How Institutional Actions Before Vaccine Affect Time Vaccination Intention Later: Prediction via Machine Learning

IF 3.4 Q2 MANAGEMENT
Jacques Bughin, Michele Cincera
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引用次数: 0

Abstract

Effective vaccination is often the only way to eliminate a major pandemic, to the extent that people welcome the cure. In general, vaccination preferences are shaped before actual vaccines are found. Factors that accelerate/ inhibit expected uptake must then be understood upfront if one hopes to nudge hesitants towards vaccination. We predict the portfolio of COVID-19 vaccination drivers through a large set of Machine Learning (ML) techniques for five European countries during the first wave of the COVID-19 and before vaccines were found and rolled out. We find better accuracy emerging from more sophisticated supervised ML techniques than regressions. While some factors are common to all ML tools, some only arise from the most accurate techniques: Gradient Boosting Machine and Support Vector Machine. In general, institutional trust (e.g. towards government actions) is a critical influencer of vaccine intent. How governments have reacted to the pandemic rise is a crucial filter as to how people will accept being vaccinated.
疫苗接种前的机构行为如何影响疫苗接种后的时间:通过机器学习预测
在人们欢迎治愈的程度上,有效的疫苗接种往往是消除重大流行病的唯一途径。一般来说,疫苗偏好在实际疫苗被发现之前就形成了。如果希望促使犹豫者接种疫苗,就必须预先了解加速/抑制预期吸收的因素。我们通过大量机器学习(ML)技术预测了五个欧洲国家在COVID-19第一波期间和疫苗发现和推广之前的COVID-19疫苗接种驱动因素组合。我们发现,与回归相比,更复杂的监督机器学习技术出现了更好的准确性。虽然有些因素是所有机器学习工具共同的,但有些因素只来自最精确的技术:梯度增强机和支持向量机。总的来说,机构信任(例如对政府行动的信任)是疫苗意向的关键影响因素。各国政府对疫情上升的反应是决定人们如何接受接种疫苗的关键因素。
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来源期刊
CiteScore
17.00
自引率
16.70%
发文量
31
期刊介绍: The Journal of Industrial Integration and Management: Innovation & Entrepreneurship concentrates on the technological innovation and entrepreneurship within the ongoing transition toward industrial integration and informatization. This journal strives to offer insights into challenges, issues, and solutions associated with industrial integration and informatization, providing an interdisciplinary platform for researchers, practitioners, and policymakers to engage in discussions from the perspectives of innovation and entrepreneurship. Welcoming contributions, The Journal of Industrial Integration and Management: Innovation & Entrepreneurship seeks papers addressing innovation and entrepreneurship in the context of industrial integration and informatization. The journal embraces empirical research, case study methods, and techniques derived from mathematical sciences, computer science, manufacturing engineering, and industrial integration-centric engineering management.
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