tailieunhanh - Lecture Hotel management and operations (5th Edition): Chapter 8.7 - Michael J. O'Fallon, Denney G. Rutherford

Understanding and managing the risks and challenges of hotel security in the 21st Century. The cost of the hotel room is not always the best predictor of how safe the room will be. There are a few security rules of thumb that should apply to any hotel room you rent. | Data Mining for Hotel Firms: Use and Limitations Vincent P. Magnini, Earl D. Honeycutt, Jr., and Sharon K. Hodge Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Introduction Hotel corporations accumulate large amounts of consumer date. This information can be organized and integrated in databases that can then be tapped to guide marketing decisions. From stores of information, data-mining technology extracts meaningful patterns and builds predictive customer-behavior models tat aid in decision making. Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Introduction Cont. Data mining is a largely automated process that uses statistical analyses to sift through massive data sets to detect useful, non-obvious, and previously unknown patterns of data trends. The purpose of this paper is to educate hotel managers about the benefits and application of data mining on the properties they oversee. Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Data Mining vs. Statistical Modeling Data mining differs from traditional statistical modeling in a variety of ways. Data mining focuses on machine-driven model building, while statistical modeling stresses theory-driven hypothesis testing. Data-mining techniques build models, whereas classical statistical tools are supervised by a trained researcher who possess a preconceived notion of what to examine. Data mining offers enormous gains in terms of performance, speed of use, and user friendliness. Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Data Mining vs. Statistical Modeling Cont. Data mining techniques overcome limitations of statistical techniques. Data mining has the ability to easily handle large and complex datasets. Data mining techniques are more data driven that they are user driven. Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Harrah’s Data-mining Success Story In 1997 Harrah’s hotels and casinos introduced a trademarked loyalty-card . | Data Mining for Hotel Firms: Use and Limitations Vincent P. Magnini, Earl D. Honeycutt, Jr., and Sharon K. Hodge Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Introduction Hotel corporations accumulate large amounts of consumer date. This information can be organized and integrated in databases that can then be tapped to guide marketing decisions. From stores of information, data-mining technology extracts meaningful patterns and builds predictive customer-behavior models tat aid in decision making. Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Introduction Cont. Data mining is a largely automated process that uses statistical analyses to sift through massive data sets to detect useful, non-obvious, and previously unknown patterns of data trends. The purpose of this paper is to educate hotel managers about the benefits and application of data mining on the properties they oversee. Copyright © 2011 by John Wiley & Sons, Inc. All rights reserved Data

• Du lịch
• Hotel management
• Hotel operations
• Hotel management and operations
• Hotel management system
• Hospitality industry
• Hotel performance
• Hotel organization structure
• Hotel general manager’s job
• Hotel lobby
• Hotel engineering function
• Contemporary hotel catering
• Hotel pricing
• Hotel Sales Organization
• Final year hotel management students
• Hotel Management Graduates
• Human capital requirement
• Multinational hotel companies
• Hotel management institutes
• Yield management
• Revenue management
• Beverage management
• Resort spas
• On line pricing
• Lodging industry
• Resort spas
• Organizational design
• Grooming future hospitality leaders
• General managers