284 Cornell Hotel and Restaurant Administration Quarterly AUGUST 2007 Guest Satisfaction and Restaurant Performance

This study demonstrates a methodology to quantify the links between customer satisfaction, repeat-purchase intentions, and restaurant performance. Using data from a national restaurant chain, the authors constructed a series of mathematical models that predict how the level of customer satisfaction with certain attributes of guests ’ dining experience affects the likelihood that they will come back. In turn, the model shows how guests’ “comeback ” scores and other variables affect restaurant performance (i.e., sales and entrée counts). Robust and statistically significant, the models showed that restau-rants that pay attention to food quality, appropriate cost, and attentive service have the greatest chance to increase guests ’ intent to return. In turn, that intent to return is a chief driver of increased sales