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Blockchain technology has been highlighted as one of the most promising technologies to emerge in the 21st century. However, the expansion of blockchain applications is progressing much more slowly than initially expected, despite its promising properties. These considerations motivate this study, which evaluates the drivers that facilitate the adoption of this technology through blockchain-based loyalty programs (BBLPs). The analytical framework used is the conceptual groundwork known as the cognitive–affective–normative model. Thus, we propose to explain the behavioural intention to use BBLPs (BEHAV) with two cognitive variables, namely perceived usefulness (USEFUL) and perceived ease of use (EASE); two affective variables, namely positive emotions (PEMO) and negative emotions (NEMO); and a normative factor, namely, the subjective norm (SNORM). A partial least squares-structural equation modelling analysis suggests that, to explain the expected response of BEHAV, only the positive relationships of the cognitive constructs with the response variable are significant. The results of the quantile regression suggest that the cognitive constructs, especially USEFUL, have a consistently significant positive influence across the entire response range of the response variable. The affective variables are significant in explaining the lower quantiles of BEHAV but not across the full response range. NEMO consistently has a significant negative influence on BEHAV in the percentiles at or below the median response. PEMO has a significantly positive influence on some of the BEHAV percentiles below the median, although this impact is not consistent across the lower quantiles of the median. The normative variable appears to have a residual influence on BEHAV, which, when significant (at the 90th quantile), is, contrary to expectations, negative. The results highlight that, while cognitive variables are essential in the acceptance of BBLPs, emotions—particularly negative ones—play an especially significant role among potential users whose level of acceptance falls below the central trend. [ABSTRACT FROM AUTHOR]

This study investigated the rise of implantable or cyborg technologies, also known as insideables, which offer the potential to improve health‐related conditions and enhance the capabilities of healthy individuals. This research focused on the acceptance of insideables among university students in Spain, utilizing the unified theory of acceptance and use of technology (UTAUT) framework along with analytical tools such as partial least squares structural equation modelling (PLS‐SEM) and fuzzy set qualitative comparative analysis (fsQCA). The PLS‐SEM analysis revealed that factors such as performance expectancy, effort expectancy, and social influence positively influenced the intention to use insideables. However, the fsQCA revealed that no single variable is a necessary condition for explaining technology acceptance or rejection. Instead, a combination of constructs is needed to understand both intention to use and rejection. Configurational analysis emphasized the importance of factors such as performance expectancy, social influence, and hedonic motivation in explaining technology acceptance, whereas effort expectancy and perceived risk were less conclusive in their impact on behavioral intention. Moreover, the research revealed that the configurations related to the acceptance and rejection of insideables are asymmetrical. This study sheds light on the complex dynamics of implantable technology acceptance and provides valuable insights into the factors influencing its adoption. From a theoretical perspective, the sequential use of both correlational and configurational methods within the UTAUT framework allows us to gain a deeper understanding of the reasons behind the adoption of emerging technology rather than using only one data analysis methodology. [ABSTRACT FROM AUTHOR]

(1) Background: Loyalty programmes are business strategies aimed at increasing customer fidelity to brands. One of the most promising technologies of the 21st century is blockchain, whose application to the management of loyalty programmes can increase transparency and reliability, enable interoperability, and facilitate centralised management. (2) Methods: This study evaluates the antecedents of the acceptance of blockchain-based loyalty programmes (BBLPs) using a model grounded in the technology acceptance model UTAUT2. The four basic constructs of UTAUT, which we call the UTAUT-baseline, are considered explanatory factors: performance expectancy (PER), effort expectancy (EFF), social influence (SOC), and facilitating conditions (FAC). Additionally, we consider the constructs introduced in UTAUT2: hedonic motivation (HED) and perceived price value (PRI), to which we add innovativeness (INN) and trust (TRU), and we refer to these as UTAUT-extended, along with the moderating variables of UTAUT and UTAUT2: gender, age, and experience. The analytical approach used is complexity theory, which aims to capture the configurations that lead to both acceptance and rejection positions regarding BBLPs. This analysis is performed via fuzzy set qualitative comparative analysis (fsQCA). (3) Results: Eight explanatory configurations of the acceptance of BBLPs have been obtained, in which the presence of all UTAUT-baseline and UTAUT-extended constructs is a condition in at least three prime implicates. The constructs with the greatest presence as core conditions are PER, EFF, and TRU. On the other hand, nine configurations leading to the rejection of BBLPs have been identified. The absence of all UTAUT-baseline and UTAUT-extended variables is a condition in at least three configurations. The core conditions with the greatest presence in the rejection of BBLPs are the lack of FAC, HED, and PRI. (4) Practical implications: The results obtained are of great interest to business owners, as they allow for the characterisation of different profiles of people potentially engaged with BBLPs, as well as the profiles of consumers reluctant to adopt them. [ABSTRACT FROM AUTHOR]

Understanding the factors that influence the intention to use vaccines is crucial for implementing effective public health policies. This study examined the impact of various cognitive, affective, normative, and sociodemographic variables on the intention to be vaccinated against COVID-19 with the first-generation AstraZeneca vaccine. A survey of 600 residents of Spain was used to assess the influence and hierarchy of the drivers of the intention to vaccinate via least-squares and quantile regressions. The most significant factors were the perceptions of efficacy and social influence, both of which had positive impacts (p < 0.0001). The positive influence of fear of COVID-19 and the negative influence of fear of the vaccine were also significant in shaping the central tendency toward vaccination. However, these fear-related variables, particularly the fear of COVID-19, lost importance in quantile adjustments outside the central tendency. Among the sociodemographic variables, only the negative impact of income was statistically significant. These results are valuable for the development of vaccination policies because they measure the sensitivity of attitudes toward vaccination to exogenous variables not only in the central values, as is common in similar studies, but also across the entire range of responses regarding the intention to vaccinate. This additional analysis, which is not commonly performed in studies on vaccine acceptance, allows us to distinguish between variables which are consistently related to the intention to vaccinate and those that influence only expected responses. [ABSTRACT FROM AUTHOR]

Determining the peculiarities of the technological acceptance of disruptive vs. conventional products is a need for both academics and practitioners. Forecasting how consumers will behave with emerging disruptive technology products is key to successfully launching them on the market. The UTAUT2 model has been widely used for new technologies, but not yet to compare conventional and disruptive technology products. A survey comparing the acceptance of wearables and insideables, which are implantable technologies aimed at human augmentation, was carried out. The sample consisted of 1,563 higher-education students in 7 countries. The findings show similarities and differences in expected behaviours with regard to conventional (wearables) and disruptive (insideables) technologies. The explanatory power of the model could be very valuable for both research and business decision-making in this field. [ABSTRACT FROM AUTHOR]