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The explanation of behaviors concerning telemedicine acceptance is an evolving area of study. This topic is currently more critical than ever, given that the COVID-19 pandemic is making resources scarcer within the health industry. The objective of this study is to determine which model, the Theory of Planned Behavior or the Technology Acceptance Model, provides greater explanatory power for the adoption of telemedicine addressing outlier-associated bias. We carried out an online survey of patients. The data obtained through the survey were analyzed using both consistent partial least squares path modeling (PLSc) and robust PLSc. The latter used a robust estimator designed for elliptically symmetric unimodal distribution. Both estimation techniques led to similar results, without inconsistencies in interpretation. In short, the results indicate that the Theory of Planned Behavior Model provides a significant explanatory power. Furthermore, the findings show that attitude has the most substantial direct effect on behavioral intention to use telemedicine systems.

This study aims to examine the influence of personality types on the acceptance of information technologies at work. Based on the model of the five dominant personality traits and the unified theory of acceptance and use of technology, 155 users of Enterprise Resource Planning systems were examined in two Chilean organizations. A cluster analysis applied to personality traits identified three different types of personalities. Subsequently, a multi-group analysis in Partial Least Squares of the technology acceptance model detected statistically significant differences among these types of personalities. Specifically, although for all personality types, the intention to use technology is explained in more than 60 percent, the strength of the antecedent variables changes radically depending on the type of personality. These findings indicate that personality type plays an essential role as a moderator of technology acceptance at work. This study is one of the first attempts where personality types, instead of specific personality traits, have been associated with technology acceptance models. In it, we performed an analysis of statistically significant differences among the types. Its practical implications are to identify the personality type of employees and adapt the implementation of innovations accordingly. This can help organizations to implement technology successfully, which, in turn, contributes to their sustainability.

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This study aims to predict and explain the acceptance of social video platforms for learning. A research model is proposed that explains that the intention of using these platforms is based on the perception of performance, social influence, and hedonic motivation. To validate the model, 568 Brazilian YouTube users were surveyed. The data were analyzed with partial least squares structural equations modeling (PLS-SEM). In particular, the predictive power of the model was assessed using the PLSpredict procedure. The results of this study can help to understand and forecast the use of these platforms for learning in developing countries.