Measuring Users’ Value Experience on a Travel Website (e-Value)

Abstract

Despite the widespread use of travel websites, our understanding of how best to capture users’ value experiences when using such websites is limited. This article introduces a multidimensional measurement of a user’s value experience on a travel website (e-Value). We then assess the extent to which website users contribute to their own value experience. Based on 175 UK survey respondents, e-Value is formed mainly by cognitive effort, utilitarian value/control, and to a lesser extent by perceptions of emotional value and value for money. Social value experiences do not contribute to e-Value. A user’s own activities on a website (i.e., participation) affect most value dimensions but at different magnitudes. Our findings suggest that website “participation” should be seen as phenomenologically determined by the user as perceived participation affects e-Value dimensions more strongly than actual participation.

Keywords

value experience measurement customer participation travel websites value dimensions

With the popularity of e-travel services, customers have become far more powerful, sophisticated, and experienced and are increasingly able to determine elements of their tourism products. Intense competition among travel websites means that companies need to understand how users compare across sites (Kim, Kim, and Han 2007). Maximization of customer value is widely accepted to be the ultimate goal for firms (Woodruff 1997), as it drives customer loyalty and repurchase intention. Users’ value perceptions are consequently crucial in choosing a website for travel planning and booking. To assist businesses, we need answers to the following questions: how best can we capture a user’s value perception from using a travel website? What are its components and how do they contribute to the overall value perception of using a specific site? Despite extensive research on tourism website evaluation (see Law, Qi, and Buhalis 2010 for an overview) to understand better how customers rate the quality and functionality of such websites (e.g., Kaynama and Black 2000; Ho and Lee 2007; Kim and Lee 2004), our understanding of a customer’s value experience and its subdimensions is still underdeveloped. Website quality is only seen as an antecedent to value in the now widely accepted “quality-value-satisfaction-loyalty chain” (Kashyap and Bojanic 2000; Gallarza and Gil-Saura 2006), while value is seen as a richer measure (Prebensen et al. 2013) and better predictor of loyalty (Cronin, Brady, and Hult 2000). In line with research on website effectiveness, our focus is on the following service activities and functions undertaken by an individual on a travel website: searching for travel information, performing transactions, using it as a communication forum, and receiving personalized services (e.g., itinerary design) (see also Ho and Lee 2007). Our first objective is to introduce a multidimensional measurement of a user’s value experience when using a travel website (e-Value). Such a generic measure provides a valuable contribution to work on tourism website evaluation. As Law, Qi, and Buhalis (2010) concluded in their meta-analysis, more work on website evaluation is needed; in particular, we need to develop mutually agreed standards and techniques.

Recent literature has stressed the salient role of the customer in cocreating their own value experience (Prahalad and Ramaswamy 2004; Vargo and Lusch 2004). Within the Service Dominant (S-D) logic literature, the customer is seen as having a dual role as cocreator: contributing to the experience, as well as assessing its value (Vargo and Lusch 2004; Gummerus 2013). In the context of using a travel website, customers contribute to their value experience by using the features of that site (Prahalad and Ramaswamy 2004). Despite our abstract understanding of the customer as a cocreator of value, little empirical evidence is available to demonstrate how a customer’s own activities affect their value perceptions. For example, do website users derive more fun (i.e., emotional value) by using more of its features; do users who make more extensive use of the website perceive that they get better value for money? Against this background, our second objective is to establish the extent to which individual value dimensions are affected by a user’s own activities on a travel website.

Perceived Value and Value Experiences

Scholars in tourism, marketing, and management have for some time tried to understand the value concept. Conceptualizations and operationalizations of value as an outcome have predominantly taken place in interpersonal contexts (e.g., Lin, Sher, and Shih 2005; Ruiz et al. 2008); rather less attention has been paid to self-service contexts, despite their increasing importance. Because of the complex, rich, and subjective nature of the value construct, scholars have viewed it in different ways. Three broad perspectives have been employed to try to understand how customers determine the value of an outcome. The means–end theory (Woodruff 1997) links product evaluations to use consequences but has been criticized as making it difficult to define and operationalize value (Parasuraman 1997). Literature building on Zeithaml’s (1988, p. 14) work regards value as a cognitive assessment, that is, “an overall assessment of the utility of a product based on perceptions of what is received and what is given.” It compares functional and economic benefits versus sacrifices (see Kashyap and Bojanic 2000; Hutchinson, Lai, and Wang 2009). The most comprehensive perspective is to define value as an experience outcome (Hirschman and Holbrook 1982; Holbrook and Hirschman 1982) which supplements the cognitive assessment by adding affect and defining value as an “interactive relativistic preference experience” (Holbrook 1994, p. 27). As pointed out in an extensive review of the value literature by Gummerus (2013), examining holistic experiences might justify a phenomenological approach to value research. Nevertheless, the dominant approach is to examine value perceptions as a multidimensional outcome incorporating cognitive and a range of sociopsychological value dimensions such as emotional value, social value, and epistemic value (Sheth, Newman, and Gross 1991; Sweeney and Soutar 2001; Sánchez et al. 2006). This differs from a benefit versus sacrifice perspective that is more aligned with a purely cognitive assessment (Sánchez et al. 2006). Useful overviews of value dimensions are developed by Smith and Colgate (2007) and Holbrook (1999). As Sánchez et al. (2006) explain in detail, such a multidimensional perspective captures the experiential view of value, which has conceptual support from the cognitive–affective–behavior paradigm. This is the approach employed most widely in tourism and service research as can be seen in studies examining, for example, the change in timeshare owners’ value perceptions (Bradley and Sparks 2012), adventure tourism (Williams and Soutar 2009), or festival tourism (Lee, Lee, and Choi 2011). To capture the multidimensionality of the construct, Petrick (2002) developed the SERV-PERVAL scale to measure the value perceptions of cruise travelers (Petrick 2003, 2004) and golf travelers (Petrick and Backman 2002), while Sánchez et al. (2006) developed GLOVAL, which captures the consumption and purchase experience of a tourism product.

The value construct is also central to the S-D logic literature, where work on value is mainly theoretical and concentrates on “value-in-use,” which is defined by the user (Vargo and Lusch 2004). To accommodate better the phenomenological nature of value, “value-in-use” was subsequently relabeled as “value-in-context” (Vargo et al. 2010). Helkkula, Kelleher, and Pihlström (2012, p. 59) argue that the phenomenological perspective of value is best captured by actual or even imagined experiences of a customer and coined the term “value in the experience,” which is framed by “service customers’ broader lifeworld contexts.” From a strict phenomenological perspective, value experiences need to be examined in terms of their deeper meaning for an individual; however, Gummerus (2013) argues that Vargo and Lusch (2008, p. 150) are vague as to their phenomenological perspective, regarding value as created when the customer’s “wellbeing has somehow been improved.” Such a perspective can be reconciled with the literature that regards value as an experience outcome (Gummerus 2013) and is consistent with the multidimensional view of value, combining cognitive and affective dimensions.

The dearth of research on customer perceived value from the context of technology-based services, such as travel websites, has been highlighted in the literature (Heinonen 2004, 2009), where the focus has tended to be on understanding e-service quality (e.g., Parasuraman, Zeithaml, and Malhotra 2005; Ho and Lee 2007) and website usability and effectiveness (Law, Qi, and Buhalis 2010). Although this work overlaps with the functional dimension of value, as well as with the cognitive effort involved, it fails to cover the richness of a user’s value experience that ultimately affects loyalty.

e-Value and Modeling Its Constituent Dimensions

Empirical research has mainly studied value by examining value perceptions at the dimensional level (e.g., Petrick and Backman 2002; Prebensen et al. 2013), but has not yet developed a mutually agreed set of dimensions (Bradley and Sparks 2012). There is also confusion as to the ways in which these various value dimensions are modeled (see Lin, Sher, and Shih 2005 and Mayr and Zins 2012 for a review). Modeling these dimensions as predictors of a generic value measure (e.g., Al-Sabbahy, Ekinci, and Riley 2004; Duman and Mattila 2005; Petrick 2004) is theoretically unparsimonious, while a generic value measure lacks validity (Woodruff and Gardial 1996). Even more problematic is the use of a unidimensional overall value measure (Chen and Chen 2010; Prebensen et al. 2013) as it cannot capture the complexity of the value construct. Lin, Sher, and Shih (2005) argue that theoretical parsimony can only be achieved when the overall abstraction of perceived value is conceptualized within the model and is “specified as formative in the second-order” (Lin, Sher, and Shih 2005, p. 324; see also Sánchez et al. 2006; Ruiz et al. 2008; Mayr and Zins 2012). Sánchez-Fernández and Iniesta-Bonillo (2007, p. 444) stressed the need to “clarify the formative nature of the relationship between this multi-dimensional construct and its constituent dimensions.”

With this in mind, we undertook an extensive literature review to identify constituent dimensions capturing the value experience of travel website users (e-Value). Dimensions were derived from the theory of consumption value (Sheth, Newman, and Gross 1991), as it contains both cognitive and affective aspects of consumption (i.e., use), as well as from technology adoption theory. We propose six integral first-order dimensions that together constitute e-Value, that is, a customer’s value experience when using travel websites. These include utilitarian value, emotional value, social value, perceived control and freedom, value for money, and user’s cognitive effort.

Utilitarian value is consistently included in all value typologies (e.g., Babin, Darden, and Griffin 1994; Sigala 2006). Utilitarian or functional value is derived from effective task fulfillment (Sheth, Newman, and Gross 1991; Sánchez et al. 2006), or from efficient and timely service delivery (Childers et al. 2001). It is also seen to be closely related to the concepts of perceived usefulness in the Technology Acceptance Model (TAM; Davis 1989) and website usability literature (Kim and Eom 2002; Ranganathan and Ganapathy 2002), as well as relative advantage in perceived characteristics of innovations (Rogers 2003).

Emotional value refers to affective states generated from a product or service such as fun and enjoyment (Holbrook 1994; Mathwick, Malhotra, and Rigdon 2001; Richins 1997; Lee, Lee, and Choi 2011). It captures the feelings of pleasure/enjoyment a customer/user gains from using the product/service, which is particularly relevant within the context of holiday travel (Williams and Soutar 2009; Lee, Lee, and Choi 2011), described as a pleasure-seeking activity (Gnoth 1997). Drawing from work on online purchasing of services, emotional value may be realized as part of the process of searching and purchasing travel services (e.g., Mathwick, Malhotra, and Rigdon 2001; Heinonen 2009; Sánchez et al. 2006). Emotional value is widely included in conceptual value typologies and empirical studies (Sheth, Newman, and Gross 1991; Sweeney, Soutar, and Johnson 1999; Sweeney and Soutar 2001).

Social value

Sheth, Newman, and Gross’s (1991) theory of “consumption value” advocates that customers can also experience “social value” as part of their consumption experience, as “the very act of participation and performance of the relevant tasks can yield experiences that provide psychological benefits” (Etgar 2008, p. 102). Sweeney and Soutar (2001) defined social value as the utility derived from the constructs of esteem, fashion, and sociability (see also Holbrook 2006; Williams and Soutar 2009; Sánchez et al. 2006). Work on the diffusion of innovations has shown that consumers’ use of electronic innovations can enhance a person’s status and image (Pura 2005; Sigala 2006). By analogy, the use of Internet self-service technologies may be expected to have a similar impact.

Perceived control and freedom

One of the key features of interactive technology such as the Internet is user control (e.g., Meuter et al. 2000), since the performance of online services is independent of employees’ involvement, location, and time. Perceived control and freedom in the context of Self-Service Technology (SST) environments has been defined as the “subjective assessment of control over a task” (Zhu et al. 2007, p. 494). Studies within the SST context have highlighted that users regard being in control as one of the benefits when using, for example, mobile services (e.g., Kleijnen, De Ruyter, and Wetzels 2007) or completing transactions on the Internet (e.g., Wolfinbarger and Gilly 2001).

Value for money

The foundation for the notion of value as a trade-off between benefits and sacrifices is based on economic theory of exchange where quality is associated with benefits and price paid is associated with monetary sacrifice (Zeithaml 1988). Lin, Sher, and Shih (2005) and Sigala (2006) used this terminology in the context of online shopping and mobile services. Multidimensional measures of value vary in terminology, including “functional value due to price” (Sweeney and Soutar 2001), monetary price (Petrick 2002), economic value (Mathwick, Malhotra, and Rigdon 2001), or value for money (Williams and Soutar 2009). Mayr and Zins (2012) even differentiated between price assurance and unreasonable price. Despite these terminological differences, the common idea is to assess the relative price with respect to the service/goods received.

User’s cognitive effort

Based on the complexity of innovation characteristics (Rogers 2003) and ease of use in TAM (Davis 1989), user’s cognitive effort is a widely applied component of value measures (e.g., Kleijnen, De Ruyter, and Wetzels 2007; Mayr and Zins 2012). Meuter et al. (2005) found a significant relationship between complexity and the propensity to try a particular SST. Website users were also found to want to limit their cognitive effort in comparing prices across online offers (Tanford, Baloglu, and Erdem 2012). In line with Kleijnen, De Ruyter, and Wetzels (2007), we associate cognitive effort with the complexity of using a specific website.

Following the multidimensional–formative approach recommended by Lin, Sher, and Shih (2005) and Sánchez et al. (2006), the six proposed dimensions are regarded as the integral parts (first-order dimensions) that form e-Value in the context of a travel website (see Figure 1); this allows us to quantify the contribution of each value dimension towards overall e-Value.

Figure 1.

The e-Value Construct.

Customer Participation

In the context of travel websites, customers participate directly in service creation through utilization of the features and functionalities of websites and consequently cocreate service experiences (e.g., Prahalad and Ramaswamy 2004) as they think, act and sense when using these features (Gummerus 2013). Customer participation has been linked to a whole range of concepts such as customer satisfaction with service delivery (Ennew and Binks 1999), contribution to quality (Sigala 2006), self-serving bias (Bendapudi and Leone 2003), new product development processes (Fang 2008; Shaw, Bailey, and Williams 2011), and customer loyalty (Auh et al. 2007). The concept of customer participation is well established (see Bendapudi and Leone 2003 for a review) and has received new momentum through the perspective of customers cocreating their value experience (Vargo and Lusch 2004). For example, Prebensen et al. (2013) examined tourists’ motivation and involvement as antecedents to perceived value of their destination experience, implying that tourists cocreate their own value experience. Customer participation has been studied from the perspective of human-to-human interaction, and in an online setting, as is the case in travel communities (e.g., Wang and Fesenmaier 2004; Casaló, Flavián, and Guinalíu 2010–11). Recently researchers have begun to explore how customer participation affects value perceptions in an Internet Self-Service Technology (ISST) context (Dong, Evans, and Zou 2008; Heinonen 2009) such as a travel website. However, these studies were either exploratory (Heinonen 2009) or centered on service recovery (Dong, Evans, and Zou 2008).

To gain more insights on the crucial role the customer plays in cocreating their value experience in an ISST context, we also consulted the extensive research on TAM (Davis 1989), Diffusion of Innovations (Rogers 2003) and Technology Readiness (TR) (Parasuraman 2000), which attempted to understand consumer behavior relative to technology adoption, acceptance, and usage.

Participation has so far almost exclusively been defined as a behavioral concept. Silpakit and Fisk (1985, p. 117) referred to customer participation as “the degree of consumers’ effort and involvement, both mental and physical, necessary to participate in production and delivery of services.” Definitions have generally been context specific, for example, in response to a service failure (Dong, Evans, and Zou 2008) or a customer’s involvement in the organization’s NPD process (Fang 2008; Shaw, Bailey, and Williams 2011).

The S-D logic literature refers to customer participation as cocreation activities. Customers create experiences when engaging in these activities (Prahalad and Ramaswamy 2004), and consequently reflect on these experiences (Gummerus 2013); these then result in value assessments (Helkkula and Kelleher 2010). As a result, customers form a perception about both the cocreation/customer participation process as well as the outcome experience. Research in organizational behavior already distinguishes between actual and perceived participation when studying an individual’s participation in decision-making. Results show that perceived participation, “the extent to which the individual feels that he or she has influenced the decision” (Vroom and Jago 1988, p. 15), can occasionally be much higher than actual participation on the basis that people believe that their impact on the decision is substantially greater than it actually is.

Empirical work measured participation predominantly through multi-item measures with a Likert-type scale response format and consequently captured perceived participation (e.g., Chan, Yim, and Lam 2010). An exception is Heinonen’s (2009) work in an ISST context which inquired about the use of specific features with a yes/no response format. The sum of the features employed represented an actual measure of participation (see also Barki and Hartwick 1994). In summary, the construct of customer participation can be measured from two different perspectives (i.e., actual and perceived participation). In the context of travel websites where customers actively participate in cocreating the service, the above discussion has shown that the act of participating in creating the service experience can also be uniquely and phenomenologically perceived by the customer. As a consequence, the magnitude of the effect of perceived participation on various value components might differ from the effect of actual participation.

Hypotheses: The Effect of Customer Participation on e-Value Dimensions

Customer Participation and Utilitarian Value

Utilitarian value is defined as effective task fulfilment (Sheth, Newman, and Gross 1991); in the context of a travel website, utilitarian value then relates to convenience, speed, access, and efficiency of accessing information and booking travel arrangements (Christiansen 1990). This is consistent with work on e-quality (Zeithaml 2002), since performance/quality is seen by some authors as functional value (Sweeney, Soutar, and Johnson 1999; Sweeney and Soutar 2001). There is reason to argue that customers who participate more widely and thus make extensive use of the features and functionality of the website will gain more utilitarian value from the website.

Hypothesis 1: A customer’s participation level (actual and perceived) positively influences utilitarian value perceptions.

Customer Participation and Emotional Value

Experience derived from using SST (Dabholkar and Bagozzi 2002) and online services are reported to result in emotional responses such as fun and enjoyment (Mathwick, Malhotra, and Rigdon 2001; Pura 2005; Sigala 2006). These responses will not be experienced unless users participate. Heinonen (2009) highlighted the importance of emotional aspects when considering a service such as online travel. Bloch, Pigneur, and Steiner (1996) claimed that travelers (or customers generally) develop a self-service mentality through the experience of gathering together relevant travel services such as transportation, accommodation and leisure on the Internet. The multifunctional nature of these websites is aimed at providing fun and enjoyment as well as functional value to its users.

Hypothesis 2: A customer’s participation level (actual and perceived) positively influences emotional value perceptions.

Customer Participation and Social Value

Within the context of SST, social and psychological factors resulting from the use of technology such as self-control (Bateson 1985), social anxiety and need for social interaction (Dabholkar and Bagozzi 2002) have been identified as being of importance. Etgar (2008, p. 102) argued that “the very act of participation and performance of the relevant tasks can yield experiences that provide psychological benefits…”. For example, it was found that customer participation in online coproduction (e.g., codesigning a motorbike) can offer social benefits (Sawhney, Verona, and Prandelli 2005). However, these arguments may be strongest in an environment where a select few customers are participating, or opportunities for interaction with the firm and other customers are high, e.g., social networking. Although participation in the context of a travel website is now widespread, we argue that social benefits still occur as users who explore a larger proportion of its features are likely to come across aspects that more basic users would not have explored, and consequently can discuss their searches and purchases with peers and derive social value from these discussions.

Hypothesis 3: a customer’s participation level (actual and subjective) positively influences social value perceptions.

Customer Participation and Perceived Control and Freedom

Literature on technology-based services and SST has highlighted the salience of perceived control derived from a customer’s participation in the service (e.g., Bateson 1985; Meuter et al. 2000). While this approach regards perceived control as an outcome of participation, the technology adoption and diffusion literature posits that greater controllability of a service by a user will lead to a higher intention to adoption. This suggests that perceived control can either be a driver or an outcome of people’s use of technology (i.e., customer participation). Based on the S-D logic perspective of value-in-use where customers derive benefits from their participation, we subscribe to the latter argument and propose customer participation as a driver of perceived control.

Hypothesis 4: A customer’s participation level (actual and perceived) positively influences perceived control and freedom perceptions.

Customer Participation and Value for Money

Studies on online consumer behavior reported monetary savings as one of the key factors contributing to the use of the Internet (e.g., Kim, Kim, and Han 2007). It is expected that customers who participate more extensively on travel websites will benefit from monetary savings and hence perceive that they obtain value for money.

Hypothesis 5: A customer’s participation level (actual and perceived) is positively related to value-for-money perceptions.

Customer Participation and User’s Cognitive Efforts

Travel websites offer a multitude of functions (e.g., booking, information search, seat reservation). Given that ease of use (Davis 1989) and perceived complexity (Rogers 2003) are key in whether consumers adopt innovations, and that more participative customers are those who are more experienced (Uzkurt 2010), we propose that more participative users will find the website easier to use and, consequently, have to devote less cognitive effort in exploring its various features.

Hypothesis 6: A customers’ participation level (actual and perceived) is inversely related to their perception of cognitive effort.

Methodology

Sample and Data Collection

Online travel websites represent an ISST context whereby customers participate in cocreating the service experience and consequently derive value from using such websites. A computer-generated random sample of 3,000 UK consumers experienced in using online travel websites was obtained from Experian UK. We selected this company because of its reputation as one of the most reliable marketing intelligence companies in the UK (Shao 2009; Xiang and Gretzel 2010). Our mail survey includes a personalized cover letter, a questionnaire, and a freepost return envelope; 213 questionnaires were returned undelivered, leaving 2,787 potential respondents. A total of 197 questionnaires were returned of which 175 were usable, resulting in a 6% response rate.

Respondents were prompted to identify and evaluate one travel website that they had used most frequently during the past 12 months from a list of popular sites based on a keyword search in Google UK and a popularity report from Experian Hitwise UK (see Appendix A). All questions related to a website were asked within the context of the respondents’ chosen travel website. This method of asking respondents to report their experience with providers has been commonly applied by scholars in the area of marketing and information systems (e.g., Mano and Oliver 1993; Ganesh, Arnold and Reynolds 2000; Li, Browne, and Chau 2006). The questionnaire underwent extensive pretesting involving 22 online travel purchasers.

Our respondents were considered representative of the UK online travel purchaser after comparing the sample with data from the UK Office for National Statistics and Nielsen’s Online report on Internet usage by income (see Table 1).

Table 1.

Demographics of the Sample.

Variable	Frequency	Percentage
Gender
Male	75	42.9
Female	100	57.1
Age
18–24	11	6.3
25–34	11	6.3
35–44	35	20.0
45–54	53	30.3
55–64	45	25.7
≥65	20	11.4
Education level
High school	34	19.4
Certificate/diploma	60	34.3
Bachelor’s degree	40	22.9
Postgraduate diploma/master’s	24	13.7
Doctorate degree	8	4.6
Others	9	5.1
Personal annual gross income (£)
<15,000	39	22.3
15,000–19,999	23	13.1
20,000–24,999	17	9.7
25,000–29,999	17	9.7
30,000–49,999	38	21.7
≥50,000	28	16
Choose not to disclose	13	7.4

Using the time trends extrapolation method (Armstrong and Overton 1977), an independent-samples t-test on items of the key constructs demonstrated that nonresponse bias was not a major cause of concern.

Measurements

Actual participation was captured by a tick list of 24 website features. The sum of features used at any point in time on their most frequently used website measured actual participation. The tick list was based on Heinonen (2009) and further supplemented by features derived from a web-content analysis of 13 popular travel websites in the UK. Following guidance provided by Weare and Lin (2000), our sampling frame was initially based on popularity of a website and then cross-checked via a search engine. The sample of “Top 10 Travel Websites” ranked by search clicks was obtained from the Experian Hitwise UK website. Google UK was then used as a tool to double-check the consistency of the samples from Experian Hitwise UK. Keywords such as “online travel websites” and “online travel service” were used and the search was limited to the first 10 websites on the first page of Google UK. As the study focused on commercial travel websites, websites listed under the categories of media companies (e.g., Timesonline.co.uk) and Internet portals were removed from further analysis. Next, we identified on each of the selected online travel websites features/activities available for customer participation, resulting in a list of 24 features (see Appendix B).

As the number of available features varies slightly across websites, the index of actual participation per respondent was based on the proportionate use of possible features on a particular website. Our analysis only includes respondents that ticked features available on their chosen website. On average, respondents utilized 57.8% (SD = 20.95) of possible features.

Perceived participation was captured by a six-item measure, derived from Searfoss and Monczka (1973) and Vroom and Jago (1988); it measures the extent to which individuals perceive that they have participated on the website through the use of its features or activities. Based on a seven-point response format (1 = fully disagree to 7 = fully agree), respondents’ average perceived participation was 3.97 (SD = 1.40). Actual and perceived participation were only moderately correlated (r = .378).

The first-order value dimensions, which together form the second-order formative measure of a customer’s value experience when using a travel website (e-Value), were drawn from existing multi-item measurement scales. Utilitarian value was captured by a five-item scale based on Sigala (2006); emotional value on a four-item scale by Agarwal and Karahanna (2000); social value by three items based on Pura (2005) and Sigala (2006); perceived control and freedom by four items from Kleijnen, De Ruyter, and Wetzels (2007); value for money by three items by Sigala (2006); and user’s cognitive effort by four items from Meuter et al. (2005) and Kleijnen, De Ruyter, and Wetzels (2007). A seven-point response format (1 = fully disagree to 7 = fully agree) was used for all items except actual participation. Appendix C details the measurements included in this study after purification.

To demonstrate the nomological validity of the second-order formative value measure, we included a five-item measure for customer satisfaction (based on Ruiz et al. 2008) and a three-item measure for behavioral intention (based on Cronin, Brady, and Hult 2000).

Analysis and Findings

Measure Validation

We ran exploratory factor analysis followed by confirmatory factor analysis in LISREL 8.54 to assess validity and reliability of the value dimensions and our validation constructs (i.e., customer satisfaction and behavioral intention). The initial results indicated a lack of discriminant validity between the constructs “perceived control and freedom” and “utilitarian value.” Although the literature differentiates between these dimensions, given the nature of the chosen context it appears reasonable to assume that control and freedom are seen as key utilitarian value and not as a distinct value dimension. We consequently merged these constructs. After eliminating further items, the purified measurement model fitted the data well: χ² = 308.3, df = 186, p = .000, χ²/df = 1.66; root mean square error of approximation = .062, comparative fit index = .972, nonnormed fit index = .965; average variance extracted (AVE) for all constructs ranged from .463 to .816 and composite reliability (CR) from .76 to .93, demonstrating convergent validity of all measurements (see Table 2). The measurements also display discriminant validity, since the square root of the AVE of each construct is higher than any correlation with a respective construct (Fornell and Larcker 1981). We also set construct correlations for each possible combination at unity, and in each case the fit worsened, confirming that the measurements display discriminant validity (Bagozzi and Phillips 1982).

Table 2.

Correlation Matrix and Descriptives for Measurement Scales.

		Mean	SD	CR	AVE	1	2	3	4	5	6	7	8	9
1	Utilitarian/control value	5.26	1.14	.84	.566	.752 ^a
2	Social value	2.72	1.33	.83	.629	.260	.793
3	Emotional value	3.88	1.39	.76	.617	.525	.649	.785
4	Value for money^b	2.96	1.42	n/a	n/a	−.588	−.028	−.317	n/a
5	Users’ cognitive effort	2.34	1.17	.84	.592	−.566	−.012	−.343	.711	.770
6	Satisfaction	5.40	1.09	.93	.816	.713	.146	.558	−.627	−.707	.903
7	Behavioral intentions	5.86	1.14	.88	.591	.580	.018	.305	−.686	−.620	.736	.769
8	Perceived participation	3.97	1.40	.87	.463	.252	.391	.662	−.261	−.355	.330	.296	.680
9	Actual participation^c	57.78	20.95	n/a	n/a	.240	.151	.356	−.105	−.147	.203	.145	.378	n/a

Note: CR = composite reliability; AVE = average variance extracted.

Values in bold are square root of AVE.

Single-item measure.

Percentage of possible features used.

Validity of the second-order formative measurement of e-Value was assessed following Diamantopoulos and Winklhofer (2001). First, to capture fully the domain of the construct, we undertook a review of the value literature (see above). Second, indicator collinearity was established (variance inflation factor for each value dimension ranging from 1.24 to 1.61). Third, external validity of the e-Value construct was checked by linking it to behavioral intention and satisfaction. Higher value perceptions should lead to increased levels of satisfaction (Bradley and Sparks 2012; Cronin, Brady, and Hult 2000) and stronger behavioral intentions (e.g., Petrick and Backman 2002; Gallarza and Gil-Saura 2006). The results of the partial least squares (PLS) analysis show that the model fits the data well. Both the path from e-Value to satisfaction (β = .770, R² = 59.3%, p < .01) and behavioral intention (β = .598, R² = 35.8 %, p < .01) show strong positive relationships with substantial amounts of variance explained, confirming the external validity of the second-order e-Value measurement. Using the weightings of the first-order dimensions of e-Value as indications of their importance in forming a customer’s overall value experience, we find cognitive effort to be most influential (–.490, p < .01), followed by utilitarian/control value (.438, p < .01), emotional value (.239, p < .01), and value for money (–.168, p < .05). The link between social value and e-Value (.082) was not significant (see Figure 2).

Figure 2.

Assessment of external/nomological validity.

Structural Model and Hypotheses Testing

We tested the proposed hypotheses linking participation to individual value dimensions using SmartPLS 2.0 (Ringle, Wende, and Will 2005). The proposed model explains a considerable proportion of the variance in emotional value (R² = 33%), social value (R² = 12.3%), and user’s cognitive effort (R² = 10%), but showed only a weak link to utilitarian/control value (R² = 8%) and no link to value for money perceptions (R² = 2.5%). The predictive power of the overall model is considered acceptable, as indicated by a Stone-Geisser’s Q² value of .10 (Stone 1974).

Our hypotheses link actual and perceived participation to the proposed value dimensions. The moderate correlation of .378 between these two measurements of participation suggests that customers’ actual use of features (percentage of possible features) on a travel website might not necessarily be a good proxy for how they perceive their participation. As a consequence, differences in how actual and perceived participation affect the various value dimensions are to be expected. Most of our hypothesized relationships are supported (see Table 3). Actual participation increases utilitarian/control value (β_{actual participation} = .185, p < .05) as proposed in hypotheses 1 and 4, while the effect of perceived participation on utilitarian/control value is somewhat marginal (β_{perceived participation} = .154, p < .10). Hypothesis 2 is also supported as actual participation and perceived participation (β_{actual participation} = .178, p < .01; β_{perceived participation} = .483, p < .01) enhance emotional value perceptions. With regard to hypothesis 3, only perceived participation is positively associated with social value (β_{perceived participation} = .343, p < .01), whereas the relationship between actual participation and social value is not significant (β_{actual participation} = .018, n.s.). No support could be found for hypothesis 5; actual/perceived participation does not appear to affect value for money perceptions (β_{actual participation} = –.057, n.s.; β_{perceived participation} = –.127, n.s.). Finally, our data only partially support hypothesis 6; that is, while increased levels of perceived participation are associated with lower levels of cognitive effort perceptions (β_{perceived participation} = –.289, p < .01), actual participations are not linked with users’ cognitive effort perceptions (β_{actual participation} = –.045, n.s.).

Table 3.

Results of Hypotheses Test (Standardized Coefficients and R²).

	Utilitarian/Control Value (hypothesis 1 + hypothesis 4)	Emotional Value (hypothesis 2)	Social Value (hypothesis 3)	Value for Money (hypothesis 5)	User’s Cognitive Effort (hypothesis 6)
Actual participation	.185**	.178***	.018 (n.s.)	−.057 (n.s.)	−.045 (n.s.)
Perceived participation	.154*	.483***	.343***	−.127 (n.s.)	−.289***
R ²	.080	.330	.123	.025	.100

p < .10; **p < .05; ***p < .01.

Only utilitarian/control value is more strongly associated with actual participation while emotional, social, and user’s cognitive effort perceptions are more affected by the user’s perception of their participation compared to their actual behavior. In our chosen context, value-for-money perceptions are not affected by any form of customer participation.

Discussion

This research sets out to identify relevant value dimensions employed by customers to evaluate their travel website experience in order to conceptualize e-Value, and to examine how users’ own activities (i.e., participation) on a travel website affect their value experience (e-Value).

Measurement of e-Value

We conceptualized e-Value (value experience when using a travel website) as a formative second-order construct, with utilitarian value, emotional value, social value, freedom and control, value for money, and users’ cognitive efforts as first-order value dimensions. Respondents regarded freedom and control as an integral part of the functionality of a travel website (see also Kim, Kim, and Han 2007). Having merged these dimensions, our conceptualization of e-Value has nomological validity; it explains 59.3% of customer satisfaction and 35.8% of behavioral intention.

The formative nature of the e-Value construct allows us to identify the subdimensions that are most influential in driving a user’s overall value experience when using a travel website. The latter is mostly affected by a user’s perception of the cognitive effort involved, by the utilitarian/control value gained, and the emotional value, that is, the level of enjoyment and fun derived by using the website. Descriptive analysis (see Table 2) also showed that respondents rated their most frequently used travel website very high in terms of utilitarian/control value (mean = 5.26, SD = 1.14; 1 = fully disagree to 7 = fully agree), fairly high on emotional value (mean = 3.88, SD = 1.39) and low in terms of cognitive effort involved (mean = 2.34, SD = 1.17). The latter clearly highlights that website users see themselves as cocreating the value experience (Vargo and Lusch 2004), and their most preferred travel website is one that is easy to understand and use. This is consistent with work on mobile service delivery (Kleijnen, De Ruyter, and Wetzels 2007) and work on diffusion of innovation (Rogers 2003). Value for money was found to be less influential in forming overall value perceptions; the mean value of 2.96 (SD = 1.42) is likely to be a reflection of the competitive nature of travel websites, which leads to almost identical prices. Travel website users appear to see insufficient price differences across sites. Social value is by far the least important aspect feeding into e-Value, with a low respondent rating (mean = 2.72; SD = 1.33). Considering that social value reflects enhancement of self-image in his or her social system (Sheth, Newman, and Gross 1991), usage of a travel website does not assist in raising a person’s status and image. Although the social value component has strong theoretical grounding in diffusion of innovation theory, the results are likely a reflection of the widespread utilization of travel websites.

The Effect of Customer Participation on the Various Value Dimensions

Although recent literature advocates the active role of customers in value creation (Vargo and Lusch 2004), this debate has so far referred to a somewhat abstract level of value. To our best knowledge, this is the first study quantifying the extent to which customers cocreate their experience on a travel website and how this translates into their value perception of a travel website. By examining levels of cocreation activities (i.e., actual customer participation) and a customer’s reflection on those activities (i.e., perceived participation) we were able to see which value dimensions are most impacted by a customer’s own activities. This provides richer insights for website developers and travel websites.

Actual participation is an index based on the number of features used on a travel website, while perceived participation relates to the user’s perception of the extent to which they have made use of the features on their most frequently used travel website.

The results demonstrate that (1) the extent to which customer participation affects their e-Value experience varies greatly in magnitude across dimensions, and (2) there are distinct differences in the effects of actual and perceived customer participation, hence providing support to the different operationalizations of the construct.

As expected, customers who make more use of features (i.e., actual participation) gain more utilitarian/control value and also derive more emotional value from their most frequently used travel website. Only utilitarian/control value was predicted better by actual website usage compared to perceived participation. Conversely, increased levels of perceived participation better explain users’ emotional and social value perceptions. About one-third (R² = 33%) of the fun and enjoyment users experience can be attributed to their own activities, followed by social value (R² = 12.3%). Clearly, a significant proportion of fun and enjoyment of using a travel website is derived from customers’ own activities on the website (i.e., researching and creating their own holidays, searching, mixing, and matching various travel components). This finding supports the importance of emotional aspects reported in the context of experience-based online services (Mathwick, Malhotra, and Rigdon 2001; Pura 2005; Sigala 2006) such as online travel services.

In terms of perceived participation, more participative users felt that less cognitive effort was involved when using their favorite travel website, while actual participation levels were unrelated to cognitive effort perceptions. Cognitive effort is a key contributor to overall value experience (R² = 10%). Since value is uniquely determined by the user, cognitive effort perceptions also will be personal. A form of confirmation bias would lead those who believe they are participating to a high degree also to believe that the effort involved is relatively low. Accordingly, the higher the perceived participation, the lower the assessment of cognitive effort. Although actual participation does not significantly affect social value, the impact of perceived participation is strong and significant. Use of travel websites is not visible to others; it is widespread and no longer regarded as innovative or novel. Nevertheless, those who perceive their activities on such sites as more extensive also derive more social value, perhaps because of their ability to describe their perceived participation to others. However, the magnitude of social value derived appears to be too low to contribute substantively towards e-Value.

Users’ levels of participation (actual or perceived) on their most frequently used travel website do not affect value-for-money perceptions. In summary, users’ actual activities on the web are less relevant in shaping their value experiences; perceptions of their participation levels are crucial. An exception is functional/control value, which is slightly better explained by actual participation levels. These are the first results that quantify the extent to which customers contribute to their own value experience, as proposed by Prahalad and Ramaswamy (2004) and Vargo and Lusch (2004). Our conceptualization of e-Value allows us to be more specific and pinpoint which components of the value experience are directly influenced by a customer’s own activities on a website.

Evaluation of the Study and Recommendations for Future Research

The study is not without limitations. Grouping together responses from a range of websites might have masked distinct difference across websites. Nevertheless, our overall conceptualization and measure of e-Value is sufficiently broad to have shown convergent and nomological validity.

The above results clearly show that customers contribute to their value experience by their use (actual or perceived) of website features. However, such general statements only offer a partial picture of the effect of customer participation for both researchers and practitioners. The limited explanation offered by participation levels on the key drivers of value (i.e., cognitive effort and utilitarian/control value) suggests that adopting the e-Value conceptualization offers future opportunities to explore further factors to explain value experiences at the dimension level that go beyond the firm-based offering. We would also encourage researchers to validate further the conceptualization of e-Value in specific contexts, such as on social-networking sites (e.g., TripAdvisor), which is likely to show differences in the relative importance of value dimensions driving overall value. This would confirm the dimensionality of the e-Value construct and its adaptability to commercial and noncommercial tourism contexts.

Managerial Implications

Practitioners in the travel sector can utilize the e-Value conceptualization and associated measurements of first-order dimensions to benchmark how customers perceive a specific website in comparison to competitors. Identifying the key drivers of value in a particular context and linked to the magnitude of how well a website performs on this dimension allows companies to make more informed choices about how to develop their websites. In our context, the main building blocks of e-Value on their favorite travel website are lack of cognitive effort involved and the utilitarian/control value gained. The results also show that developing travel websites to trigger emotional value experiences might offer the best way to raise e-Value perceptions. Currently, users rate their emotional value experience at 3.88 (on a 1–7 scale); however, even with such a low average score, it is the third highest contributor to e-Value perceptions, indicating that users gain intrinsic value from the experience itself.

Second, e-Value offers a powerful tool to segment customers that can be employed in a range of contexts (e.g., test attractiveness of additional functionality of the website). Third, the findings show clearly that objectively measured customer participation through, for example, clickstream data might offer a distorted picture of customers’ own perception of participation. We advise web designers and travel companies to think of customer participation also as a subjective process to open up new avenues in understanding and engaging customers. For example, actual use of a website (i.e., the diversity of features used) has no effect on users’ perceptions of cognitive effort involved; conversely, perceived participation levels are negatively related to perceptions of cognitive effort.

Contribution

We provide a theoretically grounded and empirically validated measurement of e-Value of travel websites. Unlike other measurements of value, this approach takes into account the multidimensional nature of this construct and models how individual dimensions affect overall value perceptions (e-Value). Our findings have supported calls for not only conceptualizing value as a multidimensional construct but also specifying it in a formative way at a higher level of abstraction (Lin, Sher, and Shih 2005; Sánchez et al. 2006; Sánchez-Fernández and Iniesta-Bonillo 2007; Ruiz et al. 2008; Mayr and Zins 2012). From an online travel viewpoint, the multidimensional approach is ideal as customers’ value experience derived from using a particular website is multifaceted, including both cognitive and affective elements as supported by the notion of human-to-technology interaction in the ISST environment. Second, we provide the first empirical investigation that quantifies the effects of customer participation on the components that comprise e-Value. Managers will benefit from knowing which components of value are affected by customers’ own use of a website. The magnitude and direction of the effect will assist travel websites in better tailoring their websites to the demands of their customers. In line with the notion that value perceptions are phenomenologically defined, we also differentiate between customers’ actual and perceived participation on a travel website and demonstrate that objective data on website usage are insufficient as users’ perceptions about their participation levels generally explain customers’ value experiences better.

Footnotes

Appendix

Appendix C.

Items and Standardized Factor Coefficients.

Perceived participation	On this website I like to use as many features as possible	.792
	I believe I have used the full potential of the features on this website	.822
	I think I have used only a minimal amount of features available on this website	.745
	I think I have significantly used the features available on this website	.794
Customer satisfaction	I am happy with this website	.900
	My choice to use this website was a wise one	.860
	Overall, I am satisfied with this website	.947
Behavioral intentions	The probability that I will use this website again is . . .	.855
	The likelihood that I would recommend this website to others is . . .	.748
	If I had to do it over again (i.e., to browse and/or purchase travel services online), I would make the same choice	.903
Utilitarian value/Control	Using this website makes it easier to meet my travel needs	.796
	I value the convenience of using this website for my travel needs	.753
	Using this website helps me accomplish tasks related to my travel needs more quickly	.761
	Using this website for my transactions allows me to make a lot of decisions on my own	.695
User’s cognitive effort	I believe that this website is difficult to use	.690
User’s cognitive effort	It takes a lot of effort to understand how to use this website	.814
Social value	Other people will be impressed that I use this website	.810
	Using this website improves the ways I am perceived by others	.878
	Using this website helps me to feel accepted by others	.678
Value for money	I feel that the service(s) I purchase from this website is/are expensive	.732
Emotional value	I have fun interacting with this website	.751
Emotional value	Using this website provides me with a lot of enjoyment	.818

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Amrul Asraf Mohd-Any is lecturer in marketing at the University of Malaya, Kuala Lumpur, Malaysia. He completed his MSc at the University of Strathclyde, Scotland, and his PhD at the University of Nottingham, United Kingdom. His research interests focus on services marketing and Internet marketing including customer participation/consumer engagement behavior in self-service technology, customer perceived value, and consumption and practice theory. He is currently involved in several local and international research projects under the Service Research and Innovation Centre (ServRI) and the Social Security Research Centre (SSRC), University of Malaya.

Heidi Winklhofer is professor of marketing at Nottingham University Business School. Her current research interests lie in the area of services marketing focusing on value cocreation and customer learning. She has published in a number of leading international journals, including Journal of Marketing Research, Journal of Service Research, The International Journal of Research in Marketing, Journal of Business Research, Journal of Interactive Marketing, and International Journal of Forecasting.

Christine Ennew is professor of marketing and provost at the University of Nottingham Malaysia Campus. Her research interests lie in the area of services marketing and specifically financial services, tourism, and higher education. She has focused her research on key strategic themes, including service quality and delivery, loyalty and retention, and service failure and recovery. She has also undertaken business-oriented research specifically in the areas of customer satisfaction, marketing relationships, and trust, including on behalf of a number of major banking organizations. She has published more than 100 articles in refereed journals, presented over 60 refereed conference papers and produced 5 books.

References

Agarwal

Ritu

Karahanna

Elena

(2000). “Time Flies When You’re Having Fun: Cognitive Absorption and Beliefs about Information Technology Usage.” MIS Quarterly, 24 (4): 665-94.

Al-Sabbahy

Hesham Z.

Ekinci

Yuksel

Riley

Micheal

. (2004). “An Investigation of Perceived Value Dimensions: Implications for Hospitality Research.” Journal of Travel Research, 42 (3): 226-34.

Armstrong

J. Scott

Overton

Terry S.

(1977). “Estimating Nonresponse Bias in Mail Surveys.” Journal of Marketing Research, 14 (3): 396-402.

Auh

Seigyoung

Bell

Simon J.

McLeod

Colin S.

Shih

Eric

. (2007). “Co-production and Customer Loyalty in Financial Services.” Journal of Retailing, 83 (3): 359-70.

Babin

Barry J.

Darden

William R.

Griffin

Mitch

. (1994). “Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value.” Journal of Consumer Research, 20 (4): 644-56.

Bagozzi

Richard P.

Phillips

Lynn W.

(1982). “Representing and Testing Organizational Theories: A Holistic Construal.” Administrative Science Quarterly, 27 (3): 459-89.

Barki

Henri

Hartwick

Jon

. (1994). “Measuring User Participation, User Involvement, and User Attitude.” MIS Quarterly, 18 (1): 59-82.

Bateson

John E.

(1985). “Self-Service Consumer: An Exploratory Study.” Journal of Retailing, 61 (3): 49-76.

Bendapudi

Neeli

Leone

Robert P.

(2003). “Psychological Implications of Customer Participation in Co-Production.” Journal of Marketing, 67 (1): 14-28.

10.

Bloch

Michael

Pigneur

Yves

Steiner

Thomas

. (1996). “The IT-enabled Extended Enterprise, Applications in the Tourism Industry.” In Information and Communication Technology in Tourism, edited by Klein

Schmid

Tjoa

A. M.

Werthner

Wien: Springer, pp. 113-20.

11.

Bradley

Graham L.

Sparks

Beverley A.

(2012). “Antecedents and Consequences of Consumer Value: A Longitudinal Study of Timeshare Owners.” Journal of Travel Research, 51 (2): 191-204.

12.

Casaló

Luis V.

Flavián

Carlos

Guinalíu

Miguel

. (2010–2011). “Antecedents and Consequences of Consumer Participation in Online Communities: The Case of the Travel Sector.” International Journal of Electronic Commerce, 15 (2): 137-67.

13.

Chan

Kimmy Wa

Yim

Chi Kin (Bennett)

Lam

Simon S. K.

(2010). “Is Customer Participation in Value Creation a Double-Edged Sword? Evidence from Professional Services across Cultures.” Journal of Marketing, 74 (3): 48-54.

14.

Chen

Ching-Fu

Chen

Fu-Shian

. (2010). “Experience Quality, Perceived Value, Satisfaction and Behavioral Intentions for Heritage Tourists.” Tourism Management, 31 (1): 29-35.

15.

Childers

Terry L.

Carr

Christopher L.

Peck

Joann

Carson

Stephen

. (2001). “Hedonic and Utilitarian Motivations for Online Retail Shopping Behavior.” Journal of Retailing, 77 (4): 511-35.

16.

Christiansen

D. R.

(1990). “Adventure Tourism.” In Adventure Education, edited by Miles

J. C.

Priest

State College, PA: Venture.

17.

Cronin

J. Joseph

Brady

Michael K.

Hult

G. Tomas M.

(2000). “Assessing the Effects of Quality, Value, and Customer Satisfaction on Consumer Behavioral Intentions in Service Environments.” Journal of Retailing, 76 (2): 193-218.

18.

Dabholkar

Pratibha A.

Bagozzi

Richard P.

(2002). “An Attitudinal Model of Technology-based Self-service: Moderating Effects of Consumer Traits and Situational Factors.” Journal of the Academy of Marketing Science, 30 (3): 184-201.

19.

Davis

Fred D.

(1989). “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly, 13 (3): 318-40.

20.

Diamantopoulos

Adamantios

Winklhofer

Heidi M.

(2001). “Index Construction with Formative Indicators: An Alternative to Scale Development.” Journal of Marketing Research, 38 (2): 269-77.

21.

Dong

Beibei

Evans

Kenneth R.

Zou

Shaoming

. (2008). “The Effects of Customer Participation in Co-created Service Recovery.” Journal of the Academy of Marketing Science, 36 (1): 123-37.

22.

Duman

Teoman

Mattila

Anna S.

(2005). “The Role of Affective Factors on Perceived Cruise Vacation Value.” Tourism Management, 26 (3): 311-23.

23.

Ennew

Christine T.

Binks

Martin R.

(1999). “Impact of Participative Service Relationships on Quality, Satisfaction and Retention: An Exploratory Study.” Journal of Business Research, 46 (2): 121-32.

24.

Etgar

Michael

. (2008). “A Descriptive Model of the Consumer Co-production Process.” Journal of the Academy of Marketing Science, 36 (1): 97-108.

25.

Fang

Eric

. (2008). “Customer Participation and the Trade-off between New Product Innovativeness and Speed to Market.” Journal of Marketing, 72 (4): 90-104.

26.

Fornell

Claes

Larcker

David F.

(1981). “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error.” Journal of Marketing Research, 18 (1): 39-50.

27.

Gallarza

Martina G.

Gil-Saura

Irene

. (2006). “Value Dimensions, Perceived Value, Satisfaction and Loyalty: An Investigation of University Students’ Travel Behavior.” Tourism Management, 27:437-52.

28.

Ganesh

Jaishankar

Arnold

Mark J.

Reynolds

Kristy E.

(2000). “Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers.” Journal of Marketing, 64 (3): 65-87.

29.

Gnoth

Juergen

. (1997). “Tourism Motivation and Expectation Formation.” Annals of Tourism Research, 24 (2): 283-304.

30.

Gummerus

Johanna

. (2013). “Value Creation Processes and Value Outcomes in Marketing Theory.” Marketing Theory, 13 (1): 19-46.

31.

Heinonen

Kristina

. (2004). “Reconceptualizing Customer Perceived Value—The Value of Time and Place.” Managing Service Quality, 14 (2/3): 205-15.

32.

Heinonen

Kristina

. (2009). “The Influence of Customer Activity on E-service Value-in-Use.” International Journal of Electronic Business, 7 (2): 190-214.

33.

Helkkula

Anu

Kelleher

Carol

. (2010). “Circularity of Customer Service Experience and Customer Perceived Value.” Journal of Customer Behaviour, 9 (1): 37-53.

34.

Helkkula

Anu

Kelleher

Carol

Pihlström

Minna

. (2012). “Characterizing Value as an Experience Implications for Service Researchers and Managers.” Journal of Service Research, 15 (1): 59-75.

35.

Hirschman

Elizabeth C.

Holbrook

Morris B.

(1982). “Hedonic Consumption: Emerging Concepts, Methods and Propositions.” Journal of Marketing, 46 (3): 92-101.

36.

Chaang-Iuan

Lee

Yi-Ling

. (2007). “The Development of an E-travel Service Quality Scale.” Tourism Management, 28 (6): 1434-49.

37.

Holbrook

Morris B.

(1994). “The Nature of Customer Value: An Axiology of Services in the Consumption Experience.” In Service Quality: New Directions in Theory and Practice, edited by Rust

Roland T.

Oliver

Richard L.

Thousand Oaks, CA: Sage, pp. 21-71.

38.

Holbrook

Morris B.

(1999). Consumer Value: A Framework for Analysis and Research. London: Routledge.

39.

Holbrook

Morris B.

(2006). “Consumption Experience, Customer Value, and Subjective Personal Introspection: An Illustrative Photographic Essay.” Journal of Business Research, 59 (6): 714-25.

40.

Holbrook

Morris B.

Hirschman

Elizabeth C.

(1982). “The Experiential Aspects of Consumption: Consumer Fantasies, Feelings, and Fun.” Journal of Consumer Research, 9 (September): 132-40.

41.

Hutchinson

Joe

Lai

Fujun

Wang

Youcheng

. (2009). “Understanding the Relationships of Quality, Value, Equity, Satisfaction, and Behavioral Intentions among Golf Travellers.” Tourism Management, 30 (2): 298-308.

42.

Kashyap

Rajiv

Bojanic

David C.

(2000). “A Structural Analysis of Value, Quality, and Price Perceptions of Business and Leisure Travellers.” Journal of Travel Research, 39 (1): 45-51.

43.

Kaynama

Shohreh A.

Black

Christine I.

(2000). “A Proposal to Assess the Service Quality of Online Travel Agencies: An Exploratory Study.” Journal of Professional Services Marketing, 21 (1): 63-88.

44.

Kim

Dong Jin

Kim

Woo Gon

Han

Jin Soo

. (2007). “A Perceptual Mapping of Online Travel Agencies and Preference Attributes.” Tourism Management, 28 (2): 591-603.

45.

Kim

Eyong B.

Eom

Sean B.

(2002). “Designing Effective Cyber Store User Interface.” Industrial Management and Data Systems, 102 (5): 241-51.

46.

Kim

Woo Gon

Lee

Hae Young

. (2004). “Comparison of Web Service Quality between Online Travel Agencies and Online Travel Suppliers.” Journal of Travel & Tourism Marketing, 17 (2/3): 105-16.

47.

Kleijnen

Mirella

De Ruyter

Wetzels

Martin

. (2007). “An Assessment of Value Creation in Mobile Service Delivery and the Moderating Role of Time Consciousness.” Journal of Retailing, 83 (1): 33-46.

48.

Law

Rob

Shanshan

Buhalis

Dimitrios

. (2010). “Progress in Tourism Management: A Review of Website Evaluation in Tourism Research.” Tourism Management, 31:297-313.

49.

Lee

Jin-Soo

Lee

Choong-Ki

Choi

Youngjoon

. (2011). “Examining the Role of Emotional and Functional Values in Festival Evaluation.” Journal of Travel Research, 50 (6): 685-96.

50.

Dahui

Browne

Glenn J.

Chau

Patrick Y. K.

(2006). “An Empirical Investigation of Web Site Use Using a Commitment-Based Model.” Decision Sciences, 37 (3): 427-44.

51.

Lin

Chien-Hsin

Sher

Peter J.

Shih

Hsin-Yu

. (2005). “Past Progress and Future Directions in Conceptualizing Customer Perceived Value.” International Journal of Service Industry Management, 16 (4): 318-36.

52.

Mano

Haim

Oliver

Richard L.

(1993). “Assessing the Dimensionality and Structure of the Consumption Experience: Evaluation, Feeling, and Satisfaction.” Journal of Consumer Research, 20 (3): 451-66.

53.

Mathwick

Charla

Malhotra

Naresh

Rigdon

Edward

. (2001). “Experiential Value: Conceptualization, Measurement and Application in the Catalog and Internet Shopping Environment.” Journal of Retailing, 77 (1): 39-56.

54.

Mayr

Thomas

Zins

Andreas H.

(2012). “Extensions on the Conceptualization of Customer Perceived Value: Insights from the Airline Industry.” International Journal of Culture, Tourism and Hospitality Research, 6 (4): 356-76.

55.

Meuter

Matthew L.

Ostrom

Amy L.

Roundtree

Robert I.

Bitner

Mary Jo

. (2000). “Self-Service Technologies: Understanding Customer Satisfaction with Technology-based Service Encounters.” Journal of Marketing, 64 (3): 50-64.

56.

Meuter

Matthew L.

Bitner

Mary Jo

Ostrom

Amy L.

Brown

Stephen W.

(2005). “Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-service Technologies.” Journal of Marketing, 69 (2): 61-83.

57.

Parasuraman

Ananthanarayanan

. (1997). “Reflections on Gaining Competitive Advantage through Customer Value.” Journal of the Academy of Marketing Science, 25 (2): 154-61.

58.

Parasuraman

Ananthanarayanan

. (2000). “Technology Readiness Index (TRI) a Multiple-Item Scale to Measure Readiness to Embrace New Technologies.” Journal of Service Research, 2 (4): 307-20.

59.

Parasuraman

Ananthanarayanan

Zeithaml

Valarie A.

Malhotra

Arvind

. (2005). “ES-QUAL—A Multiple-Item Scale for Assessing Electronic Service Quality.” Journal of Service Research, 7 (3): 213-33.

60.

Petrick

James F.

(2002). “Development of a Multi-dimensional Scale for Measuring the Perceived Value of a Service.” Journal of Leisure Research, 34 (2): 119-34.

61.

Petrick

James F.

(2003). “Measuring Cruise Passengers’ Perceived Value.” Tourism Analysis, 7 (3): 251-58.

62.

Petrick

James F.

(2004). “The Roles of Quality, Value, and Satisfaction in Predicting Cruise Passengers’ Behavioral Intentions.” Journal of Travel Research, 42 (4): 397-407.

63.

Petrick

James F.

Backman

Sheila J.

(2002). “An Examination of the Construct of Perceived Value for the Prediction of Golf Travelers’ Intentions to Revisit.” Journal of Travel Research, 41 (1): 38-45.

64.

Prahalad

Coimbatore K.

Ramaswamy

Venkat

. (2004). The Future of Competition: Co-creating Unique Value with Customers. Boston, MA: Harvard Business School Press.

65.

Prebensen

Nina K.

Woo

Eunju

Chen

Joseph S.

Uysal

Muzaffer

. (2013). “Motivation and Involvement as Antecedents of the Perceived Value of the Destination Experience.” Journal of Travel Research, 52 (2): 253-64.

66.

Pura

Minna

. (2005). “Linking Perceived Value and Loyalty in Location-based Mobile Services.” Managing Service Quality, 15 (6): 509-38.

67.

Ranganathan

Ganapathy

Shobha

. (2002). Key Dimensions of Business-to-Consumer Websites.” Information and Management, 39:457-65.

68.

Richins

Marsha

. (1997). “Measuring Emotions in the Consumption Experience.” Journal of Consumer Research, 24 (September): 127-46.

69.

Ringle

Christian M.

Wende

Sven

Will

Alexander

. (2005). “SmartPLS 2.0 (Beta).” SmartPLS, Hamburg (available at www.smartpls.de)

70.

Rogers

Everett M.

(2003). Diffusion of Innovation. New York: Free Press.

71.

Ruiz

David Martín

Gremler

Dwayne D.

Washburn

Judith H.

Carrión

Gabriel Cepeda

. (2008). “Service Value Revisited: Specifying a Higher-order, Formative Measure.” Journal of Business Research, 61 (12): 1278-91.

72.

Sánchez

Javier

Callarisa

Luis

Rodriguez

Rosa M.

Moliner

Miguel A.

(2006). “Perceived Value of the Purchase of a Tourism Product.” Tourism Management, 27 (3): 394-409.

73.

Sánchez-Fernández

Raquel

Iniesta-Bonillo

M. Ángeles

. (2007). “The Concept of Perceived Value: A Systematic Review of the Research.” Marketing Theory, 7 (4): 427-51.

74.

Sawhney

Mohanbir

Verona

Gianmario

Prandelli

Emanuela

. (2005). “Collaborating to Create: The Internet as a Platform for Customer Engagement in Product Innovation.” Journal of Interactive Marketing, 19 (4): 4-17.

75.

Searfoss

D. Gerald

Monczka

Robert M.

(1973). “Perceived Participation in the Budget Process and Motivation to Achieve the Budget.” Academy of Management Journal, 16 (4): 541-54.

76.

Shao

Guosong

. (2009). “Understanding the Appeal of User-Generated Media: A Uses and Gratification Perspective.” Internet Research, 19 (1): 7-25.

77.

Shaw

Gareth

Bailey

Adrian

Williams

Allan

. (2011). “Aspects of Service-Dominant Logic and Its Implications for Tourism Management: Examples from the Hotel Industry.” Tourism Management, 32 (2): 207-14.

78.

Sheth

Jagdish N.

Newman

Bruce I.

Gross

Barbara L.

(1991). “Why We Buy What We Buy: A Theory of Consumption Values.” Journal of Business Research, 22 (2): 159-70.

79.

Sigala

Marianna

. (2006). “Mass Customization Implementation Models and Customer Value in Mobile Phones Services: Preliminary Findings from Greece.” Managing Service Quality, 16 (4): 395-420.

80.

Silpakit

Patriya

Fisk

Raymond P.

(1985). “Participatizing’ the Service Encounter: A Theoretical Framework.” In Service Marketing in a Changing Environment, edited by Block

T. M.

Upah

G. D.

Zeithaml

V. A.

Chicago: American Marketing Association, pp. 117-21.

81.

Smith

J. Brock

Colgate

Mark

. (2007). “Customer Value Creation: A Practical Framework.” Journal of Marketing Theory and Practice, 15 (1): 7-23.

82.

Stone

Mervyn

. (1974). “Cross-validatory Choice and Assessment of Statistical Predictions.” Journal of the Royal Statistical Society, 36:111-47.

83.

Sweeney

Jillian C.

Soutar

Geoffrey N.

(2001). “Consumer Perceived Value: The Development of a Multiple Item Scale.” Journal of Retailing, 77 (2): 203-20.

84.

Sweeney

Jillian C.

Soutar

Geoffrey N.

Johnson

Lester W.

(1999). “The Role of Perceived Risk in the Quality-Value Relationship: A Study in a Retail Environment.” Journal of Retailing, 75 (1): 77-105.

85.

Tanford

Sarah

Baloglu

Seyhmus

Erdem

Mehmet

. (2012). “Travel Packaging on the Internet: The Impact of Pricing Information and Perceived Value on Consumer Choice.” Journal of Travel Research, 51 (1): 68-80.

86.

Uzkurt

Cevahir

. (2010). “Customer Participation in the Service Process: A Model and Research Propositions.” International Journal of Services and Operations Management, 6 (1): 17-37.

87.

Vargo

Stephen L.

Lusch

Robert F.

(2004). “Evolving to a New Dominant Logic for Marketing.” Journal of Marketing, 68 (1): 1-17.

88.

Vargo

Stephen L.

Lusch

Robert F.

(2008). “Service-Dominant Logic: Continuing the Evolution.” Journal of the Academy of Marketing Science, 36 (1): 1-10.

89.

Vargo

Stephen L.

Lusch

Robert F.

Akaka

Melissa Archpru

. (2010). “Service-Dominant Logic: A Review and Assessment.” In Review of Marketing Research, Vol. 6, edited by Malhotra

Naresh K.

Bingley, WA: Emerald Group, pp. 125-67.

90.

Vroom

Victor H.

Jago

Arthur G.

(1988). The New Leadership: Managing Participation in Organizations. Englewood Cliffs, NJ: Prentice Hall.

91.

Wang

Youcheng

Fesenmaier

Daniel R.

(2004). “Modeling Participation in an Online Travel Community.” Journal of Travel Research, 42 (3): 261-70.

92.

Weare

Christopher

Lin

Wan-Ying

. (2000). “Content Analysis of the World Wide Web: Opportunities and Challenges.” Social Science Computer Review, 18 (3): 272-92.

93.

Williams

Paul

Soutar

Geoffrey N.

(2009). “Value, Satisfaction and Behavioral Intentions in Adventure Tourism Context.” Annals of Tourism Research, 36 (3): 413-38.

94.

Wolfinbarger

Mary

Gilly

Mary C.

(2001). “Shopping Online for Freedom, Control, and Fun.” California Management Review, 43 (2): 34-55.

95.

Woodruff

Robert B.

(1997). “Customer Value: The Next Source for Competitive Advantage.” Journal of the Academy of Marketing Science, 25 (2): 139-53.

96.

Woodruff

Robert B.

Gardial

Sarah

. (1996). Know Your Customer: New Approaches to Customer Value and Satisfaction. Cambridge, MA: Blackwell.

97.

Xiang

Zheng

Gretzel

Ulrike

. (2010). “Role of Social Media in Online Travel Information Search.” Tourism Management, 31 (2): 179-88.

98.

Zeithaml

Valarie A.

(1988). “Consumer Perceptions of Price, Quality and Value: A Means-end Models and Systems of Evidence.” Journal of Marketing, 52 (3): 2-22.

99.

Zeithaml

Valarie A.

(2002). “Service Quality in E-Channels.” Managing Service Quality, 12 (3): 135-38.

100.

Zhu

Zhen

Nakata

Cheryl

Sivakumar

Grewal

Dhruv

. (2007). “Self-Service Technology Effectiveness: The Role of Design Features and Individual Traits.” Journal of the Academy of Marketing Science, 35 (4): 492-506.