Exploring factors on customers’ restaurant choice: an analysis of restaurant attributes

Abstract

Purpose The purpose of this paper is to identify the importance and performance of customers’ full-service restaurant selection factors in the USA using the importance-performance analysis model. Design/methodology/approach An online survey was distributed to participants who were 19 years of age or older and had dined at a full-service restaurant in the past month. A total of 413 valid surveys were collected. Descriptive statistics were used to summarize the demographic information, satisfaction of restaurant attributes, revisit intention, and scores of importance-performance items. Path analysis was applied to group customer’s perceived importance of restaurant attributes and was used to analyze relationships among five attribute dimensions, satisfaction and revisit intention. Findings “Accurate guest check,” “prompt service,” “overall value of the dining experience,” and “lighting” were very important to customers but the restaurants’ performances in these areas were not satisfactory. Three attribute dimensions (food, service, and price and value) were positively and directly related to customer satisfaction and their effects are partially mediated. However, atmosphere and satisfaction are negatively and partially mediated in this study. Practical implications Food, service, price and value, and atmosphere dimensions have larger direct effects than indirect effect on revisit intentions. Their impacts on revisit intentions are partially mediated by satisfaction. Thus, great performance alone may not significantly improve revisit intentions. However, great performance can increase customer satisfaction, which has a stronger influence on revisit intentions. Originality/value This research explored the mediating effects of satisfaction between five restaurant dimensions and behavioral intentions.

Marketing Strategy, Technological Innovation and Inventory Management Towards Malaysia’s Food Industry Performance

“…As a conclusion, there were so many attributes that have positive significant relationship towards restaurant performance but not all of them may increase the customer satisfaction. This is supported by previous study by (Liu & Tse, 2018) which found that food, service, price and value have a positive relationship with restaurant's performance but does not improve the revisit intention of customer as it indirectly influences the customer's satisfaction.…”

Factors Affecting Brand Equity in Fast Food Restaurants Industry in Egypt

“…Gallarza, et al (2016) concluded that customer satisfaction is influenced significantly and positively by quality value, monetary value and emotional value. Liu and Tse (2018) indicated that price and value of full-service restaurants affect significantly and positively customer satisfaction. Mahmoud, et al (2018) pointed out that customer satisfaction is influenced significantly by customer value.…”

Cost-Effective Service Excellence: Exploring the Relationships Among Restaurants’ Operational Efficiency, Size and Service Quality

“…Moreover, all new models are based on the concept of service quality gaps, as first suggested by Parasuraman, Zeithaml, and Berry (1988). Therefore, Liu and Tse (2018) have stated that the generic SERVQUAL instrument (with all its modifications) remains the predominant diagnostic tool for service quality evaluation in the hospitality sector.…”

“…The global restaurant industry market is driven by quick changes in customers' preferences and their ongoing sense of exploration of new offers. Restaurant managers must be constantly innovating and offering high-quality services to satisfy their guests' quality expectations and gain a competitive advantage (Liu and Tse 2018). Moreover, guests are becoming more demanding in terms of healthy food (e.g., low-fat, gluten-free, organic and locally produced food, etc.)…”

“…Scholars have also proposed alternative models for restaurant quality measurement, such as a marketing-oriented (7P) quality model (Kukanja, Gomezelj Omerzel, and Kodrič 2017) and a quality model combining the importance-performance analysis (IPA) and the quality function deployment (QFD) method (Cheng, Tsai, and Lin 2015). According to Liu and Tse (2018), although alternative models have been proposed, DINESERV remains the most popular and frequently used diagnostic tool for service quality evaluation in the restaurant industry. Additionally, besides the possibility of using the presented (quantitative) measurement techniques, restaurant managers can also monitor the level of guests' quality perceptions by using simple (qualitative) approaches, such as observations, direct communication with guests, by following guests' reviews and comments, etc.…”