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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.

The growth of older adults in new regions poses challenges for public health. We know that these seniors live increasingly alone, and this impairs their health and general wellbeing. Studies suggest that social networking sites (SNS) can reduce isolation, improve social participation, and increase autonomy. However, there is a lack of knowledge about the characteristics of older adult users of SNS in these new territories. Without this information, it is not possible to improve the adoption of SNS in this population. Based on decision trees, this study analyzes how the elderly users of various SNS in Chile are like. For this purpose, a segmentation of the different groups of elderly users of social networks was constructed, and the most discriminating variables concerning the use of these applications were classified. The results highlight the existence of considerable differences between the various social networks analyzed in their use and characterization. Educational level is the most discriminating variable, and gender influences the types of SNS use. In general, it is observed that the higher the educational level, the more the different social networking sites are used.

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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.

This work, which is a first advance of a project in development, presents a study whose objective is to establish if the success of information systems affects the job satisfaction and job commitment among the people, affecting the organizational performance considering as a study area the university education institutions. It is also analyzed if certain capacities associated with information systems can influence the success of these systems. To this end, surveys have been applied to non-academic professionals with at least one year of seniority in the institution and who use information systems as a support tool in their usual work. Given that this study is in the process of development, an analysis of the results obtained for 50 people surveyed from these institutions is presented. The analysis of results indicates that there are capacities associated with information systems that influence the success of these systems, and that this success affects job satisfaction and job commitment, and through the latter to organizational performance.

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