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The purpose of this study is to develop a theoretical model for consumer behavioral intention by integrating the technology acceptance model (TAM) and the theory of perceived risk, which is tested on the intended use of credit cards in Vietnam.

The data were collected from 485 bank customers through a nationwide online survey. An exploratory and confirmatory factor analyzes were performed to validate the factor structure of the measurement items while structural equation modeling was used to validate the proposed model and testing the hypotheses.

The results of structural equation modeling reveal that perceived risk, perceived usefulness, social influence and perceived ease of use were significant determinants of consumer intention to use a credit card. Of them, only perceived risk discouraged the intended use of a credit card, which was synthesized from psychological, financial, performance, privacy, time, social and security risk.

This study measured the first-order risk dimensions based on the payment function of the credit card only; these measurements missed potential losses relevant to credit function of credit cards.

This study can be beneficial to banks enacting policies to attract more consumers and to help decide how to allocate resources to retain and expand their customer base.

The study adds value to the literature on consumer behavior by confirming the impact of second-order perceived risk on the intended use of credit cards, which most previous studies have not demonstrated. The research also provides an empirical evidence to the academic research platform on e-banking services in Vietnam, especially related to the credit card industry.

Developed by Stewart Myers (1984), the pecking order theory has turned out to be a spotlight in the recent trend of shifting from the traditional static trade‐off optimal model to other theories as an effort to look for an explanation of corporate capital structure behaviour. This article proposes a rational justification to the pecking order hypothesis through the establishment of its relationship to the paradox Modigliana‐Miller proposition I. In the process of reasoning to support our justification, we have resorted to various existing theoretical hypothesis including tax‐shelter theory, bankruptcy costs theory, agency theory, signalling theory, and managerial risk aversion theory. Some implications of this rational justification to the pecking order hypothesis are also briefly discussed.

This paper aims to analyze the current responses applied in Vietnam to the Coronavirus disease (COVID-19) pandemic and link these measures to priority actions highlighted in the Sendai Framework for Disaster Risk Reduction (SFDRR). From there, strengths, limitations and recommendations on applying the SFDRR to build the pandemic resilience in the future are discussed.

The authors synthesize literature on response measures to the COVID-19 pandemic in Vietnam from January to June 2020 and compare to four priority actions of the SFDRR including understanding risk, strengthening governance, investing in risk reduction for resilience and enhancing preparedness for effective response and resilient recovery.

Vietnam has effectively controlled the pandemic with 401 infected cases and no death so far. Well preparation, timely policies’ implementation, risk communication and comprehensive approaches are key strategies. These measures are same as the four priority actions in the SFDRR.

To the best of the authors’ knowledge, this is the first study in Vietnam to link the COVID-19 response and the SFDRR, which can serve as an important example for other countries in responding to the pandemic. Some measures have surpassed SFDRR’s guidance, especially preventive responses applied nationwide with strong political will and the community’s commitment accompanied by sanctions. Cultural factors such as the habit of using masks to prevent air pollution have contributed to the good observance of wearing mask regulations during the pandemic. However, some areas that need more attention include specific solutions for vulnerable groups, limiting fake news and ensuring patient privacy.