Artificial Intelligence to Identify Factors Linking with Purchase Intention in Restaurants in Ecuador

Abstract:

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 H<inf>4</inf> (The Personal factor positively influences consumer purchase intention).

Año de publicación:

2026

Keywords:

• Artificial intelligence scientific statistics
• determinants
• purchase intention
• RESTAURANTS

Fuente:

scopus