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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.

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.

This study aims to estimate the pass-through rate of the increases in the excise tax and TCF tax on tobacco in Vietnam. This study seeks to shed light on how the tax burden is split between consumers and producers and inform policy discussions in the country. Using panel micro-level data collected from three waves of a nationwide retailer's survey, this study provides an evidence-based pass-through estimation for tobacco tax in Vietnam and contributes to the understanding of tax policy on smoking and smoking-related issues.

Following increases in the excise tax and TCF tax on tobacco in 2019, the differential effect of the tax hike on the “treatment group” (domestic cigarettes) versus the “control group” (illicit cigarettes) using a difference-in-difference (DID) analysis has been studied. The study utilized unique longitudinal retailers’ data on cigarettes prices in Vietnam from 2018 to 2019 to estimate the tax pass-through rate for some of the most popular factory-made cigarette brands.

This study found evidence of an over-shifting of cigarette taxes on smokers. Specifically, it discovered that the tax increase is absorbed more by low-priced brand smokers compared to premium brand users due to (1) the limited increase in prices under a pure ad valorem system and (2) the way the Vietnamese currency is denominated. Additionally, there is evidence of cushioning to mitigate price shock on consumers as the real prices increase gradually over the period of one year after the tax change.

To the best of the authors’ knowledge, this study is the first to collect and analyze a unique panel micro-level data from three waves of a nationwide retailers’ survey, which captures the changes in marketing and pricing strategies of the tobacco industry in Vietnam before and after an increase in excise tax in 2019. The results of this study could be used as a reference for future policymakers in considering increasing taxes on tobacco.

The study applied the Unified Theory of Technology Acceptance and Use Theory 2 (UTAUT2) to predict blended learning acceptance by students in universities in Zimbabwe. Blended learning is a heterogeneous mode of teaching and learning that combines face-to-face (F2F) and online modes. Owing to advances in technology, and recently, the advent of pandemics, such as COVID-19, the need for multimodal teaching approaches, such as blended learning, to enhance access to education in universities has become very important.

A quantitative approach that used a structured questionnaire for data collection from a sample of 432 postgraduate students was used. Data validation was done using confirmatory factor analysis (CFA). The structural equation modelling technique was used for data analysis.

Results showed that out of the seven factors of the UTAUT2, the factors such as performance expectancy, effort expectancy, social influences, facilitating conditions and hedonic motivation significantly and positively influenced the behavioural intentions of students in universities to accept blended learning. On the other hand, habit and price value did not significantly influence university students' behavioural intentions to accept the bended learning mode. It was further shown in the study that behavioural intentions significantly influenced the acceptance of blended learning by university students. In light of the above results, it was concluded that the UTAUT2 could be used to predict the acceptance of blended learning by university students.

The main study limitation was that it was only carried out at universities that had information and communication technology (ICT) infrastructure challenges owing to the fact that the economic situation in Zimbabwe is depressed. Limited ICT infrastructure in the universities might have had some impact on the nature of behavioural intentions of students to accept blended learning as a learning mode. Further research could be carried out in countries with better economies that are able to fund ICT infrastructures of their universities and to establish whether the results of the current study could either be confirmed, disconfirmed or enriched.

The paper suggests that universities need to increase investment in ICT infrastructure as well as in capacitating students with the necessary ICT skills for the effective use of institutional ICT when learning using the blended learning mode. Without adequate and appropriate ICT infrastructure as well as necessary ICT skills, students may develop low motivation levels and negative attitudes towards blended learning, which may eventually may affect their acceptance of the learning mode.

There is no known study that has been conducted using the UTAUT2 to establish antecedents of behavioural intentions of students to accept blended learning in the context of Zimbabwean universities. This study therefore opens new ground on factors influencing the acceptance of blended learning in the context of Zimbabwean universities. Also, the results showed that habit and price value do not significantly contribute to the behavioural intentions of university students to accept blended learning, which is not consistent with findings of past studies. This inconsistency opens new opportunities for further studies on the conditions under which these two factors can be used to significantly contribute to the development of behavioural intentions of students to accept blended learning.