The Impact of Restaurant Innovativeness on Consumer Loyalty: The Mediating Role of Perceived Quality

Abstract

Although hospitality industry has consistently invested resources in innovation, the path by which a brand’s innovativeness influences consumers’ loyalty remains unclear. The purpose of this study is to establish a research model that represents the relationships of customers’ perceived restaurant’s innovativeness at brand level, perceived quality, and levels of loyalty. Specifically, five subdimensions (differentiation, dynamic brand, innovativeness brand, new leader, and idea generator) measure restaurant’s innovativeness at brand level. Perceived quality consists of the food and service aspects. The result shows that among brand innovativeness, differentiation predicts better loyalty whereas dynamic brand, innovativeness brand, new leader, and idea generator are less effective, with mediating effects of food quality and service quality. This outcome potentially expands the theoretical foundation of brand innovativeness in the hospitality discipline, while providing a promising marketing approach that empowers patrons with brand innovativeness through differentiation.

Keywords

restaurant innovativeness consumer loyalty food quality service quality lodging

Introduction

Innovativeness is an ongoing trend and one of the drivers for success in business. Many businesses elucidate themselves as innovative companies and invest billions of dollars to project a contemporary brand image (Henard & Dacin, 2010). Firms focus on innovative activities to improve the value of their products and services, thereby strenghening competitiveness in the marketplace (Berry et al., 2006) and effectively responding to consumers’ increasing expectations and choices (Teece, 2010). In the hospitality industry, Starbucks and Marriott International Inc. have continuously invested in innovations to improve consumers’ experiences and have both appeared on Forbes’ list of the world’s most innovative companies (2017). Previous studies in the hospitality context showed that innovative activities could improve business performance (Lee et al., 2016; Nicolau & Santa-María, 2013). However, whether all the resources applied by such firms actually increase consumers’ perceptions of innovativeness and in turn, affect their patronage behavior remains unclear. Although marketers in diverse industries, including hospitality and tourism, have continuously invested resources in innovative practices over the past decades, the research on the impact of consumers’ perceptions of innovativeness in academia has advanced slowly (e.g., Gomezelj, 2016; Hjalager, 2010; Kim et al., 2018).

Research on innovativeness in hospitality and tourism has received considerable attention during the past decade but remains insufficient (Gomezelj, 2016), because measurement of innovativeness from the consumer’s perspective is rare and evaluation of innovativeness has not been conducted at an enterprise level. The majority studies of innovativeness in the hospitality and tourism contexts have approached the topic from a micro-level or from a supplier side (i.e., the manufacturer) view (Gomezelj, 2016). Kim et al. (2018) also claimed that most studies investigated innovativeness from the manufacturer perspective, while sporadic research examined innovativeness from the consumer’s perspective. Moreover, studies of hospitality investigated innovativeness myopically or only focused on a specific aspect such as the adoption of technology (e.g., Andrea, 2012) rather than measuring innovativeness at the brand level. Specifically, although how consumers perceive a restaurant brand as innovative is important to the competitive position of restaurants, most innovativeness studies in the restaurant industry has focused on menu innovations (e.g., Ottenbacher & Harrington, 2009). That is to say, garnering immediate attention for the agenda of consumers’ perceived innovativeness research at the brand level is lacking and critical. Curiously, despite restaurant innovativeness being a rising research topic and consumers’ loyalty as a primary goal of a business’ innovative practices, few studies have attempted to address the effect of consumers’ perceived innovativeness on loyalty in general business (Pappu & Quester, 2016; Shams et al., 2015). Moreover, the focus of these studies was on electronic products (e.g., TV) in the manufacturing industry. Taking the hospitality practitioners’ interests in innovation into consideration, substantial doubt has arisen over whether innovativeness in service industries is truly a driver of consumers’ loyalty. Therefore, the questions become the mechanics of consumers’ perceptions of a brand restaurant as being innovative and the influence of the perceptions of innovativeness’ affecting consumers’ loyalty.

Given the relatively nascent state of the innovativeness literature, limited empirical research has examined the linkage between innovativeness and consumers’ loyalty, especially in the service industries like hospitality. In order to fill the gap, the purpose of the present study is to establish and test a research model that represents the impact of brand innovativeness and food and service quality on consumers’ levels of loyalty in the context of restaurants. While the impact of perceived quality on consumers’ loyalty is a fundamental element of consumers’ dining experiences that affects loyalty, as emphasized in previous studies, the empirical study of the avenues by which innovativeness affects loyalty remains unclear. Considering loyalty may appear in different degrees, inherent and latent levels of intensity must exist, measurable by ordinal categories. Accordingly, the use of ordered probit model (OPM) not only fits the scale for measuring the variable “loyalty” naturally but also permits identification of the magnitude of the effect for each determinant factor (e.g., brand innovativeness and perceived quality) on every level of loyalty. In other words, it is possible for deconstructing consumers’ intention for future patronage into several degrees, and the model will quantify the effects of the explanatory variables on each loyalty level. Moreover, apart from the theoretical contribution to the literature that quantification implies, quantification is also relevant because estimations and use of marginal impacts have critical managerial implications. With this outcome, decision makers can determine the degree to which the introduction of a brand-related novelty (brand innovation) and an amelioration of a food or service (quality enhancement) will favor consumers’ loyalty. Notably, the estimated marginal effects of restaurant innovativeness and perceived quality on loyalty contribute to the theoretical analysis of the relationship between innovativeness and loyalty. The results of the present study should deepen and broaden the theoretical foundation of innovativeness for hospitality and tourism. This research provides industry practitioners a promising marketing approach that attracts patrons with brand innovativeness.

Literature Review

Innovativeness

Innovativeness means creating and implementing something novel for the purpose of producing benefits (Hausman, 2005) and represents “openness to new ideas” (Hurley & Hult, 1998, p. 44). Notions of innovativeness gain concepts from the viewpoints of different stakeholders (e.g., managers [supplier] vs. consumers [demander]). Innovativeness from the standpoint of managers focuses solely on technical and functional aspects of products/services, while this notion from a consumer’s perspective addresses a consumer’s subjective perception of a firm’s capability and performance of offering novel and creative products/services (Danneels & Kleinschmidtb, 2001). Therefore, the two groups of stakeholders may not agree with all innovative practices due to distinctly different interests and goals (Danneels & Kleinschmidtb, 2001; Kunz et al., 2011). Kunz et al. (2011) underlined the significance of the consumer-centric perspective because consumers’ experiences and feedback on innovative activities ultimately determine the success of innovativeness. Particularly, consumers’ perceptions of a company’s innovativeness are important for a “people” industry such as hospitality (Kim et al., 2018). Accordingly, the assessment of innovativeness only from managers’ perspectives may fail to provide solutions for satisfying consumers’ actual needs (Kunz et al., 2011). Furthermore, the dominant of the innovativeness research has centered on the managerial perspective in the context of hospitality and tourism (e.g., Binder et al., 2016; Sandvik et al., 2014). However, limited studies investigated innovativeness in hospitality and tourism from a consumer-centric perspective (e.g., Jin et al., 2015; Kim et al., 2018).

Consumers’ perceptions of innovativeness are further classified according to different levels of abstraction (Kim et al., 2018; Pappu & Quester, 2016), such as product (Calantone et al., 2006), menu (Ottenbacher & Harrington, 2009), technological (Kandampully et al., 2016), service (Zolfagharian & Paswan, 2008), physical environment (Ariffin & Aziz, 2012), firm (Kim et al., 2016), and brand (Pappu & Quester, 2016) innovativeness. Unlike brand innovativeness, menu, service, physical environment, or technological innovativeness represent a limitation to a specific aspect. Kim et al. (2018) also addressed that consumers’ perceptions of innovativeness with a holistic approach are an important benchmark for the general assessment of a company’s innovative activities. Furthermore, Shams et al. (2015) suggested that a successful business depends on consumers’ perceptions of brand innovativeness, rather than the mere attributes of innovations (e.g., product or service). Therefore, the focus of the current study is consumers’ perceptions of innovativeness in branding.

Consumers’ Perceptions of Innovativeness in Branding

A brand’s innovativeness represents the elements of consumers’ perceptions of a brand’s innovativeness, perhaps similar to firms’ innovativeness, representing “consumer’s perceptions of an enduring firm [sic] capability that results in novel, creative, and impactful ideas and solutions for the market” (Kunz et al., 2011, p. 817). However, most consumers have difficulty identifying a brand (e.g., Oral-B) and its corresponding firm’s name (e.g., Proctor & Gamble Corp. owns the brand of Oral-B; Shams et al., 2015). In a similar vein, a restaurant firm may include multiple well-known brands, while consumers are unaware of the firm’s name. For example, many consumers are familiar with Olive Garden or LongHorn Steakhouse as reputed casual dining restaurant brands, but few associate these brand names with Darden Restaurant, Inc. Considering consumers cannot easily connect a firm and a brand, recent research has begun to realize the importance of consumers’ perceptions of innovativeness at the brand level (Eisingerich & Rubera, 2010; Pappu & Quester, 2016). Accordingly, the present study investigated consumers’ perceptions of innovativeness in branding (hereafter brand innovativeness) in the context of restaurants.

A few studies have conceptualized brands’ innovativeness. In an initial attempt, Eisingerich and Rubera (2010) conceptualized a brand’s innovativeness as “the extent to which consumers perceive brands as being able to provide new and useful solutions to their needs” (p. 66). However, Shams et al. (2015) challenged this notion by arguing that such a definition is too narrow, thereby restraining a brand’s activities to the needs of existing or potential consumers. However, consumers can still consider a brand as innovative without the intention to use a certain product/service. Accordingly, Shams et al. (2015) conceptualized brand innovativeness with the combination of both qualitative and quantitative approaches. A definition of “consumers’ perception of a brand’s track record for product innovation, the degree of creativity, and potential for continued innovative activities in the future in a given marketplace” (p. 1594). In the study of Brexendorf and Keller (2017), a brand’s innovativeness is “a firm’s reputation in providing a novel and useful solutions for its constituents” (p. 1535). Differentiation is the most relevant factor of brands’ innovativeness (Shams et al., 2015) and leads to a firm’s performance (Bradley et al., 2012). A higher level of consumers’ perceptions of a brand’s innovativeness may become a sustainable competitive advantage (Danneels & Kleinschmidtb, 2001) which associates with differentiation (Shams et al., 2015). In the restaurant industry, Erkuş-Öztürk and Terhorst (2016) investigated innovativeness of restaurants based on differentiation (menu, service, promotion, physical facility, etc.) and found higher quality restaurants are more innovative than lower quality ones. Consumers also perceive a dynamic brand as innovative, and an innovative brand has the potential for continuously generating new ideas (Kunz et al., 2011; Shams et al., 2015). Furthermore, successful innovativeness can help a brand create an image of market leadership (Shams et al., 2015; Srinivasan et al., 2002). Comprehensively, an innovative brand refers to the degree to which consumers perceive a brand to be innovative (Barone & Jewell, 2014). Therefore, the current study defines consumers’ perceptions of innovativeness of a restaurant brand as the extent to which a brand is perceived to be innovative, differentiating, dynamic, generative, and primary in the industry.

The concept of brand innovativeness from the consumer’s perspective gains explanation from the signaling theory (Spence, 1974). Originally, this theory describes informational asymmetry or imperfection between a business and its employees in the workplace within the discipline of economics. Later, extensive application of the signaling theory have been for marketing in which a brand conveys information intended to manipulate intangible attributes such as innovativeness (Henard & Dacin, 2010). Shams et al. (2015) developed another approach to understand brand innovativeness based on the associative network model of memory (Anderson, 1983), which explains the representation of brand innovativeness in memory and its processing by consumers. Associative network model views semantic memory or knowledge as a cognitive system, consisting of a set of nodes and associative links. The nodes are pieces of information that connect via associative links (Krishnan, 1996). Therefore, a brand is a collection of associations (Keller, 1993). In other words, a highly innovative brand is likely to have a richer link between the brand name and nodes, such as innovativeness and novelty, resulting in remembrance of the brand name when a consumer considers innovativeness (Shams et al., 2015). In spite of the importance of positioning brand innovativeness in consumers’ minds, researches in hospitality and tourism industry have not investigated the impact of brand innovativeness on consumers’ perceptions and behaviors.

The Effect of Brand Innovativeness on Perceived Quality

The common perception of quality was the attribute of the performance of products or services (Johnson & Fornell, 1991). Perceived quality is “the consumer’s judgment about an entity’s overall excellence or superiority” (Zeithaml, 1988, p. 3): the consumer’s subjective evaluation of product performance rather than actual quality (Zeithaml, 1988). Since hospitality and tourism are service industries, both product (food) and service are offerings at restaurants. While food quality has general acceptance as the fundamental aspect of the overall restaurant experience (Raajpoot, 2002), service quality has gained much attention in the literatures regarding restaurants since it is a barometer of consumers’ loyalty (Brady & Cronin, 2001). Gauging food quality uses different attributes, such as presentation, menu variety, healthy options, taste, freshness, temperature, and safety (Andaleeb & Conway, 2006). SERVQUAL (Parasuraman et al., 1988) and DINESERV (Stevens et al., 1995) are two classic benchmarks for service quality, which measure consumers’ expectations and perceptions with five dimensions (i.e., tangibles, reliability, responsiveness, assurance, and empathy).

Drawing on the signaling theory, the present study explores the relationship between brand innovativeness and perceived quality. As discussed in the previous section, the signaling theory explains that signalers (e.g., a brand) convey or communicate information intended to manipulate unobservable attributes (e.g., product quality; e.g., Boulding & Kirmani, 1993; Srivastava & Lurie, 2004) via signals. Brand innovativeness was identified as potential signal to which consumers could reply, and these signals affect consumers’ perceptions of the quality of offerings by the business (Shams et al., 2015). In other words, the perception of a brand can serve as a signal of the product/service’s attributes. Thus, brand innovativeness from a consumer’s perspective can positively affect consumers’ evaluation of quality of the product/service (Brown & Dacin, 1997). Notwithstanding the mechanics of consumers’ perceptions of a brand as being innovative and the influence of the perception on product quality and service quality has not explored in hospitality and tourism sectors.

Hypothesis 1₀: Consumers’ perceptions of brand innovativeness have no effect on perceived quality (food quality and service quality).

Hypothesis 1_a: Consumers’ perceptions of brand innovativeness positively affect perceived quality (food quality and service quality).

The Effect of Brand Innovativeness on Consumers’ Loyalty

Consumer loyalty demonstrates consumers’ commitment to patronizing a preferred product/service in the future (Oliver, 1999). The expected outcomes of developing consumer loyalty are a reduction of marketing cost, improvement of brand image, and creating a preeminent identity among competitors (Palmer, 1994). The intention for repeat patronage is an effective index for brand loyalty (Heskett et al., 1994). Bowen and Shoemaker (1998) particularly addressed that consumers’ loyalty in hospitality and tourism should reflect the possibility of consumers’ repeat patronage and even create volunteerism as members of the business.

Ehrenberg and Scriven (1999, pp. 53-54) described consumer loyalty as “an ongoing propensity to buy the brand, usually as one of several,” meaning that consumers show different levels of loyalty (repeat patronage in restaurants; Curran & Healy, 2014) among lesser forms of loyalty compared with true loyalty (Dick & Basu, 1994), because consumers may choose to dine at more than one restaurant (Uncles et al., 2003). Accordingly, this study uses levels of loyalty to measure precisely the extent of consumers’ intentions for future patronage as the final stage of the proposed model.

Innovativeness plays a critical role at the prepurchase stage of consumers’ purchase cycle (Lemon & Verhoef, 2016), which can lead to postpurchase of a product or service. Innovativeness allows businesses to capture a share of consumers’ consciousness at the initial stage of a purchasing process, as a trial of the brand. Consumers may generate positive feelings toward the brand from its innovative activities (Shams et al., 2015), which perhaps lead to repeated consumption and contribute to the formation of faith in the brand. Since innovativeness requires an understanding of the complicated nature of consumers’ needs (Kandampully & Duddy, 1999) and consumers believe that an innovative brand is more likely to satisfy ongoing needs (Eisingerich & Rubera, 2010), innovativeness may influence consumers’ purchase cycle.

Furthermore, innovation is one of the factors contributing to brand loyalty and the capability for innovation serves to promote consumers’ loyalty (Foroudi et al., 2016). Kunz et al. (2011) also contended that innovativeness covers both functional and hedonic attributes, which affect cognitive and affective loyalty, respectively. Kim et al., (2019) confirmed that consumers’ perceptions of innovativeness indirectly affect satisfaction through their cocreation behavior, leading consumer loyalty.

The study of Nicolau and Santa-María (2013) argued that measuring innovation effectiveness through the relationship between the consumers’ perceptions of innovativeness and their satisfaction is critical and required in the hospitality industry. However, the issue of whether or not consumers’ perceptions of innovativeness of a brand impacts loyalty has not had an empirical investigation for the hospitality industry, although practitioners are constantly seeking ways to be innovative to retain consumers. For example, Starbucks, known as the most innovative brand in the foodservice industry, creates sustainable stores and provides a personalized, lifestyle-based experience beyond providing high-quality foods and services. Due to Starbucks’ efforts toward innovation, consumers perceive this brand as an innovative brand, a dynamic brand, a generator of ideas, and a leader in the marketplace. Therefore, expectedly, consumers’ positive perceptions toward a brand’s innovativeness would generate higher levels of loyalty. Especially, consumers’ loyalty may show different degrees; consequently, measuring loyalty by ordinal categories would give deep insight into building consumers’ loyalty. Accordingly, the hypotheses proposed are as follows:

Hypothesis 2₀: Consumers’ perceptions of brand innovativeness have no effect on the level of consumers’ loyalty.

Hypothesis 2_a: Consumers’ perceptions of brand innovativeness positively affect the level of consumers’ loyalty.

The Mediating Effect of Perceived Quality between Brand Innovativeness and Consumers’ Loyalty

Quality is an attitude-like construct that drives consumers’ loyalty (Zeithaml, 1988). A positive relationship between these two constructs has general acknowledgement in the marketing literature (Tsiotsou, 2006) as well as in the hospitality and tourism literature (Namkung & Jang, 2007) since a consumer’s perception of a high-quality product/service provides a convincing reason to be loyal toward the associated brand. However, the impact of brand innovativeness on perceived quality and consumer loyalty and the role of the perceived quality between these two constructs has attracted little attention in previous literature.

Perceived quality can be an attribute affecting the relationship between brand innovativeness and loyalty based on the signaling theory. Pappu and Quester (2016) first investigated the relationship between brand innovativeness and perceived product quality of electronic products by articulating that brand innovativeness can serve as a signal by invoking heuristics to infer the quality of the brand being evaluated, and equate high innovativeness with high quality. Prior studies support this argument with the notion that when consumers are uncertain about product quality (Lichtenstein & Burton, 1989), they invoke heuristics for evaluating a product (Rao & Monroe, 1988), which influences loyalty (Pappu & Quester, 2016). In the hospitality and tourism industry, perceived quality of offerings consists of both product and service components, so investigating the roles of both product and service qualities would be critical. However, none of previous research has investigated the impact of brand innovativeness and the roles of product and service qualities to provoke consumers’ loyalty.

These previous discussions give rise to the hypotheses for the mediating role of perceived quality in the relationship between brand innovativeness and loyalty (Figure 1). Accordingly, consumers’ perceived quality of products/services could be a mediator between perceived brand innovativeness and loyalty, which conveys impact of innovativeness onto consumer loyalty toward the brand. Notably, the proposal is that brand innovativeness consists of several subdimensions (differentiation, dynamic brand, innovative brand, new leader, and idea generator).

Hypothesis 3₀: Perceived quality (food quality and service quality) has no mediating effect between brand innovativeness and loyalty.

Hypothesis 3_a: Perceived quality (food quality and service quality) mediates the positive relationship between brand innovativeness and loyalty.

Figure 1

Proposed Model

Method

Data Collection

A self-administered questionnaire was developed for research purposes in the present study. The participants from the survey panel of a global online market research firm received an invitation by email, which contained the link to the survey’s website on Qualtrics The screening question at the beginning of the survey requested identification of the respondent’s most familiar casual dining restaurant visited during the previous six months. The survey included a list of the top 15 branded chains for casual dining restaurants identified by NRN staff (2012). Participants with no patronage experience of any casual-dining restaurant during the designated half a year were asked to terminate participation in the survey. The questions in the survey focused on consumers’ experiences and perceptions at the chosen brand restaurant. It is noted that while the respondents consider a specific brand to make their assessment, we look at brands from an industry level to conduct the analysis; in this way, more generalizable results can be obtained.

Quota sampling based on the U.S. census was used to guarantee representativeness of the American population along five demographics: gender, age, income, region, and ethnicity. A total of 561 usable responses were used for data analysis after deleting 204 unqualified or incomplete responses. However, 56.33% of the respondents were female and 43.67% were male. The age group between 25 to 34 years comprised the highest proportion (22.64%) of the total sample. However, 21.57% of the participants were 35 to 44 years old, and 18.36% ranged between 45 to 54 years, 76.11% of the respondents were Caucasian (including Hispanic), followed by African American (12.12%) and Asian (4.99%). However, 35.12% of the respondents resided in the South in the United States, while 23.89% and 22.82% of the respondents resided in the Midwest and Northeast, respectively; 26.20% of the respondents obtained a bachelor’s degree, while 19.25% held high school diplomas. The sampling error was 4.13%.

Measurement of Variables

Brand innovativeness. The five items were used to measure brand innovativeness (modified from Kunz et al. [2011] and Shams et al. [2015]). We combined these measures to create a brand innovativeness composite score (Cronbach’s α = .94). Besides this composite score, the five subdimensions were used individually in a refined analysis; thus, we label them as differentiation, dynamic brand, innovative brand, new leader, and idea generator.

Perceived quality. To measure perceived quality in the restaurant context, food quality and service quality were used in this study. Regarding food quality, eight items were based on Liu and Jang (2009) and Namkung and Jang (2007). As before, we combined these measures to create a food quality composite score (Cronbach’s α = .94). Regarding service quality, five items were measured based on DINESERV proposed by Stevens et al. (1995). The resulting service quality composite score has a Cronbach’s α equal to .89.

Loyalty level. Participants responded to the dependent variable measuring loyalty toward the restaurant. The three items were modified from Oliver (1999) with a Likert 7 scale. We combined these measures to create a loyalty composite score (Cronbach’s α = .91). As the frequency of the first four values of the composite is too low (i.e., 3 observations for Value 1, 3 for Value 2, 7 for Value 3 and 19 for Value 4, respectively), we collapsed them into a single category, so that the groupings reflecting loyalty are analyzed by Level 1 through Level 4. These four levels, which are measured according to the subjective approach to capturing loyalty by which individuals self-report their feeling about the firm, could be named as “not loyal” (32 individuals), “little loyal” (64), “loyal” (136), and “very loyal” (329).

Table 1 shows the descriptive statistics and measurement items of the variables.

Table 1

Descriptive Statistics of Variables

Variables^a	M	SD
Brand Innovativeness (five items; α = .94)	5.33	1.25
(Measured on a Likert-type scale: 1 = strongly disagree . . . 7 = strongly agree)
BI01 (Differentiation): This restaurant sets itself apart from the others when it comes to casual dining restaurant industry.	5.37	1.29
BI02 (Dynamic Brand): This restaurant is dynamic, with regards to casual dining restaurants.	5.40	1.26
BI03 (Innovative Brand): This restaurant is an innovative brand when it comes to casual dining restaurant industry.	5.37	1.27
BI04 (New Leader): This restaurant is a new leader in the market of casual dining restaurants industry.	5.09	1.39
BI05 (Idea Generator): This restaurant constantly generates new ideas, with regard to casual dining restaurant industry.	5.26	1.32
Food Quality (eight items; α = .94)	5.99	0.95
(Measured on a Likert-type scale: 1 = very low . . . 7 = very high)
This restaurant’s food quality is _______in terms of:
FQ01: Presentation	5.70	1.09
FQ02: Variety	5.81	1.07
FQ03: Healthy options	5.16	1.29
FQ04: Taste	6.15	1.00
FQ05: Freshness	6.00	1.05
FQ06: Temperature	6.05	0.98
FQ07: Food safety	5.97	1.05
FQ08: Overall food quality	6.08	0.99
Service Quality (five items; α = .89)	6.01	0.91
(Measured on a Likert-type scale: 1 = strongly disagree . . . 7 = strongly agree)
SQ01: This restaurant serves food exactly as I ordered it.	6.08	0.98
SQ02: This restaurant makes you feel comfortable and confident in your dealings with them	6.08	0.97
SQ03: This restaurant provides prompt and quick service	5.90	1.03
SQ04: This restaurant has a visually attractive physical facilities or appearances.	5.99	0.98
SQ05: This restaurant anticipates my individual needs and wants.	5.64	1.15
Consumer Loyalty (3 items; α = .91)	6.31	1.03
(Measured on a Likert-type scale: 1 = not at all . . . 7 = very much)
CL01: When choosing a casual-dining restaurant, I would visit this restaurant again.	6.32	1.05
CL02: In the future, I would probably dine at this restaurant.	6.30	1.06
CL03: I would patronize this restaurant.	6.17	1.17

As the variables food quality and service quality are used as dependent variables as well, their number of categories have been collapsed into four to follow the same structure as the main dependent variable, which is loyalty. Otherwise, the comparability of parameters between models could be compromised. Note that brand innovativeness and the two control variables age and income are only used as independent variables, so the original seven-, six- and seven-point scales are used, respectively. While including ordinal variables as independent variables as if they had a linear effect is not without limitations, the parsimony derived from doing so may be enough to offset any disadvantages that could result (Long & Freese, 2014; Pasta, 2009).

Research Model

To test the effect of brand innovativeness on levels of loyalty and the mediating effect of food quality and service quality, the OPM was used. This model was employed because the consumers’ potential responses show a different level of loyalty. Considering that the current study is based on the notion that loyalty may appear through different degrees—with its inherent and latent levels of intensity—ordinal categories are used. Consequently, a model that is capable of capturing those categories and explicitly dealing with each of them separately must be used; that is, we need a model that can explain each shift in the levels of loyalty. Intuitively, as inherent intensity levels of loyalty are posited to exist, the ordinal categories that the OPM captures through the dependent variable can be accommodated to those different levels of loyalty. Also fundamental is the fact that this model allowed us to estimate the marginal effects of each independent variable on each ordinal category. Accordingly, the different degrees of loyalty was established as “not loyal,” “little loyal,” “loyal,” and “very loyal.” The response variable that measures the loyalty level for individual t was captured by a nonobserved latent variable U_t, so that higher levels of U_t imply greater levels of loyalty. Although this magnitude U_t is continuous, the individuals were classified, according to their responses, into the four categories mentioned above. Therefore, if U_t is under a specific threshold k₁ the individuals are not loyal at all; if U_t is above k₁ and under k₂ they are little loyal; if U_t is above k₂ and under k₃ they are loyal; and if U_t is above k₃ they are very loyal. Consequently, the probability that a consumer decides to be “not loyal” was obtained by the probability that U_t is under k₁, P(U_t ≤ k₁), the probability of “little loyal” by P(k₁ < U_t ≤ k₂), the likelihood of “loyal” by P(k₂ < U_t ≤ k₃) and the probability of “very loyal” by P(k₃ ≤ U_t).

Additionally, the latent variable U_t can be explained by observable variables x_t (such as perceptions of brand innovativeness) and by unobservable variables ε that are assumed to be random. Thus, it is obtained the following expression U_t= β′x_t + ε_t, where β are the parameters showing the effects of the individual characteristics on the level of the latent variable. Assuming a normal density φ for the random term ε_i, the above probabilities are defined as follows:

P (" not loyal ") = P (U_{t} < k_{1}) = P (β ’ x_{t} + ε_{t} < k_{1}) = P (ε_{i} < k_{1} - β ’ x_{i}) = ϕ (k_{1} - β ’ x_{i})

\begin{array}{l} P (" little loyal ") = P (k_{1} < U_{t} < k_{2}) = P (k_{1} < β ’ x_{t} + ε < k_{2}) = P (k_{1} - β ’ x_{t} < ε_{t} < k_{2} - β ’ x_{i}) \\ = ϕ (k_{2} - β ’ x_{t}) - ϕ (k_{1} - β ’ x_{t}) \end{array}

\begin{array}{l} P (" loyal ") = P (k_{2} < U_{t} < k_{3}) = P (k_{2} < β ’ x_{t} + ε_{t} < k_{3}) = P (k_{2} - β ’ x_{t} < ε_{t} < k_{3} - β ’ x_{t}) \\ = ϕ (k_{2} - β ’ x_{t}) - ϕ (k_{3} - β ’ x_{t}) \end{array}

\begin{array}{l} P (" very loyal ") = P (k_{3} < U_{t}) = P (k_{3} < β ’ x_{t} + ε_{t}) = P (ε_{t} > k_{3} - β ’ x_{t}) \\ = 1 - ϕ (k_{3} - β ’ x_{t}) \end{array}

This model allows us to identify the impact of brand innovativeness on loyalty level and the mediating effect of food quality and service quality. Specifically, the marginal effect of each variable x on every alternative i can be obtained by calculating:

\frac{\partial P (y = i)}{\partial x} = \frac{\partial Φ (k_{i + 1} - x ’ β)}{\partial x} - \frac{\partial Φ (k_{i} - x ’ β)}{\partial x}

where Φ is the normal cumulative function. The mediating effect was tested by following Baron and Kenny’s (1986) three-step procedure. To confirm the mediating effect, three separate regressions should be estimated and the following pattern must be found: first, the independent variable (brand innovativeness) must have an effect on the dependent variable (loyalty); second, the independent variable (brand innovativeness) must have an influence on the mediators (food quality and service quality); and third, the mediators (food quality and service quality) must have an effect on the dependent variable (loyalty) when the independent variable (brand innovativeness) is included as the explanatory variable. Additionally, to really show a mediating effect, a reduction in the size of the parameter of the independent variable (brand innovativeness) in the third regression must take place when compared with the parameter of this independent variable in the first regression. The Sobel test is designed for this purpose. If this reduction turns the parameter nonsignificant, then perfect mediation exists; however, if there is a reduction but the parameter is still significant, then there is partial mediation.

Results

Table 2 presents the different models that analyze the effect of brand innovativeness on loyalty and the results of the mediating effect of food quality and service quality. As indicated previously, the mediating effect was tested by following Baron and Kenny’s (1986) three-step procedure. Model 1 shows the results of the first step, wherein loyalty intensity was regressed on brand innovativeness: a significant and positive effect was found. Model 2 and Model 3 present the results of the second step by regressing food quality and service quality¹ (the proposed mediators) on brand innovativeness: a significant and positive parameter is obtained in each case. Model 4, where loyalty intensity was regressed on brand innovativeness, and food quality and service quality (which corresponds with Step 3), finds that the three variables had significant and positive effects, with brand innovativeness undertaking a statistically significant reduction in size compared with Model 1, as a consequence of the mediating effect of food quality and service quality (This reduction was confirmed by using both moderating variables (Table 3): for food quality, Sobel test = 6.35, p < .001, and for service quality, Sobel test = 5.09, p < .001). These results imply that there is mediation, specifically partial mediation, as food quality and service quality (the mediating variables) account for a percentage—but not all—of the effect of brand innovativeness on loyalty intensity. To reinforce the existence of these mediating effects, note that Model 4, when compared with Model 1, had a greater explanatory power as measured by the pseudo R² (which shows an increase of 83.83%) and was more efficient—despite having two extra parameters than Model 1—as measured by the Schwarz criterion.

Table 2

Effect of Brand Innovativeness on Levels of Loyalty and Mediation Detection

	Model 1: DV = Loyalty	Model 2: DV = Food Quality	Model 3: DV = Service Quality	Model 4: DV = Loyalty	Model 5: DV = Loyalty	Model 6: DV = Food Quality	Model 7: DV = Service Quality	Model 8: DV = Loyalty
Brand innovativeness	0.5615*** (0.0450)	0.6354*** (0.0435)	0.6952*** (0.0456)	0.2205*** (0.0555)
Differentiation					0.3683*** (0.0711)	0.2066** (0.0658)	0.2269*** (0.0662)	0.2960*** (0.0754)
Dynamic brand					0.2121* (0.0892)	0.2277** (0.0833)	0.1904* (0.0838)	0.1135 (0.0941)
Innovative brand					0.2452 ** (0.0865)	0.3097*** (0.0819)	0.2237** (0.0819)	0.0977 (0.0910)
New leader					−0.1390 (0.0745)	−0.0691 (0.0673)	0.0526 (0.0669)	−0.1392 (0.0779)
Idea generator					−0.0489 (0.0739)	0.0467 (0.0680)	0.1175 (0.0677)	−0.1197 (0.0789)
Food quality				0.5776*** (0.0819)				0.5598*** (0.0832)
Service quality				0.4826*** (0.0894)				0.4887*** (0.0913)
Income (control)	−0.0661 (0.0351)	−0.0474 (0.0325)	−0.0257 (0.0326)	−0.0743* (0.0369)	−0.0688 (0.0355)	−0.0456 (0.0328)	−0.0291 (0.0331)	−0.0770* (0.0372)
Age (control)	0.1327 *** (0.0340)	0.0767* (0.0312)	0.0665* (0.0312)	0.1032** (0.0356)	0.1010** (0.0347)	0.0608 (0.0319)	0.0602 (0.0320)	0.0759* (0.0362)
Threshold k₁	1.2766*** (0.2753)	1.5983*** (0.2620)	1.8426*** (0.2670)	2.1141*** (0.3003)	1.5617*** (0.2898)	1.9985*** (0.2777)	2.3526*** (0.2865)	2.1381*** (0.3093)
Threshold k₂	2.0632*** (0.2766)	2.5827*** (0.2671)	2.8569*** (0.2732)	3.1043*** (0.3076)	2.3846*** (0.2927)	3.0199*** (0.2849)	3.4116*** (0.2953)	3.1460*** (0.3169)
Threshold k₃	2.9825*** (0.2873)	3.8972*** (0.2881)	4.4983*** (0.3048)	4.2534*** (0.3290)	3.3485*** (0.3055)	4.3783*** (0.3087)	5.1274*** (0.3318)	4.3332*** (0.3397)
Pseudo R²	.1497	.1719	.1968	.2752	.1769	.1906	.2220	.2901
Schwarz criterion	1.8831	2.0902	1.9954	1.6377	1.8701	2.0897	1.9801	1.6510
LR statistic	179.30***	235.54***	265.01***	329.62***	211.90***	261.08	298.90***	347.50***

Note: Standard deviation in parenthesis.

p < .05. ^**p < .01. ^***p < .001.

Table 3

Significance (Sobel Test’s Values) of the Reduction of the Independent Variables

	Model 4	Model 8
Brand innovativeness (mediator: food quality)	6.35***
Brand innovativeness (mediator: service quality)	5.09***
Differentiation (mediator: food quality)		2.84***
Differentiation (mediator: service quality)		2.88***
Dynamic brand (mediator: food quality)		2.53*
Dynamic brand (mediator: service quality)		2.09*
Innovative brand (mediator: food quality)		3.29**
Innovative brand (mediator: service quality)		2.43*

p < .05. ^**p < .01. ^***p < .001.

Regarding the specific effects of the variables (Model 4), the significant and positive signs of brand innovativeness, and food quality and service quality lead to a greater propensity toward loyalty. In fact, the top panel of Table 2 shows that, if reaching good levels of brand innovativeness, and food quality and service quality favors loyalty, it does for the highest category of loyalty (“very loyal”). In other words, these two dimensions, if pursued, help guarantee the maximum level of loyalty.

These results cannot reject the alternative Hypothesis 1_a that brand innovativeness positively affects food quality and service quality, alternative Hypothesis 2_a that brand innovativeness positively affects the level of consumer loyalty and alternative Hypothesis 3_a that food and service quality mediates the positive relationship between brand innovativeness and loyalty.

As for the control variables, income was significant with a negative sign and age presents a significant and positive parameter, showing a propensity of low-income and older people to patronize these restaurants.

In an attempt to refine the analysis, the dimension brand innovativeness was broken down into the five subdimensions described above (differentiation, dynamic brand, innovative brand, new leader, and idea generator). To confirm the appropriateness of decomposing brand innovativeness into these five submissions, we ran a regression where the dependent variable is “brand innovativeness” and the independent variables are “differentiation,” “dynamic brand,” “innovative brand,” “new leader,” and “idea generator.” All five submissions are significant at a p value lower than .001 and the explanatory power of the variables is almost 95% (for the sake of space, we are not showing the results of the Tobit model in the article, but they are available from the authors on request). Therefore, the five variables explain “brand innovativeness”; however, they look at different facets of brand innovativeness, which explains the distinct impacts found for these submissions on loyalty. Specifically, and following process of the analysis of mediating effects. Model 5 (Step 1) finds three significant brand innovation-related subdimensions; in particular, differentiation, dynamic brand, and innovative brand. Model 6 and Model 7 (Step 2) shows that the same three subdimensions have a significant effect on food quality and service quality, respectively; and Model 8 (Step 3) presents the regression of loyalty intensity on the five dimensions of brand innovativeness plus the proposed mediators food quality and service quality. Only the subdimension differentiation kept its significant parameter, with a statistically significant reduction when compared with Model 5 (this reduction was confirmed by using both moderating variables: for food quality, Sobel test = 2.84, p < .001, and for service quality, Sobel test = 2.88, p < .001); therefore, food quality and service quality partially mediates the effect of differentiation on loyalty intensity. Note, however, that the two subdimensions that were significant in Model 5 (dynamic and brand innovativeness), lost their significance in Model 8, resulting in full mediation. For them, food and service quality accounts for all the impacts of dynamic and innovative brand on loyalty intensity. As before, the Sobel test was computed to confirm this reduction in effects from Model 5 to Model 8 regarding the two subdimensions of interest: for dynamic brand the value of this test was 2.53 (p < .05) when using food quality and 2.09 (p < .05) when using service quality; and for innovative brand is 3.29 (p < .01) when using food quality and 2.43 (p < .05) when using service quality. Also, the existence of these mediating effects was reinforced by the greater explanatory power (with an increase of 63.99%) and efficiency of Model 8 relative to Model 5.

Concerning the effects of the variables (Model 8), the significant and positive sign of differentiation led to a greater propensity toward loyalty. As before, the bottom panel of Table 4 shows that this positive effect occurs for the top loyalty category only: when differentiation determines loyalty, it does so that the consumers become very loyal. The variables food quality and service quality were significant and positive; note that the breakdown of brand innovativeness allowed us to detect how the effects of the subdimensions are carried over by food quality and service quality (the mediating variables). While the effect of food quality and service quality conveyed a portion of the effect of differentiation, it included the full impacts of dynamics and innovative brand. As for the control variables, the same pattern as in Model 4 was found: income was significantly negative, and age had a significant and positive effect.

Table 4

Marginal Effect of the Significant Variables on Each Loyalty Level in Models 4 and 8

	Not Loyal	Little Loyal	Loyal	Very Loyal
Model 4
Brand innovativeness	−0.00467	−0.02683	−0.05298	0.084471
Food quality	−0.01222	−0.07029	−0.13881	0.221323
Service quality	−0.01021	−0.05872	−0.11597	0.184896
Model 8
Differentiation	−0.00549	−0.03463	−0.07335	0.113473
Food quality	−0.01039	−0.06551	−0.13873	0.214622
Service quality	−0.00907	−0.05719	−0.12111	0.187361

From an analytical viewpoint, the use of different levels of loyalty is relevant in the current literature. Considering loyalty may appear in different degrees, it implies that inherent and latent levels of intensity must exist, which could be measured by ordinal categories. This model allows us to explain the shift, for example, from loyal to very loyal. As pointed out later, categorizing different intensities of loyalty would facilitate the design of segmentation strategies as restaurants could directly identify and distinguish those very loyal customers from those little loyal customers. This is even more important if we are able to provide the marginal impacts of different explanatory variables, as in this case.

Finally, to confirm the results, we have estimated the parameters by using a Tobit model reaching the same results in terms of signs and significance in the parameter estimates. As before, we are not showing the results of the Tobit model in the article, but they are available from the authors on request.

Conclusion and Implications

The result of this study shows that, while brand innovativeness (via differentiation) has an impact on loyalty, food quality and service quality partially mediate this impact. This effect is mostly observed for the category of the highest loyalty. Thus, when seeking high-loyal consumers, these three variables, brand innovativeness, food quality and service quality, become critical. Also, in an attempt to further delve into the effect of brand innovativeness, this study deconstructs brand innovativeness into different subdimensions (differentiation, dynamic brand, innovative brand, new leader, and idea generator). The results show that food quality and service quality carry over to the effects of only three significant subdimensions, differentiation, dynamic brand, and innovative brand; in particular, partially mediating differentiation, and fully mediating dynamic and brand innovativeness by the two quality-related variables. Beyond the specific outcomes, this study’s empirical application offers important implications, academic as well as managerial.

Regarding academic implications, first, this study is the first attempt to understand the relationship among brand innovativeness, food/service quality and the level of consumer loyalty. Second, the empirical application shows that the OPM has proven ability to capture the different levels of loyalty and the effects of the independent variables. By decomposing the consumer’s intention for future patronage into several latent levels of intensity, using a model that permits quantification of the effects of each explanatory variable at every level is fundamental. Accordingly, the use of models whose dependent variables appear as ordinal categories naturally fit the scale measuring “intention for future patronage” or loyalty. Third, the estimated marginal effects of the critical variables of interest, brand innovativeness, and perceived quality on loyalty contribute to the theoretical analysis of the relationship between brand innovativeness and loyalty, and the quantification of these relationships. Finally, the proposed model is also able to incorporate analysis of mediation, thereby confirming the mediating effect of perceived quality. Last, even though brand innovativeness as one construct might have a global effect on loyalty, notably decomposing the construct into several dimensions might unearth some intricacies not detected by the analysis of that construct per se. Specifically, and more importantly, not only can the subdimensions undergo individual analysis but also the mediating relationships can bear scrutiny beyond the general construct. In this case, the effects of the subdimensions of brand innovativeness extend the proposed mediating variables food quality and service quality, allowing detection of whether or not the mediation is full or partial. This approach allows researchers to discover hidden effects that, otherwise, would not be easily discernable with other widely used techniques in research of hospitality and tourism.

In addition to academic significance, this study provides unique contributions to practitioners in hospitality. First, practitioners should understand the formation of consumers’ loyalty through innovativeness, especially differentiation-related innovativeness. Innovativeness creates awareness in a consumer’s mind, which triggers the initial stages of a purchase process. Innovation allows companies to engage targeted segments and explains the reasons new products/services are better solutions than current ones, which triggers the next stage of the purchase decision, research among the competition. Assuming that the innovation is sufficiently different, innovativeness ultimately leads the consumer to a trial purchase and experience. From this trial experience, the consumer ultimately decides whether or not to repeat the experience and become loyal to the brand after multiple experiences. However, without a new idea or reason that captures the attention of consumers, industry practitioners cannot expect to affect a consumer’s unique purchase process, grow the business, or acquire market share from competitors. To deploy successfully resources in support of differentiation in a competitive environment requires promotion of innovativeness to communicate the values to current and potential consumers. Finally, innovativeness creates opportunities for the hospitality industry to create a competitive advantage to improve consumers’ lives, offering new options that may address an unaddressed or underserved need. Without innovation, the product or service offered by a specific industry can eventually be replicated or worse yet, replaced altogether, ultimately leading to demise.

Second, knowledge of the effect of brand innovativeness on consumers’ loyalty can be beneficial for practitioners when developing effective managerial strategies. Specifically, the estimation of marginal impacts allows decision-makers to assume the degree to which introduction of a brand-related novelty (brand innovation) and improvement of products or services (quality increment) will impact consumers’ loyalty. The use of specific information on the activities related to brand innovativeness, especially in terms of costs incurred in the investment, has the potential to clarify the costliness of the formation of consumers’ perceptions. While the results of this study show a positive effect from brand innovativeness, this effect is not constant across all the levels of loyalty. Therefore, considering that innovative activities usually require significant investments, an analysis of their costs along with the expected level of loyalty achieved is necessary. In other words, some brand innovations might be only viable if attaining a high level of loyalty.

Third, when examining the subdimensions that build a global construct of brand innovativeness, practitioners have a responsibility for being aware of the most influential determinants to determine the best returns on investment. Accordingly, the results of this study’s empirical application show that while brand innovativeness generally results in increased loyalty, the only subdimension driving a significantly positive impact is differentiation, which in turn leads to the highest level of loyalty. Consequently, the key focal points in the “loyalty-brand innovativeness” relationship from management’s standpoint are differentiation (as the main influencer among the components of brand innovativeness), and the two mediating variables: food quality and service quality.

Fourth, restaurateurs could use innovative activities to differentiate themselves from the competition. The result of the current study shows that being a dynamic brand, new leader, or idea generator does not significantly affect consumers’ loyalty while differentiation shows a significant effect on consumers’ loyalty. In addition, innovativeness does not have to focus only on menu innovation. As discussed in Kim et al. (2018) innovativeness regarding technology-related services, promotions, and experience should be in combination with menu innovativeness for a holistic approach. Embodying innovativeness does not mean restaurateurs need to be first-to-market with their ideas. For example, well-established restaurant chains, such as McDonald’s facing menu innovation stagnation during 2013-2014, are unable to entice consumers to return to their restaurants. To combat this trend, McDonald’s introduced all-day breakfast, improved its digital ordering platform, and began offering delivery, all new to McDonald’s operations and consumers’ experience. The combination of these innovations further differentiates McDonald’s from competitors and contributed to market valuation as evidenced by a 100% increase in stock price during the period 2015 to 2018.

Fifth, practitioners could use the results of this study to analyze the potential profitability of an investment in innovation for the selected market segment. Knowledge of the subdimensions of brand innovativeness that are most valued by customers, which lead them to become more or less loyal can help determine the courses of action when it comes to brand innovativeness.

Limitations and Directions for Future Research

As with any other research, this study is not without limitations. First, the current study uses a categorization of loyalty according to a ranking; nevertheless, the use of other taxonomies could offer a broader view in terms of academic and managerial perspectives for hospitality. For example, Dick and Basu (1994) classified loyalty into “no loyalty, latent loyalty, spurious loyalty,” and “true loyalty,” which entails resorting to models of discrete choices which again would permit the estimation of the marginal effects of each dimension and corresponding subdimensions. Second, a sample with different types of restaurants (e.g., fast food, fine dining) would estimate the relationships proposed in the present study and identify differences among various categories of restaurants. The potential edification includes whether or not global differences exist among types of restaurants (for the loyalty-brand innovativeness relationship), and which of those among the types are more similar in terms of the determinants for loyalty. Third, with an even broader perspective, the analysis of the proposed model in the present study may show differing results in other sectors of hospitality and tourism (e.g., travel agencies, airlines, etc.). Hospitality and tourism scholars and practitioners might gain further insights from edited models applicable to different sectors of the industry. Last, according to the “emotional approach” rather than the “behavioral approach” followed to measure the loyalty levels, subjectivity might play a role. Although Chan (2009) showed that the belief that interviewees’ responses lead to inaccurate data in self-reports—especially when “driven by social desirability”—should be nuanced as this inaccuracy does not occur all the time, we recognize it as a limitation; a limitation that will lead us to open up a future research line that tests the effects analyzed in this article under the behavioral approach, with objective measures.

Concluding Summary

This study’s motivation arises from the lack of research aimed at understanding the effect of consumers’ perceptions of brand innovativeness on perceived quality and the level of loyalty. The study confirmed that brand innovativeness (via differentiation) has an impact on loyalty with mediating effects of food quality and service quality. This study has the potential for important contributions to the emerging field of theory of innovativeness. As hospitality brands continue efforts toward positions of being innovative, the findings from the present study would provide a critical implication for practitioners.

Footnotes

ORCID iDs

Eojina Kim

Juan L. Nicolau

Liang (Rebecca) Tang

Notes

Eojina Kim, PhD (e-mail: eojina@vt.edu), is an assistant professor in the Howard Feiertag Department of Hospitality and Tourism Management, Pamplin College of Business, Virginia Tech. Juan L. Nicolau, PhD (e-mail: jnicolau@vt.edu), the J. Willard and Alice S. Marriott Professor of Revenue Management in the Virginia Tech Pamplin College of Business. Liang (Rebecca) Tang, PhD (e-mail: rebeccat@iastate.edu), is an associate professor at the Department of Apparel, Events, and Hospitality Management, Iowa State University, Ames.

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