ONLINE CONTENT ANALYSIS

5.6.1.1

TRIPADVISORREVIEWSITEASONLINEWORD-OF-MOUTH

Online ‘word-of-mouth’ as a form of social media includes referrals and forums where user- generated content is shared and evaluated (Stephan and Galak, 2009). In social media, the opinion of the average online user is much more valuable than that of an off-line professional critic (Onishi and Manchanda, 2009; Thevenot, 2007). Consumers are actively demanding participation in the assessment of the consumer process (Zarella, 2010; Doyle, 2008). It seems what mostly applies to word-of-mouth equally and typically does so too to online, except in cases of time and space differences, limited offline reach, online credibility, and non-altruistic motives (Steffes and Burgee, 2009). Social media is useful in conveying abstract qualities such as service attitude via communicative narrative content, supported by photos and video. Rich interactive content has mind-set undertones which can enhance customer learning and participation (Stokes, 2008). They have great potential in informing and managing dining expectations and experiences.

Pre-existing liaisons are not required with review sites; they only share connection via discussion forums about a common interest or issue (Miguens et al., 2008). Hensens et al. (2010) found that TripAdvisor mostly provides reliable and trustworthy sources of information for online peers enquiring as to the quality of a product or service.

5.6.1.2

DELIGHTANDFRUSTRATIONFACTORS

The expected core service of ‘reliability’ in any commercial transaction needs to be augmented by other differentiated service skills; it is these skills that create competitive advantage

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(Zeithaml and Bitner, 2003; O’Sullivan and Spangler, 1998). These differentiated service skills ultimately determine between ‘delighted’ or ‘frustrated’ customers. However, research confirms that doing the basics right for restaurants is imperative (i.e. delicious food, appropriate cost, cheerful greeting, and attentive service).

‘Desired’ service which customers hope to receive is rarely achieved, whereas ‘adequate’ service which is the minimum accepted to stay in business, is achieved three out of four times, according to research (Zeithaml and Bitner, 2003:469). Exceeding adequate service with ‘delight factors’ is probably nevertheless unremarkable; it frequently leads to the business overpromising, resulting in inconsistency in service quality standards (Carbone and Haeckel, 2005). The mere fact of businesses trying to understand customer expectations usually exceeds them (Zeithaml and Bitner, 2003).

‘Satisfying factors’ are parallel to Zeithaml and Bitner’s tiered expectations of desired service, the zone of tolerance, and adequate service. Desired service anticipates an expected desire to be fulfilled. It does not bring in the element of ‘surprise’. To determine a state of ‘delight’ the element of surprise is required (Zeithaml and Bitner, 2003). The equivalent surprise factor of going below adequate service is termed a ‘frustration factor’ (Hensens, 2010). Being delighted or frustrated requires disconfirmation – beyond desired or adequate service delivery. ‘Predicted service’ is parallel to satisfying factors (Wilson et al., 2008; Hensens, 2010). This is based on what customers normally believe they will get as an experience.

New customers display a greater vulnerability to business relationship mishaps than existing customers (Peppers and Rogers, 2004). Longer and satisfied relationships seem to require less maintenance, less attention, less cost and less subsequent effort. Especially in the case of delight and frustration factors, ‘fewer surprises’ is also a result of longer satisfied relationships.

Contemporary research shows that customers with strong experience opinions are more likely to share them with others than those with milder views, and frustrated customers are also more likely to share than delighted customers (Solomon et al., 1999; Lovelock and Wirtz, 2004). Apparently frustrated customers are 90% certain not to repurchase at a business again (Solomon et al., 1999). Customers that were initially frustrated would frequently end up spreading positive word-of-mouth by being exposed to effective service recovery (Lovelock and Wirtz, 2004).

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5.6.1.3

USER-GENERATEDCONTENT

Online consumers are distinctly discriminative about what they want to be involved in (Shankar and Malthouse, 2009; Rubinson, 2009). When social media environments negatively affect customer expectations, the response is likely to be negative, probably leading to avoidance behaviour (Williams and Dargel, 2004). Additionally, customer experiences may also include too much information (Gaudeul and Peroni, 2010; Meyer, 1998).

Online expectations of customers reflect their offline expectations. Substandard products and service will simply be amplified by means of social media, because of the degree of transparency demanded. Controversy has viral potential whereby brands and business interests can be badly damaged (Stokes, 2008; Safko and Brake, 2009; Phillips and Young, 2009). Furthermore, personality effects are moderated by different social media tools or applications. The actual experiences are dependent on what the users thought the tools could do for them (Sanaktekin and Aydin, 2010). Customers’ desire for ‘social interaction’, ‘economic incentives’, ‘concern for other consumers’, and the ‘potential to enhance their own self-worth’ were the main motivators for participation in social media and creating online content (Bolton and Saxena-Iyer, 2009:98). Customers’ online social media experiences positively affect offline dining experiences (Titz, Lanza-Abbott, and Cruz, 2004; Grupta et al., 2007; Menon and Dubé, 1999; Hanefors and Mossberg, 2003; Schoemaker, 1996). The more customers expect from the business’s participation online, the more likely they are to become engaged in being susceptible to the content created. Diners that embrace technology in general are more inclined to use it for adding value to their existing preferences (Dixon et al., 2009). These diners also tend to be high- end restaurant customers, who have more ego-related expectations (Murphy, 2010). Low-end restaurant customers have an approach of concern for other customers, whereas the high-end restaurant customers recognise and appreciate good service and product quality more readily. Social media customers are led to participate in ‘observational learning’, where individual behaviour is impacted by their observation of the behaviour of others because of the information contained therein (Cai et al., 2007), e.g. peers’ expectations and experiences that are converted into their opinions too. Peers’ experiences subsequently improve as and when they are increasingly presented with expert opinions on reviews and recommendations. Biased online reviews normally include factors akin to the reviewer’s purpose of travel, geographical location, perceptions of quality, or cultural exposure (Keates, 2008). Online participants

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generally trusted information most when it was generated by friends or people they know (Invoke, 2010).

Five factors have been identified by the researcher to represent overall customer experience in user-generated content, these factors consisting of service quality (with descriptors of reliability, responsiveness, assurance, empathy, and tangibles), product quality, price, and situational and personal factors (Wilson et al., 2008).

The second phase of the study involves empirical research which implies inferences made that include: dining experiences and expectations; post-experience evaluations; and other feedback methods besides social media.