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The purpose of this paper is to estimate a recent trend in climate change and its impact on livelihood of community living in Nam Dinh province, Vietnam. Further, it aims to increase the government attention for adaptation measures by providing awareness of climate change and its negative impacts on livelihood.

For study purpose, cross-sectional and secondary data sets were used. The community perceptions about climate change were recorded by face-to-face interviews of 500 respondents from Nam Dinh province, Vietnam in April 2015 by using a well-structured questionnaire, whereas secondary data were collected from the statistical yearbook of General Statistics Office of Vietnam. To accomplish the study objectives, Cobb–Douglas production function and Likert scale were used to estimate the community perceptions of climate change and impact of climate change on livelihood, respectively.

Results depict that climate change negatively impacted on the productivity of rice and livestock. Particularly, frequently occurring of droughts, floods and salinity intrusion negatively impacted on rice productivity, while livestock productivity is decreased by frequent occurring of flood storms in study area.

The study results suggest a government support is essential to achieve sustainable livelihoods for coastal communities living in the Red River Delta, particularly some adaptation measures in the context of climate change are required in study area.

This study aims to analyse the consumption inequality between farm and non-farm households in rural Vietnam, using the data from the 2016 Vietnam household living standards survey.

The present paper applies the “recentered influence functions (RIF)” in “Oaxaca-Blinder (OB)” type decomposition as proposed by Firpo et al. (2018) to allow for the flexible distribution of the outcome variables and the non-randomness of non-farm employment that violates the classical linearity assumption.

Non-farm households have significantly higher per capita consumption expenditure than farm households for the entire distribution. The gap in expenditure is large at low percentiles and narrowing with higher percentiles. At 10th percentile, the gap is estimated at 27.1%, but it is decreasing to 11.1% at 90th percentile. Most of the gaps are explained by the differences in the observed characteristics between farm and non-farm households such as ethnicity, education, income, internal transmittances and household composition. Non-farm households are endowed with more productive factors that result in higher per capita consumption expenditure.

Gaps in ethnicity and education are found to be key predictors of the inequality in consumption expenditures between farm and non-farm households, then, government policies that are aimed at increasing access to non-farm employment and education for ethnic minorities and for rural poor households are pathways to improve rural household welfare and hence reduce inequality.

This study introduces an innovative approach to long-term economic forecasting by integrating anticipatory governance (AG) and causal layered analysis methodologies. Focussing on emerging economies, with Vietnam as a case study, we explore potential economic trajectories to 2050.

The research employs a mixed-method approach, combining quantitative economic projections with qualitative scenario building and analysis.

Our findings reveal four distinct future scenarios, ranging from low growth to transformative change. The preferred scenario, characterized by adaptive change, projects a Gross National Income (GNI) per capita of $30,684 by 2050, with significant reductions in agricultural labour and improvements in human development indicators.

This study contributes to theoretical and practical domains by demonstrating the value of integrated foresight methodologies in economic planning. It offers policymakers a comprehensive framework for navigating complex, long-term economic challenges and opportunities. This research underscores the importance of adaptive governance and systemic thinking in achieving sustainable, inclusive economic growth in an increasingly uncertain global environment.

Shipping is a major source of air pollution, causing severe impacts on the environment and human health, greatly contributing to the creation of greenhouse gases and influencing climate change. The research was investigated to provide a better insight into the emission inventories in the Red River in Hanoi (Vietnam) that is often heavily occupied as the primary route for inner-city waterway traffic.

The total emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) were estimated using the SPD-GIZ emission calculation model.

The results show that CO₂ has the most significant contribution to the gas volume emitted: 103.21 tons/day. Remarkably, bulk carriers are the largest emission vehicle, accounting for more than 97% of total emissions, due to their superior number and large capacity.

The result to have a roadmap for making efforts to fulfil its commitment so that it could achieve its net-zero climate target by 2050 in Vietnam as committed at COP26.

In this research, the number of vehicles and types of vessels travelling on the Red River flowing within Hanoi territory and other activity data are reported. The tally data will be used to estimate emissions of seven different pollutants (PM₁₀, PM_2.5, SO_x, CO, CO₂, NO_x and HC) using a method combining both top-down and bottom-up approaches.

The purpose of this paper is to investigate the implementation of digital transformation in small and medium-sized enterprises in Vietnam.

The research features in-depth personal interviews with SME executives and managers.

The findings of this study may be summarized into five main areas: (1) multi-tasking role and scarcity of resources; (2) risk; (3) data-driven decision-making processes; (4) efficient communications; and (5) strategic issues. These categories emerged from the content analysis process.

Qualitative research provides a good explanation for situations in actual firms but may not always be generalizable.

Means of overcoming problems with implementing digital transformation in Vietnamese SMEs are provided.

Most studies of Vietnamese companies focus on intensive manufacturing and membership in supply chains. Few studies consider the emergent service and technology sector.

This study enhances the financial modelling of companies undergoing an Initial Public Offering (IPO) by focusing on internal capability determinants and IPO proceeds.

A hybrid logistic regression and shallow-depth decision tree approach are employed to predict the initial three-year post-IPO performance of companies listed on the Stock Exchange of Thailand (SET) using data from 2002 to 2021.

The results demonstrate that these models not only perform competitively against complex machine learning algorithms but also surpass them in terms of interpretability, an essential feature in financial modelling. The proposed approach effectively captures the effects of each determinant, offering valuable insights into strategic resource allocation and investment decision-making during transition years.

This study introduces a novel application that integrates logistic regression with decision trees to predict multiclass financial performance, filling the gap between complex machine learning techniques and interpretable financial models. It offers practical tools for companies and investors to make informed decisions in challenging post-IPO environments.

This paper attempts to develop a simple, static model of tax administration that is capable of explaining the widespread collusive petty tax administration corruption observed in developing countries.

This paper utilizes a positivist research framework and adopts a theoretical method of analysis, although secondary data will also be mentioned to support theoretical arguments whenever it is appropriate to do so.

A high rate of collusive tax corruption is inevitable in developing countries.

The model is static and needs to be extended into a dynamic model.

Traditional enforcement tools such as higher audits or a higher penalty regime against tax evasion do not work. Tax simplification can lessen the incidence of tax corruption.

Fighting tax corruption requires significant changes in the attitudes of taxpayers and tax auditors.

This paper combines the literature on Kantian economics and tax compliance in an innovative fashion.

In recent years, agricultural activities in the Mekong Delta have frequently faced the potential risks of drought, saline intrusion and unusually heavy rainfall because of climate change, leading to a decline in crop yield. Therefore, this study aimed to establish rice planting seasons in An Giang, an upper-located province in the Mekong Delta.

The impacts of seasonal variation on the key rice seasons were simulated using the Food and Agriculture Organization-crop model for the OM6976 rice variety grown in the study area. For the simulation, the model combined crop, soil, weather and crop management data.

The results show that seasonal variation because of changes in weather factors leads to alternation in crop yields across the study area. Specifically, the spring and summer rice planting seasons are advanced by one to two weeks compared with the baseline, and crop yield increased by 5.9% and 4.2%, respectively. Additionally, planting for the autumn–winter rice season on 3 August increased crop yield by up to 8.1%.

In general, rice planting seasons that account for weather factor changes effectively reduce production costs and optimise production.

Groundwater plays a critical part in both natural and human existence. When surface water is scarce in arid climates, groundwater becomes an immensely valuable resource. Dak Lak is an area that frequently lacks water resources for everyday living and production, and the scarcity of water resources is exacerbated during the dry season. As a result, it is critical to do study and understand about groundwater to meet the region's water demand. This study aims to extend the use of the MODFLOW model for groundwater simulation and assess the overall groundwater reserves and water demand in the highland province Dak Lak.

The MODFLOW model is used in this work to compute and analyze the flow, prospective reserves of groundwater from which to plan extraction and estimate groundwater variation in the future.

The application of the MODFLOW model to Dak Lak province demonstrates that, despite limited data, particularly drilling hole data for subterranean water research, the model's calculation results have demonstrated its reliability and great potential for use in other similar places. The use of the model in conjunction with other data extraction modules is a useful input for creating underground flow module maps for various time periods. The large impact of recharge and evaporation on groundwater supplies and water balance in the research area is demonstrated by simulations of climate change scenarios RCP4.5 and RCP8.5.

None of the studies has been done previously to analyze water resources of Dak Lak and the scarcity of water resources is exacerbated during the dry season. Therefore, this study will provide useful insights in the water resource management and the conservation of Dak Lak. The groundwater in Dak Lak can meet the area's water demand, according to the results obtained and water balance in the study area. However, the management of water resources and rigorous monitoring of groundwater extraction activities in the area should receive more attention.