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336.#.#.a: Artículo

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351.#.#.b: Journal of Applied Research and Technology

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856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/1456/937

100.1.#.a: Sukwadi, Ronald; Atmaja, F.X. Brian Tristya; Chen, Gary Yu Hsin

524.#.#.a: Sukwadi, Ronald, et al. (2022). Integration of Latent Dirichlet Allocation and Quality Function Deployment to Analyze Hotel Service Quality Based on TripAdvisor. Journal of Applied Research and Technology; Vol. 20 Núm. 5, 2022; 594-605. Recuperado de https://repositorio.unam.mx/contenidos/4143007

245.1.0.a: Integration of Latent Dirichlet Allocation and Quality Function Deployment to Analyze Hotel Service Quality Based on TripAdvisor

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2022

264.#.1.c: 2022-10-31

653.#.#.a: hotel; service quality; Latent Dirichlet Allocation; Quality Function Deployment

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

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520.3.#.a: The main goals of this research are to determine customers’ requirements from hotels based on TripAdvisor and the technical capabilities to fulfill customers’ requirements. Latent Dirichlet Allocation (LDA) used in this research is the method to determine the customer requirements based on review from TripAdvisor. An output from the LDA method is used as input to Voice of Customer (VOC) in the quality function deployment (QFD). A hotel is selected to be a case study for implementing the integration of LDA and QFD. Questionnaires are distributed to the respondents for the purposes of filling the QFD. The absolute weight, relative weight, absolute importance and relative importance from the QFD with the highest scores are determined as the major capabilities to fulfill customers’ requirements. Suggestion given to the hotel based on output from the QFD. The suggestions for the hotel in this research were unannounced inspections and notes for list of problem to be solved immediately by the hotel.

773.1.#.t: Journal of Applied Research and Technology; Vol. 20 Núm. 5 (2022); 594-605

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

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300.#.#.a: Páginas: 594-605

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.22201/icat.24486736e.2022.20.5.1456

harvesting_date: 2023-11-08 13:10:00.0

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Artículo

Integration of Latent Dirichlet Allocation and Quality Function Deployment to Analyze Hotel Service Quality Based on TripAdvisor

Sukwadi, Ronald; Atmaja, F.X. Brian Tristya; Chen, Gary Yu Hsin

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Sukwadi, Ronald, et al. (2022). Integration of Latent Dirichlet Allocation and Quality Function Deployment to Analyze Hotel Service Quality Based on TripAdvisor. Journal of Applied Research and Technology; Vol. 20 Núm. 5, 2022; 594-605. Recuperado de https://repositorio.unam.mx/contenidos/4143007

Descripción del recurso

Autor(es)
Sukwadi, Ronald; Atmaja, F.X. Brian Tristya; Chen, Gary Yu Hsin
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
Integration of Latent Dirichlet Allocation and Quality Function Deployment to Analyze Hotel Service Quality Based on TripAdvisor
Fecha
2022-10-31
Resumen
The main goals of this research are to determine customers’ requirements from hotels based on TripAdvisor and the technical capabilities to fulfill customers’ requirements. Latent Dirichlet Allocation (LDA) used in this research is the method to determine the customer requirements based on review from TripAdvisor. An output from the LDA method is used as input to Voice of Customer (VOC) in the quality function deployment (QFD). A hotel is selected to be a case study for implementing the integration of LDA and QFD. Questionnaires are distributed to the respondents for the purposes of filling the QFD. The absolute weight, relative weight, absolute importance and relative importance from the QFD with the highest scores are determined as the major capabilities to fulfill customers’ requirements. Suggestion given to the hotel based on output from the QFD. The suggestions for the hotel in this research were unannounced inspections and notes for list of problem to be solved immediately by the hotel.
Tema
hotel; service quality; Latent Dirichlet Allocation; Quality Function Deployment
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces