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Influence of the Quality of Food, Service, and Physical Environment on Customer Satisfaction and Behavioral Intention in Quick-Casual Restaurants: Moderating Role of Perceived Price Kisang Ryu and Heesup Han Journal of Hospitality & Tourism Research 2010 34: 310 originally published online 27 October 2009 DOI: 10.1177/1096348009350624 The online version of this article can be found at: http://jht.sagepub.com/content/34/3/310

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INFLUENCE OF THE QUALITY OF FOOD, SERVICE, AND PHYSICAL ENVIRONMENT ON CUSTOMER SATISFACTION AND BEHAVIORAL INTENTION IN QUICK-CASUAL RESTAURANTS: MODERATING ROLE OF PERCEIVED PRICE Kisang Ryu University of New Orleans Heesup Han Dong-A University This study examined the relationships between three determinants of quality dimensions (predictors: food, service, and physical environment), price (moderator), and satisfaction and behavioral intention (criterion) in quick-casual restaurants. Despite the importance of foodservice quality, academics and managers know relatively little about how the combined effects of quality (food, service, and physical environment) elicit customer satisfaction which, in turn, affects behavioral intention. Hierarchical multiple regression analysis with interactions showed that quality of food, service, and physical environment were all significant determinants of customer satisfaction. In addition, perceived price acted as a moderator in the satisfaction formation process. Finally, the results indicated that customer satisfaction is indeed a significant predictor of behavioral intention. The findings may provide restaurateurs with a guideline for enhancing customer satisfaction and behavioral intention level. KEYWORDS: quality dimensions (food, service, and physical environment); perceived price; satisfaction; behavioral intention; quick-casual restaurants

People are eating out more often, but they increasingly put a premium on saving time and eating healthy in better eating environments. As a result, the new quickcasual segment has emerged as a growth category in the foodservice industry. This new category fills a restaurant niche between fast-food and full-service. Although service is minimal, quick-casual restaurants offer menus and décor more reflective of casual dining restaurants. These restaurants tend to do their highest sales volume Authors’ Note: This study was supported by research funds from Dong-A University. Any correspondence should be directed to Dr. Heesup Han ([email protected]). The authors thank Dr. John A. Williams at the University of New Orleans for his kind comments from a marketing perspective. Journal of Hospitality & Tourism Research, Vol. 34, No. 3, August 2010, 310-329 DOI: 10.1177/1096348009350624 © 2010 International Council on Hotel, Restaurant and Institutional Education

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Ryu, Han / QUALITY DIMENSIONS IN QUICK-CASUAL RESTAURANTS 311

during lunch and generate a check average of between $6 and $9, which is slightly higher than checks at standard limited-service restaurants. The clientele are generally adult customers with middle to upper incomes (Tillotson, 2003). In the quick-casual segment of the restaurant industry, the attractiveness of restaurant facilities, exceptional food, and acceptable level of service quality can affect customer satisfaction. Service quality and customer satisfaction are inarguably the two core concepts in marketing theory and practice (Spreng & Mackoy, 1996). In today’s world of intense competition, the key to sustainable competitive advantage lies in delivering high-quality service that will in turn lead to satisfied customers (Shemwell, Yavas, & Bilgin, 1998). Customer satisfaction has become one of the most critical marketing priorities because it is generally assumed to be a significant determinant of repeat sales, positive word-of-mouth, and customer loyalty. Total foodservice in the restaurant industry encompasses both tangible (food and physical facilities) and intangible (employee–customer interaction) components. A proper combination of the tangible and intangible aspects should result in a customer’s perception of high restaurant service quality, which in turn should lead to attaining customer satisfaction and positive behavioral intention in the restaurant industry. Although the importance of a quick-casual sector in the restaurant industry has been dramatically increasing, it has not gained much attention in research. Moreover, despite the managerial importance of physical environment, empirical research on the effect of physical environment in conjunction with food and service on quality perception is scarce in the hospitality literature. Although some previous studies have been conducted on the separate influences of these three effects on customers’ perception of restaurant service quality, no studies address their combined impacts. The combined effects of food, service, and physical environment on outcomes such as customer satisfaction also have been ignored. In addition, the role of price has been rarely examined, even though price is a fundamental antecedent of customer satisfaction. Consequently, this study aimed to bridge these gaps. The primary purpose of this study was to examine the relationships between three determinants of quality dimensions (i.e., perceived quality of food, service, and physical environment), perceived price, customer satisfaction, and behavioral intention in the quick-casual dining segment. The specific objectives of the study were (a) to investigate the combined influences of the perceived quality of food, service, and physical environment on customer satisfaction; (b) to examine the impact of customer satisfaction on behavioral intention; and (c) to explore the moderating role of perceived price in the relationship between three dimensions of quality (i.e., quality of food, service, and physical environment) and customer satisfaction. HYPOTHESES DEVELOPMENT Relationship Between Quality of Food, Service, Physical Environment, and Satisfaction

Influence of food quality on satisfaction. Store image may serve as a cue to the quality of a brand (e.g., Panera Brand) and vice versa. The literature on store Downloaded from jht.sagepub.com at JHTR on August 21, 2010

312 JOURNAL OF HOSPITALITY & TOURISM RESEARCH

image treats merchandise quality, service quality, and store environment as key store image attributes (Baker et al., 1994). In particular, food quality, atmosphere, menu variety, service from staff, cleanliness, styling, price, interior design and décor, professional appearance of staff, and store location have been identified as components of store image in the restaurant industry (Baker et al., 1994; Lindquist, 1974; Prendergast & Man, 2002). The view is consistent with Baker et al.’s (1994) definition of store image as a complex mixture of a consumer’s perception of a store according to different (salient) attributes. Bloemer and Ruyter (1998) examined the relationship among store image, store satisfaction, and store loyalty, and found that store image, which consists of merchandise, location, store atmosphere, customer service, price, advertising, personal selling, and sales incentive programs, had an indirectly positive effect on store loyalty via customer satisfaction. In addition, Fu and Parks (2001) examined the service quality dimensions that influence older diners’ intention to return to a family-style restaurant. They used “the quality of food” item as one of 24 items on the questionnaire to measure older diners’ perceived quality of restaurant service. MacLaurin and MacLaurin (2000) explored nine factors of theme restaurants in Singapore and included food quality as one of the important elements in addition to theme concept, service quality, menu, atmosphere, convenience, value, product merchandise, and pricing. Clark and Wood (1998) developed dimensions relevant to creating customer loyalty in restaurant choice. Study findings suggested that food quality was the most influential predictor of consumer loyalty in restaurant choice. Mattila (2001) indicated that the top three reasons for customers to patronize their target restaurants in the casual dining sector were food quality, service, and atmosphere. Specifically, food quality was the most important attribute of overall restaurant service quality and is expected to have a positive relationship with customer satisfaction and loyalty. Thus, it can be hypothesized that Hypothesis 1: Quality of food has a positive influence on customer satisfaction.

Influence of service quality on satisfaction. There have been mixed findings about the causal direction between service quality and customer satisfaction. The most common explanation for the difference is that perceived service quality is described as a form of attitude, a long-run overall evaluation of a product or service, whereas satisfaction is a transaction-specific evaluation (Bitner, 1990; Cronin & Taylor, 1992; Oliver, 1981; Parasuraman, Zeithaml, & Berry, 1988). Based on these conceptualizations, incidents of satisfaction over time lead to perceptions of service quality. For instance, Bitner (1990) developed a model of service encounter evaluation and empirically showed that satisfaction was an antecedent of service quality. In contrast, many other researchers empirically supported the influence of perceived service quality on customer satisfaction (Cronin & Taylor, 1992; Spreg & MacKoy, 1996; Ting, 2004). For instance, Cronin and Taylor (1992) examined the conceptualization and measurement of service quality and the relationships Downloaded from jht.sagepub.com at JHTR on August 21, 2010


among service quality, consumer satisfaction, and purchase intentions. The findings suggested that service quality was an antecedent of consumer satisfaction whereas consumer satisfaction was not a significant predictor of service quality. Spreg and MacKoy (1996) also discussed the conceptual arguments behind the distinction, and investigated the relationship between service quality and satisfaction by testing a modified Oliver’s (1993) satisfaction/service quality model. The results indicated that their modified model fit the data well when perceived service quality was an antecedent of satisfaction. Moreover, H. Lee, Lee, and Yoo (2000) examined the direction of causality between service quality and satisfaction. The findings showed that perceived service quality was an antecedent of satisfaction, rather than vice versa. Consistent with these findings, Ting (2004) suggested that service quality better explains customer satisfaction, and the coefficient of the path from service quality to customer satisfaction is greater than the coefficient of the path from customer satisfaction to service quality in the service industry. With regard to the lack of consensus, Parasuraman et al. (1994) posited that “the conflicting perspectives could be owing to the global judgment focus in most service quality research in contrast to the transaction-specific focus in most satisfaction research” (p. 111). They suggested that perceived service quality and customer satisfaction could be investigated from both transaction-specific and global perspectives. Thus, we propose here that customers can evaluate (be satisfied/dissatisfied with) an object or service only after they perceive the object or service. More specifically, we propose that customers may perceive the service quality immediately after service experience as well as at a later time and compare their perceptions with their expectations. The perceived service quality, expectations, and disconfirmation lead to satisfaction/dissatisfaction (Oliver, 1989). Therefore, it can be hypothesized that Hypothesis 2: Quality of service has a positive influence on customer satisfaction.

Influence of physical environment on satisfaction. The importance of physical surroundings to create an image and to influence customer behavior is particularly pertinent in the restaurant industry (Hui, Dube, & Chebat, 1997; Milliman, 1986; Raajpoot, 2002; Robson, 1999; Ryu & Jang, 2007). Because service is generally produced and consumed simultaneously, the consumer is “in the factory,” often experiencing the total service within the property’s physical facility (Bitner, 1992). Although the food and the service should be of acceptable quality, pleasing physical surroundings (e.g., lighting, décor, layout, and employee appearance) may determine to a large extent the degree of overall satisfaction and subsequent behavior in the restaurant industry. Because services are mainly intangible and often require the customer to be present during the process, the physical environment can have a significant impact on perceptions of the overall quality of the service encounter, which in turn affects customer satisfaction in the restaurant industry (Bitner, 1990, 1992, Brady & Cronin, 2001; Kotler, 1973; Parasuraman et al., 1988; Ryu & Jang, 2007). Bitner (1990) proposed that Downloaded from jht.sagepub.com at JHTR on August 21, 2010


the physical environment may significantly affect customer’s ultimate satisfaction. Furthermore, Bitner (1992) discussed the effect of tangible physical environment on overall development of service quality image. She coined the term servicescape to describe the combined effect of all physical factors that can be controlled by service organizations to enhance customer and employee behaviors. Servicescape refers to the “built environment” or, more specifically, the “man-made, physical surroundings as opposed to the natural or social environment” (Bitner, 1992, p. 58). She identified three primary dimensions of the servicescape that influence consumers’ holistic perceptions of the servicescape (i.e., perceived quality) and their subsequent internal (i.e., satisfaction with the servicescape) and external responses (e.g., approach/avoidance, staying, repatronage). The three dimensions are (a) ambient conditions (elements related to aesthetic appeal); (b) spatial layout and functionality; and (c) signs, symbols, and artifacts. Research suggests a direct link between physical environment and outcomes such as customer satisfaction (Chang, 2000; Chebat & Michon, 2003). For instance, Wakefield and Blodgett (1996) examined the effects of layout accessibility, facility aesthetics, electronic equipment, seating comfort, and cleanliness on the perceived quality of the servicescape. The findings revealed that perceived quality of physical environment significantly affected a customer’s satisfaction in the leisure service setting. In addition, Chang (2000) suggested that perceived physical environment was a direct indicator of a customer’s satisfaction, thereby suggesting that customer satisfaction was directly and positively associated with aspects of positive approach behaviors. Thus, restaurateurs could potentially have another tool through which to manage customer satisfaction and positive approach behavior. Hypothesis 3: Quality of physical environment has a positive influence on customer satisfaction.

Moderating role of perceived price. Price has been considered a significant component in explaining consumer behaviors. Keaveney (1995), in his investigation of customer switching behaviors in the service industry, found that pricing was the one of the most significant categories among eight general categories (i.e., inconvenience, core service/service encounter failure, and competition) in the model of customer switching behavior. In his study, about 9% of respondents mentioned price as the only reason to switch to another service provider, while 21% described price as one of two or more reasons for switching. Price is an essential element in predicting and understanding customer behaviors. Perceived price can be described as “the customer’s judgment about a service’s average price in comparison to its competitors” (Chen, Gupta, & Rom, 1994, p. 25). The concept of perceived price is based on the nature of the competitive-oriented pricing approach. This approach focuses on customers’ concerns about whether they are being charged more than or about the same as charged by competitors. Chen et al. (1994) indicated that “perceived price does not eliminate objectivity; rather it adds some subjectivity with the goal of achieving greater organized Downloaded from jht.sagepub.com at JHTR on August 21, 2010


pricing structure” (p. 25). This perceived price includes both monetary and non monetary prices, including the need to consider nonmonetary costs such as time and effort to the consumer (Zeithaml, 1988). Although many researchers have agreed that perceived price is an important determinant of customers’ postpurchase behaviors and emphasized the importance of perceived value, which is highly related to perceived price, in explaining customer behaviors, little empirical research has investigated the influence of perceived price on consumer behaviors in the service industry. Deruyter, Bloemer, and Peeters (1997) found that increases in service quality levels lead to an increase in satisfaction level, and pointed out that low perceived quality may also result in high service satisfaction. They insisted that customers may not necessarily buy the highest level of quality service. That is, price, convenience, and availability may increase customer satisfaction without actually influencing customer perceptions of service quality. Similarly, in examining the moderating effect of perceived value in forming customer satisfaction in the service sector, Caruana, Money, and Berthon (2000) found that perceived value has a significant moderating role between service quality and satisfaction. Additionally, the interaction between service quality and perceived value explained more of the variance in satisfaction than the direct influence of either service quality or perceived value on satisfaction. Many researchers agree that value is highly related to price––customers assess and pay for quality, whereas the utility of a product/ service is based on customer perceptions of what is received (e.g., service/ product) and what is given (e.g., money; Caruana et al., 2000; Zeithaml, 1988). Indeed, in the marketing literature, measurement of perceived value includes price perception. Thus, although no empirical research supports the influence of customer-perceived price on the relationship between quality and customer satisfaction in the restaurant industry, because value has a moderating effect in forming satisfaction, it can be inferred that perceived price also has a significant role in the relationship between quality and satisfaction. Specifically, when customers perceive the price to be reasonable, their satisfaction with food quality will increase. In other words, customers’ perception of reasonable price intervenes as a moderator variable to increase the impact of food quality on satisfaction. In addition, customers’ perception of reasonable prices in the fast-casual restaurant industry may enhance the effect of quality of service on customer satisfaction. The addition of the interaction between quality of service and perceived price may contribute to explaining better customer satisfaction. Further, customers’ perception of reasonable price in the fast-casual restaurant industry would increase the effect of quality of physical environment (e.g., attractive interior design/décor and pleasant music/color/lighting) on satisfaction. Hypothesis 4: Perceived price has a significant influence on the relationship between quality of food and customer satisfaction. Hypothesis 5: Perceived price has a significant influence on the relationship between quality of service and customer satisfaction. Hypothesis 6: Perceived price has a significant influence on the relationship between quality of physical environment and customer satisfaction. Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Influence of customer satisfaction on behavioral intention. Numerous researchers have verified the significant relationship between customer satisfaction and behavioral intention in business and hospitality fields. Getty and Thompson (1994) examined the roles of service quality and satisfaction in explaining behavioral intention. Their findings indicated that high level of satisfaction increases customers’ intentions to repurchase and recommend the product. In their investigation of guest behaviors in the lodging industry, Han and Back (2006) explained the formation of revisit intention. The results of their study showed that guests’ intention to revisit is a positive function of satisfaction. In an upscale restaurant setting, Han and Ryu (2007) found that improving customer satisfaction level is essential to increase revisit and recommendation intentions. Dissatisfied customers are likely to switch, complain, or spread negative word of mouth (Oliver, 1997). The obvious need for satisfying customers is to acquire repeat business and positive word of mouth, thereby improving profit (Barsky, 1992). Hypothesis 7: Customer satisfaction has a significant influence on behavioral intention.

Figure 1 displays the conceptual model of the relationship among quality of food, service, and physical environment, perceived price, customer satisfaction, behavioral intention. METHOD

Based on previous research (Bitner, 1992; Brady & Cronin, 2001; Garbarino & Johnson, 1999; Kandampully & Suhartanto, 2000; H. Lee et al., 2000; Maxham & Netemeyer, 2002; Nguyen & Leblanc, 2002; Oh, 2000; Parasuraman et al., 1988; Powpaka, 1996; Prendergast & Man, 2002; Taylor & Baker, 1994; Zeithaml, Berry, & Parasuraman, 1996), a focus group, a pilot test, and a questionnaire were used to measure the quality of food, service, physical environment, price, and customer satisfaction. All items were assessed via a 7-point Likert-type scale, ranging from extremely disagree (1) to extremely agree (7). Quality of food was assessed by three items––for example, “The food was delicious.” Quality of service was also assessed by three items (e.g., “I would say that the restaurant provided superior service”). Quality of physical environment was measured by four items. For instance, “The restaurant had attractive interior design and décor.” Perceived price was measured using a single item (i.e., “Price was reasonable”). Customer satisfaction was assessed by asking respondents to respond to three statements (e.g., “I have really enjoyed myself at this restaurant”). Behavioral intention was evaluated by assessing customer intentions to revisit the restaurant, to recommend it, and to spread positive word of mouth using three items (e.g., “I would like to come back to this restaurant in the future”). One focus group was conducted by undergraduate and graduate students. To qualify for the focus group, a participant had to be a customer of a quick casual restaurant within the past 3 months. Responses from the focus group helped to construct and refine the questionnaire. Participants freely discussed their criteria Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Figure 1 Conceptual Model Showing the Relationships Between Study Variables

Quality Dimensions

Perceived Price

Quality of Food

Quality of Service

Customer Satisfaction

Behavioral Intention

Quality of Physical Environment

for choosing a quick-casual restaurant. In addition, a pilot test was conducted with actual customers at quick-casual restaurants to ensure that the items selected had acceptable psychometric qualities with respect to the salient quality (i.e., food, service, physical environment) most frequently associated with experiencing the quick-casual dining segment. Finally, data were collected from customers at quick-casual restaurants via a self-administered questionnaire. Using convenience sampling approach, this study sampled 360 responses at three quick-casual restaurants with a different brand name located in a Midwestern state. The selected restaurants provide adequate level of service and quality food, but little differ in terms of quality attributes, so customers in each restaurant may experience different service, food, and physical environment. In addition, the restaurants are located in the areas where customers are easy to find an alternative each time if they wish. After eliminating unusable responses among the completed questionnaires, 341 responses were coded for data analysis. Among the survey participants, about 71.60% indicated that they had visited a quick-casual restaurant more than 5 times over the past three months, 46.00% had visited it more than 10 times, and only 4.10% had visited it one time. Among respondents, 44.40% were male, 55.60% were female. RESULTS Data Quality Testing

The reliability of the measures used in this study is reported in Table 1. Cronbach’s alpha was used to assess the internal consistency of the result measurements. All values exceeded the suggested cut-off of .70 (quality of food = .71; Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Table 1 Reliability of the Measures Scale Mean If Item Deleted Variables Quality of food QF1 QF2 QF3 Quality of service QS1 QS2 QS3 Quality of physical environment QPE1 QPE2 QPE3 QPE4 Customer satisfaction CS1 CS2 CS3 Behavioral intention BI1 BI2 BI3

9.62 10.88 10.06 10.25 10.24 10.08

16.62 15.03 15.36 14.75 10.62 10.54 10.91 10.97 10.95 11.70

Scale Variance If Item Deleted

Corrected Item– Total Correlation

Coefficient a = .71 5.06 .55 4.21 .49 4.98 .57 Coefficient a = .91 4.45 .83 4.22 .85 4.76 .79 Coefficient a = .83 9.79 .62 8.93 .66 8.83 .68 9.59 .64 Coefficient a = .90 4.54 .82 4.54 .85 4.28 .75 Coefficient a = .89 4.96 .81 4.90 .86 4.98 .70

a If Item Deleted .60 .69 .58 .87 .85 .89

.79 .78 .77 .78 .84 .82 .91 .82 .78 .92

Note: QF = quality of food; QS = quality of service; QPE = quality of physical environment; PP = perceived price; CS = customer satisfaction; BI = behavioral intention. Because perceived price was measured by using a single item, it is not included in the table.

quality of service = .91; quality of physical environment = .83; customer satisfaction = .90; behavioral intention = .89), thus indicating that internal homogeneity exists among the items scale in this study (Nunnally, 1978). The result shows that the reliability of the measures used in the current research appears adequate to measure each construct and assess the research hypotheses. Convergent and discriminant validity, which are considered subcategories or subtypes of construct validity, assess the degree to which a measurement represents and logically connects, via the underlying theory, the observed phenomenon to the construct (McDaniel & Gates, 1993). In this study, the purpose of the correlation analysis was to assess the convergent and discriminant validity of indices representing quality of food, service, and physical environment and customer satisfaction. Table 2 presents a correlation matrix of the measurement items to allow the investigation of the convergent and discriminant validity of the obtained measures (Taylor & Baker, 1994). Based on Taylor and Baker’s (1994) suggestion, if the correlation patterns within constructs differ from the correlation Downloaded from jht.sagepub.com at JHTR on August 21, 2010


319

QS2

QS3

QPE1 QPE2 QPE3 QPE4

PP

CS1

CS2

CS3

BI1

BI2

BI3

Note: QF = quality of food; QS = quality of service; QPE = quality of physical environment; PP = perceived price; CS = customer satisfaction; BI = behavioral intention. Perceived price (PP) was measured by using a single item. **p < .01 (two-tailed).

QS1

1.00 .42** 1.00 .54** .44** 1.00 .53** .38** .57** 1.00 .47** .38** .54** .81** 1.00 .60** .40** .54** .74** .77** 1.00 .44** .27** .41** .42** .42** .53** 1.00 .33** .32** .39** .35** .38** .40** .57** 1.00 .30** .38** .44** .43** .45** .43** .44** .64** 1.00 .37** .34** .44** .39** .44** .49** .60** .45** .60** .00 .28** .24** .28** .28** .34** .38** .23** .30** .33** .34** 1.00 .60** .30** .41** .44** .45** .49** .46** .40** .31** .42** .43** 1.00 .63** .28** .39** .42** .44** .50** .44** .42** .35** .42** .38** .84** 1.00 .55** .26** .41** .43** .44** .49** .46** .33** .34** .41** .29** .70** .74** 1.00 .60** .31** .37** .41** .40** .45** .42** .33** .27** .36** .37** .78** .74** .66** 1.00 .66** .36** .43** .47** .44** .54** .37** .29** .34** .42** .44** .71** .71** .62** .86** 1.00 .58** .29** .40** .43** .44** .51** .32** .27** .34** .42** .40** .64** .65** .58** .70** .72** 1.00

QF3

QF1 QF2 QF3 QS1 QS2 QS3 QPE1 QPE2 QPE3 QPE4 PP CS1 CS2 CS3 BI1 BI2 BI3

QF2

QF1

Variable

Table 2 Correlation Matrix of the Research Variables


patterns between constructs, discriminant validity exists. If the within-construct item correlations are generally greater than the between-construct item correlations, convergent validity exists. As shown in Table 2, correlation patterns within indices differ from correlation patterns between indices, and the correlations within indices are generally greater than those between indices. This demonstrates that convergent and discriminant validity of the measures used in this study is relatively acceptable. Hierarchical Regression Analysis

To assess the main effect of quality (food, service, and physical environment) as well as the interaction effects (quality of food [QF] × perceived price [PP]; quality of service [QS] × perceived price [PP]; quality of physical environment [QPE] × perceived price [PP]) on customer satisfaction, hierarchical multiple regression analysis with interactions was used. Many researchers agree that one of the clearest ways to test moderating effects is using a hierarchical regression analysis based on Baron and Kenny’s (1986) suggestion (Aiken & West, 1991; Newsom, Prigerson, Schulz, & Reynolds, 2001; Yang & Peterson, 2004). Thus, hierarchical analysis using regression models was considered an appropriate approach in this study. A moderator can be described as a qualitative or quantitative variable that influences the direction/strength of the relationship between independent/predictor variables (quality of food, service, and physical environment) and dependent/criterion variable (customer satisfaction; James & Brett, 1984). If the interaction paths are significant, moderator hypotheses are supported. Significant main effects of the predictor and moderator (perceived price) on criterion variable (customer satisfaction) also can be found, but these effects are not directly related to testing the moderation hypothesis (Baron & Kenny, 1986). Table 3 shows the regression equations with interaction terms used in the current research. A significant beta coefficient for each interaction term (QF * PP, QS * PP, or QPE * PP) indicates that the moderator variable (perceived price) acts as a moderator. Many researchers agree that the test should be hierarchical (Aiken & West, 1991; Aydin, Ozer, & Arasil, 2005; Cronbach, 1987; Sharma, Durand, & Gur-Arie, 1981; Taylor & Baker, 1994). According to these researchers, each independent variable term and the moderator variable term (i.e., PP) should be entered prior to each interaction term to control for the effects of each independent variable and moderator variable in the interaction term. This hierarchical test also allows us to investigate the increase in the variance accounted for during a test of three regression equations. A significant R2 change means that the variables added in each step significantly improve the prediction. In this study, three regression equations were established to test hypothesized moderating role of perceived price (see Table 3). The first equation included the direct effect of three independent variables on customer satisfaction. The second equation contained the direct effects of three independent variables and perceived price on customer satisfaction. Following Aydin et al.’s (2005) approach to testing the moderating role of a certain variable in the links between multi-independent Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Table 3 Regression Models CS = a + b1QF CS = a + b1QF CS = a + b1QF CS = a + b1QF CS = a + b1QF BI = a + b1CS

+ + + + +

b2QS b2QS b2QS b2QS b2QS

+ + + + +

b3QPE b3QPE + b3QPE + b3QPE + b3QPE +

b4PP b4PP + b5(QF * PP) b4PP + b5(QS * PP) b4PP + b5(QPE * PP)

Equation 1 Equation 2 Equation 3.1 Equation 3.2 Equation 3.2 BI equation

Note: CS = customer satisfaction; QF = quality of food; QS = quality of service; QPE = quality of physical environment; PP = perceived price; BI = behavioral intention; a = intercept term, b = regression coefficient; QF/QS/QPE * PP = moderator variable interactions with independent variables.

variables and dependent variable, the third regression equation was a three-part equation that included the moderator effect of perceived price. Regression Equations 1 and 2 should not differ but should differ from Equations 3.1, 3.2, and 3.3 for perceived price to be a pure moderator in the relationships between three independent variables and the dependent variable. On the other hand, Regression Equations 1, 2, and the three-part equation (i.e., Equations 3.1, 3.2, and 3.3) should differ from each other for perceived price to be a quasi-moderator (Aydin et al., 2005; Sharma et al., 1981). Hypotheses Testing

The results of the regression are presented in Table 4. In the first regression equation of the hierarchical regression analysis, the dependent variable (customer satisfaction) was regressed on three independent variables, namely quality of food, service, and physical environment (Equation 1). Results indicated that this provides a significant R2 of .416. That is, the independent variables explained approximately 41.6% of the variance in customer satisfaction. The direct effects of all three independent variables on customer satisfaction were significant (quality of food = .284, p < .01; quality of service = .228, p < .01; quality of physical environment = .241, p < .01). Thus, Hypotheses 1, 2, and 3 were supported. The results also indicated that although little difference exists, the correlation coefficient and t-value of the path from quality of food (QF) to satisfaction (b1QF = .284, t = 4.919) was greater than the others, and the correlation coefficient and t-value of the path from quality of physical environment (QPE) to satisfaction (b3QPS = .241, t = 4.518) was greater than that of the path between quality of service (QS) and satisfaction (b2QS = .228, t = 3.928). These findings implied that quality of food was the most significant predictor of customer satisfaction among three components of the quality, followed by quality of physical environment and quality of service. The first equation was followed by a second regression of satisfaction with both the independent variables and the moderator variable (perceived price; Equ ation 2). The results shown in Table 4 indicated a higher R2 of .434. The R2 difference between the first equation and the second equation (.018) was statistically Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Table 4 Results of Regression Model Equation 1 Equation 2 Equation 3.1 Equation 3.2 Equation 3.3 BI equation

Variable

b

T Value

P Value

R2

QF QS QPE QF QS QPE PP QF QS QPE PP QF * PP QF QS QPE PP QS * PP QF QS QPE PP QPE * PP CS

.284 .228 .241 .271 .202 .208 .149 .664 .193 .215 .585 .682 .266 .565 .218 .538 .632 .266 .197 .536 .494 .559 .812

4.919 3.928 4.518 4.745 3.486 3.893 3.295 4.057 3.357 4.037 3.320 2.557 4.691 3.833 4.098 3.539 2.676 4.679 3.420 3.353 2.996 2.174 25.582

.000 .000 .000 .000 .001 .000 .001 .000 .001 .000 .001 .011 .000 .000 .000 .000 .008 .000 .001 .001 .003 .030 .000

.416

.434a

.445b

.446c

.442d

.659

Note: QF = quality of food; QS = quality of service; QPE = quality of physical environment; PP = perceived price; CS = customer satisfaction; BI = behavioral intention. a. DR 2 = .018, DF(1, 334) = 10.856, p < .001. b. DR 2 = .011, DF(1, 333) = 6.541, p < .011. c. DR 2 = .012, DF(1, 333) = 7.160, p < .008. d. DR 2 = .008, DF(1, 333) = 4.726, p < .030.

significant, DF = 10.856, p < .01. The findings also indicated that perceived price (PP) has a significant influence on customer satisfaction (perceived price = .149, p < .01). In the third regression (Equation 3.1), in addition to the independent variable and the moderator variable, the interaction term (QF * PP) was also entered. This significantly improved R2 to .445; the beta coefficient indicated a moderation effect of perceived price on the relationship between quality of food and customer satisfaction, thus supporting Hypothesis 4. The increase in R2 from .434 to .445 was statistically significant, DF = 6.541, p < .05 (Aiken & West, 1991). In Equation 3.2, the improvement in R2 from .434 to .446 was also significant with the addition of the interaction term (QS * PP), DF = 7.160, p < .01. This indicates that the addition of the interaction between quality of service and perceived price contributes to explaining better customer satisfaction. Moreover, the moderating effect of perceived price was significant. Thus, Hypothesis 5 was supported. Finally, the last interaction term (QPE * PP) was entered in Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Equation 3.3. The results indicated that when the interaction term was added, the prediction power significantly increased from .434 to .442, DF = 4.726, p < .05. Further, the beta coefficients indicate that the effect of interaction term (QPE * PP) on customer satisfaction was significant (p < .05). Thus, the results of hierarchical regression analysis 3.3 strongly supported Hypothesis 6. The three regression equations were significantly different in terms of explanatory power. In addition, the explanatory power of the three-part equation (R2 of Equation 3.1 = .445; R2 of Equation 3.2 = .446; and R2 of Equation 3.3 = .442) was significantly higher than that of Equation 1 (R2 = .416) and Equation 2 (R2 = .434). Thus, perceived price acted as a quasi-moderator in explaining customer satisfaction. Finally, Hypothesis 7 was tested. As shown in Table 4, the relationship between customer satisfaction and behavioral intention was significant (customer satisfaction = .812, p < .01), thus supporting Hypothesis 7. Customer satisfaction explained about 65.9% of the total variance in behavioral intention. This result was consistent with those from previous studies which showed that customer satisfaction is a significant predictor of behavioral intention (Getty & Thompson, 1994; Han & Back, 2006; Han & Ryu, 2007). DISCUSSION

This study makes important contributions toward understanding the formation of customer satisfaction and behavioral intention in the quick-casual restaurant industry. Findings revealed that customers’ perceived quality of food, such as delicious, nutritious, and visually attractive, is a significant predictor of customer satisfaction, and perceived price moderates the relationship between quality of food and customer satisfaction. When customers perceive that the price is reasonable, their satisfaction with food quality can be enhanced. In addition, quality of service increases customers’ satisfaction level, and customers’ perception of the reasonable price enhances the effect of quality of service on customer satisfaction. Further, when customers feel that the physical environment reflects quality, such as attractive interior design/décor and pleasant music/color/lighting, their satisfaction level increases. Customers’ perception of reasonable price also increases the effect of quality of physical environment on their satisfaction in quick-casual restaurants. Knowledge of the impact of perceived quality experienced by customers during their service encounter on retrospective satisfaction can help restaurateurs maximize satisfaction with the foodservice delivery process. Our results also provide strong support for the causal relationship from customer satisfaction to behavioral intention. This study represents the first attempt to examine the moderating role of price on the relationships among perceived quality of food, service, and physical environment and customer satisfaction in the restaurant industry, particularly in a quick-casual segment. One key contribution of our study is that our findings enrich knowledge of the satisfaction formation process by incorporating price perception into the research framework. Customers’ perception of a reasonable price intervenes as a moderator variable to enhance the impact of quality (i.e., Downloaded from jht.sagepub.com at JHTR on August 21, 2010


quality of food, service, and physical environment) on their satisfaction. Expanding this framework can be useful in both conceptual and empirical research. What is most important to customers of the quick-casual dining sector is quality of food, followed by quality of physical environment and quality of service. Our study findings are consistent in part with those of Mattila (2001), who proposed that the top three reasons for patronizing casual restaurants was food quality, service, and atmosphere. This might be true in a quick-casual dining segment because customers are increasingly interested in higher quality food preparation and taste as well as healthier food choices. Because the quality of food greatly influences a customer’s satisfaction level, in addition to good service and pleasant atmosphere restaurant operators must maintain a consistently high-quality menu to maximize the customer satisfaction level. Therefore, it is critical for restaurateurs to train their kitchen employees to provide customers with delicious and nutritious food presented attractively and in a consistent manner. This study confirms that providing high-quality food is a key component of running a successful quick-casual restaurant. Services deliver benefits that are often intangible and difficult to evaluate prior to purchase and consumption. A restaurant’s service and the quality of its food cannot be judged until those elements have been experienced. Thus, consumers seek tangible cues (e.g., lighting, table cloths) to predict what the restaurant will provide. Determinants of quality in the previous hospitality literature mainly focus on intangible attributes. However, Clark and Wood (1998) argued that tangible rather than intangible elements are of greater importance in gaining customer loyalty and continued restaurant patronage. Consumers’ favorite sandwiches/ bakery is “Panera Bread,” which is one of the leading brands in the quick-casual sector. The best attribute of the brand is atmosphere, followed by food quality, menu variety, service, and cleanliness. Consumers increasingly value atmosphere in the entire dining experience, which is consistent with the feature of physical environment in the present study. More restaurateurs are making efforts to meet that desire with innovative and exciting designs. According to the National Res taurant Association’s (2001) restaurant industry forecast, restaurant operators are investing more than ever before in restaurant design and décor as they strive to create a setting that will set them apart from the competition (Hamaker, 2000). This study revealed that perceived quality of physical environment was an important factor affecting customer satisfaction. To satisfy customers, restaurateurs should pay attention to the operation of the physical environment (e.g., attractive interior design and décor, comfortable seats, high quality of furniture, professional appearance of employee, and pleasant music, lighting, color) in quick-casual restaurants. In addition, since management can control the physical elements representing ambience (e.g., music, lighting, color, and aroma) and layout (e.g., seating arrangement) at little expense, restaurateurs should always consider physical elements that increase the entire dining experience as a marketing tool to attract/ retain more customers. It is also important to note that customers may seek a dining experience totally different from that they may obtain at home, and the atmosphere may do more to attract them than the food itself. Downloaded from jht.sagepub.com at JHTR on August 21, 2010


Although this study makes important contributions toward understanding the combined effect of total service (i.e., food quality, service quality, quality of physical environment) on customer satisfaction as well as the moderating role of perceived price, this research is not without limitations. First, because the data were collected using a convenience sampling approach, the findings from this study should be generalized with care. They were also collected at quick-casual restaurants in a small, Midwestern college town. Therefore, the results can be only generalized to quick-casual restaurants that are located in similar demographic regions. Higher external validity can be achieved by including restaurant customers at more quick-casual restaurants in various regions, obtaining samples through a random sampling method. More research is needed to examine the combined effect as well as the relative importance of the three dimensions of foodservice quality at other types of restaurants, such as casual dining, family dining, or fine-dining restaurants. It would be interesting to investigate whether the food quality dimension still plays the most important role in different types of restaurants. For instance, in the fine dining sector atmosphere might be more important than food itself to customers, who dine in such establishments principally on special occasions (e.g., wedding anniversary, etc.). Second, the proposed model can be extended to include components of postpurchase behaviors (e.g., retention or switching). Because the role of perceived price in explaining post-purchase behaviors has rarely been studied, investigating the moderating effect of perceived price on the relationships between satisfaction and postpurchase behaviors may be an interesting extension of this study. In addition, price awareness (or perception) can differ among demographic groups (Zeithaml, 1988). Specifically, female, married, and older demographic groups tend to show a higher level of awareness (Zeithaml, 1988). Thus, in future studies, developing a more comprehensive model by considering the influence of demographic characteristics may lead to a deeper understanding of satisfaction formation and subsequent customer behaviors in the restaurant industry, particularly in the quick-causal sector. Third, since perceived price was measured using a single item, triangulation issue could be raised. In addition, operationalizing this variable with only one single item could minimize the significance of the study finding about its moderating effect. Using multi-item scales for accurately measuring the construct is needed to further investigate the proposed model for the future study. In addition, only three items were used to measure food quality and service quality, respectively. This may raise the argument about the reliability and validity issue although the selection of those three items to measure food quality (G. R. Lee, Yoo, & Park, 2005; Noble, Corney, Eves, Kipps, & Lumbers, 2000; O’Hara et al., 1997; Prendergast & Man, 2002; Raajpoot, 2002) and service quality (Brady & Cronin, 2001; Powpaka, 1996) were mainly based on previous studies and the context of quick-casual restaurant. Fourth, such statistical techniques as multiple regression and hierarchical regression have a specific limitation that they assess only a single relationship between the independent and dependent variables (Hair et al., 1998). Thus, it is recommended Downloaded from jht.sagepub.com at JHTR on August 21, 2010


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Submitted May 2, 2007 First Revision Submitted February 12, 2008 Final Revision Submitted June 26, 2008 Accepted October 20, 2008 Refereed Anonymously Kisang Ryu, PhD (e-mail: [email protected]), is an assistant professor in The Lester E. Kabacoff School of Hotel, Restaurant and Tourism Administration at the University of New Orleans, Louisiana. Heesup Han, PhD (e-mail: [email protected]), is an assistant professor in the Department of Tourism Management, College of Business Administration, Dong-A University, Busan, Korea.
