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This study investigates the patterns and determinants of Korea’s horizontal intra-industry trade by employing a dynamic panel data analysis. The main findings of the study are as follows. An increase in the market size of both trading partners is associated with a higher level of horizontal intra-industry trade. Dissimilar economic sizes and per capita incomes have a negative effect on trade in horizontally differentiated products. Geographical distance and trade imbalance serve as obstacles to horizontal intra-industry trade. These findings have policy implications for reconsidering the orientation of promoting trade. Inclusive economic growth in the region, taking advantage of neighboring nations and making efforts to reduce trade imbalances between trading economies, can accelerate further trade expansion through horizontal intra-industry trade.

The purpose of this study is to examine how use of agriculture information systems could impact farmers' intention to convert from traditional to organic agriculture production in the mountainous areas of Northern Vietnam, based on a research framework developed from integrating Diffusion of Innovation Theory and Theory of Planned Behavior. Specifically, the authors aim to test the direct impact of use of agriculture information systems on converting intention and the interaction between use of agriculture information systems and perceived economic benefits, perceived non-economic benefits of organic production and market access on the formation of converting intention.

Data were collected from a sample survey that included 634 agriculture-producing households in Thai Nguyen, Tuyen Quang and Cao Bang provinces of Northern Vietnam. The logistic regression was used for data analysis.

Research findings indicate that perceived economic benefits, non-economic benefits, market access and use of agriculture information systems positively support the converting intention. Moreover, the use of information systems strengthens the links between the converting intention and perceived economic benefits, perceived non-economic benefits and market access.

This research is innovative in incorporating the use of agriculture information systems as both direct contributor and moderator in converting decisions.

This study uses a comprehensive theoretical framework that combines social cognitive theory and neighborhood effect to investigate the influence of neighborhood effects on farmers’ outcome expectations, observational learning and self-efficacy. This study aims is to analyze the mechanisms that underlie the adoption of social media by farmers for knowledge exchange in the agricultural context. Specifically, this research explores the role of neighborhood effects, outcome expectations, observational learning and self-efficacy in shaping farmers’ decision-making process regarding the use of social media platforms for exchanging agricultural knowledge.

The study data was collected through a sample survey conducted among 570 agricultural households residing in the provinces of Thai Nguyen, Cao Bang, Bac Kan and Phu Tho, located in the northern region of Vietnam. To analyze the data, structural equation modeling was used as the statistical technique of choice.

The findings of the study indicate a significant influence of neighborhood effects on outcome expectations, observational learning and self-efficacy. These factors, derived from social cognitive theory, also exhibit a positive association with farmers’ adoption of social media for knowledge exchange. Additionally, the study highlights that neighborhood contribute to a favorable adoption of social media among farmers via outcome expectations, observational learning, and self-efficacy.

The study is limited in examining farmers’ social media adoption for agriculture knowledge exchange in Northern mountainous area of Vietnam. This study could be replicated across various regions or nations, providing comparative insights into the adoption of social media among farmers for knowledge exchange.

The study findings suggest practical and innovative means to promote farmers’ social media adoption for agriculture knowledge exchange.

This study presents a pioneering approach by integrating social cognitive theory and neighborhood effect to elucidate the factors influencing farmers’ adoption of social media for the purpose of agriculture knowledge exchange.

This paper aims to analyze the impacts of institutional quality on trade flows of NAFTA with a panel data set of 105 countries spanning the period 2006–2017.

We applied the system generalized method of moment (GMM) estimator to investigate the impacts.

The results show that institutional quality is a positive and significant determinant of international trade flows of the NAFTA bloc and its trading partners. Our results also indicate that the impact of institutional quality depends on the level of economic development of NAFTA's trading partners. Specifically, the trade elasticity of institutional quality is the highest for NAFTA’s trade with middle-income countries and the lowest for NAFTA's trade with low-income countries. In the long run, the trade elasticity of institutional quality increased significantly, with the highest increase in the case of NAFTA's trade with medium-income countries and the lowest increase in the case of NAFTA's trade with low-income countries.

This study contributes to the existing literature in three different ways. First, we examine the differential impact of institutions on NAFTA's trade according to the level of economic development of NAFTA's trading partners. Second, we compare the differential trade elasticity of institutional quality in the long run. Finally, we support our findings through an improved research methodology by using the system GMM estimation. This method allows us to overcome the potential sample bias, omitted variable problems and endogeneity of explanatory variables.

This study analyzes whether farmers' incomes increase as they participate in online groups.

The study analyzed interview data from 673 farming households in three mountainous provinces of northern Vietnam, utilizing the propensity score matching (PSM) method.

The empirical results reveal that farmers participating in online groups, particularly those engaged in 1–3 groups, experience an increase in their income attributed to the three advantages of sharing-accessing-saving (SAS) information. Farming households engaged in online groups earn higher incomes, ranging from equivalent to 25.78 to 26.96 USD, in comparison to those who do not participate. Notably, farmers participating in 1–3 online groups outpace their counterparts in 4–5 groups in terms of income.

This study exclusively focuses on examining farmers' total income derived from all their agricultural activities and does not quantify the specific impact of online group participation on the income generated by each product. Furthermore, it is important to note that the PSM method has the potential to introduce bias due to unobserved factors, such as social networks and local culture. Consequently, future research should prioritize the segmentation of income from individual agricultural products, distinct from the overall income, to gain a more nuanced understanding of each product’s sensitivity to information exchanged in online groups. Simultaneously, accounting for unobserved factors is crucial to obtain unbiased estimates.

This study represents the inaugural exploration into the comparison of farmers' incomes within a novel context – participation in digital-based groups. Furthermore, it extends the inquiry by delving into the correlation between the number of online groups joined and farmers' income. The empirical findings indicate that farmers may benefit the most by limiting their participation to a select few groups that align with their information needs and analytical abilities.

This study aims to analyze the factors affecting tea-producing farmers' intention to use e-commerce exchanges (ECEs) to sell their products, combining the technology acceptance model (TAM) theory and barrier factors.

The authors use the generalized structural equation modeling (GSEM) to analyze the intermediate model that is built on TAM.

Research results show that perceived usefulness (PU) and perceived ease of use (PEU) significantly influence farmers' intention to use ECEs to sell their products. However, knowledge and information barriers hinder farmers' intention to use such ECEs.

Encouraging farmers to use ECEs is the most helpful solution for agricultural economic development in the context of the Covid-19 pandemic.

From an academic perspective, this is the first study that combines the TAM theory of Davis (1989) and barrier factors to analyze farmers' intention to use ECEs. The findings are valuable references for policymakers to propose strategies for agricultural economic development during the current pandemic. At the same time, the empirical results obtained from this study provide good orientations for agricultural economic development 4.0 in the future.

This paper aims at assessing the impact of institutional and cultural distances and trade barriers on ASEAN's trade efficiency using a panel data set of 65 countries for the period 2006–2017.

First, the authors applied an improved version of the stochastic frontier model to estimate the trade efficiency scores. After that, we used the system generalized method of moment (GMM) estimator to investigate the impacts of institutional and cultural distances on ASEAN's trade efficiency.

The results show that the trade efficiency of ASEAN countries with the rest of the world (ROW) is moderate, ranging from 0.561 to 0.612, but shows a downward trend. This result indicates that considerable trade potential exists between ASEAN countries and ROW. Institutional and cultural distances, as well as the trade barriers, negatively affect ASEAN's trade efficiency. Efforts to reduce differences in institutions and cultures and to promote trade liberalization are vital remedies for ASEAN countries to turn potentials into actual trade performance.

This study contributes to the existing literature in three different ways. First, this is the first study on the impact of the differences between internal and external characteristics on trade efficiency, specifically, the impact of institutional and cultural distances on ASEAN's trade efficiency. Second, to obtain accurate efficiency scores, the authors use an improved version of the stochastic frontier model proposed by Karakaplan (2018), which can control the problem of endogeneity. Third, in quantifying the determinants of trade efficiency, the authors apply a system GMM estimator, which allows us to overcome the problems of endogeneity, measurement errors, and omitted variables.

This study analyzes the factors that affect the decisions of micro-businesses to switch to enterprises in Thanh Hoa, Vietnam.

In order to explain the behavior of micro-businesses in switching to enterprises, the authors designed a questionnaire and collected survey data from 404 micro-businesses. The generalized structural equation modeling was applied to analyze the structured model with the dichotomous dependent variable.

First, the behavior of micro-businesses to switch was indirectly affected by needs and directly affected by attitudes, perceived behavioral control, subjective norm and institutional quality. Second, the subjective norms exerted the most influence on the behavior of the micro-businesses in switching. This finding implies that (1) the behavior of the micro-businesses depended on the assessments, perceptions and views of their friends, relatives and colleagues, and (2) the behavior to switch stems mainly from the desire to improve the businesses' position in society. Finally, both formal and informal institutions play an essential role in the behavior of the micro-businesses to switch to enterprises.

There have been no previous studies that have applied structured models to test the behavior of micro-businesses to switch to enterprises. Furthermore, previous studies had mainly addressed the psychological factors or needs of micro-businesses. In this study, apart from the above factors, the authors discuss the impact of institutions on the behavior of micro-businesses to switch.

This study aims to examine the impact of inbound logistics on dynamic supply chain capabilities and, subsequently, on supply chain resilience in the Vietnamese textile industry.

A conceptual framework based on a resource-based view was empirically tested using partial least squares structural equation modeling and data collected from 215 Vietnamese textile enterprises from December 2021 to March 2022.

The research shows that inbound logistics capability positively affects dynamic supply chain capabilities. In particular, the study has ratified reengineering as the chief factor that textile firms should consider when building a resilient supply chain.

This study considers the Vietnamese textile industry to assess the indirect effect of inbound logistics on supply chain resilience through dynamic supply chain capabilities in a theoretical sense while assisting managers in comprehending the functions of supply chain collaboration, agility and reengineering as the foundation for supply chain resilience in a managerial sense.

This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City.

The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117.

The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City.

Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost.

The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam.

This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy.

This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.