Velicia-Martin Felix, Cabrera-Sanchez Juan-Pedro, Gil-Cordero Eloy, Palos-Sanchez Pedro R
Department Business Administration and Marketing, University of Sevilla, Sevilla, Spain.
Department Financial Economy and Operations Research, University of Sevilla, Sevilla, Spain.
PeerJ Comput Sci. 2021 Jan 4;7:e316. doi: 10.7717/peerj-cs.316. eCollection 2021.
The expansion of the coronavirus pandemic and the extraordinary confinement measures imposed by governments have caused an unprecedented intense and rapid contraction of the global economy. In order to revive the economy, people must be able to move safely, which means that governments must be able to quickly detect positive cases and track their potential contacts. Different alternatives have been suggested for carrying out this tracking process, one of which uses a mobile APP which has already been shown to be an effective method in some countries.
Use an extended Technology Acceptance Model (TAM) model to investigate whether citizens would be willing to accept and adopt a mobile application that indicates if they have been in contact with people infected with COVID-19. Research Methodology: A survey method was used and the information from 482 of these questionnaires was analyzed using Partial Least Squares-Structural Equation Modelling.
The results show that the Intention to Use this app would be determined by the Perceived Utility of the app and that any user apprehension about possible loss of privacy would not be a significant handicap. When having to choose between health and privacy, users choose health.
This study shows that the extended TAM model which was used has a high explanatory power. Users believe that the APP is useful (especially users who studied in higher education), that it is easy to use, and that it is not a cause of concern for privacy. The highest acceptance of the app is found in over 35 years old's, which is the group that is most aware of the possibility of being affected by COVID-19. The information is unbelievably valuable for developers and governments as users would be willing to use the APP.
冠状病毒大流行的蔓延以及各国政府实施的特别封锁措施，导致全球经济出现了前所未有的剧烈且迅速的收缩。为了振兴经济，人们必须能够安全出行，这意味着政府必须能够迅速检测出阳性病例并追踪其潜在接触者。对于开展这一追踪过程，人们提出了不同的方案，其中之一是使用一款移动应用程序，在一些国家，该程序已被证明是一种有效的方法。
使用扩展技术接受模型（TAM）来调查公民是否愿意接受并采用一款移动应用程序，该程序能显示他们是否曾与感染新冠病毒的人有过接触。研究方法：采用了调查方法，并使用偏最小二乘结构方程模型对482份问卷的信息进行了分析。
结果表明，使用该应用程序的意愿将由对该应用程序的感知效用决定，并且用户对可能的隐私泄露的任何担忧都不会成为重大障碍。在必须在健康和隐私之间做出选择时，用户选择健康。
本研究表明，所使用的扩展TAM模型具有很高的解释力。用户认为该应用程序有用（尤其是受过高等教育的用户）、易于使用，且不会引发隐私担忧。35岁以上人群对该应用程序的接受度最高，这是最意识到可能受到新冠病毒影响的群体。这些信息对开发者和政府来说价值非凡，因为用户愿意使用该应用程序。
