The purpose of this study is an application of Lee’s Menu Engineering (LME) method for menu analysis on the eight kinds of pizza selected from 17 kinds of pizza served by an Italian restaurant near by the Keimyung College University campus. The eliminated nine items were in the third quadrant or below the trend line. The LME method is more efficient than generally used methods such as the Miller, Kasavana & Smith, Uman, Pavesic and Merricks & Jones method. The LME method comprises reference lines and four quadrants created by x, y axes and its average values. The x and y axes comprise the sales ratio (MM%, percentage of the Menu Mix) and the weighted contribution margin (WCM%, percentage of the Weighted Contribution Margin) respectively. The obtained results are such that total sales increased by 1.59% from 58,747,200 won to 59,684,000 won, despite the decrease in sales volume. Total contribution margin also increased from 35,248,320 won to 35,810,400 won. The trend line also shows from y=0.9147x (R2=0.703) to y=0.9944x (R2=0.9893). These results indicate that the LME method is superior in practical applications.

The past decades showed an increase in the number of meals consumed away from home. Restaurants could therefore play a pivotal role in improve diet quality by offering healthier food on their menus (Glanz and Hoelscher, 2004). One of the instruments that restaurants can use to increase healthier food intake is by making use of portion size. When people are served larger portions, they eat more (Steenhuis & Vermeer, 2009). In this study, we investigate the effectiveness of increased portion sizes of vegetables and lower portion sizes of meat (or fish) in a restaurant setting. Three restaurant locations from a restaurant chain in the Netherlands were selected for a field experiment. A cross-over design was used in which each restaurant was randomly assigned to a sequence of two conditions (i.e., intervention and control condition). In the intervention period, portion sizes of vegetables on plates were doubled (150 grams versus 75 grams) and portion sizes of meat and fish were cut on average with 12.5%. Consumption was calculated by subtracting the residues from the plates from the average served amount. Additionally, p3rticipants received a questionnaire in which a number of questions were asked, i.a., about their satisfaction with the meal and restaurant. In total, 536 participants in the control condition and 470 participants in the experimental condition were obtained. Vegetable consumption was higher in intervention weeks (M = 115.5 grams) than in control weeks (M = 61.7 grams; p < .001). Meat consumption was lower in intervention weeks (M = 183.1 grams) as compared to control weeks (M = 211.1 grams; p < .001). Finally, satisfaction with the restaurant visit did not differ between intervention weeks (M = 4.27) and control weeks (M = 4.35; p > .05). The results are robust given that we found the same effects across the three restaurants. An important implication of this study is that portion sizes could indeed be used as an effective instrument in stimulating healthy consumption behavior without affecting customer’s satisfaction.

This study was conducted to evaluate the menu of a Japanese restaurant in a first class tourism hotel. The calculations used for the menu analysis were conducted using MS Excel 2003. Several previous studies have been conducted to analyze menus. For example, Pavesic used of the weighted contribution margins (WCM) and potential food cost (PFC%) to evaluate menus, while Kasavana & Smith used the mix margin (MM%) and unit contribution margin (CM) to evaluate menus. The menu engineering method focused on the customer's viewpoints, while the Cost/Margin analysis method considered the manager's viewpoints. The menus that need continuous keeping Kasavana & Smith (Star) and Pavesic (Standard) included 'Assorted sashimi with side dishes (big), 'Lunch box special', 'Tempura course', 'Broiled Spanish mackerel and side dishes', 'Shrimp tempura', 'Special sushi', 'Seafood Udong', 'Buckwheat noodles'. The results of this study should increase customer satisfaction and profits at the Japanese Restaurant.

This study was designed to : (a) analyze the menus of the French restaurant in tourism hotel using the menu analysis techniques of Kasavana & Smith and Pavesic, (b) compare the characteristics of the two analysis techniques. The calculations for the menu analysis were done using the MS 2000 Excel spreadsheet program. The menu mix % and unit contribution margin were used as variables by Kasavana & Smith and weighted contribution margins (WCM) and potential food cost % (PFC%) by Pavesic. In two cases, a four-cell matrix was created and menu items were located in each according they achieved high or low scores with respect to two variables. The items that scored favorably on both variables were rated in the top category (e.g., star, prime) and those that scored below average on both were rated in the lowest category (e.g., dog, problem). While Kasavana & Smith's method focused on customer's viewpoints, Pavesic's method considered the manager's viewpoints. Therefore, it is more likely to be desirable for decision-making on menus if the menu analysis techniques chosen is suited to its purpose.