Assessing the Moderating Effect of the End User in Consumer Behavior: The Acceptance of Technological Implants to Increase Innate Human Capacities

Abstract

Today, technological implants are being developed to increase innate human capacities, such as memory or calculation speed, and to endow us with new ones, such as the remote control of machines. This study's aim was two-fold: first, to introduce a Cognitive-Affective-Normative (CAN) model of technology acceptance to explain the intention to use this technology in the field of consumer behavior; and second, to analyze the differences in the intention to use it based on whether the intended implant recipient is oneself or one's child (i.e., the moderating effect of the end user). A multi-group analysis was performed to compare the results between the two groups: implant “for me” (Group 1) and implant “for my child” (Group 2). The model largely explains the intention to use the insideable technology for the specified groups [variance explained (R2) of over 0.70 in both cases]. The most important variables were found to be “positive emotions” and (positive) “subjective norm.” This underscores the need to broaden the range of factors considered to be decisive in technology acceptance to include variables related to consumers' emotions. Moreover, statistically significant differences were found between the “for me” and “for my child” models for “perceived ease of use (PEU)” and “subjective norm.” These findings confirm the moderating effect of the end user on new insideable technology acceptance.

Model of acceptance of a new type of beverage: application to natural sparkling red wine

“…The breakdown of the PANAS scale's dimensions into other dimensions has already been reported in the literature (e.g. Pelegrín- Borondo et al, 2016). In developing the UTAUT model, Venkatesh et al (2003) identified a dimension related to anxiety towards a new technological product.…”

“…The CAN model is derived from Pelegrín et al (2016), who hold that three types of factors influence the acceptance of new technological products. The CAN framework is consistent with Siegrist's (2008) aforementioned theoretical structure for the acceptance of new food products.…”

Do Affective Variables Make a Difference in Consumers Behavior Toward Mobile Advertising?

“…Its influence on attitudes and behavioral intentions has been widely demonstrated in the academic literature (c.f., Fishbein and Ajzen, 1975; Bearden and Etzel, 1982; Bagozzi, 2000; Pelegrín-Borondo et al, 2016; Versluis and Papies, 2016). …”

“…Moreover, the literature has demonstrated the ability of emotions to stimulate individuals' behavioral intentions (Bagozzi et al, 1999; Zajonc, 2000) and the existence of groups of people who tend to react similarly to certain emotions (Mano, 2004; Pelegrín-Borondo et al, 2016). Thus, in general, objects that cause pleasant sensations are evaluated positively, while those that cause unpleasant sensations are evaluated negatively (Pham, 2007; Bargh, 2013).…”

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“…Behavioral intention (i.e., the person's willingness to exert a certain effort to use a technology) is the core concept because it has been shown to be the proxy causal factor of effective technology use (Davis, ). The CAN model proved to be useful to predict of the intention to use insideables to increase the innate capabilities for both oneself (Pelegrín‐Borondo et al, ; Pelegrín‐Borondo, Reinares‐Lara, Olarte‐Pascuala, & Garcia‐Sierra, ) or for one's child (Pelegrín‐Borondo et al, ). Like other socio‐cognitive decision‐making models (e.g., TPB, TAM), the CAN model is based on the principle of parsimony and accordingly relies on a small set of factors that are considered to be the main predictors.…”