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Is Financial Health a Determinant of Sport Success?

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Is Financial Health a Determinant of Sport Success? Is financial health a determinant of sport success? A study which examines how the financial health of professional ice hockey clubs in Sweden explains the sport success in the Swedish Hockey League (SHL). MASTER THESIS WITHIN: Business Administration NUMBER OF CREDITS: 30 ECTS PROGRAMME OF STUDY: Civilekonom AUTHOR: Marcus Hammarström & Albin Malmqvist JÖNKÖPING May 2019 Master Thesis in Business Administration Title: Is financial health a determinant of sport success? Authors: Marcus Hammarström & Albin Malmqvist Tutor: Argyris Argyrou Date: 2019-05-20 Key terms: Benchmarking, Financial benchmarking, Financial health, Ice hockey, Sport success, Grey Relational Analysis, Logistic Regression model. Abstract The purpose of this study is to find the relationship between financial health in an ice hockey club and its sport success. The study answers the research question: How can financial health of Swedish ice hockey clubs be able to explain the sport success in the Swedish Hockey League? Based on the research question, the study uses the theory Benchmarking and a more specific benchmarking terminology called Financial benchmarking. The study selects eight financial variables in order to benchmark the ice hockey clubs in the Swedish Hockey League (SHL). A particular methodology within financial benchmarking, called Grey Relational Analysis (GRA), is used in order to determine the financial health of the clubs in relation to each other and therefore be able to rank the clubs based on each individual variable. The same financial variables, with the addition of four non-financial variables and exclusion of two financial variables, are used in a selected Logistic Regression model to explain how the variables contribute to the sport success of the clubs. The main conclusions which can be drawn from the study are as follows: The variables Net sales and Net profit are the two only variables which are statistically significant and are able to contribute to sport success. Secondly, the club HV71 is overall the club with the most optimal financial health in SHL, among the 12 clubs investigated. Lastly, accounting trends within this industry affects the financial outcome and further how it explained sport success. Trends such as a minimal or no amount of long-term liabilities is common among the clubs, where instead the total amount of liabilities mainly consists of current liabilities. It can be further concluded that profitability, revenue and equity are financial corner stones in a hockey club which participates in SHL. i Acknowledgements We wish to thank our tutor, Argyris Argyrou, for his insight and guidance throughout the writing process. He has helped us with valuable feedback and expertise in accounting and thesis writing which made it possible for us to fulfill the purpose of this thesis. We also wish to acknowledge our fellow partners who during the seminars contributed with interesting thoughts and feedback in our research project to further develop it. In addition, we would like to thank our families and friends. We are grateful for their encouragement, positivity and support throughout the process of writing this thesis. ____________________ ____________________ Marcus Hammarström Albin Malmqvist Jönköping International Business School May 2019 ii Table of Contents 1 Introduction ...................................................................... 1 1.1 Background ............................................................................................ 1 1.2 The terminology of this study ................................................................. 3 1.3 Problem statement ................................................................................. 4 1.4 Purpose .................................................................................................. 5 1.5 Disposition of the thesis ......................................................................... 5 2 Frame of references ......................................................... 7 2.1 Benchmarking ........................................................................................ 7 2.1.1 Financial benchmarking ......................................................................... 8 2.1.2 Criticisms of benchmarking .................................................................... 9 2.2 Financial analysis in sport businesses .................................................. 10 2.3 Grey Relational Analysis ....................................................................... 11 2.3.1 Criticism of Grey Relational Analysis ................................................... 12 2.4 Final remarks ....................................................................................... 13 3 Methodology .................................................................... 15 3.1 Data collection ...................................................................................... 15 3.1.1 Sample selection ................................................................................... 15 3.1.2 A description of the data collection process .......................................... 16 3.1.3 Financial variables selection ................................................................. 17 3.1.4 Non-financial variables selection .......................................................... 18 3.2 Grey Relational Analysis ....................................................................... 20 3.3 Logistic Regression model .................................................................... 21 4 Results .............................................................................. 23 4.1 Logistic Regression model .................................................................... 23 4.2 Grey Relational Analysis ....................................................................... 25 4.2.1 Initial step ............................................................................................ 25 4.2.2 Normalisation step ............................................................................... 26 4.2.3 Deviation sequence ............................................................................... 27 4.2.4 Grey Relational Coefficient ................................................................... 28 4.2.5 Financial rankings ................................................................................ 29 5 Analysis ............................................................................ 31 5.1 Logistic Regression model .................................................................... 31 5.1.1 Underlying factors to Net sales and Net profit ...................................... 31 5.1.2 Non-financial aspects ........................................................................... 34 5.2 Grey Relational Analysis ....................................................................... 36 5.2.1 Profitability and revenue ...................................................................... 36 5.2.2 Assets, liabilities and equity ................................................................. 38 5.3 Overall analysis and limitations............................................................ 41 6 Conclusion ....................................................................... 43 7 Discussion ....................................................................... 45 iii 7.1 Societal and ethical concerns ................................................................ 45 7.2 Future research .................................................................................... 47 8 References ....................................................................... 48 9 Appendices ...................................................................... 52 Tables Table 1 The financial variables selected for the study……………………….18 Table 2 The non-financial variables selected for the study…………………. 19 Table 3 The variables selected for the Logistic Regression model…………. 22 Table 4 Logistic Regression model…………………………………………. 24 Table 5 Financial variables for all clubs…………………………………….. 26 Table 6 Normalisation step………………………………………………….. 27 Table 7 Deviation sequence…………………………………………………. 28 Table 8 Grey Relational Coefficient………………………………………… 29 Table 9 Rankings for each club and variable………………………………... 30 Appendices Appendix 1 Data collection…………………………………………………….52 iv 1 Introduction The first chapter provides an introduction to the study. To begin with, background information is provided, which is followed by a section of the terminology in the study. Further, the problem statement is described and lastly the purpose of the study is explained, which contains the research question and hypothesis development. This study examines how the financial health in professional ice hockey clubs in the Swedish Hockey League explains sport success. The study determines whether a certain level of financial health can contribute to the sport success in a certain club and season. The data consists of 12 selected hockey clubs over a period of the recent 10 seasons. Specific financial variables are used in the Grey Relational Analysis, to determine the financial health of each hockey club. A Logistic Regression Model is used in order to explain how the variables, financial and non-financial, can be able to contribute to the sport success in this league. 1.1 Background Ice hockey is not only a sport, it is also an industry and business that aim to maximize profits. The total amount of revenue from each of the clubs playing in the Swedish Hockey League last
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