The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments
Research has been conducted on the grading of tourism establishments but little research has been conducted on the implementation of Artificial Intelligence (AI) to increase the number of graded tourism establishments. The objective of this study was to identify variables influencing tourism gradin...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AfricaJournals
2020-11-01
|
| Series: | African Journal of Hospitality, Tourism and Leisure |
| Subjects: | |
| Online Access: | https://www.ajhtl.com/uploads/7/1/6/3/7163688/article_2_9_5__793-809.pdf |
| _version_ | 1819093735606059008 |
|---|---|
| author | Tshepo Mothoagae Nazeer Joseph |
| author_facet | Tshepo Mothoagae Nazeer Joseph |
| author_sort | Tshepo Mothoagae |
| collection | DOAJ |
| description | Research has been conducted on the grading of tourism establishments but little research has been conducted on
the implementation of Artificial Intelligence (AI) to increase the number of graded tourism establishments. The objective of this study was to identify variables influencing tourism grading and to use them to construct a Bayesian Model for increasing the number of tourism establishments. Data was collected using an online survey questionnaire developed using the Survey Monkey tool. A total of 87 responses were received from 60 non-graded and 27 graded tourism establishments. The results indicate six factors affecting tourism grading, namely cost of grading, grading benefits, simplicity/complexity of grading application process, government funding, training of prospective grading applicants and computer literacy. The results further indicate grading cost and grading benefits as the most important factors for increasing the number of tourism establishments. The study implies that using this model will assist grading professionals to make informed decisions on initiatives aimed at increasing the number of graded tourism establishments. The study is among the first on implementation of AI to increase tourism grading establishments. |
| first_indexed | 2024-12-21T23:16:14Z |
| format | Article |
| id | doaj.art-6418a5d15653467aa531767e8c74c343 |
| institution | Directory Open Access Journal |
| issn | 2223-814X |
| language | English |
| last_indexed | 2024-12-21T23:16:14Z |
| publishDate | 2020-11-01 |
| publisher | AfricaJournals |
| record_format | Article |
| series | African Journal of Hospitality, Tourism and Leisure |
| spelling | doaj.art-6418a5d15653467aa531767e8c74c3432022-12-21T18:46:55ZengAfricaJournalsAfrican Journal of Hospitality, Tourism and Leisure2223-814X2020-11-0195793809https://doi.org/10.46222/ajhtl.19770720-52The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism EstablishmentsTshepo Mothoagae0Nazeer Joseph1School of Consumer Intelligence & Information Systems, College of Business and Economics University of JohannesburgSchool of Consumer Intelligence & Information Systems, College of Business and Economics University of JohannesburgResearch has been conducted on the grading of tourism establishments but little research has been conducted on the implementation of Artificial Intelligence (AI) to increase the number of graded tourism establishments. The objective of this study was to identify variables influencing tourism grading and to use them to construct a Bayesian Model for increasing the number of tourism establishments. Data was collected using an online survey questionnaire developed using the Survey Monkey tool. A total of 87 responses were received from 60 non-graded and 27 graded tourism establishments. The results indicate six factors affecting tourism grading, namely cost of grading, grading benefits, simplicity/complexity of grading application process, government funding, training of prospective grading applicants and computer literacy. The results further indicate grading cost and grading benefits as the most important factors for increasing the number of tourism establishments. The study implies that using this model will assist grading professionals to make informed decisions on initiatives aimed at increasing the number of graded tourism establishments. The study is among the first on implementation of AI to increase tourism grading establishments.https://www.ajhtl.com/uploads/7/1/6/3/7163688/article_2_9_5__793-809.pdftourism gradingbayesian networkstourism establishmentscomputational intelligence |
| spellingShingle | Tshepo Mothoagae Nazeer Joseph The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments African Journal of Hospitality, Tourism and Leisure tourism grading bayesian networks tourism establishments computational intelligence |
| title | The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments |
| title_full | The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments |
| title_fullStr | The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments |
| title_full_unstemmed | The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments |
| title_short | The Design of a Bayesian Network Model for Increasing the Number of Graded Tourism Establishments |
| title_sort | design of a bayesian network model for increasing the number of graded tourism establishments |
| topic | tourism grading bayesian networks tourism establishments computational intelligence |
| url | https://www.ajhtl.com/uploads/7/1/6/3/7163688/article_2_9_5__793-809.pdf |
| work_keys_str_mv | AT tshepomothoagae thedesignofabayesiannetworkmodelforincreasingthenumberofgradedtourismestablishments AT nazeerjoseph thedesignofabayesiannetworkmodelforincreasingthenumberofgradedtourismestablishments AT tshepomothoagae designofabayesiannetworkmodelforincreasingthenumberofgradedtourismestablishments AT nazeerjoseph designofabayesiannetworkmodelforincreasingthenumberofgradedtourismestablishments |