Brand Engagement: It’s a story of love & hate! SANDRA MARIA CORREIA LOUREIRO & HANS RUEDIGER KAUFMANN Brand Engagement: It’s a story of love & hate!

Agenda Aim Literature review and hypotheses Methodology Findings Conclusions

Purpose: The aim of this ongoing research is to explore the effect of being positively/negatively engaged in online brand communities on the consumption focused self-expression e-word-of-mouth (CSWOM).

THE DARK SIDE OF ENGAGEMENT- A New Concept in Marketing Co-destruction of brand value, or impoverishment of value by customers and providers (Dolan, Conduit, and Fahy, 2016). Not only sharing negative feelings and messages toward a specific brand, but also becoming engaged in doing so (Juric, Smith and Wilks, 2016).

Research Gaps Lack of knowledge about the reasons and consequences of differentiated brand engagement, particularly the effects of negative engagement on the way consumers self-express their opinions and recommendations . Lack of differentiation of WOM conditions in online and offline environments .

Brand Literature Journey Brand Communities (Muniz and O’Guinn, 2001; Dholakia, Bagozzi, and Pearo (2004); McAlexander, Schouten, and Koenig (2002) Consumer Engagement (Brodie et al., 2011; Hollebeek, Glynn and Brodie (2014); Calder, Malthouse, and Schaedel (2009) Community Engagement (Algesheimer, Dholakia and Herrmann; 2005; Baldus, Voorhees, and Calantone, 2015) Online Community Engagement (Zheng et al., 2015; Rellinga et al., 2016; Chan et al., 2014) Love Brand Communities (Algesheimer, Dholakia and Herrmann, 2005; Brodie et al., 2013; Chan et al., 2014)

Brand Literature Journey WOM (Zeithaml, Berry, and Parasuraman, 1996; Mazzarol, Sweeney, and Soutar, 2007; Fu, Ju, and Hsu, 2015 Hating Brands & Destruction of Brand Value (Loureiro, 2015; Juric, Smith, and Wilks, 2016; Pansari and Kumar, 2016; Kaufmann, Loureiro, and Manarioti, 2016; Plé and Cáceres, 2010; Brodie et al., 2013; Hollebeek and Chen, 2014; Dolan, Conduit and Fahy, 2016; Lau and Ng, 2001) Explaining negative WOM: Cognitive Dissonance Theory and Social Support Theory (Chylinski and Chu, 2010; Grégoire and Fisher, 2008; Mattila, 2004; Verhagen, Nauta and Feldberg, 2013; Balaji, Khong, and Chong, 2016; Kim et al., 2016) Consumption Focused Self-Expression Word-of-Mouth (CSWOM) (Pagani, Hofacker, and Goldsmith, 2011; Thorbjørnsen, Pedersen, and Nysveen, 2007; Saenger, Thomas, and Johnson, 2013)

Hypotheses H1: The dimensions of online community engagement are related to members’ consumption-focused self-expression WOM in love brand communities. H2: The dimensions of online community engagement are related to members’ consumption-focused self-expression WOM in hate brand communities.

H1 CSWOM Love H2 CSWOM Hate Positive engagement Negative engagement Brand Influence Brand Influence Brand Passion Brand Aversion Connecting Connecting Helping Helping H1 Like-minded discussion CSWOM Love Like-minded discussion Reward s(hedonic) Reward s(hedonic) H2 Rewards(utilitarian CSWOM Hate Rewards(utilitarian Seeking Assistance Seeking Assistance Self-expression Self-expression Up-to-date information Up-to-date information Validation Validation Positive engagement Negative engagement

Methodology Data were collected in 6 online brand communities, grouped in pairs, each pair belonging to a diverse brand and comprising, within itself, both valences. The total of brands studied were 3: Starbucks, Apple, and McDonald’s (each brand with a positive and a negative brand community). 600 Online questionnaires (Pre- Test with 10 consumers) distributed in brand communities; 300 from fan and 300 from anti-brand communities; split equally for the three brands’ communities

Methodology Scale to measure consumption-focused self-expression WOM: six items adapted from Saenger et al. (2013) Likert scales, of 1 (one) to 7 (seven) were: 1 – Strongly disagree; 2 – Mostly disagree; 3 – Somewhat disagree; 4 – Neither agree nor disagree; 5 – Somewhat agree; 6 – Mostly agree; 7 – Strongly agree Questionnaire entailed socio demographic variables and others to characterize the participants: number of hours, on average, spent on the internet per week; number of posts, on average, per week; evaluating the feeling about a brand x on a scale from 0 (I hate it) to 10 (I love it).

Methodology Assumptions for multiple linear regressions (such as normality, multicollinearity, autocorrelation) tested Hierarchical Multiple Regressions conducted by SPSS23 (effects of co- variates and predictors)

Findings: Convergent Validity and Reliability

Sample Profile 1. Fan Communities Sample Profile 1. Fan Communities Gender: 53.30% are male and 46.70% are female Age: most participants are between 21 and 30 years old (68.70%) (M=26.32, SD=5.81) Nationalities: USA, UK, Canada, New Zealand, Switzerland, South Africa, Russia, India, Denmark, Germany, Brazil (mainly from USA and UK). Characteristics: The average number of hours using the Internet, per week is 37.03 (SD=17.11). The average number of posts per week and per participant is 2.53 (SD=4.62). Asking how participants felt about the brand in a scale from 0 (I hate it) to 10 (I love it), the average value is 7.43 (SD=1.61). Sample Profile 1. Fan Communities Gender: 53.30% are male and 46.70% are female Age: most participants are between 21 and 30 years old (68.70%) (M=26.32, SD=5.81) Nationalities: USA, UK, Canada, New Zealand, Switzerland, South Africa, Russia, India, Denmark, Germany, Brazil (mainly from USA and UK). Characteristics: The average number of hours using the Internet, per week is 37.03 (SD=17.11). The average number of posts per week and per participant is 2.53 (SD=4.62). Asking how participants felt about the brand in a scale from 0 (I hate it) to 10 (I love it), the average value is 7.43 (SD=1.61).

Sample Profile 2. Anti Brand Communities Gender: 77.30% are male and 22.70% are female Age: Most participants are between 21 and 30 years old (59.00%) (M=29.35, SD=7.66) Nationalities: USA, UK, Canada, Australian, South Africa, India, Belgium, Philippines, Argentine (mainly from USA and UK). Characteristics: The average number of hours using Internet, per week is 34.24 (SD=11.27). The average number of posts per week and per participant is 2.53 (SD=4.62). Asking how participants felt about the brand in a scale from 0 (I hate it) to 10 (I love it), the average value is 0.91 (SD=1.10).

Findings: Summary The results of the current study show the strength of dimensionalities of engagement on CSWOM for love versus hate online brand communities. Both hypotheses are partially supported.

Findings: Love Brand Communities 1 Brand passion, Rewards (hedonic), Rewards (utilitarian) and Validation account for an extra 12.6% of the variance in CSWOM (contradictory to Baldus et al., 2015: brand passion, rewards (Utitilitarian) and validation are no drivers of participation intentions in brand communities). Brand passion (β=.53, p<.001) and Validation (β=.22, p<.001) are the most significant predictors of CSWOM in love communities.

Findings: Love Communities 2 Important to note: Negative and significant relationships between Rewards (hedonic) and CSWOM and Rewards (utilitarian) and CSWOM in love communities. This means: The positive emotions and utilitarian awards (e.g., monetary rewards, time savings, deals or incentives, merchandise, and prizes) through their participation in the community do not entice participants to inform others of their consumption behavior (in line with Baldus et al. 2015) (less emphasis from management required on utilitarian benefits)

Note. *p< .05, ** p< .01, ***p< .001, ns not significant Table 2. Summary of Hierarchical Regression Analysis for Variables Predicting CSWOM: love brand communities Note. *p< .05, ** p< .01, ***p< .001, ns not significant   Model 1 Model 2 Construct B Std. Error Beta (Constant) 0.06 0.23 0.03 0.24 Brand Influence 0.19 0.04 0.19*** 0.09 0.05 0.09 ns Connecting 0.29 0.07 0.31*** 0.05 ns Helping 0.06 ns Like-minded discussion 0.12 0.15* 0.08 0.10 ns Seeking assistance 0.04 ns 0.02 0.02 ns Self-expression 0.07 ns 0.08 ns Up-to-date Information 0.16 0.18*** Brand passion 0.53 0.51*** Rewards(hedonic) -0.17 -0.21*** Rewards(utilitarian) -0.18 Validation 0.22 0.23*** R2 .58 .71 Adjusted R2 .57 .70 ∆R2 .13 ∆F 67.30*** 36.19***

Findings: Hate Brand Communities 1 Validation is not statistically significant Brand influence (β=0.364, p<.001), Brand aversion (β=0.447, p<.001) and Rewards (hedonic) (β=0.243, p<.001) are the most significant predictors of CSWOM in hate communities. Those who hate the brand, want to influence it and feel emotional rewards hating the brand and tend to be more active in writing comments about it. Connecting and Like-minded discussions are dimensions negatively related with CSWOM, meaning that those who enjoy socially relating with others, similar in the brand community, do not tend to talk about their consumption activities (innovative finding as to hate communities).

Table 3. Summary of Hierarchical Regression Analysis for Variables Predicting CSWOM: hate brand communities Note. *p< .10, ** p< .05, ***p< .001, ns not significant   Model 1 Model 2 Construct B Std. Error Beta (Constant) 2.594 0.326 -2.059 0.594 Helping 0.174 0.090 0.174* -0.039 0.078 -0.043 ns Like-minded discussion -0.483 0.072 -0.483*** -0.154 0.081 -0.193* Seeking Assistance -0.188 0.055 -0.188*** 0.064 0.050 0.070 ns Self-expression 0.525 0.077 0.525*** 0.041 0.071 0.035 ns Up-to-date information 0.168 0.053 0.168** 0.042 0.077 ns Validation 0.103 0.103 ns 0.000 0.000 ns Brand Influence 0.340 0.364*** Brand Aversion 0.734 0.075 0.447*** Connecting -0.228 0.100 -0.174** Rewards(hedonic) 0.216 0.051 0.243*** Rewards(utilitarian) 0.037 0.091** R2 0.26 0.55 Adjusted R2 0.25 0.54 ∆R2 0.29 ∆F 20.25*** 44.30***

Conclusions First attempt to explore online brand community engagement in both love/hate brand communities of the same brands. The valence love/hate has different drivers contributing to the CSWOM process. Lovers are more motivated by emotions, passion and validation. ”Love lights more fires that hate extinguishes” (Ella Wheeler Wilcox) Haters want to influence the brand to change the behavior or improve the features of the brand and get fun in sharing those negative comments, helping/connecting with others and receiving utilitarian rewards. “People are fascinating, especially, the ones who hate me” (Rebecca McKinsey) Limitations: Love and hate brand communities aggregate members of different countries and, so, some difference could emerge depending on the cultural differences (more data are needed to understand this issue); differentiated brand analys still to come.

Thank you! Sandra Maria Correia Loureiro sandramloureiro@netcabo.pt & Hans Ruediger Kaufmann kaufmann.r@unic.ac.cy