The effect of website features in online relationship marketing: A case of online hotel booking

Electronic Commerce Research and Applications xxx (2014) xxx–xxx

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Electronic Commerce Research and Applications journal homepage: www.elsevier.com/locate/ecra

The effect of website features in online relationship marketing: A case of online hotel booking Anil Bilgihan a,⇑, Milos Bujisic b a b

College of Business, Florida Atlantic University, 777 Glades Road, Boca Raton, FL 33431, USA Department of Human Sciences, The Ohio State University, 1945 North High Street, Columbus, OH 43210, USA

a r t i c l e

i n f o

Article history: Received 11 February 2014 Received in revised form 26 May 2014 Accepted 8 September 2014 Available online xxxx Keywords: Relationship marketing Website features Customer loyalty E-commerce Hotel booking

a b s t r a c t The primary objective of this research is to develop a theory-based model of utilitarian and hedonic website features, customer commitment, trust, and e-loyalty in an online hotel booking context. Structural Equation Modeling was deployed to test research hypotheses. Findings highlight the importance of creating loyalty by focusing on both hedonic and utilitarian features. Affective commitment is more influenced by hedonic features whereas calculative commitment is driven by utilitarian ones. Both commitment dimensions sway customers’ trust towards the online vendor and trust is an important antecedent of e-loyalty. Findings confirm that web design features are important for online relationship marketing. Both commitment dimensions were found to be precursors of trust whereas affective commitment is the precursor of e-loyalty. Ó 2014 Elsevier B.V. All rights reserved.

1. Introduction Lately, online shopping has witnessed a remarkable leap forward (Chiu et al. 2014, Kim et al. 2006, Luo et al. 2012) with sales growing more than 19% a year (Internet Retailer 2011) and has become an important distribution channel or business model for many companies (Chiu et al. 2014). Worldwide retail online sales had already reached approximately $1 trillion by the end of 2010 (Goldman Sachs 2011). More than 60% of US online users made a purchase online in 2009 (Forrester Research 2009). The Cisco IBSG Economics and Research Practice predicts that e-commerce will reach almost $1.4 trillion in 2015 globally (Bethlahmy et al. 2011). Forrester Research estimates that online shoppers will spend $327 billion in 2016 in the US alone, up 45% from $226 billion in 2012, and 62% from $202 billion in 2011 (Forrester Research 2012). However, regardless of the rapid growth in online shopping, many customers indicate that they are unsatisfied with their online purchase experiences (Luo et al. 2012). This calls for more research to better understand the factors that affect customers’ evaluations in their online shopping behaviors (Luo et al. 2012). In a similar vein, electronic distribution of various services including hotel rooms, flights, travel packages, attraction tickets, cruises, and car rentals has been on the rise due to many advantages to both consumers and e-tailers. Over the last decade, the Internet has developed into being one of the most significant ⇑ Corresponding author. E-mail addresses: [email protected] (A. Bilgihan), [email protected] (M. Bujisic).

channels for hotel room distribution (Doolin et al. 2002, Thakran and Verma 2013). The Internet allows potential guests to gather information about hotel amenities and facilities in a utilitarian nature since they can compare prices without contacting a hotel’s sales representative or travel agent and prepare their travel itineraries while looking at a screen (Runfola et al. 2013). Because of the high acceptance of e-commerce, successfully adopting a more effective e-commerce channel has become a significant matter for hospitality businesses (Kim et al. 2006). E-commerce in hospitality and tourism has progressed in recent years from the preliminary sales of less-complex products such as airline tickets, accommodations and car rentals, to embrace more complex products including vacation packages and cruises (Beldona 2005; Inversini and Masiero 2014, Nusair and Parsa 2011). However, during this evolution, it is usually claimed that online travel portals have fallen behind when creating a pleasant online environment for customers (Hassan 2013). We hypothesize that developing compelling and useful online shopping portals would help e-commerce companies build and maintain relationships with their customers. We further hypothesize that customer commitment in online environments will be established via website features. It is important to understand consumer behavior in online environments and develop strategies to increase customer loyalty towards the website. From a theoretical perspective, it is important to develop a model that explains the antecedents of relationship marketing in e-commerce. Even though hotel reservations constitute the second most frequently purchased travel product online

http://dx.doi.org/10.1016/j.elerap.2014.09.001 1567-4223/Ó 2014 Elsevier B.V. All rights reserved.

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

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A. Bilgihan, M. Bujisic / Electronic Commerce Research and Applications xxx (2014) xxx–xxx

(Card et al. 2003); limited research has investigated the factors that influence loyalty in an e-travel context. The primary objective of this study is to develop a theory-based model of utilitarian and hedonic website features, customer commitment, trust, and e-loyalty. This model investigates the relationship between website features and loyalty, as well as the relationship between various components of customer commitment, online trust and customer loyalty. 2. Literature review 2.1. Website features As a contemporary marketing channel, the Internet differs from traditional commerce structures in various ways requiring further explanation. A unique characteristic of online shopping suggests that customers have to base their judgments on service/product information presented (e.g. room pictures, virtual tours, product information, customer reviews) on the websites. Specifically, consumer purchasing decisions are usually based on the appearance and website design elements including pictures, virtual tours, graphics, quality information, and video clips of the product (e.g., Chiu et al. 2014, Hong et al. 2004, Kolesar and Galbraith 2000). This is especially important for online hotel room reservations due to the characteristics of service products (e.g. reducing the perceived risk of intangible product prior to purchase). Consequently, the promise of e-commerce and online hotel room reservation is determined by, preeminently, user interfaces and how people interact with computers and websites (Griffith et al. 2001, Hong et al. 2004). Better website designs and easier navigations nurture shopping enjoyment (Floh and Madlberger 2013). Recently, the social aspect of e-commerce design has also emerged as an important concept (Huang and Benyoucef 2013) which highlights the importance of Web 2.0 tools and online communities. Previous research identified that the positive outcomes a customer seeks from using the Web can be categorized as: (a) hedonic shopping orientations obtained when the Web is used for the enjoyment of the online experience itself (e.g. taking the virtual tour of the hotel room, looking at the pictures of the amenities offered by the hotel); and (b) utilitarian shopping orientations resulting from achieving a particular goal including the purchase of an item (e.g. comparing the prices, looking at the location of the property) (Fischer and Arnold 1990, O’Brien 2010). The online hedonic orientations are grounded on enjoyment, pleasure, fun and amusement via Web interaction, whereas utilitarian shopping orientations are related to achieving a particular goal (Babin et al. 1994, Holbrook and Hirschman 1982, O’Brien 2010). Consequently, a customer’s attitude about the product/service offered by the company is shaped by the degree to which an online hotel booking website fulfills the utilitarian or hedonic requirements of the customer. Based on a literature review of the online shopping behaviors, it is suggested that a website should be designed based on hedonic and utilitarian aspects (Poyry et al. 2012). Previous research (e.g. Childers et al. 2001, Ha and Stoel 2009; Mahfouz et al. 2008; Shen and Khalifa 2008) classified the features of e-commerce websites as explicitly utilitarian or hedonic. Utilitarian features of the website are imperative for e-retailers. These features were outlined as physical presence (Rafaeli and Noy 2005), utilitarian facet (Ha and Stoel 2009), or shopping as problem solving (Childers et al. 2001). Those features are aligned with utilization strategies (Fan and Poole 2006) suggesting an approach to focus on designing, enabling, and enhancing valuable, functional, and user-friendly tools. Characteristics of the utilitarian features include accessibility, ability to effectively search for information, and the provision of comprehensive product and service information. For users seeking utilitarian features, web designers need to

be aware of the availability of information and intuitive design interfaces that facilitate the use of the site for information searches (Wolfinbarger and Gilly 2003). Herrero and San Martín (2012) investigated the adoption of tourism accommodation websites and found that the intention to use such websites is determined by the usefulness and ease of use of websites as perceived by visitors. Their results indicate that adequacy of information positively influences the website’s perceived usefulness, whereas the interactivity and navigability have a positive effect on their perceived ease of use. In the context of online hotel booking, the focus should be on effective and reliable search systems, easy navigation, and orderly presentation of complete and consistent information. Such characteristics in the online hotel booking context include location, attractions nearby, restaurants, amenities, and prices. On the other hand, hedonic features focus on fun, fantasydriven, and arousal-laden shopping (Childers et al. 2001; Suki 2010). The hedonic features represent the interactive and social aspect of an e-commerce website (Chiu et al. 2014, Ha and Stoel 2009). Hedonic features are strongly connected to leisure activities with a focus on the fun-based aspects of using information systems, encouraging prolonged rather than the productive use (Van der Heijden 2004). The value of a hedonic website feature is a function of the degree to which the user experiences fun when using the website. Therefore, developers employ tactics that are classified as the inclusion of hedonic content: animated images and a focus on colors, sounds, social components and esthetically appealing visual layouts. Accordingly, hotel companies should be mindful of the social richness (Lombard and Ditton 1997), and create opportunities for the consumer to be an actor in the virtual environment. Enabling the multi-way communication between different social avatars can shape the social online experience (Mahfouz et al. 2008). Hedonic features also include strategies such as ‘‘gamification’’, a trending topic that supports user engagement and enhancing positive patterns in service use by providing ‘‘gameful’’ experiences (Hamari et al. 2014). Such strategies motivate behavioral outcomes. 2.2. Customer commitment Customer commitment is considered as a key element in longterm relationships (Dwyer et al. 1987, Morgan and Hunt 1994a). Moorman et al. (1993) have defined commitment as ‘‘an enduring desire to maintain a valued relationship’’ (p. 316). Several studies have recognized a multidimensional nature of commitment (Allen and Meyer 1990, Bansal et al. 2004, Pritchard et al. 1999). The first dimension is emotional and the second one is cognitive or economic. These two dimensions are often recognized in literature as affective commitment and calculative commitment (Evanschitzky et al. 2006). Affective commitment has received significant attention in marketing literature (Gundlach et al. 1995, Kumar et al. 1995a,b, Morgan and Hunt 1994b). The definition of affective commitment in marketing is very similar to the one used in organizational behavior studies (O’Reilly and Chatman 1986, Allen and Meyer 1990). Allen and Meyer’s (1990) affective commitment scale was used to create a relationship commitment instrument in Morgan and Hunt’s (1994) study. Fullerton (2005a) concluded that affective commitment helps create a marketing relationship. Further, relationships that are built on affective commitment are more stable because customers tend to have a positive rapport with the organization they identify themselves with. Calculative commitment is defined as the intent to continue the relationship, considering switching costs and lack of alternatives (Bendapudi and Berry 1997). This type of commitment is different from affective commitment because it is based on cost oriented calculations and not a true emotional relationship. The customer does not have to have a true desire to develop a long-term relationship

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

A. Bilgihan, M. Bujisic / Electronic Commerce Research and Applications xxx (2014) xxx–xxx

but might feel that it is more convenient or more cost effective to do so, compared to switching to more expensive alternatives (Allen and Meyer 1990). Therefore, the nature of calculative commitment is tied to the quality and availability of alternatives. 2.3. E-loyalty The notion of e-loyalty extends traditional brand loyalty to the technology-mediated online consumer experience (Corstjens and Lal 2000; Reichheld and Schefter 2000; Schultz and Bailey 2000). The term e-loyalty is specified as the ‘‘intention to revisit a website’’ (Corstjens and Lal 2000; Gommans et al. 2001). However, loyal behavior may also be tied to repurchasing from an online vendor (Srinivasan et al. 2002). This study defines e-loyalty as the perceived loyalty towards a hotel booking website (e.g. www.hilton.com) with the intent to either revisit the site or make a reservation from it in the future. Creating loyal customers is vital to firm’s strategy and survival (Taylor and Baker 1994), and has the capability to increase revenues and profitability (Aaker 1996; Heskett 2002; Srinivisan et al. 2002). E-loyalty is derived from the ease of ordering, product information and selection, on-time delivery, customer confidence, adequate privacy policies, online resources, and e-commerce quality (Wolfinbarger and Gilly 2000). Luarn and Lin (2003) highlighted that ‘‘understanding how or why a sense of loyalty develops in customers remains one of the crucial management issues of our day’’ (p. 156). E-loyalty was shown to be related to brand loyalty (Grommans et al. 2001). Uncles et al. (2003) recognized three different conceptualizations of brand loyalty. The first one is based on the willingness to develop a relationship with a company. The second one is based on the customer’s purchasing behavior. The final one is based on the number of moderators of purchasing behavior, such as purchasing situation and individual differences and characteristics. Oliver’s (1997) a four-stage loyalty model is deeply connected with pervious frameworks. He recognized that different types of loyalty occur over time in a consistent sequence and inferred that the four main types of loyalty are: cognitive loyalty, affective loyalty, conative loyalty and action loyalty (Oliver 1999). This model extends the ‘‘cognitive-affective- conative’’ sequence with the introduction of observable purchasing behavior. Grommans et al. (2001) argued that the e-loyalty concept extends directly from the brand’s loyalty concept. Specifically, eloyalty exists is an online consumer behavior that is an online representation of the brand loyalty. Even though theoretical concepts for both e-loyalty and brand loyalty are the same, e-loyalty has several unique characteristics (Grommans et al. 2001). Value propositions, brand building, trust and security, website and technology and customer service have been shown to be the main drivers of e-loyalty (Grommans et al. 2001; Schultz 2000). Literature considers the measurement of customer loyalty in two dimensions (e.g., Kandampully and Suhartanto 2003). The behavioral dimension focuses on a customer’s actual loyalty behaviors, such as repeat purchases from the same brand and providing positive WOM (Word of Mouth). On the other hand, the attitudinal dimension describes the consumers’ intention to engage in such loyalty behaviors. Even though these two dimensions fail to capture all four developmental stages of customer loyalty that Oliver (1999) contends, researchers and practitioners utilize them because they still tend to capture the most important aspect of loyalty from a company’s perspective. 2.4. Model of the website features and loyalty in hotel context This study proposes a model of online customer relationship and integrates an understanding of the commitment dimensions. Given the importance of two distinct website features, this study

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examines whether website features impact the commitment to a website. As shown in Fig. 1, hedonic and utilitarian website features are hypothesized to be first order independent variables. Since hedonic features are related to the fun, amusement, and pleasure, and affective commitment is related to the emotional attachment, a strong positive relationship between hedonic website features and affective commitment is expected. 2.5. Hypothesis development As presented in Fig. 1, this study proposes a model to understand why online customers commit to an e-tailer (specifically to the hotel booking website) by an integrated model that includes shopping value feature dimensions (hedonic and utilitarian), commitment dimensions (affective and calculative), trust and loyalty. Previous research shows that quality attributes have a positive effect on customer satisfaction (Cole and Scott 2004, Hung and Hsu 2013, Orel and Kara 2014). Several studies have examined the effect of satisfaction on commitment (Fullerton 2005b, Evanschitzky et al. 2006, Yi et al. 2011). Fullerton 2005a,b argued that quality and satisfaction have a positive effect on affective and calculative commitment. On the other hand, Evanschitzky et al. (2006) have shown the positive effect of different performance features on affective commitment, while calculative commitment was influenced by the scarcity of alternatives and availability of options. Similarly, Garnier (2009) shows that hedonic and utilitarian search engine website features have a positive effect on affective commitment. Based on the previous research it is expected that hedonic and utilitarian website features in the hospitality e-commerce environment have a positive effect on both affective and calculative commitment. Hedonic features evoke fun and fantasy, and influence affective commitment (Babin et al. 2005). Value and the affective emotions of consumers are important in generating long-term relationships in an online context (Kim et al. 2008). Specifically, the hedonic shopping value generates long-lasting relationships in services (Carpenter 2008, Chiu et al. 2005). Emotional pleasure is determined by the hedonic value of the service (Fiore, Jin, and Kim 2005), leading towards the intention to engage in e-shopping (Chiu et al. 2014, To et al. 2007). In addition, experiential needs motivate consumers to engage in online shopping (Ha and Stoel 2009). The hedonic shopping value has been found to be important for loyal customers, and helps in building close emotional links with target customers (Butz and Goodstein 1996). Therefore, the following hypothesis is posited. H1. Hedonic website features have a positive effect on affective commitment. Value dimensions have positive influences on commitment (Pura 2005) and value added services generate high customer commitment (Paguio and Ali 2011). Value influences relationship commitment (Wahab 2011). In the e-commerce environment, the competition is intense. There are almost an infinite number of options and available alternatives that are only one click away. Therefore websites rely on their own unique features to develop calculative commitment (Bridges and Florsheim 2008). We extend the previous research to assume that calculative commitment can be influenced by the experiential needs of consumers (hedonic values) and therefore lead to the below hypothesis. H2. Hedonic website features have a positive effect on calculative commitment. Previous research found that the utilitarian value of service offerings increases positive consumer emotions (Babin et al.

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

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A. Bilgihan, M. Bujisic / Electronic Commerce Research and Applications xxx (2014) xxx–xxx

Fig. 1. Model of online shopping commitment.

2005) and consumer engagement is motivated by fulfilling utilitarian needs (Childers et al. 2001). Utilitarian values, namely flexibility, increases commitment (Eaton 2003) and ease of use increases participation (Sinclair et al. 2005). Also, usability of the e-service increases commitment (Casaló et al. 2007). Perceived ease of use and usefulness (Gefen and Straub 2000) determine IT adoption. Ease of use of e-service has a positive influence adoption likelihood (Featherman et al. 2010). Customers’ repurchase intention is increased by the perceived usability of the website (Zhang et al. 2011). In order to be successful, e-commerce websites must be perceived as useful, easy to use, easy to understand and easy to navigate (Smith 2008). Since the utilitarian shopping value has a positive influence on consumers’ experiential needs, we hypothesize that:

affective commitment is reflected in customer trust and behavioral intention (Dick and Basu 1994; Fullerton 2003). Since previous research supports that consumer values (hedonic and utilitarian) influence affective commitment, it is a considerate interest to also look into the influence of affective commitment on long-term relationships between the e-users and hotel website. It was found previously that affective commitment has a positive influence on usage behaviors (Malhotra and Galletta 2005) and it also enhances long term relationship for e-travel vendors (Nusair 2010). Trust is believed to be the key to these relationships (Corbitt et al. 2003). Customers’ trust levels in online shopping are likely to be influenced by the website quality and users’ web experience (Corbitt et al. 2003). Therefore, led to the formation of the below hypothesis.

H3. Utilitarian website features have a positive effect on affective commitment.

H5. Affective commitment has a positive effect on trust in online hotel booking.

Previous studies have examined various influences on affective and calculative commitment (Van Goolen and Campo 2008), such as the relationship between switching costs and calculative commitment (Yanamandram and White 2010). Nusair et al. (2013) recently identified the positive effect of perceived utility of a website on calculative commitment. Calculative commitment in the online shopping context is seen in a site’s ease-of-use, transaction speed, and convenience of 24-h access (Johnson 2007). As a result of utilitarian website features, customers should be more likely to stay in the relationship because of the benefits gained from the website. Based on previous findings stating that consumers’ perception of the utilitarian value of service can influence calculative commitment, the following hypothesis is posited.

Few studies have empirically tested the relationship between customer commitment and customer loyalty (Sivadas and BakerPrewitt 2000), and there is no consensus relative to the relationships between quality, commitment and customer loyalty. Cole and Chancellor (2009) claim that the relationship between quality and customer loyalty is mediated by experience quality and reported that the entertainment attribute of quality has a direct impact on customer loyalty. It has been shown that a customer’s affective commitment positively influences affective loyalty and enjoyment (Ha and Perks 2005, Homburg et al. 2006, Janda and Ybarra 2005, Jin et al. 2008, Khalifa and Liu 2007, Kim et al. 2008, Ranaweera et al. 2008, So et al. 2005. Brand loyalty is also increased when customers show high affective commitment (Mattila 2006, Cˇater et al. 2011). Therefore, the following hypothesis is proposed:

H4. Utilitarian website features have a positive effect on calculative commitment. Fullerton (2003) described affective commitment as a psychological motivation to be in a long-term relationship. This relationship develops identifications and attachment to a company (Fournier 1998). Affective commitment has a direct effect on trust and loyalty (Harrison-Walker 2001). Customers that identify themselves with a company or a brand tend to express positive feelings about the company. The emotional attachment created by the

H6. Affective commitment has a positive effect on loyalty to the hotel booking website. Calculative commitment is defined as the intention to stay in a relationship because of the scarcity of alternatives and high switching costs. After a certain time, customers tend to develop an emotional attachment with the website (Dowling and Uncles 1997). Customers tend to stay in such relationship because they

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

A. Bilgihan, M. Bujisic / Electronic Commerce Research and Applications xxx (2014) xxx–xxx

do not wish to look for alternatives or believe that they would not be able to find any adequate ones. Burnham et al. (2003) argued that the high perceived costs of switching is the main reason why customers tend to stay in otherwise undesirable relationships. The development of calculative commitment has a strong effect both on trust and loyalty. The development of a relationship and attachment to the establishment tends to have a positive effect on trust (Dowling and Uncles 1997). In addition, loyalty is affected positively because customers with lack of alternatives tend to return to the same website. In order to keep customers with the company, it is important to develop a company website that will make consumers think that there is more to gain than to lose through the particular online-transaction. Thus the following hypotheses are posited: H7. Calculative commitment has a positive effect on trust in online hotel booking.

H8. Calculative commitment has a positive effect on loyalty to the hotel booking website. Trust in a company can play a significant role in determining a customer’s actions regarding the company’s website. Trust is the customer’s beliefs in the company’s benevolence, integrity, and capability. According to the theory of planned behavior, beliefs are significant predictors of intentions and subsequent actions. Therefore, customers’ beliefs regarding the trustworthiness of a company should affect their intentions to use the company’s website. Empirical research has shown that trust increases customer intentions to purchase a service or product from a company on the Internet (Jarvenpaa et al. 1999, Lynch et al. 2001). Perception of trustworthiness can increase a customer’s intention to return to a company both offline and online (Diamantopoulos and Winklhofer 2001, Fukuyama 1996, Gefen 2002, Lynch et al. 2001). It is hypothesized that customers who trust a company are more likely to use the company website, whether for a repeat visit to the site or to make an actual purchase. The more a consumer trusts a service provider, the more likely he or she will continue the relationship (de Ruyter et al. 2001). Cyr (2008) found website trust is strongly related to loyalty. Consumers with a higher level of trust in e-commerce are more likely to participate in it (Corbitt et al. 2003). Kim et al. (2009) reported that online customer trust is strongly related to loyalty. Therefore: H9. Trust has a positive effect on loyalty to the hotel booking website.

3. Methodology A descriptive cross-sectional survey was created using the online questionnaire service, Qualtrics. This survey included four sections. The first question was the screening question and asked whether the respondent had booked a hotel room online in the past three months. If they answered this question as ‘‘No’’, the survey navigated the respondent to the demographic questions. The second section included questions related to the respondents’ Internet shopping behaviors, such as how often they shop online, which type of products they purchase and how much they typically spend. The third section included the questions that measure the study constructs. In this section of the survey, the study participants were asked to rate their level of agreement with the statements regarding their last online hotel booking experience using a seven point Likert scale response format (see Appendix 1 for the variables that are adopted in this study). In order to ensure construct validity, all of the latent variables were measured using multiple-item scales

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adopted from previous research studies making only minor changes of wording to tailor them to the e-commerce context. Finally, the last section consisted of demographic questions. A random sample of 5000 American consumers was selected from a national database using a marketing company. A total of 549 responses were received with a 10.9% response rate. The data was imported to SPSS to detect outliers and missing variables and it was found that 186 of the respondents did not book a hotel room online in the past three months, thus failed to satisfy the screening question. Further, 29 of the respondents were eliminated from the data analysis because of missing data. This yielded a net sample of 334. Of the respondents, 45 percent were male and 24 percent were between ages of 35 and 44. In terms of yearly annual household income, 32 percent of the respondents stated that they have an income of $100–150 k (see Appendix 2 for participants’ demographic information). The sample demographic pulsation is similar to the e-buyers population demographic information reported in Hernández et al. (2011) and Wang et al. (2011), therefore indicating the validity of the study participants. 4. Results 4.1. Confirmatory factor analysis (CFA) The data was analyzed using Structural Equation Modeling (SEM) in Amos 20. This statistical technique empowers researchers to simultaneously test a set of interrelated hypotheses by estimating the relationships among multiple endogenous and exogenous variables in a theoretical model (Gefen and Straub 2000). Following the procedures of the two-step approach (Anderson and Gerbing 1988) and to achieve strong validity and reliability, a confirmatory factor analysis (CFA) was deployed. The initial step included a deployment of exploratory factor analysis (EFA) to test for unidimensionality. During this process, it is recommended that items clearly load on a single and appropriate factor. If an item fails to have a substantially high loading on any factor, it could be removed from the analysis and the EFA is computed on the remaining subset (Floyd and Widaman 1995). Until a clear factor structure emerges, inappropriately loading items can be deleted and the analysis repeated (Hinkin 1998). At this stage, two of the loyalty measurement items (LOY1 and LOY2) were dropped after EFA due to cross loadings with affective commitment factor. The final measurement model indicated a good level of fit: v2(174) = 136,229, the goodness-of-fit indices: GFI = 0.91 RMSEA = 0.042, CFI = 0.95, and NFI = 0.95. Table 1 shows the reliabilities of all constructs were above the threshold value of 0.7 (Chen and Hitt 2002) supporting the reliability of the measure. Additionally, all composite reliabilities were greater than 0.80 and all average variance extracted (AVE) estimates were greater than 0.50 ensuring that, on average, the measures share at least half of their variation with the latent variable (Fornell and Larcker 1981) (see Table 1). All standardized factor loadings for the items were also found to be significant (p < .01), in support of convergent validity (Anderson and Gerbing 1988). The AVE criterion was met for each of the latent variables, which supports the reliability of the measures. The AVE exceeded the square of correlations between constructs, confirming discriminant validity (Hair et al. 2010). This suggests that the hypothesized measurement model fits the data reasonably well, and the posited dimensions and facets showed acceptable reliability, convergent and discriminant validity. 4.2. The proposed model and hypotheses testing After the confirmation of the unidimensionality of each construct, the structural model was deployed to test the hypotheses.

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

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A. Bilgihan, M. Bujisic / Electronic Commerce Research and Applications xxx (2014) xxx–xxx Table 1 Item loadings, construct reliability and average variance extracted. Variable

Coefficient a

Standardized loadings

Construct reliability (CR)

Variance extracted (AVE)

HED1 HED2 HED3 HED4

0.81

0.78 0.83 0.69 0.72

0.96

0.82

UTIL1 UTIL2 UTIL3 UTIL4

0.91

0.76 0.82 0.76 0.84

0.88

0.73

ACO1 ACO2 ACO3

0.83

0.78 0.87 0.79

0.95

0.75

CCO1 CCO2 CCO3

0.85

0.82 0.93 0.79

0.89

0.75

TRU1 TRU2 TRU3

0.82

0.81 0.78 0.75

0.88

0.74

LOY3 LOY4 LOY5 LOY6

0.81

0.71 0.84 0.74 0.67

0.78

0.62

LOY1 and LOY2 were dropped after EFA due to cross loadings with affective commitment.

The goodness-of-fit measures were used to assess the model fit. The overall fit indices for the proposed model were acceptable, with v2/df = 1.43, RMSEA of 0.033, NFI of 0.95, CFI of 0.96, and GFI of 0.92. All the above fit indices for the final model indicated an acceptable structural model fit. Additionally, the explained variances (R2) were 32% for calculative commitment, 46% for affective commitment, 52% for trust, and 67% for loyalty. Nine hypothesized paths were tested for significance in the current research. The results of the study, as shown in Table 2 and Fig. 2, indicate that eight of the paths were significant in the structural model. Two of the paths were significant at p < .001, six paths were significant at p < .01, and one path was not significant. Hypothesis 1, stating hedonic website features have a positive effect on affective commitment, was supported. The results revealed a path coefficient between the two constructs of .81, which was positively significant at p < .001. Hypothesis 2 stated that hedonic website features have a positive effect on calculative commitment. This hypothesis was supported with a path coefficient between the two constructs of .51 (p < .01). Hypothesis 3 stated that utilitarian website features have a positive effect on affective commitment, and was supported. The results revealed a path coefficient between the two constructs of .42, which was positively significant at p < .01. Hypothesis 4 stated that utilitarian website features have a positive effect on calculative commitment. This hypothesis was supported with a path coefficient between the two constructs of .88 (p < .001).

Hypotheses 5 and 6, stating that affective commitment has a positive effect on trust and loyalty, were supported with a path coefficient of 0.38 (p < .01) and 0.79 (p < .01) respectively. Hypothesis 7 stated that calculative commitment has a positive effect on trust in online hotel booking. This hypothesis was supported with a path coefficient between the two constructs of .21 (p < .01). However, hypothesis 8, which stated that calculative commitment has a positive effect on loyalty to the hotel booking website, was not supported. The path coefficient between the two constructs was .09 which was not significant with (p > .05). Finally, hypothesis 9 was supported. A path coefficient between trust and loyalty was positive and statistically significant (st.coef = .69; p < .01).

5. Discussion and conclusions The primary objective of this study was to develop a theorybased model of utilitarian and hedonic website features, customer commitment trust and e-loyalty. Leaning on relationship marketing and customer value theories, we explained how to build long lasting relationships with customers in e-commerce contexts. Earlier research highlights the utilitarian nature of online shopping, suggesting customers are seeking for utilitarian benefits in e-commerce. However, our findings suggest that utilitarian natures are necessary, but not sufficient condition for building customer

Table 2 Test of path coefficients significance.

* **

Hypotheses

Standardized path coefficients

t

Support

H1: H2: H3: H4: H5: H6: H7: H8: H9:

0.81* 0.51** 0.42** 0.88* 0.38* 0.79* 0.21* 0.09 ns 0.69*

8.71 6.12 5.24 9.16 4.01 7.16 2.20 1.89 7.90

Yes Yes Yes Yes Yes Yes Yes No Yes

Hedonic ? Affective commitment Hedonic ? Calculative commitment Utilitarian ? Affective commitment Utilitarian ? Calculative commitment Affective commitment ? Trust Affective commitment ? Loyalty Calculative commitment ? Trust Calculative commitment ? Loyalty Trust ? Loyalty

p < .001. p < .01.

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

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Fig. 2. Structural model with path coefficients and explained variances of dependent variables. ⁄p < .001.

commitment in online environments. Our findings further highlight the importance of creating loyalty by focusing on both hedonic and utilitarian features. As our results show, affective commitment is influenced more by hedonic features. On the other hand, calculative commitment is driven by utilitarian ones. Both commitment dimensions influence customers’ trust towards the online vendor. We confirm that trust and affective commitment are the precursors of customer eloyalty. This relationship can similarly be explained through brand loyalty. Specifically, trust and affective commitment were shown to have a positive effect on brand loyalty (Sirdeshmukh et al. 2002), and brand loyalty was shown to be highly correlated with e-loyalty (Grommans et al. 2001). The notion of customer value considers what customers want and believe they get from buying a product (Woodruff 1997) from an online vendor. Online shopping produces both hedonic and utilitarian outcomes (Babin et al. 1994). As Babin et al. (1994) acknowledged two decades ago, ‘‘the consumer is portrayed, in a shopping context, as both intellectual and emotional’’ (p. 653). This approach recognizes that not all consumer behavior is directed toward satisfying some functional needs. This is especially important during the dreaming stage of decision making. Customers may visit the hotel booking website and be immersed in the pictures and virtual tours, and at a later stage decide to purchase. Hedonic consumption experiences are important in e-commerce in addition to rational choices. The total value of online shopping experience includes both the hedonic and utilitarian beliefs and perceptions of a product. Thus, website features that encompass both dimensions are likely to perform better. We hypothesized that website features will create customer loyalty by the mediating roles of customer commitment. It was found that hedonic and utilitarian features are important variables influencing future consumer decisions through relationship marketing. Hedonic features transfer to later consumption experiences by triggering affective commitment, whereas utilitarian features found to have a strong effect on calculative commitment. The hedonic aspect of web performance is the evaluation of a website based on the assessment by users regarding the amount of fun, playfulness, and the pleasure they experience or anticipate from the website. These hedonic features had significant effects on both calculative and affective commitment. The findings of this

⁄⁄

p < .01.

study suggest that hotel booking websites could create positive shopping experiences and commitments if they focus on hedonic features such as virtual tours and innovative website designs. Similar to the way a hotel employee might provide a good impression to guests, a well-designed hotel website can provide good impressions about the property to online customers before guests actually experience or stay at the property (Bilgihan et al. 2013). E-commerce websites that incorporate games, enable co-creation possibilities, build online communities, and create a pleasing online experience are likely to succeed. Utilitarian features are the goal-directed website design features. These features represent an assessment of a website based on the evaluation by users regarding the instrumental benefits they obtain from its’ non-sensory attributes. They are related to the performance perception of usefulness, value, and wisdom (Batra and Ahtola 1991). These features call users to visit a website out of necessity instead of recreation needs; consequently, this characteristic of performance is evaluated according to whether the particular purpose is accomplished (Davis et al. 1992; Venkatesh 2000). However, it was found that utilitarian features had a significant positive effect on both affective and calculative commitment. Reliable, effective, functional, practical, ordered, necessary, wise, and correct features are needed to create customer commitment in online shopping. Our findings support that consumer rationalism is an important precursor of future intentions by the mediating role of calculative commitment. Affective commitment helps create marketing relationships, which are more stable because customers tend to have a positive rapport with the organization they identify themselves with. Affective commitment was also found to be positively related to both trust and loyalty. Results from marketing literature indicated that affective commitment is positively related to involvement, loyalty and attachment (Gundlach et al. 1995). Calculative commitment is defined as the intent to continue the relationship, considering switching costs and a lack of alternatives (Bendapudi and Berry 1997). The findings of this study indicate that calculative commitment is positively related to trust but not to loyalty. One of the explanations for this result could be that trust mediates the relationship between calculative commitment and loyalty. This finding is even more probable considering that trust had a significant positive effect on loyalty.

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

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5.1. Theoretical and practical implications The results of this study provide several important theoretical and practical implications. In the first place, a comprehensive theoretical model of relationship between website features, commitment and loyalty is developed. This model indicates that e-commerce and online booking websites should focus on both hedonic and utilitarian features in order to increase customer loyalty. In practical terms, this means that the interactive and social aspects of an e-commerce website presenting hedonic features should be improved. For instance, Marriott’s Travel Brilliantly (https://travel-brilliantly.marriott.com) challenges their customers to help ‘‘shape the future of travel’’ by asking them to share their groundbreaking ideas about how to improve the modern travel experience. Members of such platforms receive both hedonic and utilitarian benefits from interacting with like-minded customers and gaining mutual assistance. In online environments, social relationships create a sense of community. Additionally, websites should work on their functionality, practical design and user friendliness. This, in turn, should improve customer loyalty and develop trust with online hotel booking websites.

which influenced the validity of participants’ responses. Although it was assumed that the respondents completed the survey objectively, the reliability could have been affected by respondents’ beliefs, attitudes, reward drive and desire to provide honest answers. In general, feedback from participating respondents did not mention that this was a concern. The instruments used in the survey could potentially be a limiting factor. These instruments were tested for validity and reliability. Nevertheless, additional follow-up studies could further improve those. Finally, the main study sample was obtained from a US-based marketing company. Therefore, findings cannot be generalized beyond that target population. Appendix 1. Measurements used in the study

Construct

Questionnaire Items

Hedonic Features (adopted from Kim and LaRose 2004, self-created)

HED1. This online booking experience was truly a joy HED2. Compared to other things I could have done, the time spent booking was truly enjoyable HED3. I felt the excitement of hunt HED4. I like email alerts of special offers from this booking website UTIL1. I use this website’s search engine for finding the room I want UTIL2. I use this website for product price information UTIL3. I feel really smart about this booking experience UTIL4. I read the reviews written by other travelers ACO1. I enjoy discussing the good aspects of this website with other people ACO2. It is easy to become attached to this website ACO3. This website has a great deal of attraction for me CCO1. I am afraid something will be lost if I stop using this website CCO2. To stop using this website would require considerable personal sacrifice CCO3. Some aspects of my life would be affected if I stop using this website now TRU1. This website can be trusted at all times TRU2. This website can be counted on to do what is right TRU3. This website has high integrity LOY1. I seldom consider switching to another hotel booking website

5.2. Future studies and limitations The study findings should provide valuable guidelines for future research stream in hospitality e-commerce. Future studies are advised to test the model in different situations (e.g. leisure travelers vs. business travelers) as different motivations may have a strong effect on the shopping experience. It is recommended for future studies to reexamine the model and collect data during the online booking. Participants would not have to recall their last booking experience but simply evaluate the present one, improving the overall validity of the results. Future studies should also test true causality using an experimental design. The present study was not directly testing causality since it was based on survey design and SEM analysis. This type of analysis only assumes causality based on theoretical support without being able to examine it directly. All of the significant relationships that were detected in the present study could be further tested for causality using scenario based experimental design in which different websites with different hedonic and utilitarian features would be created. This would help researchers recognize specific website features that have the strongest positive effect on customer e-loyalty and overall satisfaction with the website and booking experience. Additionally, results from this study could be used to develop similar models in other e-commerce settings since it is expected that hedonic and utilitarian website features have a similar effect on customer behavior regardless of the e-commerce setting. Finally, future studies should focus on the analysis of different variables that moderate the relationship between website features and customer behavior. Customer characteristics such as demographics and personality traits could act as moderators. This study had several limitations. The main limitation of the study was that the survey was conducted in an online environment and therefore asked participants to revoke memories about their last hotel booking experience. Unless the experience left a truly strong impression on participants, they would not be able to express their opinion regarding specific details that were asked in the survey. This could also create a potential non response bias. A number of potential participants would not qualify to complete the survey if they had not booked a hotel online in the previous three months. Additionally, the questionnaire length and the time needed to complete the survey might have caused questionnaire fatigue,

Utilitarian Features (adopted from Kim and LaRose 2004, self-created)

Affective Commitment (adapted from Allen and Meyer 1990)

Calculative Commitment (adapted from Allen and Meyer 1990)

Trust (adopted from Morgan and Hunt 1994)

e-loyalty (adopted from Chang and Chen 2009; Li et al. 2006)

Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001

A. Bilgihan, M. Bujisic / Electronic Commerce Research and Applications xxx (2014) xxx–xxx

Measurements used in the study (continued) Construct

Questionnaire Items LOY2. As long as the present service continues, I doubt that I would switch my hotel booking website LOY3. I try to use this website whenever I need to book a hotel room LOY4. When I need to book a hotel room, this website is my first choice LOY5. To me this website is the best booking website to do business with LOY6. I believe that this is my favorite booking website

Appendix 2. Demographic information

Gender Male Female

45% 55%

150 184

Age Under 21 21–24 25–34 35–44 45–54 55–64 Above 65

8% 9% 19% 24% 21% 13% 6%

26 30 64 80 70 43 20

Household income $0–50 k $50–100 k $100–150 k $150 k+

11% 21% 32% 36%

37 70 107 120

Education No College College Grad School

38% 43% 19%

127 144 64

Ethnicity Caucasian African American Asian Hispanic Other

81% 7% 3% 8% 1%

271 23 10 27 3

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Please cite this article in press as: Bilgihan, A., Bujisic, M. The effect of website features in online relationship marketing: A case of online hotel booking. Electron. Comm. Res. Appl. (2014), http://dx.doi.org/10.1016/j.elerap.2014.09.001