Wine: Intrinsic attributes and consumers’ drinking frequency, experience, and involvement

International Journal of Hospitality Management 44 (2015) 1–11

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International Journal of Hospitality Management journal homepage: www.elsevier.com/locate/ijhosman

Wine: Intrinsic attributes and consumers’ drinking frequency, experience, and involvement Imran Rahman a , Dennis Reynolds b,∗ a b

Nutrition, Dietetics, & Hospitality Management, Auburn University, Auburn, AL, USA School of Hospitality Business Management, Washington State University, Pullman, WA, USA

a r t i c l e

i n f o

Keywords: Wine Involvement Perceptions Path-analysis Consumer behavior Drinking frequency Intrinsic attributes Taste Bouquet Appearance

a b s t r a c t This study developed and tested a model that links the perceived importance of sensory attributes of wine with drinking frequency and experience, and in turn links all these factors with product involvement as the central framework. Results from 493 survey responses collected in the North-western U.S. region employing path analysis and moderated regression analysis revealed that consumer drinking frequency significantly and positively influenced wine involvement while years of drinking moderated this relationship. Furthermore, involvement significantly and positively influenced the perceived importance of wine appearance and bouquet—but not wine taste. As such, highly involved consumers were more interested in ancillary product attributes, which in this case entailed appearance and bouquet. Moreover, the survey results suggest that consumers perceived the importance of intrinsic wine attributes in the same way as they would evaluate the attributes in formal wine-tasting events. Specifically, the perceived importance of appearance of wine significantly influenced perceived importance of bouquet and taste, and perceived importance of bouquet influenced perceived importance of taste. © 2014 Elsevier Ltd. All rights reserved.

1. Introduction The United States is the largest wine-consuming nation in the world with consumers buying more than 375 million cases of wine in 2013, which represents $36.3 billion in retail sales (Wine Institute, 2014). The hospitality and tourism industries play a large role in generating these numbers. In the hospitality industry, the majority of wine sales occur in restaurants, banquet centers, bars, and nightclubs (Hall et al., 2004). In such settings, wine complements culinary experiences (Aune, 2002) and contributes to socializing, relaxation, and learning (Barber, 2005). In the tourism industry, wine-related tourism has grown into a very lucrative business with the potential to generate substantial revenue and growth (O’Neill and Charters, 2000). Travelers seek wine tourism experiences through such diverse channels as cultural heritage events and festivals, dining and lodging experiences, education, formal wine tastings, cellar door sales, and winery tours (Charters and Ali-Knight, 2002). According to the U.S. Travel Association (2007), about 17% of leisure travelers in the U.S. engage in culinary or winerelated activities while traveling.

∗ Corresponding author. Tel.: +1 509 335 4344. E-mail addresses: [email protected] (I. Rahman), [email protected] (D. Reynolds). http://dx.doi.org/10.1016/j.ijhm.2014.09.004 0278-4319/© 2014 Elsevier Ltd. All rights reserved.

Not surprisingly, then, wine has received considerable attention among researchers across disciplines such as hospitality, tourism, food science, enology, marketing, and consumer behavior. Winerelated research has focused on market segmentation (e.g., Bruwer et al., 2002; Thach and Olsen, 2006; Kolyesnikova et al., 2008), wine tourism (e.g., O’Neill and Palmer, 2004; Charters and Menival, 2011; Charters and Ali-Knight, 2002; Dodd and Bigotte, 1997; Dodd, 1998; Carlsen and Boksberger, 2013; Qiu et al., 2013), price (e.g., Thrane, 2004; Ali and Nauges, 2007), gastronomy (e.g., Alonso and Liu, 2011), and legal issues (e.g., Reynolds and Knowles, 2014). A large body of research has focused on consumer behavior (e.g., Lockshin et al., 2006; Rahman et al., 2014; Bruwer and RawboneViljoen, 2013; Corsi et al., 2012; Bruwer and Nam, 2010). Regarding consumer behavior, involvement with wine has been a central phenomenon of study; however, most studies have focused on segmenting consumers based on their varying levels of involvement (e.g., Bruwer et al., 2002; Lockshin et al., 2001, 1997; Bruwer and Li, 2007; Barber et al., 2007). In particular, the association of involvement with consumer engagement with wine quality has not been researched extensively (Charters and Pettigrew, 2007). This study therefore examines the interplay of the consumption experience, wine involvement, and the perceived importance of the sensory or intrinsic attributes of wine. The purpose of this study then is to develop and test a model that links the perceived importance of sensory attributes with

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drinking frequency and drinking years and in turn to link all these factors with product involvement as the central framework. Specifically, we are interested in wine involvement, which has been addressed mostly in segmentation-related studies in the extant literature. To this end, we explore how drinking frequency affects wine involvement and how the years a person has been a wine drinker moderates this relationship. In addition, we examine how involvement affects the perceived importance of intrinsic wine attributes and how these intrinsic attributes relate to each other in terms of their perceived importance to consumers. 2. Literature review 2.1. The involvement concept Involvement has emerged as a central construct of interest in consumer behavior research. Involvement is “a person’s perceived relevance of the consumption object based in inherent needs, values, and interests” (Zaichkowsky, 1985, p. 342). Consumers are ‘involved’ with a product when they perceive the product as addressing or corresponding to something of considerable value or fundamental importance in their lives (Vermeir and Verbeke, 2006). Individual consumers tend to differ in their decision processes depending on the extent of their involvement with a product (Laurent and Kapferer, 1985). For instance, involvement was found to positively influence consumers’ willingness to pay a premium price for a product (Vlosky et al., 1999; Amendah and Park, 2008). Zaichkowsky (1986) classified involvement into three categories: the personal (inherent interests, values, or needs that motivate one toward an object), the physical (characteristics of an object that cause differentiation and increase interest), and the situational (something that temporarily increases the relevance of or interest in an object). Personal involvement entails that a person’s innate value system along with his or her distinctive experiences determine the degree of involvement with an object (Zaichkowsky, 1986). Generally, involvement with an object influences attitudes and behaviors relating to that object (Slama and Tashchian, 1985). It is worth noting that another important and widely used classification of involvement divides it into two types—product involvement and purchase-decision involvement. Product involvement is commonly classified in turn into two types—product importance (Lastovicka and Gardner, 1977) and enduring involvement (Bloch, 1981). According to Mittal (1989), hedonic or self-expressive products predominantly evoke enduring involvement whereas functional or utilitarian products can be important without inducing enduring involvement. For instance, a wine enthusiast is mostly enduringly involved with wines. On the other hand, for a detergent an individual will regard it as important without inducing any enduring involvement. We are concerned with product involvement in this study, which is, in general, more enduring, and without doubt represents both experiential and symbolic value, not just utilitarian significance (Higie and Feick, 1989). Purchase-decision involvement, also known as situational involvement, on the other hand, represents a short-term phenomenon whereby an individual becomes involved with a ‘situation,’ usually a purchase decision (Mittal, 1989). 2.2. Wine involvement To understand wine consumption it is necessary to understand individual behavior relating to wine consumption (Gluckman, 1990). Wine involvement is fundamental to the wine consumption phenomenon (Lockshin et al., 2001, 1997; Quester and Smart, 1998). The significance of wine involvement is evident in the extant wine-related literature, which has found, among other things, that

wine involvement is an important driver of purchase intention (Lockshin et al., 2006; Hollebeek et al., 2007). Hollebeek et al. (2007) specifically found that high-involvement customers were more easily triggered by a cue pertaining to the region of origin of a wine and less influenced by price. Bruwer and Huang (2012) asserted that high-involved consumers are more inclined to take part in BYOB (bring your own bottle) in restaurants than low-involved consumers. Additionally, high-involved consumers are more likely to purchase wines directly from cellar doors (Lacey et al., 2009). Thus, wine related consumer behavior depends heavily on the level of wine involvement. The level of product involvement with wine demonstrates wine consumers’ generic feelings of importance and relevance with a product and their genuine level of interest in wine on a daily basis (Yuan et al., 2005). Therefore, product involvement with wine is also known as personal involvement with wine (Yuan et al., 2005). It captures an individual’s feelings of interest, enthusiasm, and excitement about the product category (Bloch, 1982). According to Dodd, personal involvement can also be characterized as product enthusiasm. Product enthusiasts are therefore consumers with an enduring involvement with certain products (Bloch, 1986). Houston and Rothschild (1978) suggested that enduring involvement is an amalgamation of a person’s past consumption experience and the fit between the product and his values. It corresponds inherently to how well the product associates with a person’s self-image or the pleasure he or she receives from feelings about the product or from using the product (Higie and Feick, 1989). More recently, Ogbeide and Bruwer (2013) classified enduring involvement with wine to exhibit dimensions such as pleasure/interest, lifestyle/enjoyment, and self-image/sign value. Prior research has linked product use with product involvement. Goldsmith and d’Hauteville (1998) found heavy wine consumers to be more involved with wine, more innovative, more knowledgeable, and more likely to develop into opinion leaders regarding wine than moderate and non-users. Dodd et al. (2005) revealed that usage experience is positively associated with both objective and subjective wine-related knowledge. Cox (2009) found that subjective knowledge and a need for cognition predicted individuals’ wine involvement. Other studies have demonstrated that consumers’ wine involvement is consistent with the level of wine regularly consumed (Klatsky et al., 1990; Hall et al., 1997; Quester and Smart, 1998; Hollebeek et al., 2007). Here we acknowledge that the reverse relationship between involvement and drinking frequency is also supported in the extant literature. In other words, studies have suggested that involvement influences drinking frequency, not the other way around (Dodd et al., 1996; Goldsmith and d’Hauteville, 1998). We believe that involvement does not happen in a vacuum and factors such as parental socialization, peer influence, and exemplars act as the root of enduring involvement (Bloch et al., 2009), the type of involvement mostly associated with wine enthusiasts. Common to all these originating factors of enduring involvement is exposure to the product and as such it can be argued that heavy consumption signifies that a person is becoming highly involved with a product. Consistent with this notion and the underlying theory of involvement, we thereby propose the following hypothesis: Hypothesis 1. Drinking frequency influences wine involvement such that the greater the frequency, the higher is the level of involvement. 2.3. The moderating role of drinking years Involvement with a product such as wine is inherently enduring (Bloch, 1982). Enduring involvement is motivated by the extent to which a product relates to an individual’s identity or the

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hedonic pleasure derived from the product (Bloch and Richins, 1983; Kapferer and Laurent, 1985). Enduring involvement is a more stable, longer-lasting type of involvement (Richins and Bloch, 1986). In an individual’s initial wine-drinking years, involvement is newly formed and it is anticipated that consumption frequency will have a strong positive effect on one’s involvement level. Here the involvement level likely remains in the developmental phase, and the more drinks an individual has in a week, the more hedonic pleasure/satisfaction the person might derive from the consumption experience. Hence, the involvement level rises accordingly. However, a consumer who has been drinking for a number of years has already established a stable level of involvement and, as such, his or her consumption frequency will most likely no longer affect the involvement level. In this phase, the consumer’s involvement level will most likely stay the same regardless of the number of drinks he or she has. These processes can also be explained from a knowledge acquisition perspective. According to Scott and Shafer (2001), consumer motivations and behaviors vary across involvement levels. High involvement with a product strengthens an individual’s motivation to process information about it (Mitchell, 1981; Celsi and Olson, 1988; Park and Moon, 2003). In other words, the higher a consumer’s level of involvement, the more product knowledge the consumer will try to obtain (Andrews, 1988; Batra and Ray, 1986; Markus, 1977; Petty et al., 1981; Park and Moon, 2003). In the process, the consumer acquires additional knowledge about the product over time and eventually becomes an expert. The level of knowledge a consumer has about a product affects the amount and type of information processing involved (Bettman and Park, 1980; Johnson and Russo, 1984; Park and Moon, 2003). Wood and Lynch (2002) showed that consumers with a high knowledge quotient about a product have the ability to learn more but essentially learn less due to motivational deficits. Even if higher drinking frequency influences wine involvement it is likely that the strength of this effect will change over the years as people acquire more knowledge about the product and become more experienced. In the initial years, drinking more wine on a regular basis would strongly influence consumer involvement level. However, as consumers become experienced drinkers, they have already become wine enthusiasts and their drinking frequency would most likely no longer have the same strong effect on their wine involvement as it used to in the initial years. We therefore propose the following hypothesis: Hypothesis 2. Drinking years moderates the relationship between drinking frequency and involvement such that the higher the years the weaker the relationship between drinking frequency and involvement. 2.4. Involvement and intrinsic attributes Intrinsic attributes, one of the major determinants of wine quality, are product characteristics that are inherent to the objective nature of the product (Veale and Quester, 2009). Intrinsic wine attributes form a much larger category than extrinsic attributes and are also considered more important (Charters and Pettigrew, 2007). Several intrinsic attributes serve in wine tasting as primary determinants of wine quality—appearance, bouquet, and taste—the main attributes that are evaluated when tasting wine (Ashland Vineyards, 2012; Island Winery, 2012; Kenswineguide.com, 2012; Rahman et al., 2014). The focus on these attributes is consistent with the widely prevalent notion that the organoleptic quality of the final product (the appearance, bouquet, taste, and other sensory states associated with a food or beverage) is the most vital aspect considered in winemaking (Pretorius and Bauer, 2002). According to Bilyk et al. (1975), taste and bouquet are primary drivers in determining wine quality. Many also regard the appearance of

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wine as a strong indicator of quality (Charters and Pettigrew, 2006). Forbes (2008) contended that consumers utilize mostly intrinsic attributes when they are making wine purchase decisions. According to Dodd et al. (2005), high-involvement consumers rely more heavily on the intrinsic attributes of a wine than low-involvement consumers. To add to this view, highly involved consumers try to maximize expected satisfaction from their product choice through an extensive choice process, such that, for instance, they compare many brands, spend more time, and rely on multiple attributes (Chaiken, 1980; Assael, 1981; Laurent and Kapferer, 1985). Thus, for the high-involvement consumer, the perceived importance of intrinsic wine attributes such as taste, appearance, and bouquet must be greater. We thereby propose the following hypotheses: Hypothesis 3. Involvement is related to the perceived importance of taste such that the higher the involvement the higher the perceived importance of taste. Hypothesis 4. Involvement is related to the perceived importance of bouquet such that the higher the involvement the higher the perceived importance of bouquet. Hypothesis 5. Involvement is related to the perceived importance of appearance such that the higher the involvement the higher the perceived importance of appearance. 2.5. Examining intrinsic wine attributes Hughson et al. (2004) asked wine consumers to select important characteristics that drive their interest in wine. Sensory aspects were found to dominate their interest. More specifically, taste came to the fore, followed by bouquet and appearance (Hughson et al., 2004). Visual clues have been found to be highly important in consumer quality evaluations (Garber et al., 2000; Imram, 1999; Veale and Quester, 2008). In a blind tasting scenario, an individual first notices the appearance of wine, followed by bouquet and the sensation of taste. Since consumers notice the appearance of wine first, it might well have an impact on the bouquet and taste of wine. Similarly, the bouquet can very well influence the taste of wine. Lawless and Heymann (1998) asserted that the initial judgment about the quality of a food or beverage is influenced by the appearance of the product, notably its color. Consumers were found to prefer the appearance of very lean and red steak, believing that these attributes contribute to a better tasting product. However, under blind taste-testing conditions, these respondents prefer the taste and texture of meat that is darker in color (aged longer and more tender) and more marbled (higher fat content means juicier meat) (Bredahl, 2003; Glitsch, 2000; Hurling and Shepherd, 2003). A number of studies have demonstrated a significant effect of increasing the level of food coloring on consumers’ ratings of taste or flavor intensity across a range of beverages (Hyman, 1983; Johnson and Clydesdale, 1982; Roth et al., 1988). In studies typically employing fruit juices, color has been shown to influence perceived aroma and taste (Zellner and Kautz, 1990; Stillman, 1993; Kemp and Gilbert, 1997; Zellner and Whitten, 1999). According to Clydesdale (1993) the esthetics, safety, sensory characteristics, and acceptability of food are all affected by color. Wine is no exception, with color and clarity often serving as the primary indicators of perceived quality. Wine appearance therefore is likely to influence the aroma, taste, and textural qualities of a wine (Parr et al., 2003). Similarly, wine bouquet is likely to influence taste perceptions. In a related study, Tournier et al. (2009) showed that aroma influenced taste perceptions of certain desserts. As noted above, testing wine involves a sequence of processes involving the three most important intrinsic wine attributes. Appearance is noticed first followed by aroma. The sensation of

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taste is the last process in the sequence. In this regard, when a person is trying a wine for the first time appearance might influence the perception of aroma and taste and aroma might also influence the perception of taste. However, research has shown that individuals place the most emphasis on taste when it comes to wine evaluation, preference, and purchase. Rahman et al. (2014) found that the taste of wine alone influenced wine preferences over other intrinsic attributes such as bouquet and appearance and extrinsic attributes such as ecocentric and anthropocentric consumer attitudes. This shows that consumers for the most part will not buy a wine solely based on its appearance or aroma if they do not appreciate its taste. Thus, consumers who would rate the importance of appearance or bouquet highly would also for the most part rate the importance of taste highly. Nevertheless, those who rate the importance of taste highly might or might not rate the importance of appearance or the importance of bouquet highly. As such, we propose the following hypotheses: Hypothesis 6. The perceived importance of appearance influences the perceived importance of bouquet such that the higher the perceived importance of appearance the higher the perceived importance of bouquet. Hypothesis 7. The perceived importance of appearance influences the perceived importance of taste such that the higher the perceived importance of appearance the higher the perceived importance of taste. Hypothesis 8. The perceived importance of bouquet influences the perceived importance of taste such that the higher the perceived importance of bouquet the higher the perceived importance of taste. 3. Methodology We conducted an experimental wine-tasting session in a university in the northwestern United States. We recruited a convenience sample of students, faculty, staff, and their families, and the local residents through a university-wide e-mail and posters in various locations in the town. More specifically the invitation email was sent to all university students, staff, and faculty. The study was conducted during dad’s weekend, a three-day weekend during which many parents visit the campus. Four different sessions were conducted. All the sessions were free of cost to the participants. Participants were offered free cookies after the sessions as a token of appreciation for their participation. Two researchers along with a laboratory assistant monitored each of the sessions. We ensured through official IDs that participants were of legal drinking age. Participants were not allowed to communicate with each other during the experiment. Before the wine tasting session was carried out, we distributed the surveys to the participants. Participants were asked to respond to the questions prior to taking part in wine tasting. Since the study’s location is a college town, it was inevitable that many of the participants would be students. The survey instrument specifically asked participants about their drinking years, drinking frequency, wine involvement, perceived importance of taste, bouquet, and appearance, and demographics such as gender, age, ethnicity, marital status, education, and income. The perceived importance of taste, bouquet, and appearance were measured by one item for each construct. Respondents were asked to judge, on a scale of 1–7 how important the taste of a wine is. Responses ranged from “very unimportant” to “very important.” Drinking years was measured by one item, “How long have you been a wine drinker?” Responses were recorded on a 6 point scale (1 = less than 1 year/no previous experience, 2 = 1–5 years, 3 = 6–10 years, 4 = 11–15 years, 5 = 16–20 years, 6 = more

than 20 years. Drinking frequency was also measured by one item, “On average, how many glasses of wine do you drink per week?” Goldsmith and d’Hauteville (1998) operationalized heavy wine consumers by using an item similar to the one we used to measure drinking frequency. Responses were recorded on a 9 point scale (1 = less than 1 glass/not a regular wine drinker, 2 = 1–2 glasses, 3 = 3–4 glasses, 4 = 5–6 glasses, 5 = 7–8 glasses, 6 = 9–10 glasses, 7 = 11–12 glasses, 8 = 13–14 glasses, 9 = more than 14 glasses). Wine involvement was measured by Zaichkowsky’s (1985) 20item involvement scale that uses semantic differential items (see Appendix). The involvement items along with drinking frequency and drinking years were measured on a 5 point scale. Zaichkowsky’s (1985) original scale was a 7-point one. Many studies across disciplines have used five point scales and/or shortened versions of the instrument, proving them reliable and valid (see Franke et al., 2009; Stokburger-Sauer and Teichmann, 2013; Bordelon, 2014). We felt that a five point scale would offer less response points and in this regard high and low would be distinguished better in addition to making the instrument concise and less confusing for the participants. Some studies have found 5 and 7 point scales can be comparable (e.g., Coleman et al., 1997; Dawes, 2008). We varied the scale points and anchor statements for different constructs to avoid/minimize common method bias. It is acknowledged in the survey research literature (Tourangeau et al., 2000) that scale format and anchors systematically influence responses (Podsakoff et al., 2003). For instance, some of the covariation observed among the constructs examined may be the result of the consistency in the scale properties rather than the content of the items (Podsakoff et al., 2003). Except for involvement, all our measures used single items. Standard linear regression as well as path analysis can be conducted using single-item measures as either dependent or independent variables (Arbuckle and Worthke, 1999). We employed path analyses using AMOS version 21 to test our hypothesized model. Additionally, moderated regression analysis was carried out using SPSS version 18 to examine the moderation hypothesis in our study. Given the plethora of scales to measure involvement prevalent in the extant literature, it is important we elaborate on our scale choice. Recent scales to measure wine related involvement have used a multi-dimensional operationalization of the construct (see Bruwer and Buller, 2013; Ogbeide and Bruwer, 2013; Bruwer and Huang, 2012). One of the most widely utilized scales developed by Zaichkowsky (1985) operationalized involvement as a unidimensional construct. The scale’s simplicity and widely established validity necessitated many researchers not only to adopt the scale to measure consumer involvement but also to adapt the scale. Enduring involvement especially has frequently been measured using Zaichkowsky’s (1985) scale (Bloch et al., 2009). For the same underlying reasons, we decided to use this scale to measure wine involvement.

4. Results We collected 508 completed surveys. Out of these 508, 15 were deleted by the list-wise deletion method, which has been consistently found to be more robust than other sophisticated methods, to account for missing values (Allison, 2002). There were 493 usable surveys. Demographic information of the participants is presented in Table 1. Cronbach’s alpha for the 20-item involvement construct was .96, which is considered excellent according to Hair et al. (2006). As a previous step to the path analysis using AMOS, the relationships between each pair of variables as suggested in the model were examined by the Pearson correlation coefficient. As shown in Table 2, significant relationships were found between all pairs

I. Rahman, D. Reynolds / International Journal of Hospitality Management 44 (2015) 1–11

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Table 1 Demographic profile of participants. N

%

Drinking frequency

Drinking years

Involvement

Gender (N = 493) Male Female

261 232

52.9 47.1

2.48 2.49

2.24 2.35

3.88 3.74

Age (N = 493; M = 28 years; range: 21–67) ⇒21; <25 ⇒25; <30 ⇒30; <35 ⇒35; <40 ⇒40; <45 ⇒45; <50 ⇒50; <55 ⇒55; <60 ⇒60; <67

299 91 26 7 3 13 24 18 12

60.6 18.5 5.3 1.4 0.6 2.6 4.9 3.7 2.4

2.39 2.67 2.30 2.00 2.00 3.31 2.92 2.61 2.17

2.05 2.26 2.70 3.00 3.20 4.00 3.00 3.28 2.92

3.84 3.84 3.81 3.73 3.80 3.67 3.97 3.52 3.25

Ethnicity (N = 492) White/Caucasian Asian Black/African American Hispanic/Latino Mixed Native American/Alaskan Others

367 42 13 34 23 6 7

74.6 8.9 2.6 6.9 4.7 1.2 1.4

2.58 1.91 2.15 2.27 2.44 2.83 2.00

2.38 1.93 1.77 2.09 2.26 2.67 1.88

3.88 3.44 3.85 3.75 3.54 4.00 3.68

Marital status (N = 493) Single Married Previously married

393 80 20

79.7 16.2 4.1

2.41 2.58 2.58

2.08 2.98 3.75

3.82 3.72 4.01

Education (N = 492) Some High School/Trade School Four-year college degree High school/GED Master’s degree Doctorate degree

34 223 180 46 9

6.9 45.3 36.6 9.3 1.8

2.74 2.58 2.29 2.59 2.11

2.56 2.39 2.01 2.67 2.33

3.91 3.82 3.81 3.75 3.76

Income (N = 492) <$15,000 ⇒$15,000; <$30,000 ⇒$30,000; <$45,000 ⇒$45,000; <$60,000 ⇒$60,000; <$75,000 ⇒$75,000; <$90,000 ⇒$90,000; <$105,000 ⇒$105,000; <$120,000 ⇒$120,000; <$135,000 ⇒$135,000

311 56 17 17 16 10 11 8 7 44

63.2 11.4 3.5 3.5 3.3 2.0 2.2 1.6 1.4 9.0

2.38 2.71 2.41 2.14 2.57 3.00 2.33 3.25 3.71 2.50

2.09 2.48 2.53 1.86 2.71 2.40 2.67 2.75 3.75 3.12

3.79 4.04 4.12 3.87 3.84 3.77 4.08 3.99 3.71 3.54

Table 2 Descriptive statistics and correlations among the variables.

1. Drinking frequency 2. Drinking years 3. Involvement 4. Perceived importance of wine appearance 5. Perceived importance of wine bouquet 6. Perceived importance of wine taste *

Mean

SD

1

2

3

4

5

6

2.48 2.29 3.81 4.58 4.78 6.27

1.36 1.12 .81 1.39 1.42 1.23

– .45* .50* .34* .29* .19*

– .31* .15* .29* .13*

– .47* .49* .34*

– .59* .46*

– .53*

–

p < .05.

of variables. Using the path analysis, the predicted relationships among exogenous and endogenous constructs were tested. Maximum likelihood (ML) estimation was employed to estimate the structural parameters of the model. In comparison with values suggested by Hu and Bentler (1999), Steiger (2007), and MacCallum et al. (1996), the overall fit of the model resulted in acceptable statistics: x2 (df) = 10.4 (3) p = .016, GFI = .99, RMSEA = .07, AGFI = .96, NFI = .99, TLI = .97, and CFI = .99. We compared our model with an alternative model. More specifically, we interchanged the involvement and drinking frequency constructs in the alternate model. The alternate model had a much poorer fit (x2 (df) = 113.3 (3) p < .001, GFI = .92, RMSEA = .27, AGFI = .62, NFI = .84, TLI = .48, and CFI = .85) compared with our original model.

Fig. 1 and Table 3 provide the results of the path analyses. Drinking frequency was positively related to involvement (ˇ = .50, p < .01). Involvement had significant positive effects on the perceived importance of wine appearance (ˇ = .47, p < .01) and the perceived importance of bouquet (ˇ = .27, p < .01), respectively. Hypotheses 1, 3, and 4 are, therefore, supported. Involvement was not found to have a significant positive effect on the perceived importance of wine taste (ˇ = .05, p > .05), rejecting Hypothesis 5. The perceived importance of wine appearance was found to positively influence the perceived importance of wine bouquet (ˇ = .47, p < .01) and the perceived importance of wine taste (ˇ = .22, p < .05), respectively, lending support for Hypotheses 6 and 7. In addition, the perceived importance of wine bouquet was found to have a

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Drinking Years

Perceived Importance of Wine Appearance .47**

-.22**

.47**

Drinking Frequency

Perceived Importance of Wine Bouquet

.27** Involvement .50**

.22**

.37**

.05

Perceived Importance of Wine Taste

Values are standardized path coefficients. *p< .05, ** p< .01 Fig. 1. Path estimates for the proposed model.

Table 3 The interaction of drinking frequency and drinking years on involvement. Variable

5 4.5 4

Involvement Step 1 B

Drinking frequency Drinking years R2 Drinking frequency × drinking years R2 Overall R2

Step 2 S.E.

**

.46 .10*

.04 .04

ˇ

B **

.46 .10*

S.E. **

.52 .14**

.05 .04

ˇ **

.52 .14**

Involvement

3.5 3 2.5

Low years

2

Med years

1.5

High years

1

.26** −.16**

.03

−.22**

0.5 0 0

1

.04** .30**

Note. VIF values ranged from 1.235 to 1.381. All variables were standardized prior to running regression analysis. * p < .05. ** p < .01.

positive effect on the perceived importance of wine taste (ˇ = .37, p < .01), confirming Hypothesis 8. We tested Hypothesis 2 using moderated regression analysis, which tests the hypotheses using a mean-centering procedure or standardization of the independent and moderating variables to minimize multicollinearity (Aiken and West, 1991). We standardized our variables accordingly. The variance inflation factor for each regression coefficient is below 2 (1.24–1.38), which is way below than the usually recommended threshold of 10 (O’Brien, 2007) showing that multicollinearity was not an impediment. To examine the moderating effect of drinking years on the relationship between drinking frequency and involvement, drinking frequency and drinking years were entered in step 1, and an interaction term between drinking frequency and drinking years was included in the second step (see Table 2). Consistent with the results of the path analysis, while controlling for the effect of drinking years, drinking frequency had a significant positive effect on involvement (ˇ = .46, p < .01). The interaction between drinking frequency and drinking experience on involvement in step 2 was found to be significant (R2 = .04, p < 01), supporting Hypothesis 2. Aiken and West (1991) suggested plotting the interaction effects. Fig. 2 depicts the interaction effects in graphical form. We also tested this moderation effect by employing bootstrapping with a sample of 2000 participants. Similar significant effects are revealed, confirming the strength of this moderation effect.

2

3

4

5

6

7

8

9

10

Drinking Frequency

Fig. 2. Effect of interaction between drinking frequency and drinking experience on involvement.

While controlling for the effect of drinking years, drinking frequency had a significant positive effect on involvement (ˇ = .46, p < .01). The interaction between drinking frequency and drinking experience on involvement in step 2 was also found to be significant (ˇ = −.15, p < 01). 5. Discussion The results reveal that drinking frequency influences involvement such that the higher the frequency the higher the involvement. Thus, it is possible to identify low- and highinvolvement consumers from their drinking habits. We cannot ignore the considerable debate in the literature regarding the direction of the relationship between drinking frequency and involvement. A few studies have shown that involvement positively and significantly affects usage. We hypothesized and confirmed that drinking frequency positively and significantly leads to involvement. We strongly believe that involvement does not grow in a vacuum, and increased product usage indicates that a person is becoming increasingly involved with a product. In order for a person to become involved with a product such as wine, consumption of the product is necessary and, as we have shown in our findings along with other studies in the literature, increased drinking frequency will lead to increased wine involvement. Among other findings, the number of years a person has been drinking wine was shown to moderate the relationship between drinking frequency and involvement. This effect is particularly

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interesting because as the number of years increases the strength of the relationship between drinking frequency and involvement becomes weaker. This indicates that, for experienced/older wine drinkers, drinking frequency will no longer act as a strong proxy for wine involvement. In the initial drinking years, a wine consumer’s motivation for gaining wine-related knowledge and experience might be higher, enabling him or her to consume more wine. Such high drinking frequency shows that these consumers are highly involved with wine. However, as these emerging wine connoisseurs age or gain more wine-related experience, their drinking frequency no longer acts as a strong signal of their wine involvement. This is possibly because at that stage, their motivation to acquire winerelated knowledge is likely lower than in the initial years. They have already become wine experts by then. In the initial drinking years, a consumer’s level of involvement might still be in the developmental stage. As a result, the consumer’s drinking frequency would strongly predict his or her wine involvement. In other words, the more wine he or she drinks the more involved he or she becomes at this stage. Involvement for products such as wine tends to be inherently enduring, constituting a more constant and long-lasting form of involvement. As consumers continue drinking wine for some years, the involvement level tends to settle in. They reach a stage at which drinking frequency no longer as reliably predicts involvement. At that stage, consumers most likely are enduringly involved and their involvement would most likely not alter much with respect to drinking frequency. Perhaps the most important findings to emerge from this study are those that support Hypotheses 3–4 and reject Hypothesis 5. Taken together, these findings imply that consumers’ wine involvement significantly influences their perceived importance of wine appearance and bouquet but not wine taste. More specifically, the higher the level of involvement of wine consumers the higher their perceived importance of wine appearance and bouquet, but not of wine taste. This suggests that highly involved consumers are more interested in the ancillary product attributes—appearance and bouquet in this case. Wine taste is the main quality attribute of wine as shown in the literature and in our study it scored the highest mean rating among the three quality attributes. In Charters and Pettigrew (2007), most informants associated the nature of wine quality with taste, signifying the importance of taste as a quality attribute. In light of the findings of our study, it can be argued that low-involvement consumers might ascribe more importance to taste when they purchase or evaluate wine but as people become more involved, they tend to place greater emphasis on specific aspects of the wine. A similar effect is observable among extrinsic wine attributes in a study conducted by Hollebeek et al. (2007). The researchers found that high-involvement consumers are more interested in country of origin than the price of wine. Accordingly, in the context of our study, the color and odor of wine may have become more important than the taste for high-involvement wine consumers. Charters and Pettigrew (2007) offered an alternative, and seemingly more plausible, explanation of this phenomenon. In their qualitative study, Charters and Pettigrew (2007) showed that participants who rated good taste as a quality element were mostly low- and medium-involvement drinkers. However, this does not mean that high-involvement drinkers do not acknowledge taste as an important quality dimension. What this means is simply that high-involvement drinkers presuppose that a wine will taste good and are using other dimensions to establish quality. As such, in the context of this study, regardless of their involvement level, consumers might rate the importance of taste perceptions highly. This is evident from the mean ratings of the perceived importance of taste. Since all levels of involved consumers perceive taste as important, involvement does not influence the perceived

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importance of taste for them. On the other hand, we can establish that high-involvement consumers are more likely than lowinvolvement consumers to perceive the bouquet and appearance of wine as important. The study’s results also revealed that the perceived importance of wine appearance influences the perceived importance of bouquet and the perceived importance of taste. In addition, the perceived importance of bouquet influenced the perceived importance of taste. This shows that, in the ordinary context of choosing wines to purchase, consumers’ perceptions work in the same way as in a formal wine-tasting session. In the extant literature, several studies have confirmed the influence of appearance on bouquet and taste and the influence of bouquet on taste. Most of these studies employing either food or beverages and utilized experimental techniques. In such a setting or in any blind tasting, consumers notice appearance first, followed by bouquet and taste. Since appearance comes first, it influences bouquet and taste and, in the same way, bouquet affects taste. Our findings reveal that consumers use these sequential processes involved in a wine-tasting session when they rate their perceptions of the importance of the quality attributes of wine without undergoing a formal wine-tasting procedure.

6. Limitations The study was limited in several respects. The relatively lower mean age of the sample indicated that most participants are young and in lower-income brackets. Thus, as evidenced in Table 1, the sample is somewhat skewed. We also conducted the study in a single university location in the northwestern United States, so it did not necessarily represent the general U.S. population. Social desirability bias might have played a role in the study since we employed a survey that recorded perceptions. Despite the strong validity, Zaichkowsky’s (1985) involvement measure might not be as good as some of the more recent scales. The recent scales developed by Bruwer and Buller (2013) and Bruwer and Huang (2012) perhaps offer a better operationalization of wine involvement and capture the different underlying dimensions of this complex construct. As such, it might have been a better idea to use one of those newer scales. However, we could not do so as the surveys were designed and conducted before those two wine specific involvement scales were published. Last but not least, perhaps it would have been better to use Zaichkowsky’s original 7-point semantic differential scale instead of the 5-point one. We did not have very strong reasons to use the shortened calibration.

6.1. Implications and future research Implications are aplenty for both practice and research. This study offers an in-depth understanding of the wine consumer behavior. Wineries and wine manufacturers will be able to better understand the underlying role of involvement and how that affects the wine consumer. In marketing to the low-involved consumers wineries can focus more on the taste attribute. On the other hand, appearance and bouquet of wine should be taken into consideration when targeting high-involved consumers. The high-involved consumer might use these two attributes heavily to establish quality of the wine. As such, blind tasting organizers and quality raters will find our study handy. They will also be able to deduce important dynamics of wine involvement from the drinking habit and experience of the consumers as our findings suggest. Overall, wine cellars and manufacturers will be able to understand consumers better, design more targeted marketing campaigns, and address different types of consumers more accurately by incorporating the findings of this study.

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Researchers need to replicate the study in better settings addressing the limitations. One particular effect that we wish we could explore further was the moderating effect of drinking experience. At this point, we only could offer anecdotal explanations of this effect. Future research needs to investigate this effect indepth. Future research also needs to incorporate more attributes of wine and find how their importance varies according to consumers’ involvement levels. Future research also needs to find out whether the underlying effects hold for different demographics of consumers. In summary, we anticipate this study will add greatly to the extant literature and encourage future research accordingly.

(Lockshin, 2002; Lockshin et al., 1997, 2001; Lockshin and Spawton, 2001). This study examined how wine quality attributes are influenced by wine involvement. In addition, it also examined how wine involvement is influenced by drinking frequency and how drinking years moderate this relationship. Additionally, the interplay of consumers’ perceptions of intrinsic wine quality attributes was also examined. Such in-depth consideration of wine consumer behavior will help wineries and wine marketers to understand their consumers better. As such, they will be able to advertise wine more effectively by targeting customers based on their level of involvement and highlighting the corresponding wine quality attributes. Identifying and segmenting consumers also would likely become easier based on wine usage, experience, and involvement.

7. Conclusion Involvement is fundamental to understanding wine quality (Charters and Pettigrew, 2006) and wine consumption

Appendix. Survey instrument

Please mark ( ) the point that most represents how you feel about Wine? Important Of no concern Irrelevant Means a lot to me Useless Valuable Trivial Beneficial Matters to me Uninterested Significant Vital Boring Unexciting Appealing Mundane Essential Undesirable Wanted Not needed

Unimportant Of concern to me Relevant Means nothing to me Useful Worthless Fundamental Not beneficial Doesn’t matter Interested Insignificant Superfluous Interesting Exciting Unappealing Fascinating Nonessential Desirable Unwanted Needed

Please mark ( ) the appropriate box. How long have you been a wine drinker? less than 1 year/no previous experience

1-5 years

6-10 years

11-15 years

16-20 years more than 20 years

On an average, how many glasses of wine do you drink per week? less than 1/ not a regular wine drinker

1-2

3-4

5-6

7-8

9-10

11-12

13-14

more than 14

On a scale of 1-7, how important is the appearance of a wine to you? Very Unimportant

Unimportant

Somewhat Unimportant

Neutral

Somewhat Important

On a scale of 1-7, how important is the bouquet of a wine to you?

Important

Very Important

I. Rahman, D. Reynolds / International Journal of Hospitality Management 44 (2015) 1–11

Very Unimportant Unimportant

Somewhat Unimportant

Neutral

Somewhat Important

Important

Very Important

Important

Very Important

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On a scale of 1-7, how important is the taste of a wine to you? Very Unimportant Unimportant

Somewhat Unimportant

Neutral

Somewhat Important

Please answer the following questions about your demographics What is your gender? Female

Male

How old are you? _______________________________________________ What is your ethnicity? Caucasian

African American/Black

Asian

Native American/Alaskan

Hispanic/Latino

Mixed

Other (please specify)

Marital Status: Single

Married

Previously Married

5. What is your income level ($)? Under $15000

15000 29999

30000 44999

45000 – 59999

60000 74999

75000 89999

90000 104999

105000 119999

120000 134999

135000 and above

6. How much school have you completed? Some High School

High school

Bachelor’s degree

Master’s degree

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