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This study empirically examines the impact of climate change and agricultural research and development (R&D) as well as their interaction on agricultural productivity in 12 selected Asian and Pacific countries over the period of 1990–2018.

Various estimation methods for panel data, including Fixed Effects (FE), the Feasible Generalized Least Squares (FGLS) and two-step System Generalized Method of Moments (SGMM) were used.

Results show that both proxies of climate change – temperature and precipitation – have negative impacts on agricultural productivity. Notably, agricultural R&D investments not only increase agricultural productivity but also mitigate the detrimental impact of climate change proxied by temperature on agricultural productivity. Interestingly, climate change proxied by precipitation initially reduces agricultural productivity until a threshold of agricultural R&D beyond which precipitation increases agricultural productivity.

The findings imply useful policies to boost agricultural productivity by using R&D in the context of rising climate change in the vulnerable continent.

This study contributes to the literature in two ways. First, this study examines how climate change affects agricultural productivity in Asian and Pacific countries – those are most vulnerable to climate change. Second, this study assesses the role of R&D in improving agricultural productivity as well as its moderating effect in reducing the harmful impact of climate change on agricultural productivity.

This study aims to investigate the determinants of public trust in e-government services (Te-GS) and participation in social media.

A quantitative cross-sectional field survey was used to collect primary data at the local government level in 11 cities, towns and districts in Tien Giang Province, Vietnam. The final data set of 529 respondents was analysed using SmartPLS4 to evaluate the measurement and structural models.

Perceived responsiveness, transparency and security have strong positive associations with Te-GS, whereas perceived accountability does not. Furthermore, perceived ease of use and perceived usefulness are positively associated with social media participation.

Although previous studies have examined citizen behaviour in the use of e-government services, the social media context has rarely been considered due to its novelty. This study adds to the knowledge of the antecedents of participation in e-government services in developing countries such as Vietnam. Furthermore, it provides a comprehensive framework for understanding participation intention that considers four elements of good governance theory and two elements of the technology acceptance model (TAM), thereby extending previous research on the effects of these variables on the adoption of e-government services.

The paper aims to investigate the difference in total factor productivity (TFP) among those firms with and without outsourcing in a developing country like Vietnam. Also, it explores the effect of outsourcing activities on total factor productivity with a specified concentration on the Vietnamese small and medium-sized enterprises (SMEs).

The panel data set of SMEs used in this study was originated from biannual surveys conducted under the collaboration between educational organizations and government agencies: Stockholm School of Economics (SSE), Department of Economics – the University of Copenhagen, the Institution of Labor Studies and Social Affairs (ILSSA) in the Ministry of Labor, Invalids and Social Affairs (MOLISA). In this study, the model is developed based on the production function in accordance with the model of Girma and Görg (2004). The firms’ TFP is the difference between the actual and the predicted output as with the approach by Levinsohn and Petrin (2003).

This study finds out that firms with outsourcing have higher total factor productivity than those without outsourcing activities. In addition, the more firms spend on outsourcing, the higher total factor productivity they can gain. Outsourcing to SMEs in a developing country can significantly increase its TFP by means of either maintaining core competencies or searching external resources in conducting some internal activities.

Although outsourcing has been widely applied by large firms, the research studying its impact on productivity at firm level is limited. Especially, this study can shed light on the impact for the case of SMEs in a developing economy.

This study aims to examine the relationship between human resource development (HRD) and the interaction between corporate social responsibility (CSR) and marketing capabilities in small and medium enterprises (SMEs) in the food industry.

This research uses the extended regression model on a sample of 2,649 food SMEs in Vietnam.

This research found that CSR and marketing strategies positively influence HRD; the interaction of CSR and marketing capabilities has a negative effect on HRD; the endogenous role of network capabilities on the effects of CSR and marketing capabilities on HRD.

This research helps food companies use their resources in allocating resources for CSR and conduct marketing reasonably and effectively. This study highlights that the impact of CSR and marketing on HRD is dominated by endogenous networking.

Task complexity is one of the significant factors that influences and is used for forecasting employee performance and determining labor cost. However, the complexity level of tasks is unstructured, dynamic and complicated to perform. This paper develops a new method for evaluating the complexity level of tasks in the production process to support production managers to control their manufacturing systems in terms of flexibility, reliability to production planning and labor cost.

The complexity level of tasks will be analyzed based on the structuralist concept. Using the structure of task, the factors that significantly affect the task complexity in an assembly line will be defined, and the complexity level of the task will be evaluated by measuring the number of task components. Using the proportional 2-tuples linguistic values, the difference between the complexity levels of tasks can be compared and described clearly.

Based on the structure of the task, three contributory factors including input factors, process-operation factors and output factors that significantly affect the task complexity in an assembly line are identified in the present study. The complexity level of the task is quantified through analyzing the details of the three factors according to two criteria and six sub-criteria within the textile case study.

The proposed approach provides a new insight about the factors that have an effect on the complexity of tasks in production and remedies some of limitations of previous methods. The combination of experts' experience and scientific knowledge will improve the accuracy in determining the complexity level of tasks.

Recognition that not every climate adaptation policy is a good one has shifted attention to new tools and methods to measure the adequacy and effectiveness of adaptation policies. This study aims to propose and apply and applies an innovative adaptation policy assessment framework to identify the extent to which climate adaptation policies in Vietnam exhibit conditions that are likely to ensure a sufficient, credible and effective adaptation.

In total, 21 conditions, categorized under five normative principles and covering critical issue areas in adaptation domain, form the climate adaptation policy assessment framework. The principles were double-checked and tested in case studies through observations and analyses of policy documents to ensure that each condition should be distinct and not overlapping across principles. To see if the principles and attendant conditions were able to capture all relevant aspects of adaptation, the authors used structured expert judgment. In total, 39 policy documents pertaining to climate change adaptation were selected for qualitative document analysis. In-depth interviews with local officials and experts were conducted to address data gaps.

The study reveals major weaknesses constituting a reasonably worrisome picture of the adaptation policies in Vietnam since several critical conditions were underrepresented. These results shed new light on why some adaptation policies falter or are posing adverse impacts. The findings suggest that a sound policy assessment framework can provide evidence on what effective adaptation policy looks like and how it can be enabled. The framework for climate adaptation policy assessment in this study can be easily adjusted and used for different socio-environmental contexts in which new conditions for policy assessment might emerge.

The findings show underlying weaknesses constituting a reasonably worrisome picture of the adaptation regime in Vietnam. In the absence of mechanisms and measures for accountability and transparency in policy processes, adaptation in Vietnam appears more likely to be prone to maladaptation and corruption. While solving these problems will not be easy for Vietnam, the government needs to evaluate whether the short-term gains in sustaining the existing adaptation policies really make progress and serve its long-term climate-adaptive development goals.

Although interpretations of adaptation effectiveness may be very divergent in different normative views on adaptation outcomes, the authors argue that a common, agreed-upon effectiveness can be reached if it is clearly defined and measurable in adaptation policies. Thus, the climate adaptation policy assessment framework proposed in this study is critical for policymakers, practitioners, donors and stakeholders dealing with adaptation to better understand the weaknesses in policymaking processes, pinpoint priority areas of action and timely prevent or prepare for possible adverse impacts of policies.

In the COVID-19 outbreak periods, people's life has been deranged, leading to disrupt the world. Firstly, the number of deaths is growing and has the potential to surpass the highest level at any time. Secondly, the pandemic broke many countries' fortified lines of epidemic prevention and gave people a more honest view of its seriousness. Finally, the pandemic has an impact on life, and the economy led to a shortage in medical, including a lack of clinicians, facilities and medical equipment. One of those, a simple ventilator is a necessary piece of medical equipment since it might be useful for a COVID-19 patient's treatment. In some cases, the COVID-19 patients require to be treated by modern ventilators to reduce lung damage. Therefore, the addition of simple ventilators is a necessity to relieve high work pressure on medical bureaucracies. Some low-income countries aim to build a simple ventilator for primary care and palliative care using locally accessible and low-cost components. One of the simple principles for producing airflow is to squeeze an artificial manual breathing unit (AMBU) iterative with grippers, which imitates the motion of human fingers. Unfortunately, the squeezing angle of grippers is not proportional to the exhaust air volume from the AMBU bag. This paper aims to model the AMBU bag by a mathematical equation that enables to implement on a simple controller to operate a bag-valve-mask (BVM) ventilator with high accuracy performance.

This paper provides a curvature function to estimate the air volume exhausting from the AMBU bag. Since the determination of the curvature function is sophisticated, the coefficients of the curvature function are approximated by a quadratic function through the experimental identification method. To obtain the high accuracy performance, a linear regression model and a least square method are employed to investigate the characteristic of the BVM ventilator's grippers angle with respect to the airflow volume produced by the AMBU bag.

This paper investigates the correlation between the exhausting airflow of the AMBU bag and the grippers angle of the BVM ventilator.

The experimental results validated that the regression model of the characteristic of the exhausting airflow of the AMBU bag with respect to the grippers' angle has been fitted with a coefficient over 98% within the range of 350–750 ml.

This paper aims to identify the disproportionate impacts of the COVID-19 pandemic on labor markets.

The authors conduct a large-scale survey on 16,000 firms from 82 industries in Ho Chi Minh City, Vietnam, and analyze the data set by using different machine-learning methods.

First, job loss and reduction in state-owned enterprises have been significantly larger than in other types of organizations. Second, employees of foreign direct investment enterprises suffer a significantly lower labor income than those of other groups. Third, the adverse effects of the COVID-19 pandemic on the labor market are heterogeneous across industries and geographies. Finally, firms with high revenue in 2019 are more likely to adopt preventive measures, including the reduction of labor forces. The authors also find a significant correlation between firms' revenue and labor reduction as traditional econometrics and machine-learning techniques suggest.

This study has two main policy implications. First, although government support through taxes has been provided, the authors highlight evidence that there may be some additional benefit from targeting firms that have characteristics associated with layoffs or other negative labor responses. Second, the authors provide information that shows which firm characteristics are associated with particular labor market responses such as layoffs, which may help target stimulus packages. Although the COVID-19 pandemic affects most industries and occupations, heterogeneous firm responses suggest that there could be several varieties of targeted policies-targeting firms that are likely to reduce labor forces or firms likely to face reduced revenue. In this paper, the authors outline several industries and firm characteristics which appear to more directly be reducing employee counts or having negative labor responses which may lead to more cost–effect stimulus.

This study explores the economic impact of the COVID-19 crisis on herding behaviour in the Australian equity market by considering liquidity, government interventions and sentiment contagion.

This study utilizes a daily dataset of the top 500 stocks in the Australian market from January 2009 to December 2021. Both predictive regression and portfolio approaches are employed to consider the impact of COVID-19 on herding intention.

This study confirms that herding propensity is more pronounced at the beginning of the crisis and becomes less significant towards later phases when reverse herding is more visible. Investors herd more toward sectors with less available information on financial support from the government during the financial meltdown. Conditioning the stock liquidity, herding is only detectable during highly liquid periods and high-liquid stocks, which is more observable during the initial phases of the crisis. Further, the mood contagion from the United States (US) market to Australian market and asymmetric herding intention are evident during the pandemic.

This is the first study to shed further light on the impact of a health crisis on the trading behaviour of Australian investors, which is driven by liquidity, public information and sentiment. Notwithstanding the theoretical contributions to the prior literature, several practical implications are proposed for businesses, policymakers and investors during uncertainty periods.