Background 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. Objective 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. Results 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. Conclusions 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.

The COVID-19 pandemic is a serious threat to human health, the global economy, and the social fabrics of contemporary societies as many aspects of modern everyday life, including travel and leisure, have been shattered to pieces. Hence, a COVID-19 mandatory vaccination as a precondition for international travel is being debated in many countries. Thus, the present research aimed to study the intention to take the COVID-19 vaccine as a precondition for international travel using an extended Norm-Activation Model. The study model integrates a new construct, namely mass media coverage on COVID-19 vaccination as additional predictor of intention to take the COVID-19 vaccine. The survey data were collected from 1221 international travelers. Structural equation modelling shows a very good fit of the final model to the data; the conceptual model based on extended Norm-Activation Model was strongly supported. Awareness of consequences related to the COVID-19 pandemic on individuals’ health has shown a positive effect on individuals’ ascribed responsibility to adopt emotionally driven (anticipated pride and anticipated guilt) pro-social behaviors that activate a personal norm towards altruistic and pro-mandatory vaccination-friendly behavior. Theoretical and practical implications are discussed.

With the total quantity of data doubling every two years, the low price of computing and data storage, make Big Data analytics (BDA) adoption desirable for companies, as a tool to get competitive advantage. Given the availability of free software, why have some companies failed to adopt these techniques? To answer this question, we extend the unified theory of technology adoption and use of technology model (UTAUT) adapted for the BDA context, adding two variables: resistance to use and perceived risk. We used the level of implementation of these techniques to divide companies into users and non-users of BDA. The structural models were evaluated by partial least squares (PLS). The results show the importance of good infrastructure exceeds the difficulties companies face in implementing it. While companies planning to use Big Data expect strong results, current users are more skeptical about its performance.

Cryptocurrencies are a new form of digital asset that operate through blockchain technology and whose purpose is to be used as a means of exchange. Some, such as bitcoin, have become globally recognized in recent years, but the uncertainty surrounding cryptocurrencies raises questions about their intended use. This study has the task of investigating the different factors that affect the intention behind the use of cryptocurrencies by developing a new research model and using Partial Least Squares (PLS) to assess it. The results show that all the constructs proposed have significative influence, either directly or indirectly, on the intention behind the use of cryptocurrencies. The findings provide value and utility for companies’ and cryptocurrencies’ intermediaries to formulate their business strategies.

No abstract