The following study assesses the impact of the Champions Hockey League’s brand prestige on trust, perceived risk, satisfaction, and loyalty of ice hockey fans and viewers. The importance of the research is justified in Section 1. The applied theory is then introduced in Section 2, and the methodology is explained in Section 3. Section 4 analyses the collected data and offers high-level strategies for improving the brand prestige of the analysed ice hockey brand. The validity and reliability of the applied construct is elaborated on in Section 5, before concluding with a reflection on the main findings and limitations of this study in Section 6.
Section 1: Background to the research
The current form of the Champions Hockey League (CHL) was established in 2014 with the aim to become Europe’s greatest ice hockey competition and crown the Champions of Europe (CHL, 2020a). Despite a social media reach of 5 million followers (accumulated from the CHL, clubs, and leagues) and 135 million accumulated TV viewers from 67 TV territories by 2019 (CHL, 2019), the CHL is met with negative social media sentiments from some fans of participating clubs. Figure 1 exhibits a selection of unsolicited comments on Twitter gathered during the quantitative data collection for this study. It is common for fans to voice their opinions on a team’s performance or club’s business practices through social media in modern-day sports (Sutera, 2013). Yet, based on the intensity of the sentiments, questioning the perceived level of prestige of the CHL brand and its impact on fans and followers becomes legitimate.
This is important, because a high level of brand prestige can positively influence brand trust (Choi et al., 2011) and decrease the perceived risk of buying the product, i.e. watching a CHL game (Jin et al., 2016). Brand prestige may also affect brand satisfaction, which is assessed by how well the tournament meets a fan’s hockey entertainment wants and needs (cf. Back and Parks, 2003). Finally, brand prestige could have an impact on the loyalty of fans and viewers to keep watching the CHL (cf. Brakus et al., 2009). Arguably, fan and viewer retention should be the ultimate goal for a sports brand (Rein et al., 2006). Therefore, the guiding research question for this article is: “What is the impact of the CHL’s brand prestige on trust, perceived risk, satisfaction, and loyalty of ice hockey fans?” Figure 2 depicts the chosen conceptual framework. The variables are defined in Section 2.
Section 2: Definitions, conceptual framework, and hypotheses
The five variables examined in this research are defined as follows:
Brand prestige can be considered the perceived value customers attribute to a brand based on hedonic and social beliefs (Baek et al., 2010). According to Jin et al. (2016), prestigious products and services are often regarded as superior in quality and allow consumers “to express a perceived sense of superior worth” (p. 525). This research adopted the scale proposed by Carlson and Donovan (2013) and assessed the perceived reputation of the CHL, its status, and how respected the tournament is among ice hockey fans and viewers.
Chaudhuri and Holbrook (2001) define brand trust as “the willingness of the average consumer to rely on the ability of the brand to perform its stated function” (p. 82). The brand trust-items proposed by Baek et al. (2010) were adapted for the context of this study, which evaluate the belief fans have on how reliable and committed they think the CHL is in delivering the high-quality hockey experience it promises.
Perceived risk can be described as “the subjective appraisal of uncertainty concerning the financial, physical, and social consequences of a consumption experience” (Jin et al., 2016, p. 526). The scale applied for this variable examines the need for additional information regarding the possible consumption of the product, i.e. do viewers need more information before watching a CHL game, and do they have a good idea of what to expect from a CHL game.
Customer satisfaction is generally expressed as the level of satisfaction resulting from the assessment of how well the chosen product or service satisfied a consumer’s wants and needs (Back and Parks, 2003). The defined fan and viewer satisfaction for this study is based on the overall sentiment towards the obtained CHL experience, as well as the individual evaluation of the decision to watch the CHL Season 2019/20.
Customer loyalty is founded on favourable and unfavourable behavioural intentions, including saying positive or negative things about the brand and its products, recommendations about the brand, and remaining loyal or switching to a competitor (Zeithaml et al., 1996). This study assesses fan and viewer loyalty by asking, if participants would like to watch the CHL in the future, recommend to watch the CHL to others, and if they would say positive things about the CHL to others.
Based on the conceptual model adopted from Jin et al. (2016) for this study, the tested relationships are visualised in Figure 2 in Section 1 and defined as follows:
- H1: Brand prestige affects trust.
- H2: Brand prestige affects satisfaction.
- H3: Brand prestige affects loyalty.
- H4: Brand prestige affects perceived risk.
- H5: Trust affects satisfaction.
- H6: Trust affects loyalty.
- H7: Trust affects perceived risk.
- H8: Perceived risk affects satisfaction.
- H9: Perceived risk affects loyalty.
- H10: Satisfaction affects loyalty.
The results to the hypothesised relationships will be discussed in Section 4. Section 3 will first elaborate on how the data was collected and on the characteristics of the respondents.
Section 3: Methodology and sample
The questionnaire utilised to collect quantitative data for this research was developed by Jin et al. (2016). It includes 15 question-items, 3 for each of the 5 scales, and 3 additional questions on the demography of the respondents. The question-items were customised for the context of this study where necessary with reference to the following literature:
- Brand prestige scale (PRE1/2/3) à Carlson and Donovan (2013)
- Perceived risk scale (RSK1/2/3) à Jin et al. (2016)
- Brand trust scale (TRU1/2/3) à Baek et al. (2010)
- Fan and viewer satisfaction scale (SAT1/2/3) à Back and Parks (2003)
- Fan and viewer loyalty scale (LOY1/2/3) à Jin et al. (2016)
Figure 5 in Section 4 presents the questions posed in the questionnaire.
Items were assessed with a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Fans and followers of ice hockey clubs and leagues associated with the CHL were targeted through social media posts and ads on Facebook, Instagram, and Twitter with a request to participate in the survey (see example in Figure 3). Data was collected through Google Forms from Sunday, 2 February 2020 until Thursday 6 February 2020.
The questionnaire was completed by 542 social media users and all responses were accepted. 91.9% of respondents are male and 8.1% female. Age distribution is balanced: 25 to 34-year-olds are the largest age-group including 29.9% of the sample, closely followed by 34 to 44-year-olds with 23.4% and 18 to 24-year-olds with 22.7%; 45 to 54-year-olds make up 14.2% of the sample. Although all European territories with associations to ice hockey were targeted, the highest participation came from people living in Sweden (52.6%) and the Czech Republic (13.3%). This can be due to the fact that the CHL final was played on Tuesday, 4 February 2020, between Frölunda Indians from Sweden and Mountfield HK from the Czech Republic and coincided with the data collection period for this study. Therefore, it can be assumed that the motivation for fans of these teams to participate was higher than from other teams that were not playing in the CHL anymore. The third-largest participation was from fans and viewers from the United Kingdom (11.1%), followed by Switzerland (6.6%), Finland (5.9%), Austria (3%), and Germany (3%). Other countries made up less than 1% of the sample individually. A visualisation of the sample is offered in Figure 4.
Section 4: Results and analysis
Figure 5 offers an overview of the question-items including their mean, standard deviation (STDEV), and factor loading, as well as Cronbach’s Alpha (α), composite reliability (CR) and average variance extracted (AVE) in order to assess the validity and reliability of the questionnaire. Factor loadings and the validity and reliability of the construct will be discussed in Section 5. In addition, Figure 6 offers a visual overview of the computed correlation coefficients (Multiple R) within the conceptual model of the study. The correlation coefficients shall explain the strength and direction of the relationships between the five variables as perceived by fans and viewers of the Champions Hockey League Season 2019/20.
Respondents slightly disagree with the statements that the CHL has a good reputation, high status, or is highly respected (PRE1/2/3). This is also highlighted in the unsolicited comments portrayed in Figure 1. These results may imply that the CHL should revise their branding and marketing communications approach regarding their aimed brand prestige. This could be improved through brand tribalism, which means that fans should be allowed collaboration and participation in the creation of the CHL brand experience to create stronger brand relationships (Veloutsou and Moutinho, 2009). The CHL introduced an official fan challenge with the aim to create a hockey community or tribe (CHL, 2020b). However, it did not yet help the CHL achieve a good reputation, high status, or high degree of respect, judging from the analysed data in Figure 5. This may be due to an ineffective implementation of the gamified campaign. A possible improvement could include to make sure that the CHL fan challenge is centred around game content instead of game mechanics (Harwood and Gerry, 2015).
As portrayed in Figure 6, CHL’s brand prestige has a strong positive impact on brand trust (H1), fan and viewer satisfaction (H2), and fan and viewer loyalty (H3). This means, if the CHL improves its brand prestige, fans and viewers would trust the brand more, would be more satisfied with the product it offers, and would be more loyal. These findings are supported by Jin et al. (2016). Furthermore, CHL’s brand prestige has a weak negative impact on perceived risk (H4), meaning that fans and viewers may find attending or watching a CHL game less risky, if the CHL is perceived to be more prestigious. However, the weak negative relationship suggests that despite improving brand prestige, the perceived risk for fans and viewers may only marginally decrease. All relationships are significant at p<.01.
Respondents slightly disagree when asked if they think that the CHL is reliable in delivering the high-quality hockey experience it promises (TRU1) and when asked if they are confident that the CHL would deliver the promised high-quality hockey experience (TRU2). Nevertheless, they moderately agree when asked if they think that the CHL is committed to deliver the high-quality hockey experience it promises (TRU3). In other words, fans believe that the CHL has been trying to offer a high-quality product, but has not succeeded yet. Hence, they do not seem to trust in the organisation’s abilities in that regard. Tsiotsou (2013) mentions research by Harris and Ogbonna (2008), who found that sport fans build brand trust based on information gathered through various forms of mass communication not through dialogue. In order to close the possible information gap leading to a low brand trust, the CHL could create an integrated marketing communications campaign highlighting the efforts undertaken by the organisation for the production and delivery of the promised high-quality ice hockey experience (Batchelora and Formentin, 2008). According to Batra and Keller (2016), public relations, social media, and influencers/opinion leaders have the greatest influence when building brand trust. The above-mentioned campaign should therefore be delivered through these communications channels.
Figure 6 illustrates that CHL’s brand trust has a strong positive impact on fan and viewer satisfaction (H5) and fan and viewer loyalty (H6). Both relationships are significant at p<.01. These findings support the notions discussed above. Looking at H7, the impact of CHL’s brand trust on perceived risk is weak and negative, but not significant, meaning no relationship can be determined from the data at hand. Nevertheless, using a sub-sample from the given population (n=257; without Swedish fans and viewers, because of their negative sentiments toward the CHL), H7 becomes significant at p<.01 with a correlation coefficient of –.231. This indicates that CHL’s brand trust could have a significant and moderately strong negative impact on perceived risk, meaning that building brand trust would reduce the perceived risk to spend time and money for a CHL game, a notion supported by Baek et al. (2010).
Respondents usually do not need additional information before watching a CHL match (RSK1). This may be due to the fact that club fans, who are already well informed about their club, mostly follow the competition. The behaviour of typical supporters includes the desire “to have the feeling of being co-producers [of the brand experience] by showing a physical and vocal presence or superiority” (Bouchet et al., 2011), a behaviour that can be observed in social media as well (Sutera, 2013). Respondents slightly agreed with the statement that the quality of a CHL game is difficult to assess before watching the game (RSK2). It can be argued that the characteristic of not knowing the outcome of a sports event is what makes it exciting (Vecer et al., 2007). However, if a sports brand can guarantee a high-quality product, i.e. an exciting sports game, it may reduce the perceived risk of spending timely and financial resources for a possibly low-quality experience (Yocco, 2016). Nevertheless, respondents believe that they don’t need to watch several CHL games to know what the competition is about (RSK3). As previously mentioned, if the respondents of this survey belong to the ‘supporters’ fan typology, they are well-informed about their club and the competitions it competes in (Bouchet et al., 2011).
The perceived risk of consuming the CHL product has a weak negative impact on fan and viewer satisfaction (H8) and fan and viewer loyalty (H9), where both relationships are significant at p<.05, as depicted in Figure 6. These findings support the notion that the greater the doubts are about spending money and time for the CHL product or experience, the less satisfied and loyal fans and viewers will be. Still, given the weak degree of the relationships, the impact may be weak as well. A further consideration should be given to the type of fan targeted by the CHL. If the ‘supporter’ type is to be targeted, the impact may be rather weak, because ‘supporter’ type fans are passionate and “support their team all the time” (Bouchet et al., 2011).
Fan and viewer satisfaction
Respondents slightly agree when asked if they are happy with their decision to watch the Champions Hockey League 2019/20 (SAT1) and if they believe they did the right thing to watch it (SAT2). However, they slightly disagree when asked if they are satisfied with the hockey experience offered by the past season (SAT3). From this, it can be deduced that the CHL product did not satisfy the sports entertainment wants and needs of fans and viewers (cf. Back and Parks, 2003). Because fan and viewer satisfaction can be considered the overall emotional response to the offered brand experience following past purchases (Nam et al., 2011), a legitimate approach to improve satisfaction is to develop the brand experience through sensory, affective, cognitive, and behavioural elements (Brakus et al., 2009). It is important to note that the standard deviation is high for all satisfaction items, which means respondents have differing views on the subject.
Nevertheless, this research finds that CHL’s fan and viewer satisfaction has a strong positive impact on fan and viewer loyalty (H10) and is significant at p<.01 (see Figure 6). This is supported by findings in various literature that examines the relationship between brand satisfaction and loyalty (e.g. Brakus et al., 2009; Jin et al., 2016).
Fan and viewer loyalty
Respondents moderately agree when asked if they would like to watch the CHL in the future (LOY1). For the question if respondents would recommend the CHL to others (LOY2), the mean falls onto ‘4.00’, meaning the sample population neither agrees nor disagrees. Lastly, respondents slightly agree when asked if they would say positive things about the CHL to others (LOY3). In summary, fans and viewers will likely watch the CHL again, but may not try to persuade others to watch it, because they may not believe as much in the product. Various literature supports the notion that brand loyalty is affected by brand satisfaction (Brakus et al., 2009; Choi et al, 2011). Hence, in order to bolster overall brand loyalty, effective marketing and communications efforts should be designed and implemented to increase brand satisfaction (Batra and Keller, 2016). As with the satisfaction-items, the resulting mean should be considered with caution, because the loyalty-items recorded a high standard deviation.
Section 5: Validity, reliability and model fit
The validity and reliability of the construct can be assessed through Cronbach’s Alpha (α), composite reliability (CR), and average variance extracted (AVE). Generally, a value of α > .7 is expected for a scale to be reliable (Saunders et al., 2007). Figure 5 indicates that all applied scales, except for the perceived risk scale (with items RSK1/2/3), are above that threshold. However, all CR values are higher than .6 and, therefore, all scales can be accepted (Fornell and Larcker, 1981).
All items loaded clearly onto a specific factor with a value above .3 (cf. Costello and Osborne, 2005) through an exploratory factor analysis (PCA; Varimax with Kaiser Normalization). Yet, although five factors were expected for the five variables, only 2 factors were computed. The three items from the perceived risk scale loaded onto the one factor and all other items loaded together onto a second factor. This suggests an association between the given question-items in regard to the respondents of this research, namely fans and viewers of the Champions Hockey League.
Structural equation modeling was applied to evaluate the model fit, through which the following values were computed: χ2 = 272.663, df = 80, RMSEA = .067, GFI = .932, CFI = .980, NFI = .972, TLI = .974, AGFI = .898, PGFI = .621, and PNFI = .741. RMSEA is slightly off the recommended maximum value of .06. All other indices are above the suggested thresholds. Figure 7 compares the model fit indices computed for this study with suggested values from the literature and demonstrates a good fit to the collected data.
Section 6: Conclusion
This research examined the impact of the Champions Hockey League’s brand prestige on trust, perceived risk, satisfaction, and loyalty of ice hockey fans and viewers. A conceptual model developed by Jin et al. (2016) was successfully adapted and applied with a sample of 542 respondents. Nine of the ten hypothesised relationships were found to be significant. The first main takeaway based on the sample discussed in Section 3 is: CHL’s brand prestige strongly and positively influences brand trust, satisfaction, and loyalty; brand trust strongly and positively influences satisfaction and loyalty; and satisfaction strongly and positively influences loyalty (see Figure 6). The second main takeaway is: Brand prestige has only weak and negative influence on perceived risk, which means that additional elements need to be considered in order to reduce perceived risk; additionally, perceived risk has weak and negative influence on satisfaction and loyalty, which is supported by Baek et al. (2010) and Jin et al. (2016). These findings support the suggested marketing and communications efforts elaborated on in Section 4.
The main limitation of this study may be the large percentage of Swedish respondents (52.6%) within the employed sample, of which a considerable amount voiced negative sentiments, as portrayed in Figure 1. This was tested with sub-samples that included either only Swedish respondents or the sample without Swedish respondents. Negative sentiments of Swedish respondents became apparent through the test. Nonetheless, the results from examining the entire sample can be deemed valid, since the values of the means and correlations coefficients only vary moderately. A further limitation could be the timing of the data collection, which was held a couple of days before and after the CHL final game. Results may vary, if data was to be collected in the group stage of the competition.
In my opinion
This was a very interesting exercise for me. I was aware that the CHL may not be regarded as highly as some national ice hockey leagues, which actually inspired me to examine the brand prestige of the competition, but I did not expect such passionate comments about the CHL, especially the negative ones. Still, I enjoyed the conversation with fans from different countries and ice hockey clubs around this research. They helped me better understand the collected data and interpret the results. My suggestions on how to improve the CHL brand prestige in Section 4 are just high-level and would, of course, require in-depth conceptualisation of a strategy and design of respective integrated marketing and communications tactics. Still, if you follow the referenced literature, you may be able to deduce a possible strategy and tactics. If you do, please let me know what you came up with. Thanks a bunch for reading this article. Let me know what you think about it either in the comments section or on Twitter.
- Average Variance Extracted (AVE): A measure to assess construct validity (Fornell and Larcker, 1981)
- Composite reliability (CR): A measure to assess construct validity (Fornell and Larcker, 1981)
- Cronbach’s Alpha (α): A method for calculating the internal consistency of a questionnaire (Saunders et al., 2007, p. 374)
- Factor loading: Correlation coefficient for the variable and factor (Statisticssolutions.com, 2020)
- Mean: Average value calculated by adding the values of each case for a variable and dividing by the total number of cases (Saunders et al., 2007, p. 595)
- Standard deviation (STDEV): Spread of data values around the mean (Saunders et al., 2007, p. 601)
List of references
- Back, K-J. and Parks, S.C. (2003). A brand loyalty model involving cognitive, affective, and conative brand loyalty and customer satisfaction. Journal of Hospitality and Tourism Research, 27(4), pp. 419-435.
- Batchelora, B. and Formentin, M. (2008). Re-branding the NHL: Building the league through the “My NHL” integrated marketing campaign. Public Relations Review, 34, pp. 156-160.
- Bouchet, P., Bodet, G., Bernache-Assollant, I. and Kada, F. (2011). Segmenting sport spectators: Construction and preliminary validation of the Sporting Event Experience Search (SEES) scale. Sport Management Review, 14, pp. 42-53.
- Brakus, J., Schmitt, B. and Zarantonello, L. (2009). Brand Experience: What Is It? How Is It Measured? Does It Affect Loyalty? Journal of Marketing, 73(3), pp. 52-68.
- Carlson, B.D. and Donovan, D.T. (2013). Human Brands in Sport: Athlete Brand Personality and Identification. Journal of Sport Management, 27, pp. 193-206.
- Chaudhuri, A. and Holbrook, M.B. (2001). The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. Journal of Marketing, 65(2), pp. 81-93.
- CHL. (2019). Club info booklet season 2019/20. [online] Available at: https://www.championshockeyleaguebrand.net [accessed 8 Feb.].
- CHL. (2020a). CHL History: Where it all began. [online] Available at: https://www.championshockeyleague.com/en/chl-history/where-it-all-began [accessed 8 Feb.].
- CHL. (2020b). CHL Fan Challenge. [online] Available at: https://www.chl-fan-challenge.com [accessed 14 Feb.].
- Choi, Y.G., Ok, C. and Hyun, S.S. (2011). Evaluating Relationships among Brand Experience, Brand Personality, Brand Prestige, Brand Relationship Quality, and Brand Loyalty: An Empirical Study of Coffeehouse Brands. Available at: hscholarworks.umass.edu [accessed 9 Feb.].
- Harris, L.C. and Ogbonna, E. (2008). The dynamics underlying service firm-customer relationships: insights from a study of English Premier League soccer fans. Journal of Service Research, 10(4), pp. 382-399.
- Harwood, T. and Garry, T. (2015). An investigation into gamification as a customer engagement experience environment. Journal of Services Marketing, 29(6/7), pp. 533-546.
- Jin, N.P., Line, N.D. and Merkebu, J. (2016). The Impact of Brand Prestige on Trust, Perceived Risk, Satisfaction, and Loyalty in Upscale Restaurants. Journal of Hospitality Marketing & Management, 25(5), pp. 523-546.
- Nam, J., Ekinci, Y. and Whyatt, G. (2011). Brand equity, brand loyalty and consumer satisfaction. Annals of Tourism Research, 38(3), pp. 1009-1030.
- Rein, I., Kotler, P. and Shields, B. (2006). The elusive fan: Reinventing sports in a crowded marketplace. New York: McGraw-Hill.
- Sutera, D. (2013). Sports Fans 2.0: How Fans Are Using Social Media to Get Closer to the Game. Lanham, Maryland: Scarecrow Press.
- Tsiotsou, R.H. (2013). Sport team loyalty: integrating relationship marketing and a hierarchy of effects. Journal of Services Marketing, 27(6), pp. 458-471.
- Vecer, J., Ichiba, T., and Laudanovic, M. (2007). On Probabilistic Excitement of Sports Games. Journal of Quantitative Analysis in Sports, 3(3), pp. n/a.
- Veloutsou, C. and Moutinho, L. (2009). Brand relationships through brand reputation and brand tribalism. Journal of Business Research, 62, pp. 314-322.
- Yocco, V.S. (2016). Design for the Mind: Seven Psychological Principles of Persuasive Design. 1st ed. Shelter Island, NY: Manning Publications Co.
- Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing, 60, pp. 31-46.
References for Section 5 and Glossary
- Arbuckle, J.L. (1995). Amos 17 User’s Guide. Chicago, IL: SmallWaters Corporation.
- Costello, A.B. and Osborne, J.W. (2005). Best Practices in Exploratory Factor Analysis: Four Recommendations for Getting the Most From Your Analysis. Practical Assessment, Research & Evaluation, 10(7), pp. n/a.
- Fornell, C. and Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), pp. 39-50.
- Hooper, D., Coughlan, J., and Mullen, M.R. (2008). Structural Equation Modelling: Guidelines for Determining Model Fit. The Electronic Journal of Business Research Methods, 6(1), pp. 53-60.
- Hu, L., and Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), pp. 1-55.
- Mulaik, S.A., James, L.R., Van Alstine, J., Bennett, N., Lind, S. and Stilwell, C.D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin, 105(3), pp. 430-445.
- Saunders, M., Lewis, P. and Thornhill, A. (2007). Research Methods for Business Students, 4th ed. Harlow: FT Prentice Hall.
- Schermelleh-engel, K., Moosbrugger, H., and Müller, H. (2003). Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures. Methods of Psychological Research Online, 8(2), pp. 23-74.
Categories: Ice Hockey