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This study focuses on analyzing the relation between money supply, inflation and output in Vietnam and China.

Using the error correction model and the vector autoregression model (ECM and VAR) and the canonical cointegration regression (CCR), the study shows similar patterns of these variable relations between the two economies.

The study points out the difference in the estimated coefficients between the two countries with different economic scales. While inflation in Vietnam is strongly influenced by expected inflation and output growth, inflation in China is strongly influenced by money supply growth and output growth.

To the best of the authors’ knowledge, this is the first empirical and comparative research on the relation between money supply, inflation and output for Vietnam and China. The study demonstrates that the relationship between money supply, inflation and output is still true in case of transition economies.

This study examines the role of technology as a driver of sustainable tourism perceptions among Generation Z.

The work considers the perspective of locals in Pakistan and uses a multi-method, multiphase embedded research design approach.

The research findings demonstrated that technology has a positive correlation with the environmental, socio-cultural and economic dimensions of sustainable tourism perception among Generation Z. Therefore, technology could be considered a dimension of sustainable tourism perception for locals, but perceptions differ significantly depending on the size of the city of the participant. The results of the experimental design phase that utilized picture stimuli demonstrated a linear relationship between technology and sustainability and enhanced their definition and implementation for developing countries.

This research diverges from most past research on these topics by focusing on Generation Z, for whom digital media and technology play a crucial role and for whom these technologies are positively correlated with sustainability and its overall perception. Implications for policies and practices for emerging country governments are provided.

This study aims to investigate aspects related to the changing trends of the rainfall extremes in the entire Mekong Delta in the period of 32 years (1984-2015) applying rainfall extreme indices. First, the homogeneity tests were applied to assess the quality of observed rainfall data series. The authors, then, investigated three rainfall indices including the number of very heavy rainfall days 20 mm (R20), number of days above 50 mm (R50) and number of days above 100 mm (R100) applying the Mann-Kendall test and Sen’s slope estimate.

First, the homogeneity tests were applied to assess the quality of observed rainfall data series. The authors, then, investigated three rainfall indices including the number of very heavy rainfall days 20 mm (R20), number of days above 50 mm (R50) and number of days above 100 mm (R100) applying the Mann-Kendall test and Sen’s slope estimate.

The results of R20 pointed out that an insignificant upward tendency was found in the coastal provinces, whereas an insignificant downward tendency was also recorded in the inland provinces. Regarding the number of R50, a similar trend to R20 was recorded with five stations slightly increased and five stations slightly decreased. For the number of R100, the results recorded an absence of significant trends over the entire study area. Approximately 58.5% of stations show a slightly decreasing trend, while 41.5% of the remaining stations recorded a slightly increasing trend.

For the number of R100, the results recorded an absence of the significant trends over the entire study area. Approximately 58.5% of stations show a slightly decreasing trend, while 41.5% of the remaining stations recorded a slightly increasing trend. Of note is the fact that the number of R100 occurred more frequently in the northern provinces, which means the northern region is facing a high risk of flooding.

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.

The purpose of this paper is to investigate the factors that affect handicraft export from Vietnam to trading partners in the period 2007–2017, and how those factors influence the export of handicraft products of Vietnam.

The research uses the approach of gravity model based on panel data to evaluate the export of Vietnamese handicraft to 50 main trading partners, covering the period from 2007 to 2017.

The estimated results reveal that Vietnam’s GDP, importer’s GDP, trading partner’s population, Vietnam’s inflation, the economic distance between Vietnam and importer, the openness of Vietnam, importing country’s common language and the issue that both Vietnam and importer are member of APEC are the main factors affecting Vietnamese handicraft export.

This study also has some limitations. It is limited in the data, as some other areas in the world have not been observed and included in the research. In the future, a study with large-scale data of space and time should be conducted, which will certainly give a universal result and fewer errors. However, this paper, in our opinion, provides a significant result and may help the government and policy makers to undertake appropriate measures to improve and promote the export of Vietnamese handicrafts to the world markets.

The research describes the current situation, and it studies factors influencing Vietnam’s handicraft export using the qualitative analysis. The result should be useful for the policy maker and enterprises to promote export activities of Vietnamese handicrafts to international markets.

Handicraft export of Vietnam plays an important part in retaining the culture value and social development as well as encouraging sustainable development for the rural poor within the country.

The past research related to Vietnamese handicraft export almost analyzed the situation to promote export handicrafts. This research is based on the study of factors affecting trade and the gravity model to elaborate and supplement the factors that affect the export of handicraft in accordance with the actual conditions of Vietnam.

This study aims to comprehensively identify supply chain risks and their causes, the factors influencing supply chain management and techniques to successfully mitigate and control supply chain risks in construction projects. This study developed a comprehensive framework showing various supply chain risks and how these risks that influence project execution are systematically identified and managed for the overall construction project success.

The research conducted was characterised by its descriptive, exploratory and quantitative nature. The collection of quantitative data was conducted by means of structured online questionnaires. The sample consisted of 205 construction project professionals who were selected randomly. This group included individuals with various roles in the construction industry, such as project managers, civil/structural engineers mechanical engineers, risk managers, architects, quantity surveyors, electrical engineers, construction managers, health, safety and environment managers, estate managers and other professionals. All participants were actively involved in construction projects located in the Gauteng province of South Africa. The data was analysed, using descriptive statistical methods, including factor analysis, reliability assessment and calculations of frequencies and percentages.

The result showed that predictable delivery, funding schedule, inventories, balanced demands, production capabilities, timely procurement, construction supply chain management coordination, delivery reliability, the proximity of suppliers, identification of supply chain risks in the conceptualisation stage of a project, identification of supply chain risks in the planning stage of a project, identification of supply chain risks in the execution stage and the reconciliation of material flows of the subcontractors with the contractors were identified as the key factors that influenced the construction supply chain management the most. The result also showed that subcontractor’s negative attitudes towards supply chain management, procurement delays, imbalanced demands, clients’ negative attitudes towards other project stakeholders, unpredictable delivery reliability, disorganised construction supply chain management approach, delayed funding, low delivery reliability, poor inventories, poor construction supply chain co-ordination, suppliers’ negative attitudes towards supply chain management and when the material flows of the subcontractors with the contractors are not reconciled were identified as the factors that have the greatest impacts on construction supply chain risks management.

For future research, it is recommended to incorporate fourth industrial revolution) such as machine learning prediction models and algorithms, Artificial intelligence and blockchain to identify and manage supply chain, supply chain risks and project stakeholders involved in supply chain in construction projects. Green construction or sustainable construction was not fully covered in this study. The findings will be beneficial for sustainable construction projects in developing countries for sustainability, although it did not extensively cover green buildings and related risks.

Supply chain risk is one of the major challenges facing the construction industry because construction projects are complex by nature involving a lot of activities and participants with different responsibilities and tasks therefore it is highly recommended to implement the proposed frameworks in this paper from the conceptualisation stage to the execution stage, carefully identifying parties involved in supply chain, supply chain management, stakeholders, tasks, activities, responsibilities and supply chain risks generated as a result of the interactions between stakeholders involved in supply chain management and coordination to realise project objectives. The findings will be a foundation for identifying and managing supply risks in sustainable buildings in developing countries.

Supply chain management is crucial in every enterprise. Managing supply chain risks is a major aspect of risk and disaster management and this implies that supply chain excellence is achievable by building communication, trust and mutual objectives, no blame culture, performance measurement, constant improvement and partnering.

The implementation of construction supply chain risk management framework involves assessing the impacts of these supply chain risks on the objectives of construction projects with respect to time, cost, safety, health, environment, stakeholders, financial performance, client satisfaction and quality.