TY - GEN
T1 - Artificial Intelligence to Identify Factors Linking with Purchase Intention in Restaurants in Ecuador
AU - Peñate, Mikel Ugando
AU - García, Ángel Ramón Sabando
AU - Herrera, Reinaldo Armas
AU - Gómez, Angel Alexander Higuerey
AU - Duque, Diego Alfredo Salazar
AU - Inga-Llanez, Elvia Rosalía
AU - Di Michele, Pierina D’Elia
AU - Rojas, Byron Vinicio Lima
AU - Montaño, Veronica Maria Rojas
AU - Pinzon, Omar Enrique Ajila
AU - Manosalvas, Andrés Wladimir Herrera
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - The objective of the research is to determine the binding and determining factors with purchase intention and consumer access to food services in 4 and 5 fork establishments in Quito, Pichincha province, Ecuador employing artificial intelligence. An updated database of the Tourism Establishment Cadastre of the Ministry of Tourism as of June 2024 was used, including 418 restaurants in this classification. A structural equation model (SEM), with PLS-SEM approach, is proposed as a methodology, with an exploratory and confirmatory approach, generating coefficients by means of artificial intelligence for the items and constructs and the validation of hypotheses. Data analysis uses SPSS version 25 and the AMOS version 24 interface. Partial results highlight the binding and deterministic factors with purchase intention in restaurants, Staff Service β = 0.207; R2 = 0.348 (0,000), Psychological β = 0.192; R2 = 0.369 (0,000), Technological β = 0.092; R2 = 0.210 (0,000). Evidence Physical and Social factors had an incidence rate of 95%. Evidence Physical and Social factors had an incidence rate of 95%. In addition, it has convergent and discriminant validity and excellent critical reliability in terms of purchase intention. However, it should be noted that the Personal factor, although it presents an important bond with the Social factor is not determinant with a negative correlation and little significant in the consumer's attitude, which contrasts with the existence of a homogeneous bond with the Psychological factor and the Social factor, that are not oriented to its determination. Furthermore, there is no evidence of acceptance the hypothesis H4 (The Personal factor positively influences consumer purchase intention).
AB - The objective of the research is to determine the binding and determining factors with purchase intention and consumer access to food services in 4 and 5 fork establishments in Quito, Pichincha province, Ecuador employing artificial intelligence. An updated database of the Tourism Establishment Cadastre of the Ministry of Tourism as of June 2024 was used, including 418 restaurants in this classification. A structural equation model (SEM), with PLS-SEM approach, is proposed as a methodology, with an exploratory and confirmatory approach, generating coefficients by means of artificial intelligence for the items and constructs and the validation of hypotheses. Data analysis uses SPSS version 25 and the AMOS version 24 interface. Partial results highlight the binding and deterministic factors with purchase intention in restaurants, Staff Service β = 0.207; R2 = 0.348 (0,000), Psychological β = 0.192; R2 = 0.369 (0,000), Technological β = 0.092; R2 = 0.210 (0,000). Evidence Physical and Social factors had an incidence rate of 95%. Evidence Physical and Social factors had an incidence rate of 95%. In addition, it has convergent and discriminant validity and excellent critical reliability in terms of purchase intention. However, it should be noted that the Personal factor, although it presents an important bond with the Social factor is not determinant with a negative correlation and little significant in the consumer's attitude, which contrasts with the existence of a homogeneous bond with the Psychological factor and the Social factor, that are not oriented to its determination. Furthermore, there is no evidence of acceptance the hypothesis H4 (The Personal factor positively influences consumer purchase intention).
KW - Artificial intelligence scientific statistics
KW - Determinants
KW - Purchase intention
KW - Restaurants
UR - https://www.scopus.com/pages/publications/105030260495
U2 - 10.1007/978-3-031-98768-7_13
DO - 10.1007/978-3-031-98768-7_13
M3 - Contribución a la conferencia
AN - SCOPUS:105030260495
SN - 9783031987670
T3 - Lecture Notes in Networks and Systems
SP - 225
EP - 239
BT - Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024 - Volume 1
A2 - Garcia, Marcelo V.
A2 - Reyes, John-Paul
A2 - Nuñez, Carlos
A2 - Gordón-Gallegos, Carlos
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2024
Y2 - 21 October 2024 through 25 October 2024
ER -