Research question: Does a football team’s decisions affect their fans’ passion?
Hypothesis: A football club’s decision does affect fans’ passion.
Intro – Doeke Dobma
Good morning and welcome to our presentation on Research Methods. This morning we are going to critically analyse two different papers. Our research question is ‘Does a football club’s decision affect their fans’ passion?’. Our hypothesis is ‘Football teams decisions do affect the loyalty of fans to their supported clubs’.
The qualitative paper that we found and therefore chose to analyse to find out different factors that affect fans’ passion with Football Clubs decision was written by Cayolla and Loureiro. And the paper is called, ‘Consequences of being deeply in love: The fan football club relationship’.
The quantitative paper that we chose to analyse to find out different factors that affect fans’ passion with Football Clubs decisions was written by Martin, Toleda, Palos-Sanchez. The paper is called, ‘How deep is your love? Brand love analysis applied to football teams’.
Summary of quantitative – Nick Golding
The quantitative paper which we have critically analysed is called “How deep is your love? Brand love analysis applied to football teams” by (Martin et al 2020). This paper is solely primary research with the objective of determining the main components of a brand that becomes “beloved” in the minds of consumers, specifically to this paper the brand in question was football teams. The paper falls under the top-down deductive theory, unlike the bottom up inductive theory, as it starts with a theory, followed by a hypothesis, an observation and then confirmation or rejection of the theory. Not only this but the paper is also ontology-based research due to the objectivism approach to the theory. As identified by the researchers, this is the first attempt at establishing a model of how brand love works with regards to football teams. However, researchers such as (Popp et al, 2016) have investigated how the relationship between the brand and the consumer can be strengthened. Martin et al’s paper could prove to support the findings of this previous paper. Furthermore, showing the importance and value this paper holds in publishing a proven model for ‘brand love’ which could support and provide opportunity for future secondary research based around these papers, the quantifiable data gathered could prove instrumental to future studies.
The authors carried out the primary quantitative research using an online questionnaire with a sample of exactly 824 participants, there is no mention of the sampling method however we can safely predict a form of random sampling was used. The quantitative casual study used partial least squares (PLS). Considering this paper was published during the first wave of the ongoing pandemic, an online questionnaire due to its ease and allowing participants to take part from their home would have been the only possible method of gathering a wide sample of quantifiable data. Not only this but it is important to take into consideration that the majority of the world was under lockdown during this period. PLS is a regression method that is used when the number of independent variables is larger than the number of data points. Margins of error are also measured so this method is robust, traditionally it is used to develop predictive models, which the authors are (Ng, 2013).
The authors findings were that Brand Love is a construct made up of five dimensions: passion, connection with the brand, intrinsic rewards, emotional attachment and thinking and frequent use. The paper also concludes that when framing the model specifically for football teams the consequences of brand love are loyalty, the willingness to invest and word of mouth communication. The findings can be supported by (Papadimitriou et al, 2019), where a questionnaire based on assessing brand personality and loyalty was answered by 724 Greek football fans. Their results showed that brand personality influences the fans positivity, loyalty, attractiveness and attitude towards them. This would support our hypothesis of a team’s decision affecting loyalty. An example would be a manager sacking causing a disconnection with fans. This paper replicated (Blank et al 2013, 2018). (Martin et al, 2020) proves the importance of a correct marketing strategy to build a long-term emotional relationship.
Summary of qualitative – Jamie Carr
The qualitative paper which we chose to analyse to find out the effect of football teams’ decisions on their fans was by Cayolla and Loureiro (2013). It mainly looks at the authenticity of football fans by exploring their personality and other parts of their background which prompts the question, what are the consequences of being in love with your club?
Research that’s been done since by behavioural economist Dr George Mackerron (2018) suggests that “football makes fans less happy”. However, in this case study Kayolla and Lureiro take a look at why that may be, with their primary research examining what the causes for consequence are on fans.
The methodology used by Cayolla and Loureiro (2013) for this paper was a long series of 28 structured interviews that were in depth and lasted around 30-70 minutes. The participants were picked from a list of 97 potential respondents between the ages of 22-70 and were 85% men, with a wide variety of working class jobs. They made sure everyone remained anonymous and allowed for a wide variation in ages. This was to give a better understanding of the ‘socio-cultural’ aspects that drive relationship behaviours regarding a club and its brand.
The 28 selected were contacted in line with the procedures of a snowballing sample type which started with personal contacts and then led on to create a list of 97 which Cayolla and Loureiro (2013) then selectively picked from for the final participants. This non probability method also falls right under the Grounded Theory as the data uncovered things such as social relationships and behaviours of groups. Previous studies of this theory by Ian Dey (2004) suggest it used to be an ‘alternative methodology’ however, as this case now shows, it’s clearly common.
When carrying out these methods through the interviews, before they started, they would request for consent to record and then later transcribe so there were no ethical problems. Transcription was used for later analysis and to help this process Cayolla and Loureiro (2013) used Nvivo, a computer software made to help qualitative researchers find insight and organise qualitative or unstructured data (Mcniff, November 9th, 2016) like these interviews.
The results of this analysis showed six main themes arise from the data; personal, financial, family, life planning, jobs and friends. These were all noticeable factors collected in the individual interviews which were then put into a table for a better understanding. The table showed that Personal was the most spoken about factor with 54% referring to it. This then caused Caylolla and Lureiro (2013) to make a subcategory for it, focusing on the positives and negatives in the relevant issues.
The positives show the joy of victory being very influential on their happiness whilst the negatives show that there are a lot of physical risks that can happen or have been suffered due to a lack of football security. Ultimately, because Personal was most referenced, these factors can be labelled the most impactful and furthermore meant the value of these two aspects were established to be equal.
Advantages of quantitative- Nick Golding
With reference to the advantages of the quantitative methods used by the authors, many factors of a positive nature can be drawn from the paper. Firstly, the use of Partial Least Squares allows the ability to handle more variables robustly, which when investigating an area of research where several different outcomes are possible is a real positive in regard to data collection and handling, there is also a much lower risk of chance correlation (Cramer, 1993). With the research being open to multiple answers, which was the case with the five dimensions, the use of PLS helps to improve the accuracy and legibility of the results.
The authors study is most definitely quantifiable due to the methods used, it is also clearly simple to understand and compare data to as I previously mentioned on how this new model can be used to support other studies as well as our hypothesis. The findings will be a particular advantage to sports clubs, not just football alone and particularly their marketing teams as the conclusions made from this paper can be used for clubs/ teams respective marketing strategies in the future. A further advantage to the methods used is that it has allowed a greater psychological understanding of how fans behave as consumers to their team of preference.
With regards to the method used for sample collection, it can be assumed a method of random probability sampling was used as an online questionnaire was used specifically for football fans, which is the target population in this paper. Random probability sampling eliminates sampling bias as the researcher isn’t picking the sample from personal preference, and when done properly the study can be well controlled, which when considering the paper was done during a pandemic, being in control is imperative for respectable results. As well as the samples safety, the sample being able to take part from the safety of their homes is reassuring for all involved.
Disadvantages of quantitative- Jack Devonport
When looking in more depth at the quantitative data in the study disadvantages become noticeable. In general quantitative datas main flaw is that it is very limited in how much of an understanding you can gain and what conclusions you can draw from it. Because quantitative data comes in the form of figures or multiple choice questioning it is difficult to probe deeper into answers and understand the thought process behind the answers that participants might give you unlike with qualitative data where you can ask open follow up questions to help with this understanding.
In this particular study a problem with the quantitative data is that there might be a lack of accuracy. One of the questions in the questionnaire asks how long the participant has been a football fan however being a fan is down to personal opinion. Some people see being a football fan as a casual affair so may say they have been a fan since they first watched the team on television while others may say you are not a fan until you attend a game live. This should have been set out in the questionnaire brief as this would have increased the accuracy of the quantitative results by removing the chance of them being altered solely by a difference in opinion between participants (The Social Research Centre, 2008).
In this paper the authors used a Partial Least Square method to analyse the quantitative data gathered by the questionnaire and the disadvantage to this is that although it can help show relations between multiple variables it offers very little explanation for those relations. The Partial Least Square method is a good way to present the data but it has difficulty interpreting the results in a way in which you can develop an understanding and draw conclusions (Pirouz, 2006). With these weaknesses considered, the main drawback for this study is that when quantitative research methods are used it is very difficult to interpret the data in a manner that allows conclusions to be drawn, no matter how large the sample size.
Advantages of qualitative- Jamie Carr
In the Kayolla and Lureiro (2013) case you can clearly see from their purposeful sampling that it benefitted and that having participants with better expertise boosted their results. The 28 that were selected were hopefully more aware of pros and cons involved with having this passion for their team, and therefore it allowed them to give a well rounded conclusion to the debate. Furthermore, rather than straight numbers or hard facts, having this greater knowledge or experience certainly meant the respondents chosen would have given a more detailed answer than what quantitative research could have produced. For example, fan ‘AS’ said “I take a part of my salary to follow the team”, “As we had no money, we slept in the airport” clearly showing the financial struggles the team causes them.
Some of the answers to the questions in the interviews were ‘coded’ using an inductive coding approach. The use of both axial and open coding was useful to the findings as it allowed Kayolla and Lureiero (2013) to categorise their results, in particular their ‘personal’ section, which then helped find the conclusion. For example, an assumption came from the research when a fan said “Even among friends there are many discussions, conflicts of ideas and interests” and this was then a connection in the results with the quote “Often it depends on where we are, we can not have our own opinions”. This could be due to the fact they are both implying there is tension when watching football with friends who support different sides, only a perspective that could be distinguished using qualitative research.
Qualitative research also has an advantage because its opinionated results are always analysed to find a conclusion. This is beneficial because it carries out in depth research when trying to establish a different stance on the variable. An example of this would be when fan ‘JO’ said “to be a member of my club (paying monthly) and go to the games I made many sacrifices” implying that the clubs prices required them to make life changes. This shows that the analysis can spot a change of view and ultimately find another consequence of being in love with your team.
Disadvantages of qualitative- Jack Devonport
From delving deeper into studies we also realised that there are disadvantages to using qualitative research techniques as a way of obtaining data to investigate this hypothesis. The major downside of qualitative data is that because the interviewee is free to express themselves in their answers they become very subjective. Although you can analyse an answer to draw a conclusion it is very difficult to compare multiple interviewee’s data to form a generalised conclusion because the answers will be completely subjective to the person. No matter how to form a sample group you will always see differences in how the subject represents the demographic because of their individual expressive answers to what are very open questions. Another disadvantage of qualitative data is that the skill set of the research group can heavily affect the quality of the data gathered. As previously mentioned the advantage of qualitative data is the ability to probe further into answers with open questions and follow up questions in the interview however if the researcher struggles to gain rapport with the interviewee it can severely limit the quality and the depth of the data acquired.
The problem with the qualitative data within this study is that participants were sampled using snowball sampling starting from personal acquaintances and although this means that the researchers will likely have good rapport with the interviewees it will be difficult to apply data to a larger group of people as well as opening the door to potential research bias. In the conclusion of the study the researchers state that all the interviews were acquired with only one club, in one country and this is because of the snowball method. The participants were gathered via personal acquaintance and this is why the data all revolves around one club. This means the qualitative data in this study is effectively invalidated when generally applying the findings. Any conclusions drawn are limited to the specific club used in the study unless the method is repeated by other research groups in other areas. To counter this the study could have used volunteer sampling which is where a study brief is put out to the public and anyone who feels like they fit the criteria for the demographic required can volunteer to participate in an interview (Morse, 1991). This would help this study in particular because it allows participants to be from all over the world, supporting all different clubs while still allowing the researchers to ensure the qualitative data is valid by making sure the participants are football fans. They do this by mentioning in the brief that volunteers should be football supporters
Summary of research, conclusion- Doeke Dobma
In Conclusion, both papers show positives and negatives to the argument. The qualitative paper uses 28 in depth interviews which is a good way of finding more in-depth results. However considering the amount of fans there are in the world, 28 is only a small minority and you would need more fans to partake in the interviews to get more reliable and trustworthy results to answer our research question. However despite the small number of fans partaking in the interview, the age range was very broad as were the professions and jobs of the 28 fans, which could help us find out whether age and type profession you have could affect your love for a football club. Even though the interviews were all of different backgrounds it would have made the result more clearer if they used more types of subjects for example, what country they’re from and what clubs they support. However most themes used in this paper would in an ideal world help us find our final result. Participants to the interview were only being asked regarding one football club, so if they supported different clubs that could be performing well or performing poorly we could have had more reliable and a wider range of trustworthy results to conclude to our research question. Overall the qualitative paper did not help us find out our answer to our question as it was only based around one club so we couldn’t see if another football club’s decision could affect fans’ passion. However the results from the qualitative paper were clear to see that the fans were always passionate towards the club no matter what decision but there weren’t enough themes and data to help us answer or question. This paper would give us an inductive answer where we could only get a theory instead of a straight up clear answer, this paper needed more samples.
The quantitative paper had 824 participants using an online questionnaire as primary source of research. This already would have helped us find an answer to our question better than the qualitative paper purely because there are more participants involved helping us to see a clearer and more reliable correlation on how football clubs’ decisions affect fans. Because the quantitative paper uses more participants for its primary research it will give us a deductive answer which means it gives us confirmation to our question and will back up our hypothesis or will prove our hypothesis wrong. In the quantitative paper it gives us statistical analysis where as previously said can give us a clear visual correlation between football clubs’ decisions and the change in passion and loyalty by fans. Although this quantitative paper does make it difficult to notice the themes they used considering the qualitative paper used multiple to give us a broad and convenient idea that people from that different backgrounds were asked. If there were noticeable themes involved in the quantitative paper it would have been more helpful for us to find out whether our hypothesis was correct or not. However overall we believe that the quantitative paper added more security to giving us an answer to our research question and helped us understand if our hypothesis was correct. This is because the number of samples was much greater than that of the qualitative paper. The qualitative paper would have had to use a much larger focus group for us to find a clear correlation with our research question and hypothesis. The quantitative paper helped us notice this clear correlation. So overall the quantitative paper was of better use for us.
If we were to research our question we would use a quantitative approach this way we could get a variety of different people and a larger sample to be able to find out a more transparent correlation. As well as there will be more people being used as samples compared to a qualitative approach. Thank you for listening.
References
Cayolla, Ricardo & Loureiro, Sandra. 2013. Consequences of Being Deeply in Love: the Fan-football Club Relationship – https://www.researchgate.net/publication/277475053_Consequences_of_Being_Deeply_in_Love_the_Fan-football_Club_Relationship
Cramer, R.D. 1993. Partial Least Squares (PLS): Its strengths and limitations. Perspectives in Drug Discovery and Design 1, 269–278.
Dey, Ian. 2004 “Grounded Theory” Qualitative research practice, Chapter 5, pg 80, Sage Publications – https://books.google.co.uk/books?hl=en&lr=&id=vazvXmmq4hkC&oi=fnd&pg=PA80&dq=grounded+theory+research+paper&ots=praSjMMbuk&sig=qnq9FSYFGNTi7mTiPuKehaKeTSE#v=onepage&q=grounded%20theory%20research%20paper&f=false (accessed: 21/2/21)
Dr George Mackerron. 2013. Football makes fans less happy, University of Sussex – http://www.sussex.ac.uk/broadcast/read/44576 (accessed: 22/2/21)
Morse, J. 1991. Qualitative Nursing Research. Sage [accessed on 23/2/21] available at: https://books.google.co.uk/books?hl=en&lr=&id=_-NyAwAAQBAJ&oi=fnd&pg=PA127&dq=best+sampling+method+for+qualitative+research&ots=9Kmnc9feg9&sig=pcBfUIBkJ23MoZzfse_DS3ehYs4#v=onepage&q&f=false
Kath, Mcniff, 2016, “What is Qualitative Research?”, Nvivio – https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/resources/blog/what-is-qualitative-research (accessed: 21/2/21)
Ng, Kee Siong. 2013. “A simple explanation of Partial Least Squares” Available at: http://users.cecs.anu.edu.au/~kee/pls.pdf (webpage accessed: 21st February 2021)
Papadimitriou, D., Kaplanidou, K., Alexandris, K. and Theodorakis, N. (2019), “The brand personality of professional football teams: A refined model based on the Greek professional football league”, Sport, Business and Management, Vol. 9 No. 5, pp. 443-459
Pirouz, D. 2006. An Overview of Partial Least Squares. Pp9 [accessed on 23/2/21] available at: https://www.researchgate.net/publication/228296847_An_Overview_of_Partial_Least_Squares
Popp, B., Germelmann, C.C. and Jung, B. (2016), “We love to hate them! Social media-based anti-brand communities in professional football”, International Journal of Sports Marketing and Sponsorship, Vol. 17 No. 4, pp. 349-367.
Scribbr. 2020. “An Introduction to Quantitative Research” Available at: https://www.scribbr.com/methodology/quantitative-research/ (webpage accessed: 22nd February 2021)
Stadler Blank, Ashley & Koenigstorfer, Joerg & Baumgartner, Hans. 2017. Sport team personality: It’s not all about winning!. Sport Management Review. 21.
The Social Research Centre, 2008. Football Passions. Pp4. Canon [accessed on 23/2/21] available at: http://www.sirc.org/football/football_passions.pdf
Velicia Martín, F., Toledo, L.D. and Palos-Sanchez, P. 2020, “How deep is your love? Brand love analysis applied to football teams”, International Journal of Sports Marketing and Sponsorship, Vol. 21 No. 4, pp. 669-693.
My Individual Research:
- About quantitative data
- Quantitative research is the method of collecting and analysing numerical data.
- Used to find patterns and averages or make predictions.
- Results are generalised to a wider population.
- Opposite of qualitative research, no non-numerical data is gathered.
- Can be used for Descriptive, Correlational or Experimental research.
- Aim/Methodology/Findings
- Aim- Determine the components of a brand that becomes loved in the minds of its consumers. The brand being football teams and the consumer being their fans.
- Method- Quantitative casual study using PLS.
- Casual study is the investigation into a cause and effect relationship.
- Sample of 824 participants who all did a online questionnaire.
- Findings- Brand love is constructed from five areas, passion, connection, intrinsic rewards, emotional attachment and use.
- Positives/Negatives
- Consequences are loyalty, willingness to invest and word of mouth communication.
- Greater emotional attachment results in greater investment.
- First analysis of establishing a model between brand love and the consumer.
- Supports Papadimitriou et al, 2019
- Done during a pandemic, sample safety important
- About PLS
- PLS- is a regression model used when the number of independent variables used is greater than the number of data points.
- PLS- allows robust handling of data

















