Consilz Tan and Chee Yoong Liew
The paper examines the ‘Intention to Receive the COVID-19 Vaccines’ or IRV from three perspectives: the health belief model, behavioural economics, and institutional quality.
Abstract
Purpose
The paper examines the ‘Intention to Receive the COVID-19 Vaccines’ or IRV from three perspectives: the health belief model, behavioural economics, and institutional quality.
Design/methodology/approach
This study provides quantitative analysis by applying Chi-squared test of contingencies, paired sample t-tests, exploratory factor analysis, and multiple linear regression (stepwise method) on the data collected from 591 respondents mainly from Malaysia.
Findings
The results show that Perceived Benefits, Perceived Barriers, Perceived Susceptibility, Herding, and Institutional Quality play roles as predictors of IRV. Perceived Benefits play the most crucial role among the predictors and Perceived Barriers is the least important predictor. People have the herding mentality after being exposed to information encouraging such behaviour.
Originality/value
This study reveals that the respondents changed their behaviour in different circumstances when exposed to information that incorporates the effect of herding. Herding mentality, the effectiveness of government authorities, and regulatory quality have become important factors in enriching public health policies and the effectiveness of interventions.
Details
Keywords
Both investors and the stock markets are believed to behave in a perfectly rational manner, where investors focus on utility maximization and are not subjected to cognitive biases…
Abstract
Purpose
Both investors and the stock markets are believed to behave in a perfectly rational manner, where investors focus on utility maximization and are not subjected to cognitive biases or any information processing errors. However, it has been discovered that the sentiment of the social mood has a significant impact on the stock market. This study aims to analyze how did the protest event of Tesla happened in April 2021 have a significant effect on the company's stock performance as well as its competitors, Nio, under the competitive effect.
Design/methodology/approach
The research is based on time series data collected from Tesla and Nio by employing 10 days, 15 days and 20 days anticipation and adjustment period for the event study. This study employed a text sentiment analysis to identify the polarity of the sentiment of the protest event using the Microsoft Azure machine learning tool which utilizes MPQA subjective lexicon.
Findings
The findings provide further evidence to show that a company-specific negative event has deteriorating effects on its stock performance, while having an opposite effect on its competitors.
Research limitations/implications
The paper argues that negative sentiments through social media word of mouth (SWOM) affect the stock market not just in the short run but potentially in the longer run. Such negative sentiments might create a snowball effect which causes the market to further scrutinize a company's operations and possibly lose confidence in the company.
Originality/value
This study explores how the Tesla's protest event at Shanghai Auto Show 2021 has a significant impact on Tesla's stock performance and prolonged negative impact although Tesla implemented immediate remedial actions. The remedial actions were not accepted positively and induced a wave of negative news which had a more persistent effect.