important role that private semi-natural areas play in UGI, habitat connectivity, and essential ecosystem services. [ABSTRACT FROM AUTHOR]

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]

In this article, we explore the effects of China's foreign aid on its exports. To do this, we use a sample of 165 countries during the period 2000–2014 and employ a gravity model. We find that the return on Chinese exports for every dollar spent on foreign aid is from $0.156 to $0.4, at the aggregate level. The aid provided in past periods continues to promote China's exports. We also show, while taking into account aid heterogeneity, that China experiences a higher return in terms of exports when providing development aid intended for infrastructure, to the recipients. Additionally, we find that China's international aid helps the country to trade more with similar income-level economies. Hence, it can, to a certain extent, foster South-South trade relations. [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.)

This study employs the stochastic frontier gravity model (SFGM) to objectively assess the determinants of India’s rice exports from 2001 to 2019 across 22 major export destinations, highlighting untapped export potential and providing actionable policy recommendations for enhancing competitiveness in global rice markets. Results show that India's economic growth (GDP) and the GDP of importing nations positively impact rice exports. Conversely, geographical distances (representing transportation costs) and higher import tariffs act as deterrents. The devaluation of the Indian rupee positively influences export revenues. Common language benefits exports, while regional trade agreements show minimal impact. The study estimates significant untapped export potential between India and its partners, emphasizing the need for improved trade facilitation, logistics, and agreements.To maximize India's rice export potential, policymakers should prioritize quality compliance, streamline regulations, and invest in infrastructure and R&D for rice cultivars. Negotiating favorable trade agreements and implementing existing export policies like the New Agricultural Export Policy will aid market access and competitiveness. [ABSTRACT FROM AUTHOR]

A variety of complex socioeconomic phenomena, for example, migration, commuting, and trade can be abstracted by spatial interaction networks, where nodes represent geographic locations and weighted edges convey the interaction and its strength. However, obtaining fine-grained spatial interaction data is very challenging in practice due to limitations in collection methods and costs, so spatial interaction data such as transportation data and trade data are often only available at a coarse scale. Here, we propose a gravity downscaling (GD) method based on readily accessible socioeconomic data and the gravity law to infer fine-grained interactions from coarse-grained data. GD assumes that interactions of different spatial scales are governed by the similar gravity law and thus can transfer the parameters estimated from coarse-grained regions to fine-grained regions. Results show that GD has an average improvement of 24.6% in Mean Absolute Percentage Error over alternative downscaling methods (i.e., the areal-weighted method and machine learning models) across datasets with different spatial scales and in various regions. Using simple assumptions, GD enables accurate downscaling of spatial interactions, making it applicable to a wide range of fields, including human mobility, transportation, and trade. [ABSTRACT FROM AUTHOR]

The gravity model is widely used to estimate the effect of a reduction in trade costs on international trade flows. Researchers face many analytical decisions in their choice for an empirical strategy. This paper uses a specification curve analysis method to study the effect of these choices on estimated trade effects. I find that despite significant heterogeneity in estimated trade effects, the distribution in the empirical international trade literature overlaps fairly well with the estimates in this specification curve analysis. However, individual decisions have a significant impact on average estimated trade effects. [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]

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]

Trade is considered one of the main drivers of a country's economic growth and development. Therefore, a successful analysis that identifies the bilateral trade flows, their determinants, and the regional integration costs and benefits opens new horizons for international trade perspectives. This study examines the effects of new and existing regional agreements on the international trade patterns of Western Balkan countries based on the Albanian case. In this regard, an extended trade gravity model is applied with a panel data set of trade flows between Albania and 43 of its regional strategic partners during the period of 2008 to 2022. This work considers two different similarity indexes to explain the effect of the economic structures of partner countries on their trade volumes: the relative factor endowment and the absolute factor endowment. The first is used to test the Linder Hypothesis, and the latter is used to test the effect of similarity in economic size between trading partners. Empirical results indicate that the effect of the selected explanatory variables, such as transportation costs, economic size, economic strength, exchange rate, and their relative as well as absolute endowment, is within expectations. Unexpectedly, the domestic economic size and strength are found to be insignificant in explaining the import flows and inversely proportional to the exports of Albania. Finally, it is indicated that trade flows are clearly dependent on traditional ties rather than on new incentives like the Open Balkan, which cannot offer a new regional center of gravity. To the best of our knowledge, this is the first time that the gravity of the Open Balkan initiative has been tested for one of the participating countries. The study concludes that while the Open Balkan initiative shows potential, the Berlin Process remains a more reliable path toward EU integration for Albania. [ABSTRACT FROM AUTHOR]

Copyright of Mexican Journal of Economics & Finance / Revista Mexicana de Economia y Finanzas is the property of Instituto Mexicano de Ejecutivos de Finanzas 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.)

Studies analyzing the pattern of international refugee flows have so far focussed on movements to OECD destinations, even though the vast majority of refugees live in non‐OECD countries. Employing a standard gravity model of international migration, we fill this research gap by investigating the impact of destination country characteristics on south‐south refugee movements over the period 2004–2019. Our findings suggest that refugees tend to move to safe neighboring countries but also positively respond to local pull factors such as relatively high per‐capita income levels and the availability of education and health services when choosing their country of destination. Donors have the ability to affect the direction of south‐south refugee movements by investing in the social infrastructure of potential destination countries. [ABSTRACT FROM AUTHOR]

This study uses a panel of monthly data to investigate the effects of antidumping (AD) duties imposed on shrimp imports to the U.S. The results from the augmented gravity model show that initiating AD investigations and the final AD duty rate harm trade with the named countries. Distribution of AD duties among domestic industry producers stimulates a positive supply response. Rejection of imports by European countries for food safety reasons deflects trade to the U.S. The pass-through effects of the AD duty rate (and exchange rate) on import prices are small, indicating minimal adverse effects of AD policy on consumer welfare. [ABSTRACT FROM AUTHOR]

Abstract 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.

When the ground communication base stations in the target area are severely destroyed, the deployment of Unmanned Aerial Vehicle (UAV) ad hoc networks can provide people with temporary communication services. Therefore, it is necessary to design a multi-UAVs cooperative control strategy to achieve better communication coverage and lower energy consumption. In this paper, we propose a multi-UAVs coverage model based on Adaptive Virtual Force-directed Particle Swarm Optimization (AVF-PSO) strategy. In particular, we first introduce the gravity model into the traditional Particle Swarm Optimization (PSO) algorithm so as to increase the probability of full coverage. Then, the energy consumption is included in the calculation of the fitness function so that maximum coverage and energy consumption can be balanced. Finally, in order to reduce the communication interference between UAVs, we design an adaptive lift control strategy based on the repulsion model to reduce the repeated coverage of multi-UAVs. Experimental results show that the proposed coverage strategy based on gravity model outperforms the existing state-of-the-art approaches. For example, in the target area of any size, the coverage rate and the repeated coverage rate of the proposed multi-UAVs scheduling are improved by 6.9–29.1%, and 2.0–56.1%, respectively. Moreover, the proposed scheduling algorithm is high adaptable to diverse execution environments.© 2022 Published by Elsevier Ltd.

Purpose – This study aims to identify the location of regional growth poles in Vietnam. Design/methodology/approach – A potential gravity model is constructed to estimate how attractive a location is in relation to other locations within a specifically defined region using spatial interpolation tools. Findings – We present the calculated and visualized potential gravitational energy (or attractiveness) for every province showcasing regional growth poles in Vietnam. Research limitations/implications – Graphical evidence need to be supported by statistical analysis to establish causal effects of driving factors on growth measures. Originality/value – This is the first study to use a potential gravity model to study growth poles in Vietnam.

Abstract A variety of complex socioeconomic phenomena, for example, migration, commuting, and trade can be abstracted by spatial interaction networks, where nodes represent geographic locations and weighted edges convey the interaction and its strength. However, obtaining fine-grained spatial interaction data is very challenging in practice due to limitations in collection methods and costs, so spatial interaction data such as transportation data and trade data are often only available at a coarse scale. Here, we propose a gravity downscaling (GD) method based on readily accessible socioeconomic data and the gravity law to infer fine-grained interactions from coarse-grained data. GD assumes that interactions of different spatial scales are governed by the similar gravity law and thus can transfer the parameters estimated from coarse-grained regions to fine-grained regions. Results show that GD has an average improvement of 24.6% in Mean Absolute Percentage Error over alternative downscaling methods (i.e., the areal-weighted method and machine learning models) across datasets with different spatial scales and in various regions. Using simple assumptions, GD enables accurate downscaling of spatial interactions, making it applicable to a wide range of fields, including human mobility, transportation, and trade.

ABSTRACTThe rapid surge in large-scale land acquisitions (LSLAs) has been triggered by the convergence of food, financial and environmental crises in the late 2000s. Since the 2008 commodity price spike, several Asian countries have become preferential targets for LSLAs carried out by foreign companies and governments. The rising interest in Asian farmlands and natural resources arose in a complex set of political transitions and socioeconomic dynamics that have shaped the whole continent in the last decades. This study relies on a dataset built on different data sources, from 2003 to 2021 for a total of 14,724 million hectares involved in LSLAs in Asia. The southeastern region is the most targeted one, with Indonesia and the Philippines as the principal host countries. The main investors are intraregional and, especially in private or stock-exchange listed companies, are from China and Malaysia, who intend to produce palm oil or rubber. Results partially confirm the initial hypothesis, showing that the endowment of land and water resources in host countries is positively related to the amount of land acquired. Findings also show that investors are looking for free market areas, with low trade barriers and low fiscal pressure, where the protection of workers’ rights is lower than that in their homeland.

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.

The Internet has become essential in increasing output between corporate and country levels. However, the impact of the Internet on trading potential still needs to be known. On the other hand, Indonesia has great potential to export agricultural food products in global trade. Therefore, the relationship between the Internet development and agri-food export potential could be explored. This study aims to investigate the effect of Internet development on Indonesia’s export potential in the global market. The export potential estimation was measured using gravity estimation in 124 destination countries from 2010 to 2020. Furthermore, the panel regression was employed to determine the three indicators of Internet development: Internet users, secure Internet servers, and fixed broadband subscriptions on Indonesia’s agricultural export potential. This study also utilized simulation due to the possibility of rising the number of Internet indicators. The results revealed several positive factors of Indonesia’s agricultural exports, such as importers’ gross domestic bruto (GDP), contagious border, and colonial relationship. Otherwise, geographical distance, exchange rate, and being a landlocked country negatively affected Indonesia’s agricultural exports. Indonesia possessed a greater potential for agricultural exports in Europe, especially in the conditions of emerging and developing economies. There were 85 destination countries with higher potential for Indonesia’s agri-food export. Additionally, Internet users and secure Internet servers positively influenced the agricultural export potential to target countries. The simulation revealed that improving Internet indicators boosted the new market rather than raising the export value to target countries.

Mangosteen is one of Thailand’s major agricultural exports, generating income and employment in the country’s agricultural sector. This research examined whether Thailand’s durian fruit can complement mangosteen in the global market. The country-pair and time-fixed effects of Poisson maximum likelihood were employed in the model, and the estimated results were separated into eight cases. The findings indicate that Thailand’s durian complements mangosteen in the global market. Thai mangosteen exporters are advised to implement high pricing strategies, divide their market into upper-middle-income and high-income nations, and promote durian along with mangosteen. Improving the skill of mangosteen farmers to achieve a higher yield and quality than competitors is an essential factor.

This study estimates the influence of three significant concepts on the international trade flows between countries participating in the One Belt One Road (OBOR) initiative and Regional Comprehensive Economic Partnership (RCEP). These concepts, which have been previously examined individually in literature, include the effects of intranational trade, international borders and more importantly, regional trade agreements, on international trade flows. This study employs the structural gravity model with data for various variables such as international trade, intranational trade and regional trade agreements (RTAs) ranging between 1999 and 2019. The approach used in this study produces econometrically robust estimates of the impact of RTAs on trade among OBOR member countries, while various sensitivity analyses including phasing-in effect of the RTAs, endogeneity, reverse causality, and multilateral trade resistances. The findings of this study indicate that the impact of RTAs on trade between OBOR and RCEP countries becomes insignificant when the effects of globalization are isolated. Additionally, the declining influence of international borders on trade flows between OBOR and RCEP countries suggests that trade is facilitated to a greater extent between open economies.

With the rapid development of China’s economy and society, the income level of Chinese residents is increasing day by day, and the dietary consumption structure of domestic residents is constantly optimized and upgraded. The consumption demand for livestock products such as meat, eggs and milk, and corn starch industrial products is increasing day by day. Therefore, as the main raw material of feed industry and deep processing owners, the consumption scale of China corn market is constantly expanding. However, the corresponding domestic corn production scale has not expanded, and the domestic corn production presents an obvious problem of insufficient supply scale, which leads to a sharp and rapid increase in the number of corn imports in China, which seriously impacts the domestic corn market and affects China’s healthy development of corn industry. In recent years, the continuous spread of the COVID-19 epidemic has seriously affected the global grain production and trade. The fierce military conflict between Russia and Ukraine, the two major grain exporting countries, has once again brought a serious adverse impact on the supply and price of the global grain market, resulting in an increase in the import cost of corn in China and a change in the import pattern of corn in China. In this regard, this study analyzes the current situation of corn production and import trade in China, and based on the relevant trade data between China and major corn importing countries from 2013 to 2022, establishes a trade gravity model to quantitatively evaluate the main factors affecting China’s corn import trade, and analyzes the trade potential of sample countries. It was found that in 2022, China’s import and export trade volume and trade value were 20.62 million tons and 7.11 billion US dollars, respectively, compared with 2013, trade volume and trade volume increased by 6.3 times. Statistics on the potential types of various trading countries showed that the proportion of potential countries was 14.2%, and Brazil had the greatest potential in China’s corn import trade. The proportion of potential expanding countries is about 71.4%, and Laos is a mature country with less opportunities for further development. In order to promote the benign development of the domestic corn industry and the development of China’s corn import trade, this paper puts forward a series of countermeasure suggestions based on the above research.

In the conditions of instability of the Russian economy, Russian regions have faced the problem of finding new directions of foreign economic development. Mathematical modeling methods, considering the distance between partner regions and their economies volumes, can be effective tools for solving the problem. The article touches upon the modeling foreign trade relations issues in the Republic of Tatarstan on the gravity models’ basis. The purpose of the study is to identify potential trade partners and assess the prospects for the export relations development in the Republic of Tatarstan. The structure, dynamics, and main directions of exports of the constituent entity have been analyzed. Potential trade partners of the Republic of Tatarstan among the Commonwealth of Independent States countries have been identified using the classical gravity model based on assessing the internal regional product and the distance among the regions. The prospects of foreign trade relations with Belarus and the Republic of Uzbekistan have been assessed. Based on J. Tinbergen’s gravity model models of interaction among the regions have been built and forecast values of export volumes for the short term calculated. It was revealed that the Republic of Azerbaijan can become a potential partner for the Republic of Tatarstan. The analysis of the forecast data on the domestic regional product of the Republic of Tatarstan and the gross domestic product of Azerbaijan in 2023 suggests that the exports volume between these entities is expectedly high.

This study aims to assess the impact of the Korean Wave on the export of consumer goods from South Korea to the ASEAN-5 countries (Indonesia, Malaysia, Thailand, Singapore, and the Philippines) from 2010 to 2020. This study took into account various factors to analyze the export dynamics, such as gross domestic product (GDP) per capita, interest rates, Google search trends, and the geographical distance between countries. Cultural goods exported from South Korea were used as a measure of the Korean Wave, employing the gravity model and the fixed effects model (FEM) for analysis. The results of this study indicated a positive impact of the Korean Wave variable on the export of South Korean consumer goods. Additionally, the findings revealed that variables such as South Korea’s GDP per capita, distance, and exchange rates had a negative impact on the export of such goods. Furthermore, this study highlights the positive impacts of the ASEAN-5 countries’ GDP per capita and Google search trends on the export of South Korean consumer goods.

Abstract 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 The selection of research topics by scientists can be viewed as an exploration process conducted by individuals with cognitive limitations traversing a complex cognitive landscape influenced by both individual and social factors. While existing theoretical investigations have provided valuable insights, the intricate and multifaceted nature of modern science hinders the implementation of empirical experiments. This study leverages advancements in Geographic Information System (GIS) techniques to investigate the patterns and dynamic mechanisms of topic-transition among scientists. By constructing the knowledge space across 6 large-scale disciplines, we depict the trajectories of scientists’ topic transitions within this space, measuring the flow and distance of research regions across different sub-spaces. Our findings reveal a predominantly conservative pattern of topic transition at the individual level, with scientists primarily exploring local knowledge spaces. Furthermore, simulation modeling analysis identifies research intensity, driven by the concentration of scientists within a specific region, as the key facilitator of topic transition. Conversely, the knowledge distance between fields serves as a significant barrier to exploration. Notably, despite potential opportunities for breakthrough discoveries at the intersection of subfields, empirical evidence suggests that these opportunities do not exert a strong pull on scientists, leading them to favor familiar research areas. Our study provides valuable insights into the exploration dynamics of scientific knowledge production, highlighting the influence of individual cognition, social factors, and the intrinsic structure of the knowledge landscape itself. These findings offer a framework for understanding and potentially shaping the course of scientific progress.

Global services trade declined by 20% during 2020 with significant heterogeneity across countries, geographical regions and sectors. We present stylized facts and provide hypotheses and empirical analysis seeking to explain this heterogeneity. The decline is found to be correlated with COVID-19 case and mortality rates; stringency of imposed lockdowns; the decline in merchandise trade; and with different ways of transacting services trade. The latter depends on the sectoral composition of services trade across countries, which in turn emanates from more fundamental determinants of comparative advantage in services, generating testable hypotheses to explain the observed heterogeneity in services trade decline. Focusing on attributes of digitalization and the role of value-chains, we find that human-capital-intensive countries with favourable digital-trade policies and greater ability to leverage ICT infrastructure were associated with relatively smaller declines. Moreover, the expected role of GVC-integration in accentuating the services trade decline finds little support in empirical results across sectors providing evidence instead for the GVC-resilience narrative. [ABSTRACT FROM AUTHOR]

The gravity model is a widely recognized tool for estimating the movement of people and goods. In this study, we introduce two gravitational variables, population size and regional GDP per capita (RGDPPC), to explain the characteristics of population movement between and within cities in South Korea. A log-linearized gravity model is employed to run regression analyses at three spatial levels: the national level (encompassing the entirety of South Korea), the metropolitan level (focusing on the Seoul and Busan Metropolitan Transportation Areas) and the city level (specifically in Seoul and Busan). The study incorporates data on various modes of transportation from 246 of the 250 municipalities in South Korea. Predictive performance of the model is better when utilizing national-level data. However, as spatial area decreases and population density increases, the models explanatory power decreases significantly when relying solely on data related to either population size or RGDPPC. The findings suggest that incorporation of both population size and RGDPPC into the gravity model best captures the dynamics of traffic flow within economically integrated regions. This relationship is analogous to gravitational fields generated by two distinct types of mass. Including both population size and RGDPPC, the gravity model can be leveraged effectively to estimate traffic patterns, particularly within regions characterized by high economic integration. [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]

This study aims to assess the impact of the Korean Wave on the export of consumer goods from South Korea to the ASEAN-5 countries (Indonesia, Malaysia, Thailand, Singapore, and the Philippines) from 2010 to 2020. This study took into account various factors to analyze the export dynamics, such as gross domestic product (GDP) per capita, interest rates, Google search trends, and the geographical distance between countries. Cultural goods exported from South Korea were used as a measure of the Korean Wave, employing the gravity model and the fixed effects model (FEM) for analysis. The results of this study indicated a positive impact of the Korean Wave variable on the export of South Korean consumer goods. Additionally, the findings revealed that variables such as South Korea’s GDP per capita, distance, and exchange rates had a negative impact on the export of such goods. Furthermore, this study highlights the positive impacts of the ASEAN-5 countries’ GDP per capita and Google search trends on the export of South Korean consumer goods. [ABSTRACT FROM AUTHOR]

In this study, we investigate the potential effects of the Regional Comprehensive Economic Partnership (RCEP) agreement on Vietnam's rice exports from 2000 to 2016. For this analysis, we employ the panel data augmented gravity model with some modifications. The estimated results suggest a positive relationship between Vietnam's per capita export and the capita real gross domestic product (GDP) of the importer, Vietnam's rice production, export price, and ASEAN dummy. We confirm that there is a negative relationship between Vietnam's per capita rice export value and import country agricultural land and import tariffs. Additionally, this paper forecasts Vietnam's rice export value per capita at each market in RCEP partners by using the autoregressive model. Our forecast results show that among RCEP members, Vietnam has potential markets if import tariff reductions are lowered in Singapore, Brunei, Korea, Japan, and Malaysia. To reap the benefits of rice exports' potential, Vietnam must move from low-grade and cheap rice to high-quality rice production instead of expanding rice production and exports with the following implications: changing its present rice trading partners to potential markets and adopting market-oriented policies to meet the international demand and to increase the export elasticity of rice. [ABSTRACT FROM AUTHOR]

Regional trade agreements (RTAs) have experienced significant growth worldwide, leading to an increase in studies assessing their impact on bilateral trade flows. With the availability of disaggregated trade data, numerous studies have examined the influence of these agreements specifically on agri‐food trade. However, the results of these studies exhibit heterogeneity, posing challenges for policymakers seeking to understand the effects of RTAs on agri‐food trade. To address this issue, we conducted a meta‐analysis of 61 studies investigating the effects of various RTAs on agri‐food trade. Using funnel asymmetric testing, our analysis reveals the presence of publication bias in the existing literature. By accounting for this bias, we found robust evidence that RTAs positively and significantly promote agri‐food trade. Notably, the extent of this effect depends on the depth of economic integration within the RTA, distinguishing between customs unions and free trade agreements, as well as the classification of agri‐food products as primary or processed. The ex‐post effects of RTAs on agri‐food trade are less pronounced when we control for both publication bias and heterogeneity, compared to controlling only for publication bias. [ABSTRACT FROM AUTHOR]

Joint innovation across countries plays a vital role in international networks of knowledge-intensive businesses. We study how the cultural backgrounds of collaborators influence success in international innovation. Intercultural proximity implies shared values and norms that can engender trust and cooperation in innovation. However, social fragmentation can induce conflict and mistrust, whereas joint innovation can progress through the tolerance and acceptance of different views. Our gravity model analysis of international patent cooperation data shows that social fragmentation complements intercultural proximity along the social identity dimensions of religion, ethnicity, and language to promote joint innovation. Intercultural proximity operates through trust, especially for countries with weak intellectual property rights laws, while social fragmentation operates through tolerance and acceptance, especially for countries with strong IPR laws. Economic strength, trade, and institutional differences are also important predictors of collaborative innovation. We confirm that geographical distance between countries lowers cooperation, but it cannot explain away the positive effects of intercultural proximity and social fragmentation. Plain English Summary: Co-innovation increases with intercultural proximity – and even more so when countries are socially fragmented. International joint innovation allows knowledge-intensive businesses to synergistically draw upon the ideas, expertise, and experience of innovators from their respective cultures (countries). However, such collaborations are often hampered by the uncertainty of partner exploitation and free-riding especially in the absence of formal institutions such as strong intellectual property rights (IPR) protection. In such cases, while intercultural proximity (e.g., along the dimensions of religion, ethnicity, and language) can promote cooperation through the informal institution of trust, social fragmentation can induce mistrust and in turn hamper collaboration. This is puzzling in light of evidence that fragmentation also promotes innovation. Thus, we empirically show that the positive effect of intercultural proximity operates through trust especially when IPR protection is weak. The positive effect of fragmentation on international patent cooperation operates through tolerance and acceptance especially when IPR protection is strong. This implies that nurturing tolerance and acceptance while strengthening IPR and developing the intellectual property ecosystem in fragmented societies, building intercultural trust, and increasing diversity in countries, alliances, or firms can promote co-patenting success. [ABSTRACT FROM AUTHOR]

Scientific research has increasingly been becoming a group effort, which has been the main driving force in the growth of scientific productivity. While there have been multiple contributions toward intercity and interregional interactions in the analysis of these collaborations, intracity studies have been lagging. This study addresses this gap with the example of Istanbul, Turkey. Turkey has implemented a radical expansion policy in the spatial organization of universities after 2006 during which Istanbul has further strengthened its role as a science hub for the country. However, despite the increase in the number of universities and their personnel, the role of their collaborations in knowledge production has not been studied. In this setting, the study uses a gravity model for the measurement of Istanbul's intracity collaborations in six research fields. The study measures intracity coauthorship chances by spatial proximity, domestic coauthorships, international coauthorships, institutional distance based on public-private university coauthorships and the difference between founding years. The results show that spatial proximity within the city is mostly relevant for soft science fields such as humanities and social sciences. In comparison, intracity coauthorships in hard science fields grow with domestic coauthorships beyond Istanbul. Additionally, coauthorships between public and private universities did not have a positive association with higher coauthorship chances while differences in founding years did not prevent the growth of coauthorships despite organisational differences between new and old universities. [ABSTRACT FROM AUTHOR]

We examine the impact of terror on international trade in financial services and the role of financial institutions in alleviating this impact. Using a sample of 67 countries from 2000 to 2020, we find that a 10% increase in the number of terrorist incidents in the importer and/or the exporter results, on average, in a 1.77–2.05% annual reduction in their bilateral financial service trade which is more economically significant than what has been documented for trade in commodities. Top exporters and importers of financial services, however, are less affected by the incidence of terrorism. Confirming the critically important role of systemic stability, we further find that financial institutions' stability (measured by the Z score) is the most powerful factor in mitigating the detrimental impact of terrorism on trade. There is also some limited evidence that exporting countries where financial institutions exhibit more efficiency (measured as the ratio of overhead costs to total assets) cope better with terrorism. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the effect of natural hazards on migration in the United States (US) and the importance of spatial dependence in such assessments. We use two measures of migration: migration rates and flows. The model for migration flows is estimated using the gravity model, whereas out- and in-migration rates are analyzed using the spatial Durbin model. Our results indicate there is a major and significant impact of economic damage caused by natural hazards on out-migration rates and outward migration flows. In the spatial Durbin model and in the gravity model, a $1,000 dollar damage per capita is associated with an increase in out-migration of 16.0% and 9.1%, respectively. However, when spatial dependence is not accounted for, the effect of natural hazards on migration is substantially overestimated: the coefficients are 1.5–2 times larger when spatial dependence is not considered. [ABSTRACT FROM AUTHOR]

Introduction: With the increase in non-tariff measures (NTMs) in recent years, understanding their impact on trade policies and agricultural exports is of utmost importance for countries like Sri Lanka, where the proliferation of NTMs has posed substantial impediments to its mango export industry. However, studying NTMs can be challenging due to their complex nature, diverse range, and limited information availability. Methods: This research aims to investigate the significant effect of NTMs on Sri Lankan mango exports, identify the pivotal drivers influencing mango exports, and analyze the performance of mango exports in Sri Lanka. This study utilized a panel dataset of 16 importing countries spanning the period from 2000 to 2021. The primary focus was on examining NTM-related challenges and obstacles faced by the mango export industry in Sri Lanka. The identification and quantification of these obstacles were achieved through a multifaceted approach in which assessment of NTM-related rejections, both domestic and overseas, evaluation of NTM incidences using frequency and coverage ratio measures, and the deployment of various gravity model equations to quantify the effect of NTMs were taken into consideration. Probit, Ordinary Least Square, Random Effects, and Poisson Pseudo Maximum Likelihood estimation techniques were utilized for data analysis. Results: The findings indicate a significant inverse correlation between the increase in the total count of NTMs and Sri Lankan mango exports if the country aims to export more mangoes to relevant markets, while Sanitary and Phytosanitary Measures (SPS), Technical Barriers to Trade (TBT), and Pre-shipment Inspection (PSI) contributed to increased mango exports. Among other explanatory variables, the GDP of both importing and exporting countries had a positive influence on Sri Lankan mango exports. Surprisingly, the distance to the importing country had no significant effect, though it shows a negative sign. Discussion: This study provides valuable insights into the impact of NTMs on Sri Lankan mango exports. It highlights the considerable influence of NTMs on the overall fresh fruit export sector. We recommend proactively aligning internal quality testing regulations with the standards required by destination countries to promote future expansion. [ABSTRACT FROM AUTHOR]

This paper investigates linear and nonlinear impacts of political relations on China's service trade import and export to 8 countries from 2005 to 2019. The result shows that positive effect of political relations on both service trade import and export can be obtained. Using a threshold model, it is found that when the trading country's economy level reaches the first threshold, the role of political relations will change. [ABSTRACT FROM AUTHOR]