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This study aims to evaluate the impact of climate change on some specific areas of agricultural production in Quang Nam Province, including assessing the possibility of losing agricultural land owing to sea level rise; assessing the impact on rice productivity; and, assessing the impact on crop water demand.

This study used the method of collecting and processing statistics data; method of analysis, comparison and evaluation; method of geographic information system; method of using mathematical model; and method of professional solution, to assess the impacts of climate change.

Evaluation results in Quang Nam Province show that, by the end of the 21st century, winter–spring rice productivity may decrease by 33%, while summer–autumn rice productivity may decrease by 49%. Under representative concentration pathway (RCP) 4.5 scenario, water demand increases by 31.1% compared to the baseline period, of which the winter–spring crop increases by 28.4%, and the summer–autumn crop increased by 34.3%. Under RCP 8.5 scenario, water demand increases by 54.1% compared to the baseline period, of which the winter–spring crop increases by 46.7%, and the summer–autumn crop increased by 63.1%. The area of agricultural land likely to be inundated by sea level rise at 50 cm is 418.32 ha, and at 80 cm, it is 637.07 ha.

To propose adaptation solution to avoid the impacts of climate change on agriculture, it is necessary to consider about the impact on losing land for agriculture, the impact on rice productivity, assess the impact on crop water demand and other. The result of this assessment is useful for policymakers for forming the agriculture development plan.

“The world needs science, science needs women” is the message given by UNESCO in the program for the development of women in science” (UNESCO, 2017). In Vietnam, women’s participation and achievements in scientific research is considered a great and important resource for industrialization and modernization. Even so, are there gender differences in scientific achievement in the social science research institutes in Vietnam? What factors influence the scientific achievement of female social researchers? The answers will be based on data from a 2017 survey with a sample of 756 researchers, of which 77.6% were female. The survey was conducted by the Vietnam Academy of Social Sciences, a leading, ministry-level national center for the social sciences in Vietnam. This chapter analyzed the scientific achievements of researchers through their position as principal investigators of research projects and their publications, and factors that may impact this. Bivariate and multivariate analyses of factors that may affect the scientific achievement of researchers found that gender differences in academic achievement in the social sciences in Vietnam was still prevalent. Female researchers’ scientific achievements were lower than those of their male counterparts. The contribution to science of Vietnamese female researchers was limited by many different factors; the most important were the academic rank of the researchers and gender stereotype that considered housework the responsibility of women.

This study aims to investigate whether the participation in land rental markets helps to mitigate impacts by climate change on multidimensional poverty in Thailand and Vietnam.

The authors use precipitation data from the National Aeronautics and Space Administration (NASA) and self-reported shocks from the Thailand Vietnam Socio-Economic Panel (TVSEP) project to estimate climate change. Data from the TVSEP are also used to calculate a multidimensional poverty index (MPI). Fixed-effect logit panel regressions with interaction terms are implemented to analyze the above mentioned.

The results show that land rental markets are used as mitigation strategies to climate change in Thailand and Vietnam. The participation in land rental markets also reduces multidimensional poverty. However, as a mitigation strategy, land rental markets are only successful in certain circumstances.

The results show that there is potential in using land rental markets as mitigation strategies to climate change. Further research is needed to better understand which adaptation strategies, besides land rental market participation, and which combinations of different adaptation strategies are successful to mitigate negative effects induced by climate change.

The results show that there is potential in using land rental markets as mitigation strategies to climate change. Therefore, education in the participation in land rental markets and how to use them as a mitigation strategy can be a way to increase households' resilience to negative effects induced by climate change. Households make better decisions regarding their land when they are better informed on the functionality of land rental markets. Additionally, being better informed increases self-confidence to participate in land-rental markets.

Land rental markets as a mitigation strategy to climate change rarely have been studied, and if so, mainly the effect of leasing land has been studied. Additionally, the authors implement new measures of poverty – a multidimensional view on poverty which provides new insights into who are the poor and how they can be lift out of poverty.

The purpose of this paper is to examine the effect of innovation on the performance of small and medium-sized enterprises (SMEs) in Vietnam.

The paper uses data from the surveys on SMEs in Vietnam conducted by the Development Economics Research Group at the University of Copenhagen, the United Nations University’s World Institute for Development Economics Research, Central Institute for Economic Management and Institute of Labor Science and Social Affairs, and applies least squared regressions and 2SLS regressions to examine the effect of innovation on the performance of SMEs.

The authors find that SMEs with innovation tend to perform better than SMEs without innovation. The authors further show that the positive effect of innovation on firm performance mainly comes from the effect of improvement of existing products, an important type of innovation in SMEs. This result is persistent when the authors use propensity matching score and 2SLS regression with instrumental variable approaches. Overall, the results show the important role of innovation in enhancing the firm performance of SMEs, which sheds light on the literature on the controversial relation between innovation and SMEs performance in the world.

The major limitation of the paper is the lack of data. Although the database used in the paper is widely used to analyze SMEs in Vietnam, it covers about 2,500 firms in only nine provinces/cities in Vietnam.

Policymakers should enact relevant policies to support SMEs with innovation activities, thereby increasing firm performance and their competitiveness. For instance, encouragement policies or financial incentives (tax reduction or subsidies) for innovative firms should be implemented and/or fostered.

To the best of the authors’ knowledge, this is the first paper to examine the effect of different types of innovation on the performance of SMEs in Vietnam.

This paper focuses on dry port as a key notion in port-hinterland development. We first discuss the concept of dry port by reviewing existing literature. Then, we explore the reasons behind the emergence and development of inland node systems in different geographical, economic and institutional contexts. Next, the paper presents a classification of dry ports based on a multitude of factors and dimensions and the respective benefits to different parties. The study then focuses on the specific characteristics of dry ports and associated transport networks in developing countries.

In the last part, we present a case study on the dry port system in Vietnam by reviewing the seaport and inland transport system and analyzing the current status of inland terminals in Vietnam. To conclude, a SWOT analysis is presented with regard to the development of the dry port network in Vietnam, followed by recommendations for policy makers.

This study aims to explore the impact of social, financial and institutional factors on women’s entrepreneurship in Vietnam, emphasizing motivation’s role in addressing challenges. Women’s entrepreneurship holds economic significance, driving local economies and creating opportunities. Government efforts to support women entrepreneurs have increased, but research on this in developing economies, especially in Vietnam, is limited.

The paper investigates women’s entrepreneurship in Vietnam, examining social, financial and institutional influences and emphasizing motivation in overcoming challenges. Using a qualitative approach, it conducts in-depth interviews with 28 female entrepreneurs, analyzing data thematically. Methodologically, the study uses purposive sampling, triangulation and member checking to enhance credibility.

Findings reveal key motivations like financial incentives, self-achievement and social impact. These motivations empower women to overcome financial constraints, skill gaps, limited support and societal perceptions. This research guides women entrepreneurs to enhance success through learning, persistence, skill development and self-awareness.

This paper presents a novel exploration into women’s entrepreneurship in Vietnam, offering original insights into the interplay of social, financial and institutional factors, with a spotlight on motivational drivers. It provides unique perspectives on their motivations, challenges and support mechanisms. The study’s contribution lies in its comprehensive understanding of women’s entrepreneurship dynamics in a developing economy like Vietnam, offering valuable insights for policymakers, practitioners and academics alike. Its originality lies in its holistic approach and nuanced examination, enriching the discourse on women’s entrepreneurship in emerging

This study examines the convergence of energy diversification, financial development and per-capita income in OECD countries.

The research employs the club convergence test to assess convergence among OECD countries and uses Granger causality tests and panel regressions to identify the determinants of convergence, using data from 1997 to 2021.

The convergence tests showed no overall convergence but revealed convergence clubs for each factor. Granger causality tests indicated short-run bi-directional relationships between the variables. Long-run panel regression analysis confirmed that technological progress significantly improves per capita income and energy diversification. Additionally, it revealed bi-directional relationships between energy diversification and financial development, a uni-directional relationship from financial development to per capita income and a U-shaped effect of per capita income on energy diversification, with a turning point at $67,112.8 per year.

The findings suggest that within each convergence club, implementing microeconomic incentives for technology development and diffusion in energy, production and financial services could help lagging countries catch up.

This study pioneers the testing of convergence in energy diversification, financial development and per capita income in OECD countries and identifies the determinants of this convergence.

To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This study examines the operational dynamics of a supply chain (SC) in Vietnam as a case study utilizing an ML simulation approach.

A robust fuel consumption estimation model is constructed by leveraging multiple linear regression (MLR) and artificial neural network (ANN). Subsequently, the proposed model is seamlessly integrated into a cutting-edge SC simulation framework.

This paper provides valuable insights and actionable recommendations, empowering SC practitioners to optimize operational efficiencies and fostering an avenue for further scholarly investigations and advancements in this field.

This study introduces a novel approach assessing sustainable SC performance by utilizing both traditional regression and ML models to estimate transportation costs, which are then inputted into the discrete event simulation (DES) model.