Assessing acceptance of blockchain-based loyalty programs using correlational and configurational methods and a cognitive-affective-normative framework

Identificador:  imarina:9468892

Handle: https://hdl.handle.net/20.500.11797/imarina9468892

Autores:  de Andrés-Sánchez, J; Arias-Oliva, M; Souto-Romero, M; Llorens-Marín, M

Resumen:
Purpose Blockchain-based loyalty programs (BBLPs) offer several benefits over traditional loyalty programs (LPs), such as tokenization, adding value to noncash points and real-time reward redemption. However, successful adoption of BBLPs relies on the acceptance of potential users. This study aimed to assess BBLP acceptance by surveying 661 participants from the Western United States.Design/methodology/approach The analysis employed partial least squares structural equation modeling (PLS-SEM) and fuzzy set qualitative comparative analysis (fsQCA) using the cognitive-affective-normative (CAN) model for technology acceptance.Findings The results of PLS-SEM showed that perceived usefulness (PU) has the greatest impact on BBLP acceptance, followed by perceived ease of use (PEoU) and affective variables, albeit with smaller effect sizes. The use of fsQCA allows for the identification of various configurations that explain acceptance and rejection. Acceptance is most commonly associated with the presence of PU, PEoU, positive emotions (PEM) and the absence of negative emotions (NEM). In contrast, rejection is primarily explained by the absence of PU alongside the absence of PEoU, trust (TR), social influence (SI) and the presence of NEM.Research limitations/implications From a methodological perspective, it has been demonstrated that the sequential use of correlational and configurational methods can be useful for understanding how behavioral intention toward a new technology is formed. This study shows that the combined use of PLS-SEM and fsQCA provides a deeper explanation of BBLP acceptance than using a single analytical tool.Practical implications The configurations obtained with fsQCA allow the visualization of different profiles of potential BBLP users, facilitating the design of various market penetration strategies based on the user profile the seller seeks to reach and/or the type of technology they intend to commercialize.Originality/value While studies on the acceptance of cryptocurrencies are abundant, research on the acceptance of blockchain in other areas, such as marketing, is scarce, and its application in the implementation of LPs is nonexistent. This study pioneered the analysis of the acceptance of BBLPs. The complementary use of fsQCA alongside regression findings allows for more insightful conclusions than those obtained using PLS-SEM alone.