Optimal Ticket Pricing in the Sport Industry. the Case of the Italian Serie A

Optimal Ticket Pricing in the Sport Industry. the Case of the Italian Serie A

UNIVERSITÀ DEGLI STUDI DI VERONA DIPARTIMENTO DI SCIENZE ECONOMICHE Sede di Verona Corso di Laurea Magistrale in Economics Optimal ticket pricing in the sport industry. The case of the Italian Serie A Relatore Ch.mo Prof. Angelo Zago Laureando Federico Silvestri, VR403236 Anno Accademico 2016/17 Table of Contents INTRODUCTION ................................................................................................................................ 1 1.THE FOOTBALL INDUSTRY ........................................................................................................ 7 1.1 Introduction: the economic profile of European professional football ....................................... 7 1.2 Revenue sources of a professional football club ...................................................................... 10 1.3 Matchday-related revenues ....................................................................................................... 13 1.4 Demand for football and the relationship between revenue sources ........................................ 16 1.5 Concluding remarks .................................................................................................................. 21 2.TICKET PRICING IN THE FOOTBALL INDUSTRY ................................................................. 23 2.1 Introduction: ticket pricing issues ............................................................................................. 23 2.2 Optimal price level ................................................................................................................... 25 2.3 Price discrimination .................................................................................................................. 34 2.3.1 Second-degree quality discrimination: tier pricing ............................................................ 35 2.3.2 Second-degree discrimination: bundling (season tickets).................................................. 39 2.3.3 Third-degree discrimination: market segmentation ........................................................... 41 2.4 Variable ticket pricing .............................................................................................................. 42 2.4.1 Motivation ......................................................................................................................... 42 2.4.2 Implementation .................................................................................................................. 46 2.5 Dynamic ticket pricing ............................................................................................................. 48 2.6 Managerial issues concerning variable and dynamic ticket pricing ......................................... 54 2.7 Concluding remarks .................................................................................................................. 57 3.ESTIMATION OF GAME TICKETS DEMAND IN THE ITALIAN SERIE A ........................... 59 3.1 Introduction .............................................................................................................................. 59 3.2 Literature review ....................................................................................................................... 60 3.2.1 Determinants of attendance ............................................................................................... 60 3.2.2 Econometric modeling ....................................................................................................... 63 3.3 The model ................................................................................................................................. 67 3.3.1 Variables and sources ........................................................................................................ 67 3.3.2 Econometric model ............................................................................................................ 70 3.4 Empirical results ....................................................................................................................... 73 3.4.1 Diagnostics ........................................................................................................................ 73 3.4.2 Results ............................................................................................................................... 74 3.4.3 Subsample: matches against “David” ................................................................................ 77 3.5 Limitations and concluding remarks......................................................................................... 79 4.EMPIRICAL ANALYSIS ............................................................................................................... 83 4.1 Introduction .............................................................................................................................. 83 4.1.1 Methodology ...................................................................................................................... 84 4.1.2 Team-specific seasonal elasticities .................................................................................... 86 4.2 Propositions discussion (1-4) .................................................................................................... 88 4.2.1 Proposition 1 ...................................................................................................................... 88 4.2.2 Proposition 2 ...................................................................................................................... 91 4.2.3 Proposition 3 ...................................................................................................................... 94 4.2.4 Proposition 4 ...................................................................................................................... 95 4.3 Simulations ............................................................................................................................... 97 4.3.1 Impact of deviating from unitary elasticity ........................................................................ 97 4.3.2 Impact of variable ticket pricing ........................................................................................ 99 4.4 Further optimization: match-specific VTP vs category-specific VTP .................................... 104 4.5 Concluding remarks ................................................................................................................ 110 4.6 Appendix: optimal price level with a quadratic demand function .......................................... 112 4.6.1 Mono-product case .......................................................................................................... 112 4.6.2 Multi-product case and mono/multi product comparison ................................................ 114 4.6.3 Motivation for variable ticket pricing .............................................................................. 116 4.6.4 Motivation for proposition 6 ............................................................................................ 117 CONCLUSION ................................................................................................................................ 121 BIBLIOGRAPHY............................................................................................................................. 125 ACKNOWLEDGEMENTS .............................................................................................................. 131 IV Figures and Tables Figure 0.1: Hellas Verona Game Tickets Pricing p.2 Figure 1.1: Giulianotti’s matrix p.19 Figure 2.1: Optimal ticket price for a mono-product monopolist p.28 Figure 2.2: Optimal ticket price: mono-product vs multi-product monopolist p.33 Figure 2.3: Motivation for price discrimination: unexploited surplus p.35 Figure 2.4: Quality discrimination p.36 Figure 2.5: Inefficient distribution of seats per price category p.39 Figure 2.6: Motivation for Variable Ticket Pricing (mono-product monopolist) p.42 Figure 2.7: A DTP model with no time-discrimination p.52 Figure 2.8: Price movements during the selling periods for Virtus Entella (2017-18, first eleven p.54 home matches) Figure 4.1: Relationship between STH/Attendance and the season-specific elasticity, by club p.97 and season (2014-15 to 2017-18). Figure 4.2: Motivation for Variable Ticket Pricing, quadratic demand function p.116 Table 1.1: Revenues, Costs and Profits. Country-level, top-tier leagues data (2015) p.8 Table 1.2: Top 20 teams by Recurrent Revenues: Wages, Operating Costs, Profits&Losses p.8 (2015) Table 1.3: Revenue mix. Country-level, top-tier leagues data (2015). p.11 Table 1.4: Top 20 teams by Recurrent Revenues: Revenue-mix (2016) p.13 Table 1.5: Matchday figures by country (2015-16) p.15 Table 1.6: Capacity utilization, Serie A clubs (2014-15 to 2017-18, first half). p.17 Table 2.1: Pricing Strategies in the Italian Serie A (2017-18, first half of the season) p.38 Table 2.2: Price categories of selected teams (2017-18) p.47 Table 3.1: Descriptive statistics for dependent, explanatory and instrumental variables. p.70 Table 3.2: Diagnostic testing p.73 Table 3.3: First Stage Regression p.75 Table 3.4: Estimation of tickets demand: panel fixed-effects model with instrumental p.76 variables. Table 3.5: Model 2.1 (subsample “vs David”). Comparison with Model 2. p.78 Table 4.1: Analysis of elasticity estimates, by club and season p.87 Table 4.2: Average

View Full Text

Details

  • File Type
    pdf
  • Upload Time
    -
  • Content Languages
    English
  • Upload User
    Anonymous/Not logged-in
  • File Pages
    138 Page
  • File Size
    -

Download

Channel Download Status
Express Download Enable

Copyright

We respect the copyrights and intellectual property rights of all users. All uploaded documents are either original works of the uploader or authorized works of the rightful owners.

  • Not to be reproduced or distributed without explicit permission.
  • Not used for commercial purposes outside of approved use cases.
  • Not used to infringe on the rights of the original creators.
  • If you believe any content infringes your copyright, please contact us immediately.

Support

For help with questions, suggestions, or problems, please contact us