Conjoint Analysis for Ticket Offerings at the Cleveland Indians

References

• Bates D, Maechler M, Bolker B, Walker S (2013) lme4: Linear mixed-effects models using Eigen and S4. Accessed July 11, 2013, http://CRAN.R-project.org/package=lme4.Google Scholar
• Chelst K, Yavuz BC (2011) Value-Added Decision Making for Managers (CRC Press, Boca Raton, FL).Crossref, Google Scholar
• Fisher E (2009) MLB FanPass to make paperless ticketing push. Accessed February 24, 2013, http://www.sportsbusinessdaily.com/Journal/Issues/2012/03/19/Leagues-and-Governing-Bodies/MLB-FanPass.aspx.Google Scholar
• Fylstra D, Lasdon L, Watson J, Waren A (1998) Design and use of the Microsoft Excel solver. Interfaces 28(5):29–55.Link, Google Scholar
• Gigerenzer G, Todd PM, ABC Research Group (2000) Simple Heuristics That Make Us Smart (Oxford University Press, New York).Google Scholar
• Greenwell TC, Popp N, Jordan JS, Brownlee E (2007) Customer preference and student tickets: Using conjoint analysis to develop ticket policy. Internat. J. Sport Management 8(3):280–294.Google Scholar
• Lee YH, Kang J-H (2011) Designing ticket price strategies for professional sports teams using conjoint analysis. Internat. J. Sports Marketing Sponsorship 12(2):124–137.Crossref, Google Scholar
• Mullen K, Ardia D, Gil D, Windover D, Cline J (2011) “DEoptim”: An R package for global optimization by differential evolution. J. Statist. Software 40(6):1–26.Crossref, Google Scholar
• Muret D (2008) Loaded tickets catch on among MLB teams. Accessed October 17, 2012, http://www.sportsbusinessdaily.com/Journal/Issues/2008/03/20080310/This-Weeks-News/Loaded-Tickets-Catch-On-Among-MLB-Teams.aspx.Google Scholar
• R Core Team (2011) The R project for statistical computing. Accessed November 11, 2011, http://www.R-project.org/.Google Scholar
• Samuelson P (1974) Complementarity: An essay on the 40th anniversary of the Hicks-Allen revolution in demand theory. J. Econom. Literature 12(4):1255–1289.Google Scholar
• Talluri KT, Van Ryzin GJ (2004) The Theory and Practice of Revenue Management (Springer, New York).Crossref, Google Scholar
• Van Zyl C (2008) A conjoint analysis of festival attributes for successful positioning of selected arts festivals in South Africa. Southern African Bus. Rev. 12(3):129–155.Google Scholar
• Varian H (2006) Intermediate Microeconomics: A Modern Approach (Norton, New York).Google Scholar
• Wittink DR, Vriens M, Burhenne W (1994) Commercial use of conjoint analysis in Europe: Results and critical reflections. Internat. J. Res. Marketing 11(1):41–52.Crossref, Google Scholar
• Zufryden FS (1983) Course evaluation and design optimization: A conjoint analysis-based application. Interfaces 13(2):87–94.Link, Google Scholar