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Farmers' risk attitudes and risk perceptions play an essential role in shaping risk management strategies to address risks and uncertainties. Contract farming is considered as one of the feasible approaches to tackle farmers' concerns. However, risk perspectives under various categories have not been included in studies on farmers' preferences for contract farming in the literature, especially in Vietnam. This study aims to determine factors affecting farmers' choices of different contract farming practices.

The explanatory factor analysis (EFA) and multinomial logit model (MNL) were applied to explore the impacts of risk perspectives on farmers' preferences for contract farming. Data have been collected from 211 rice farmers in An Giang Province, “the rice bowl” of the Mekong Delta, Vietnam.

The study found that farm size, cooperatives, extension, market access and trust have significantly impacted on contract participation while a delay payment was a barrier for farmers' motivation to opt for the contract. Farmers' contract choices were also influenced by their risk attitudes and perceptions under different risk dimensions. The financial, policy and human risk-averse behavior predisposed farmers to single out the full contract while the policy and human risk-loving and production, market and finance risk-averse respondents were in favor of the marketing contract. Moreover, the findings indicated that the more farmers concerned about risk of weather and market, the more choices for the full contract, whereas the risk perceptions of weather and policy encouraged farmers to use the limited contract. By contrast, farmers who perceived the impacts of risk of diseases/pests and human were likely to adopt the marketing contract.

This study just focuses on collecting data from farmers’ perspective. Future studies involving stakeholders such as enterprises and policy makers are strongly recommended so as to design suitable contracts and enforce contract schemes effectively in Vietnam.

The findings also contribute to the literature on different types of contracts and the multidimensional aspect of risk for rice production in Vietnam.

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 paper investigates the key determinants affecting household spending for university degree in Vietnam. This paper serves as empirical evidence for policymakers to select appropriate factors to estimate financial needs for university students in Vietnam.

We employ an innovative variable selection approach with adaptive LASSO for Tobit Regression Model.

The results suggest income, region and ethnicity play significant roles in determining higher education expenditure at Vietnamese households. Gender-related indicators (such as gender of household head, student’s gender), distance to school, occupations, etc. are empirically insignificant.

This study proposes a data-driven method by interfering regulation and Tobit regression to understand the divergence in higher education spending. Especially, adaptive LASSO was first introduced to identify key determinants of higher education expenditure at household level in Vietnam. It hopes to tackle over-fitting problems of traditional OLS regression in previous literature.

Climate change increases systematic risk for firms, especially those in the agricultural industry. Therefore, the need to examine the consequences of climate-related risks on agribusiness companies' financial performance across the globe and emerging markets has risen. In this context, the paper aims to investigate the effects of climate change risks on the financial performance of agriculture listed firms in Vietnam.

The study sample includes 77 Vietnamese listed firms in the agricultural industry in the period of 2015–2019. The authors chose temperature, wind, rainfall and humidity proxies to measure climate change. The OLS regression, random regression and sub-sample analysis have been used to examine the impacts of climate risks on firms' financial performance.

Empirical results show that rain and temperature have positive impacts on financial performance of Vietnamese agriculture listed firms, while wind and humidity have insignificant impacts on financial performance.

The research helps researchers, businesses, practitioners and policymakers interested in the agricultural industry, especially those in developing and emerging countries, to develop a deep understanding of the impact of climate change risks on firm performance and therefrom prepare necessary measures to reduce the negative impacts.

This study adds to the literature stream on the impacts of climate change on financial performance. It is the first study to investigate this impact in Vietnam, a country which depends mainly on agriculture.

This paper examines why farmers self-select out of formal credit markets even though they need external funds.

We use probit and Bayesian probit estimators to detect the determinants of self-selection behavior based on a primary dataset of 2,212 rice farmers in Vietnam. After that, we use the multinomial probit (MNP) and Bayesian MNP estimators to reveal the impact of relevant factors on the decision to self-select for farmers belonging to each self-selection category.

The probit and Bayesian probit estimators show that the decision to self-select depends on household head age, income per capita, farm size, whether or not to have relatives or friends working for banks, the number of previous borrowings, risks related to natural disasters, diseases, and rice price, and the number of banks with which the farmer has relationships. The MNP and Bayesian MNP estimators give further insights into the decision of farmers to self-select in that determinants of the self-selection behavior depend on the reasons to self-select. In concrete, farm size and the number of previous borrowings mitigate the self-selection of farmers who did not apply for loans due to having access to other preferred sources of credit. The self-selection of farmers not applying for loans because of unfavorable loan terms is conditional on household head age, farming experience, income, farm size, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with. Several factors, including education, income, the distance to the nearest bank, whether or not having relatives or friends working for banks, the number of previous borrowings, risks, and the number of banks the farmer has relationships with, affect the self-selection of farmers not applying for loans because of high borrowing costs. The self-selection of farmers not applying for loans because of complex application procedures depends on income and the number of previous borrowings. Finally, the household head’s age, gender, experience, income, farm size, the amount of trade credit granted, the number of previous borrowings, natural disaster risk, and the number of banks the farmer has relationships with are the determinants of the self-selection of farmers not applying for loans because of a fear not being able to repay.

This paper fills the knowledge gap by investigating why farmers self-select out of formal credit markets. It provides evidence of how the farmers’ subjective perceptions of rural credit markets contribute to their self-selection.

This paper shows that demand-side constraints are also vital for farmers’ access to bank credit. Improving credit access via easing supply-side constraints may not increase credit uptake without addressing demand-side factors. Given that finding, it recommends policies to improve access to bank credit for farmers regarding the demand side.

This research aims to investigate how emerging destinations cope with digitalization of information, where they are in the process and how digitalization of information takes place in destination marketing organizations (DMOs). As a case for emerging destinations that must deal with the negative consequences of the digital divide, the Vietnamese Mekong Delta (VMD) will be examined. A new framework, solutions in general, and potential innovative approaches will be presented.

A mixed methods approach was used. Firstly, a content analysis comprising 68 criteria to examine 10 destination websites was conducted to evaluate the performance of provincial destination websites of VMD. Secondly, the authors interviewed five managers from VMD DMOs to reveal the strategy, status quo and their challenges with digitalization.

Some digitalization is evident in VMD DMOs, with the digitization of tourist information provision developing from analog formats to digital modes. The content analysis of the websites shows that provincial destination websites of VMD perform well with regard to communication but need improvements for transaction, and especially relationship aspects. Emerging destinations like VMD DMOs are reaching the second or third level in the digitalization process. Yet they face challenges with human and financial resources.

This research provides recommendations concerning destination website performance, the process of digitalization and how to promote digitalization and apply more digital instruments to move to the next stages of destination digitalization. Also, suggestions on how to overcome existing challenges/barriers in similar areas of the world are provided.

A new, extended more granulated version of the digitalization framework by Karpova et al. (2019) has been developed. The new model acknowledges the continued importance of printed information, provides information about the sequence of steps how to implement website dimensions, and which instruments are realistic to implement in different levels of digitalization considering the challenges and barriers developing destinations face.

This study explores the effect of local budget retention rate changes (RER) on total factor productivity (TFP) and its components in Vietnam.

The study employs a two-system generalized method of moments (GMM) estimator and data from 2012 to 2019 across all 63 provinces/cities of Vietnam.

The study finds that local budget retention rates significantly influence public investment, affecting scale and allocation efficiency. The reallocation of budgets between regions and from the central government to local levels incurs certain costs, often resulting in economically robust provinces experiencing reductions in their retention rates.

Recognizing the challenges of immediate structural budget changes due to cultural and historical factors, the study suggests a more gradual policy approach. It emphasizes the importance of policy predictability, as abrupt reductions in the retention rate lead to higher costs than gradual reductions, thus implementing budget policies with a clearer timeline. This study provides insight into local budget allocation regimes and their impact on productivity in transitioning countries.

First, the study provides fresh evidence of the impact of retention rate changes on TFP and its components in Vietnam. Second, the study provides insights into the mechanisms of the nexus of increased budget spending, capital efficiency and, most importantly, attaining improvement in education. We also offer further insights into inefficient budget allocation agents in Vietnam, especially in large cities, which should alert scholars to explore this topic further in the future.

This study aims to examine the relationship between corporate social responsibility (CSR) and worker turnover rate (WTR) and worker turnover cost (WTC) in Vietnamese garment companies, using the mediating role of symbolic image dimensions (SID) of employer image and the moderating role of unemployment rate.

This study uses Signaling Theory and Job Embeddedness Theory as theoretical frameworks to examine the mediating role of SID and the moderating role of the unemployment rate on the link between CSR and WTR, as well as the associated cost. Data from 119 Vietnamese garment companies are analyzed using structural equation modeling – AMOS software.

The findings suggest that CSR has a direct adverse effect on the WTR and an indirect effect on WTC through WTR. The results also indicate a direct relationship between the level of CSR adopted by companies and workers’ perception of the symbolic attributes of their company’s employer image as sincere, innovative, competent and prestigious. This, in turn, leads to a reduced rate of worker turnover. In addition, this study discovers the moderating influence of the region’s unemployment rate on the correlation between companies’ CSR and WTR.

The results indicate that companies should view CSR as a strategic tool to obtain better performance by achieving a win-win state of affairs with their workers. It also implies the influence of external economic factors on the relationship between CSR and worker turnover.

This study contributes to the literature by highlighting the economic benefits of CSR and the SID.

This study aims to understand the socioeconomic impact of flood events on households, especially household welfare in terms of changes in consumption and coping strategies to deal with flood risk. This study is based on Bihar, one of the most frequently flood-affected, most populous and economically backward states in India.

Primary data were collected from 700 households in the seven most frequently flood-affected districts in Bihar. A total of 100 individuals from each district were randomly selected from flood-affected villages. Based on a detailed literature review, an econometric (probit) model was developed to test the null hypothesis of the availability of consumption insurance, and the multivariate probability approach was used to analyze the various coping strategies of these households.

The results of this study suggest that flood-affected households maintain their consumption by overcoming various losses, including income, house damage and livestock loss. Households depend on financial transfers, borrowings and relief, and migrate to overcome losses. Borrowing could be an extra burden as the government compensates for house damage and crop loss late to the affected households. Again, there is no compensation to overcome livelihood loss and deal with occurrences of post-flood diseases, which further emphasizes the policy implications of strengthening the health infrastructure in the state and generating alternative livelihood opportunities.

This study discusses flood risk in terms of changes in household welfare, identifies the most effective risk-coping capabilities of rural communities and contributes to the shortcomings of the government insurance and relief model.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0569

In the cosmic expanse of the digital universe, a new celestial body emerges the Metaverse. This study embarks on an interstellar journey to scrutinize the dynamics of entrepreneurial learning (EL) and opportunity in the burgeoning realm of the metaverse. This study aims to understand how personal entrepreneurial characteristics (PEC) and Metaverse environment characteristics (MEC) influence these processes.

The study devotes a dual-lens approach, combining the power of interviews (Phase I) and the precision of a survey (Phase II). It harnesses the insights of the entrepreneurial event model (EEM) and the technology acceptance model (TAM), serving as twin beacons guiding our exploration of the constructs under PEC/MEC.

The study uncovers a fascinating tapestry of interwoven variables. Certain threads in the PEC/MEC weave significantly into the fabric of EL, which in turn embroiders the pattern of opportunity exploitation. However, some threads, namely, Metaverse scalability, entrepreneurial risk-taking and innovativeness, do not significantly contribute to the design of EL.

The findings serve as a compass for various stakeholders in the metaverse. They guide the design of entrepreneurial education programs, inform the development of user-friendly metaverse platforms, shape policies promoting entrepreneurship in the metaverse and provide strategic insights for entrepreneurs and investors.

This study is a trailblazer, being among the first to apply the EEM and TAM in the context of the Metaverse. It offers fresh perspectives on entrepreneurial processes in virtual environments, enriching the emerging narrative on metaverse entrepreneurship and charting unexplored territories for future research.