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Figure 1. Research model Methodology/approach The relationships among brand trust, dissatisfaction, negative brand relationships and negative eWom and the effect of negative eWom on switching behaviour are tested through structural equation modelling techniques.

Data was collected in May-June 2014 using a sample of 302 Spanish university students who have posted negative reviews online in the past year. According to the “V Study of Social Media in Spain” (International Advertising Bureau, April 2014), young adults (18-30 years old) represent the largest group of social media users in Spain. As in previous studies on social media (Lee et al., 2008; Zhou, 2011), selecting students as our sample was deemed as appropriate.

A questionnaire was drafted using existing scales which was pilot tested with 25 individuals with previous experience writing negative reviews online. All questions were related to a brand with which respondents have had a bad experience. Negative brand relationships were measured as a second order construct adapting the scale developed by Veloutsou (2007) which captures two dimensions of brand relationships: two-way communications and emotional exchange. The scale of dissatisfaction is based on Keaveney et al (2001) research and trust is captured using three items based on Kim et al (2009). Negative eWOM is measured with 3 items adapted from Bougie et al. (2003) and switching intentions with 3 items adapted from Putrevu and Lord (1994). All the variables were measured using 7-point Likert scales (“strongly agree-strongly disagree”).

Findings After validating the measurement model, a structural equation model was estimated. Data analysis shows that negative electronic word of mouth has a direct and strong influence on brand switching intentions (β=0.82, p0.01). The results show that negative brand relationships represent an important outcome of dissatisfaction (β=0.87, p0.01) and lack of trust (β=-0.12, p0.01). Trust is very dependent on dissatisfaction (β=-0.59, p0.01). As the empirical study also found a direct influence of consumer negative brand relationships on negative eWom (β=0.84, p0.01), dissatisfaction arises as the key variable to explain negative eWom as it directly increases negative brand relationships and reduces trust.

Theoretical implications This study contributes to existing research in three ways. Firstly, the academic literature on the behavioural outcomes of eWom (Cheung et al., 2008, Park et al., 2007; Verhagen et al.,

2013) is extended, by focusing on the sender perspective. The proposed model rooted in brand relationship literature, self-perception and dissonance theory, demonstrates that negative eWom is indicative for the intended switching behaviour of the sender of these messages.

Secondly, the role of negative eWom as a direct outcome of negative brand relationships captures the long-term emotive connection between the consumer and the brand. The findings show that an important goal of brand communications in social media should be to build emotional relationships and allow consumers to exchange experiences in a two-way communication with the brand. The findings support previous research stating consumers form relationships with the brands they interact with (Morgan-Thomas and Veloutsou, 2013).

Thirdly, the research model goes beyond dissatisfaction. A thorough assessment on how different variables related to brand experience (dissatisfaction), consumer beliefs (brand trust) or brand relationships, affect consumers’ willingness to disclose negative comments about the brand is offered. Previous studies (Casaló et al, 2008; Hazra et al., 2009; Morgan and Hunt,

1994) highlight that the variables included in this research model contribute to building longterm relationships. The research model identifies trust and dissatisfaction to be key antecedents of negative brand relationships in a web 2.0 context.

Practical implications This research provides companies with knowledge of what aspects to highlight in their communication strategies to minimize switching behaviour and to deal with the negative comments posted by their customers. Managing negative eWom is of vital importance to companies because goes beyond being not only of influence for other consumers, but also it being highly predictive of senders’ intended conduct.

Practical recommendations to improve consumer negative relationships with brands, to increase trust and guidelines to reduce dissatisfaction are provided. Companies need to maintain strong brands based on emotional connections with users that go beyond the technical performance. The influence of trust in negative brand relationships involves a series of actions by companies. Firstly, sincerity and transparency are worthwhile in terms of fulfilling the commitments and the promises made by the brand. Secondly, the brand communication policy must promote achievements of objectives, which are complementary to those of the brand target. Thirdly, considerable investment is necessary to provide resources to ensure that consumers perceive greater competence and skill in the organization which owns the brand they are interacting with. The importance of the role of dissatisfaction for trust and on negative brand relationships means that brands need to analyse continuously the factors in the consumer experience with the brand which can generate consumer satisfaction (customer care, design, product quality, etc..), as in the end, more satisfied consumers mean more loyal ones. Companies might want to use customer centered-care teams to resolve problems. This customer care teams should build emotional attachments to the brand and to engage in two-way communication with consumers who recently expressed themselves negatively. This would result in fewer negative messages online. Finally, in order to minimize the negative eWom, trust has to be enriched with brand related feelings that connect the consumer with the brand. Creating trust bonds and positive interactions with the brand, companies can minimize the negative eWom.

Limitations The study focuses on the antecedents of brand switching from the consumer perspective.

However, customers often engage in activities after switching that may still affect the switched-from brand (spreading negative eWom about the dropped brand etc.). Further research could focus on the behaviour of consumers after having switched to another brand.

Another limitation of the study is the potential response bias because data has been collected from a student sample. Students are heavy-users of websites 2.0 where it is normal to engage in complaining behaviour, but alternative sample groups might be used to further test the robustness of our findings. Due to the importance of trust, more research with the alternative conceptualization of trust (trust as an intention instead of a belief) would be useful in understanding the role of trust in switching intentions. Previous studies have identified antecedents of trust such as brand familiarity and disposition to trust (Gefen et al., 2003; SeeTo and Ho). Therefore, further research considering these factors could also enhance the understanding of consumer brand switching behaviour.

Originality/value Unlike most research focused on examining key drivers of loyalty in online environments, this paper deals with negative assessment, attitudes and behaviour. This work aims to combine the influence of trust, dissatisfaction, negative brand relationships and negative eWom in order to construct an improved model for explaining brand switching. Although the linear relationship between dissatisfaction and negative eWom seems almost intuitive, the interaction with other variables in web 2.0 environments can affect these relationships. This research is novel in that it integrates the mediating effect of negative brand relationships and a variable associated with the uncertainty of behaviour (trust), on the relationship between dissatisfaction and negative eWom. Moreover, this paper is one of the few studies that consider the negative eWom from the sender perspective. Finally, this paper extends the notion of brand relationships to include the emotive responses (emotional exchange) and connections with the brand (two-way communications) that consumers build over the time on web 2.0 environments. Despite new dimensions having been discovered in brand relationships that go beyond technical performance (Veloutsou, 2007), this is the first study that analyse the direct influence of negative brand relationships on negative eWom.

KeywordsTrust, satisfaction, brand relationships, eWom, switching behaviour.

References Bougie, R., Pieters, R., & Zeelenberg, M. 2003. Angry customers don't come back, they get back: the experience and behavioral implications of anger and dissatisfaction in services.

Journal of the Academy of Marketing Science 31(4), 377-393.

Casaló, L. V., Flavián, C., & Guinaliu, M. 2008. Promoting consumer's participation in virtual brand communities: a new paradigm in branding strategy. Journal of Marketing Communications, 14(1), 19-36.

Cheung, C. M., Lee, M. K., & Rabjohn, N. 2008. The impact of electronic word-of-mouth:

The adoption of online opinions in online customer communities. Internet Research, 18(3), 229-247.

Gefen, D., Karahanna, E., & Straub, D. W. 2003. Trust and TAM in online shopping: an integrated model. MIS quarterly, 27(1), 51-90.

Hazra, S. G., & Kailash, B. L. Srivastava 2009. Impact of Service Quality on Customer Loyalty, Commitment and Trust in the Indian Banking Sector. Journal of Marketing Management, 3(3), 75-95.

Hennig-Thurau, T., Gwinner K. P., Walsh, G., & Gremler, D. D. 2004. Electronic word-ofmouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing 18(1), 38-52.

International Advertising Bureau. 2014. V Study of Social Media in Spain. Available through:

http://www.iabspain.net/redes-sociales/, accesed 3 May, 2014.

Keaveney, S.; Parthasarathy, M. 2001. Customer switching behaviour in online services: an exploratory study of the role of selected attitudinal, behavioural and demographic factors.

Journal of the Academy of Marketing Science, 29 (4), 374–390 Kim, J., Jin, B., & Swinney, J. L. 2009. The role of etail quality, e-satisfaction and e-trust in online loyalty development process. Journal of Retailing and Consumer Services, 16(4), 239Lee, J., Park, D. H., & Han, I. 2008. The effect of negative online consumer reviews on product attitude: An information processing view. Electronic Commerce Research and Applications, 7(3), 341-352.

Lee, D., Kim, H. S., & Kim, J. K. 2012. The role of self-construal in consumers’ electronic word of mouth (eWOM) in social networking sites: A social cognitive approach. Computers in Human Behavior, 28(3), 1054-1062.

Mollen, A., & Wilson, H. (2010). Engagement, telepresence and interactivity in online consumer experience: Reconciling scholastic and managerial perspectives. Journal of Business Research, 63(9), 919-925.

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, 58(3), 20-38.

Morgan-Thomas, A., & Veloutsou, C. 2013. Beyond technology acceptance: Brand relationships and online brand experience. Journal of Business Research, 66(1), 21-27.

Park, D. H., Lee, J., & Han, I. 2007. The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce, 11(4), 125-148.

Putrevu, S., & Lord, K. R. (1994). Comparative and non-comparative advertising: attitudinal effects under cognitive and affective involvement conditions. Journal of Advertising, 23(2), 77-91.

Rappaport, S. D. (2007). Lessons from online practice: new advertising models. Journal of Advertising Research, 47(2), 135-141.

See-To, E. W., & Ho, K. 2014. Value co-creation and purchase intention in social network sites: The role of electronic Word-of-Mouth and trust. A theoretical analysis. Computers in Human Behavior, 31, 182-189.

Sundaram D.S., Mitra K. & Webster, C. 1998. Word of mouth communications: A motivational analysis. Advances in Consumer Research 25, 527-531.

Veloutsou, C. 2007. Identifying the dimensions of the product-brand and consumer relationship. Journal of Marketing Management 23(1-2), 7-26.

Verhagen, T., Nauta, A., & Feldberg, F. 2013. Negative online word-of-mouth: Behavioral indicator or emotional release?. Computers in Human Behavior, 29(4), 1430-1440.

Zhou, T. (2011). Understanding online community user participation: a social influence perspective. Internet Research, 21(1), 67-81.

The importance of brand competence to seaports in the Middle East Rutter, Richard al Shamisi, Suwaid Lettice, Fiona Purpose This paper will present the results of a study which explores the relationship between seaport brand personality, capacity and performance. The study is based on an empirical analysis of the text from the websites of 10 seaports in the Middle East. Each seaport’s website is content analysed. Regression analysis is used to ascertain whether interaction relationships existed and whether brand personality dimensional strength (Competence, Excitement, Ruggedness, Sincerity and Sophistication) moderated the relationship between a seaport’s capacity (number of births) and performance (twenty-foot equivalent units or “TEUs”).

A port’s brand acts as “shorthand” to aid and increase speed and brevity to choice by improving recollection of information, resulting in faster transaction judgments (Cohen, 2009, Jain and Golosinski, 2009). A brand’s personality is an anthropomorphisation. It involves attributing human characteristics to a non-human creature or physical object. A brand personality represents the character of the brand as if it were a person (Phau and Lau, 2001, Cappara et al., 2001, Aaker, 1997, Grohmann, 2009). It is a way to sustain individuality and create differentiation by emphasising psychological values, beyond a brand or product’s functional utility. A brand permeates the entire company and in this way, the sum of a seaport actions, behaviour, dealings and communications form its brand personality.

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