Machine Learning in Business Intelligence 4.0: Cost Control in a Destination Hotel
Cost control is a recurring problem in companies where studies have provided different solutions. The main objective of this research is to propose and validate an alternative to cost control using data science to support decision-making using the business intelligence 4.0 paradigm. The work uses Ma...
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| Veröffentlicht in: | International journal of interactive multimedia and artificial intelligence 2022-03, Vol.7 (3), p.86-95 |
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| container_title | International journal of interactive multimedia and artificial intelligence |
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| creator | Sanchez-Torres, Fulgencio Gonzalez, Ivan Dobrescu, Cosmin C |
| description | Cost control is a recurring problem in companies where studies have provided different solutions. The main objective of this research is to propose and validate an alternative to cost control using data science to support decision-making using the business intelligence 4.0 paradigm. The work uses Machine Learning (ML) to support decision-making in company cost-control management. Specifically we used the ability of hierarchical agglomerative clustering (HAC) algorithms to generate clusters and suggest possible candidate products that could be substituted for other, more cost-effective ones. These candidate products were analyzed by a panel of company experts, facilitating decisions based on business costs. We needed to analyze and modify the company's ecosystem and its associated variables to obtain an adequate data warehouse during the study which was developed over three years and validated HAC as a support to decision-making in cost control. KEYWORDS Business Analysis With Expert Assessment, Business Intelligence 4.0, Candidate Product, ICT Ecosystem, Machine Learning. |
| doi_str_mv | 10.9781/ijimai.2022.02.008 |
| format | Article |
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The main objective of this research is to propose and validate an alternative to cost control using data science to support decision-making using the business intelligence 4.0 paradigm. The work uses Machine Learning (ML) to support decision-making in company cost-control management. Specifically we used the ability of hierarchical agglomerative clustering (HAC) algorithms to generate clusters and suggest possible candidate products that could be substituted for other, more cost-effective ones. These candidate products were analyzed by a panel of company experts, facilitating decisions based on business costs. We needed to analyze and modify the company's ecosystem and its associated variables to obtain an adequate data warehouse during the study which was developed over three years and validated HAC as a support to decision-making in cost control. 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| identifier | ISSN: 1989-1660 |
| ispartof | International journal of interactive multimedia and artificial intelligence, 2022-03, Vol.7 (3), p.86-95 |
| issn | 1989-1660 1989-1660 |
| language | eng |
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| source | Electronic Journals Library; Dialnet; DOAJ Directory of Open Access Journals |
| subjects | Algorithms Backup software Business Analysis With Expert Assessment Business Intelligence Candidate Product ICT Ecosystem Machine Learning Cost control Decision-making Machine learning |
| title | Machine Learning in Business Intelligence 4.0: Cost Control in a Destination Hotel |
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