@article{Ciftci_Choi_Berezina_2020, title={Customer Intention to Use Facial Recognition Technology at Quick-Service Restaurants}, volume={17}, url={https://ertr-ojs-tamu.tdl.org/ertr/article/view/558}, abstractNote={<p>This study aims to provide a model that examines the predictors of intention to use facial recognition technology by customers in quick-service restaurants. The proposed model combines the unified theory of acceptance and use of technology (UTAUT) and contextual constructs, such as hedonic motivations, personal innovativeness, trust, perceived privacy, and security protection. The model was tested via structural equation modeling (SEM) by using data collected from a sample of quick-service restaurant customers. The findings of the study provide a valuable theoretical contribution to academia and practical implications for the restaurant managers.</p>}, number={5}, journal={e-Review of Tourism Research}, author={Ciftci, Olena and Choi, Eun-Kyong (Cindy) and Berezina, Katerina}, year={2020}, month={Jan.} }