HOTVal Toolkit

**************************************************************************** Scroll down to "Additional Files" to access the HOTVal Toolkit. **************************************************************************** HOTVal is a hotel valuation spreadsheet based on a regression model discussed in the Center for Real Estate and Finance at Cornell called Cornell Hotel Indices: Second Quarter 2012: The Trend is Our Friend by Crocker H. Liu, Adam D. Nowak, and Robert M. White, Jr. The model which will be continually updated, provides a rough estimation of the value of a hotel property once the user inputs information on whether the hotel is a large or small hotel, the year and quarter of the valuation, the state where the property is located, the number of rooms, the number of floors, the land area of the hotel property, the actual age of the hotel and whether the hotel is located in a Gateway city. For the first three inputs as well as the last input, if the user clicks on a cell highlighted in yellow, a pull down menu will appear to expedite inputting. The model is provided as a free public service by The Center for Real Estate and Finance at the School of Hotel Administration at Cornell University to academics and practitioners on an as-is, best-effort basis with no warranties or claims regarding its usefulness or implications. The estimates should be considered preliminary and subject to revision. *This October 2016 version updates the previous Hotel Valuation model, published in 2012 , provides valuation estimates up to and including the third quarter of 2016.

The Business Case for (and Against) Restaurant Tipping

Recent interest in replacing tipping with service charges or higher service-inclusive menu pricing prompted this review of empirical evidence on the advantages and disadvantages to restaurants of these different compensation systems. The evidence indicates that these different pricing systems affect the attraction and retention of service workers, the satisfaction of customers with service, the actual and perceived costs of eating out, and the costs of hiring employees and doing business. However, the author comes away from the data believing that the biggest reason for restaurateurs to replace tipping is that the practice takes revenue away from them in the form of lower prices and gives it to servers in the form of excessively high tip income. The biggest reason for restaurateurs to keep tipping is that it allows them to reduce menu prices, which increases demand. Thus, restaurateurs’ decisions to keep voluntary tipping or not should ultimately depend on the relative strengths of these benefits. The more that a restaurant’s servers are overpaid relative to the back of house and the wealthier and less price-sensitive a restaurant’s customers are, the more the owner of that restaurant should consider abandoning tipping. By this reasoning, many upscale, expensive restaurants (especially those in states with no or small tip credits) probably should replace tipping with one of its alternatives.

Early Bird & Night Owl Evaluation Tool (EBNOET) v2015

The early bird and night owl restaurant tool found in the accompanying Excel file provides an estimate of the effects of offering off-peak special menu prices. Unlike the classic back-of-envelope calculation, the tool includes the effect of anticipated cannibalization of full-price covers and seeks to optimize table use. The tool also considers the revenue from new customers attracted by the early bird or night owl promotions, as well as the level of increased business needed to achieve the net monetary value target for the promotion.

The Influence of Table Top Technology in Full-service Restaurants

The use of tabletop technology continues to grow in the restaurant industry, and this study identifies the strengths and weakness of the technology, how it influences customers, and how it can improve the bottom line for managers and business owners. Results from two studies involving a full-service casual dining chain show that dining time was significantly reduced among patrons who used the tabletop hardware to order or pay for their meals, as was the time required for servers to meet the needs of customers. Also, those who used the devices to order a meal tended to spend more than those who did not. Patrons across the industry have embraced guest-facing technology, such as online reservation systems, mobile apps, payment apps, and tablet-based systems, and may in fact look for such technology when deciding where to dine. Guests’ reactions have been overwhelmingly positive, with 70 to 80 percent of consumers citing the benefits of guest-facing technology and applications. The introduction of tabletop technology in the full-service segment has been slower than in quick-service restaurants (QSRs), and guests cite online reservation systems, online ordering, and tableside payment as preferred technologies. Restaurant operators have also cited benefits of guest-facing technology, for example, the use of electronic ordering, which led to increased sales as such systems can induce the purchase of more expensive menu items and side dishes while allowing managers to store order and payment information for future transactions. Researchers have also noted the cost of the technology and potential problems with integration into other systems as two main factors blocking adoption.