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Previous studies in customer experience focused on different relationship, such as B2C and B2B relationships (Mascarenhas et al., 2006, Grewal et al., 2009, Abbasi et al., 2011). Those studies examined customer experience in the offline context. Mascarenhas et al. (2006) examined total customers experience conceptually and its relation to lasting customer loyalty.

As stated above, they argued that customer experience in the last decade became an important asset for companies looking to provide competitive advantage and be different from others in the market. Grewal et al. (2009) developed a conceptual model to examine how macro factors

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in the retail environment, such as psychographic variables, low price products and compensation offerings, can shape customer experiences and behaviour. They proposed that customers’ experience will be affected by firm controlled factors, such as promotion, price, merchandise, supply chain and location, and macro factors as stated above. Meanwhile, Abbasi et al. (2011) extended the Technology Acceptance Model and examined empirically the model in the context of higher education in Pakistan. They investigated how the relationship between perceived usefulness and behavioural intention; perceived usefulness and behavioural usage; perceived ease of use and behavioural intention; and subjective norm and behavioural intention are moderated by experience. Abbasi et al. (2011) found that only the relationships between perceived usefulness and behavioural usage, and perceived ease of use and perceived usefulness were moderated by individuals experience.

In the online marketing context, customer experience was examined (Gefen et al., 2003a, Boyer and Hult, 2006, Puccinelli et al., 2009, Hong and Sternthal, 2010, Sun et al., 2010).

Gefen et al. (2003a) developed and examined a model in order to compare the relative importance of customers trust towards e-vender (amazon.com) to TAM constructs (perceived ease of use and usefulness), between new (potential) customers and experienced (repeat) ones. They found that potential customers’ behavioural intention was significantly influenced by trust perception and familiarity with the website but not by perceived usefulness, while it was affected significantly by perceived usefulness, trust and familiarity in the case of experienced customers. They also found that potential and repeat customers’ trust perception was impacted by familiarity and their disposition to trust. In the B2C relationship, Boyer and Hult (2006) proposed a model which was examined empirically across US, the UK and Canada to determine customer experience in the growing market for groceries and foodstuffs ordered via the Internet and telephone delivery picking methods. They found that customers experience had significant influence on behaviour intention for repeat and new customers.

Puccinelli et al. (2009) developed a consumer decision process and investigated conceptually how customer experience can be managed. They argued that when marketers understand how customers make their decision towards a particular service or product, customers’ experience can be successfully managed. They stated that customers’ decisions went through five stages:

need recognition, information search, evaluation, purchase and post-purchase. At each of these stages, customers decision will be influenced by their goals, schema and information processing, memory, involvement, attitudes, affect, atmospherics attributions and choices. In the USA market, Hong and Sternthal (2010) examined under which conditions consumers’

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prior knowledge influence the subjective experience that arose from their judgment and decision-making process. They found that customers’ experience changes when prior knowledge was either limited or extensive. Product evaluation and information processing and style changed across customers with limited or extensive prior knowledge. Sun et al.

(2010) developed a theoretical model to examine how perceived ease of use in prior e-commerce experiences affected by the motivational factors (general self-efficacy, technological innovativeness and consumer self-determination and found all the proposed relationships were supported.

A number of studies have examined how prior experience with service influence customer loyalty (Shankar et al., 2003) and how quality of prior experience with the online seller and quality of prior experience with e-commerce influence loyalty perception towards the online seller and e-commerce (Pizzutti and Fernandes, 2010). Shankar et al. (2003) found significant influence of prior experience on overall satisfaction and loyalty. While, Pizzutti and Fernandes (2010) examined prior customer experience as a moderator for Internet shopping, in general, and customer interaction with a particular online seller. They found that customers’ prior experience with a specific online seller moderated the relationship between satisfaction with complaint handling and trust, while the relationship was not moderated by quality of prior experience with e-commerce. This indicated that when customers with prior positive experiences did not have any complaints about poor handling, they tend to excuse the company (Pizzutti and Fernandes, 2010). In the online trust literature, Gefen (2000) developed a model to examine how the importance of trust in the context of e-commerce varies with different tasks and examines the relationship between familiarity and inquiry and purchase tasks. Gefen (2000) used familiarity with a particular website (amazon.com) to reflect customers’ experiences. The influence of familiarity on inquiry and purchase tasks were supported. McKnight et al. (2002) validated measures for a multidisciplinary and multidimensional model of trust in e-commerce in the context of USA and proposed that general web experience will have significant influence on institution-based trust. They found that web experience contributed significantly to institution-based trust. The importance of customers’ familiarity with e-commerce for building trust and reducing risk perception was highlighted (So and Sculli, 2002). Harridge-March (2006) explored the role of trust and risk to convert customers from Internet browsers to potential online purchasers. They argued that over time, customers are more likely to improve their experience through their previous interactions and their accumulated information about a particular e-vendor so that the

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information will be used to evaluate that e-vendor. As a result, customers trust is more likely to be built.

Customer experience has been the focus in the context of Internet banking (Ricard et al., 2001, Thornton and White, 2001, Nielsen, 2002, Rotchanakitummuai and Speece, 2003, Eriksson et al., 2005, Laforet and Li, 2005, Corrocher, 2006, Gan et al., 2006, Guriting and Ndubisi, 2006, Sayar and Wolfe, 2007, Grabner-Kräuter and Faullant, 2008, Johns and Perrott, 2008, Li and Lai, 2011). Tan and Teo (2000) found that prior experience with the Internet was one of the most influential factors that determined a person’s intention to adopt Internet banking. Ricard et al. (2001) examined the influence of customers’ use of banking self-services on their interest in a relationship approach and proposed that relationship duration, measured by the numbers of years the customer has been dealing with the bank and frequency of use measured by number of times per month the customers used credit cards, automated teller machines, point-of-sale terminals and home banking. They found that the more customers used self-services, the more their accumulated experience improved. This had significant influence on relationships with their banks. In Australia, Thornton and White (2001) examined whether customers’ knowledge has any influence on their attitudes towards financial distribution channels, such as automated teller machines, point of sale, credit cards and Internet banking, and found that customers’ attitude towards electronic services is positively and significantly influenced by customers’ knowledge. Nielsen (2002) found a significant impact of users’ IT knowledge on Internet banking adoption across Denmark, Finland, Norway and Sweden. In the B2B relationship, Rotchanakitummuai and Speece (2003) examined factors that influence corporate customers to use Internet banking, provided by Thai banks in Thailand, and found that lack of knowledge was the most significant factor influencing corporate customers to being non-Internet banking users. Eriksson et al. (2005) highlighted the relationship between internet banking usage and customers’ experience, stating that customers’ experience is an ambiguous concept because it refers to the experience of the services content and the delivery distribution channel. In addition, they claimed that the more customers who have experience of trial and error , the more their learning might be improved. Laforet and Li (2005) examined the demographic characteristics of electronic banking users and non-users. More specifically, they examined how users and non-users’

attitudes are affected by prior computer/new technology experience and prior personal banking experience, finding that there was significant difference between users and non-users of Internet banking. The users tend to have more previous computer experience than

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users. In Italia, Corrocher (2006) investigated the determinants of Internet banking adoption by Italian retail banks, and the relationship between experience and technology adoption was highlighted. Corrocher (2006) stated that the adoption of ICT-based innovations might be explained by the degree of information technology literacy and previous experience. Gan et al. (2006) developed a model to examine what factors influence customers’ choices between electronic and non-electronic banking in New Zealand. They found that individuals’

experience and knowledge had significant influence on Internet banking adoption between users and non-users of Internet banking. The Technology Acceptance Model was extended by Guriting and Ndubisi (2006) and it proposed that prior computing experiences and computer self-efficacy would contribute significantly on behavioural intention mediated by perceived usefulness and ease of use. They found that perceived ease of use and usefulness would not mediate the influence of customers’ experience on behavioural intention, and no significant influences from prior computing experience on perceived usefulness and ease of use were found. McKechnie et al. (2006) examined whether customers’ experiences with technology and purchases have any significant influence on perceived ease of use and usefulness.

Empirically, the influence of experience with technology and purchase experience were supported.

The importance of users’ prior Internet banking experience was stated by Sayar and Wolfe (2007) as an important construct determined customers’ behaviour towards Internet banking.

Grabner-Kräuter and Faullant (2008) found significant influence of Internet familiarity on Internet trust in the context on Internet banking in Austria. They used two observed variables to measure familiarity with the Internet: namely the length of time using the Internet and how often the Internet was used. Johns and Perrott (2008) developed a conceptual model to relationship marketing theory in the context of internet banking in the B2B relationship. They proposed that customers’ experience would have a significant influence on relationship marketing. Li and Lai (2011) examined the influence of demographic differences on the acceptance of internet banking in Hong Kong, and found that users with high IT competence find internet banking easy to use, but no influence was found between IT competence and usefulness, attitude and behaviour intention.

The Technology Acceptance Model was applied to examine users’ acceptance toward systems acceptance and usage across experienced and non-experienced users (Taylor and Todd, 1995a, Szajna, 1996, Jackson et al., 1997, Agarwal and Prasad, 1999, Dishaw and

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Strong, 1999, Venkatesh and Morris, 2000, Gefen et al., 2003b, McKechnie et al., 2006, Hernandez et al., 2009). Taylor and Todd (1995a) developed a model based on TAM to predict experienced and inexperienced users. They found that the relationships from ease of use to usefulness, perceived usefulness to attitude, subjective norms and perceived behaviour control to behaviour intention, and between behaviour intention and actual behaviour were significant in both experienced and inexperienced users, while the relationships between ease of use to attitude and perceived behaviour control and actual behaviour were significant in the case of inexperienced users and not significant for experienced users. Szajna (1996) examined TAM, carrying out a longitudinal study to examine the TAM model, both pre-implementation and after 13 weeks (post-pre-implementation). Szajna (1996) found that the relationship between perceived ease of use and usefulness was insignificant in pre-implementation version, while it was significant in the post-pre-implementation version. In addition, the relationship between behavioural intention and actual usage was stronger in the post-implementation version. This might be because when users gain experience with the system, their intention to use the system in the future will be stronger and predicted their actual usage (Szajna, 1996). Jackson et al. (1997) found that when users had previous usage, where they gained information and knowledge or they developed their learning and experience, it significantly influenced their behavioral intention. However, they also found that there was no significant influence of prior usage on usefulness perception of the system.

Agarwal and Prasad (1999) examined whether perceived ease of use and usefulness would be influenced by prior or similar experience, finding that similar experience associated had significant influence on ease of use beliefs. Dishaw and Strong (1999) integrated task technology fit and TAM, and found that system utilization was significantly associated with users experiences with IT. In addition, when task technology fit and TAM were integrated, they found that perceived ease of use was influenced by tool functionality and users’

experiences, and tool experience was associated with perceived usefulness. Venkatesh and Morris (2000) found that users’ experiences moderated the relationship between perceived usefulness and perceived ease of use on behavioural intention which indicated that, when users gain experience over time, they were more likely to improve the system usefulness and ease of use so that their behavioural intention to use the system will be stronger. However, they found that, with increased experience, perceived usefulness was not influenced by perceived ease of use. Venkatesh and Davis (2000) extended the Technology Acceptance Model and examined the moderating role of experience on the relationship between subjective norm on perceived usefulness and intention to use. They found that when users’

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experience increased, the influence of subjective norm on perceived usefulness and intention to use decreased. Gefen et al. (2003b) examined the influence of knowledge-based familiarity with an e-vendor on customers’ trust, arguing that customer trust would be developed when customers have greater contact with an e-vendor over time as more trust-relevant knowledge is accumulated. It was found that familiarity with an e-vendor affected trust only through perceived ease of use (Gefen et al., 2003b). Based on the Technology Acceptance Model, Venkatesh and Bala (2008) developed Technology Acceptance Model 3 and examined the moderating role of experience on the relationships between computer anxiety and perceived ease of use, and between perceived ease of use and perceived usefulness and behavioral intention. They found that the significance of experience was confirmed. Hernandez et al.

(2009) examined a model in the context of online shopping across experienced and inexperienced customers. They found that with increase customers’ experience, perceived ease of use loses its importance because, when customers do more online transactions, the more their experience is improved so their intention or actual behaviour will depend less on their perception of the ease of use.

A few studies that focused and examined customers’ experiences from the culture perspective (Gefen and Heart, 2006, Al-Gahtani et al., 2007). For example, Gefen and Heart (2006) examined the relationship between customers’ familiarity with an e-vendor, and predictability across US and Israel, finding that familiarity had a significant effect on trust beliefs through its influence on predictability and it has a significant influence on making inquiries and purchase intentions in the US. They also found that making inquiries and purchase intentions were affected by customers’ familiarity through predictability. In Saudi Arabia, Al-Gahtani et al. (2007) applied and attempted to validate the Unified Theory of Acceptance and Use of Technology (UTAUT). They examined the moderating role of users’

experience on the relationships between effort expectancy and subjective norm on behavioral intention, and between facilitating conditions and use behavior. They found that user experience has a significant and positive moderating role on the relationships between effort expectancy and subjective norm on behavioral intention, and positive interaction between facilitating conditions and use behavior.