A number of research problems are uncovered due to data limitation which presents future opportunities for future research in this area. The data we obtained is limited with only price and date of the performances. There are still a lot of data that can be tracked as many performance tickets are sold by online systems. Customers need to click many steps before making a purchase. When those customer behaviors are documented, people can discuss topics related to purchase process and link the information to ticket sales speed and cumulated sales. Another information we do not have is seat numbers. When seat number data is combined with sales data, we can map our analysis on to the scope of actual theater in a much more realistic scope. A price band is consist of plenty of seats with varied views. Most consumers think of the seat location and the cost-performance ratio in corresponds first when making a purchase. The result of the correlation might vary among theaters. Ticket selling has many interesting characteristics. As mentioned
before, it has various price bands in a performance and one interacts with another. It has many uncertainties in comparison to that of normal physical goods like books. Due to the growing convenience of data acquisition, there are many aspects of ticket selling that can be discussed in the future.
Appendix A
Figures of Exploratory Data Analysis
(a) N umSoldikt of CumSoldikt (b) N umSoldikt of CumOtherikt
Figure A.1: The First Part of Experiment Analysis.
(c) Cumulated Sales of CumSelfikt (d) Cumulated Sales of CumOtherikt
(e) P eriodk (f) T imek
(g) Regionk (h) Y eark
Figure A.1: The First Part of Experiment Analysis (cont.).
(a) N umSoldikt of Performances (b) Cumulated Sales of P1kt
(c) P eriodk (d) T imek
(e) Regionk (f) Y eark
Figure A.2: The Second Part of Experiment Analysis
Bibliography
Alevy, J. E., M. S. Haigh, J. A. List. 2007. Information cascades: Evidence from a field experiment with financial market professionals. The Journal of Finance 62(1) 151–180.
Anderson, E. W. 1998. Customer satisfaction and word of mouth. Journal of service research 1(1) 5–17.
Bikhchandani, S., D. Hirshleifer, I. Welch. 1992. A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of political Economy 992–1026.
Bone, P. F. 1995. Word-of-mouth effects on short-term and long-term product judgments.
Journal of business research 32(3) 213–223.
Boyd, D. W., L. A. Boyd. 1998. The home field advantage: Implications for the pricing of tickets to professional team sporting events. Journal of Economics and Finance 22(2-3) 169–179.
Chen, Y., Q. Wang, J. Xie. 2011. Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of marketing research 48(2) 238–254.
Courty, P. 2002. Ticket pricing under demand uncertainty .
Courty, P. 2003. Some economics of ticket resale. The Journal of Economic Perspectives 17(2) 85–97.
Drayer, J., D. A. Rascher, C. D. McEvoy. 2012. An examination of underlying consumer demand and sport pricing using secondary market data. Sport Management Review 15(4) 448–460.
Gallego, G., G. Van Ryzin. 1994. Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management science 40(8) 999–1020.
Hall, R. L., C. J. Hitch. 1939. Price theory and business behaviour. Oxford economic papers (2) 12–45.
Herr, P. M., F. R. Kardes, J. Kim. 1991. Effects of word-of-mouth and product-attribute information on persuasion: An accessibility-diagnosticity perspective. Journal of con-sumer research 17(4) 454–462.
Ho, E., T. Kowatsch, A. Ilic. 2014. The sales velocity effect on retailing. Journal of Interactive Marketing 28(4) 237–256.
Howard, D. R., J. L. Crompton. 2004. Tactics used by sports organizations in the united states to increase ticket sales. Managing Leisure 9(2) 87–95.
Hsieh, C. Y. 2015. The impact of pricing on tickets sales in the theater industry.
Huntington, P. A. 1993. Ticket pricing policy and box office revenue. Journal of Cultural Economics 17(1) 71–87.
Kimes, S. E. 1989. The basics of yield management .
Kotler, P. 2009. Marketing management: A south Asian perspective. Pearson Education India.
Kung, M., K. B. Monroe, J. L. Cox. 2002. Pricing on the internet. Journal of Product &
Brand Management 11(5) 274–288.
Leslie, P. 2004. Price discrimination in broadway theater. RAND Journal of Economics 520–541.
Liang, X., L. Ma, L. Xie, H. Yan. 2014. The informational aspect of the group-buying mechanism. European Journal of Operational Research 234(1) 331–340.
Liu, Y. 2006. Word of mouth for movies: Its dynamics and impact on box office revenue.
Journal of marketing 70(3) 74–89.
McAfee, R. P., V. Te Velde. 2006. Dynamic pricing in the airline industry. forthcoming in Handbook on Economics and Information Systems, Ed: TJ Hendershott, Elsevier .
Nahmias, S. 1982. Perishable inventory theory: A review. Operations research 30(4) 680–708.
Ramanathan, R. 2006. Stocking and discounting decisions for perishable commodities using expected profit approach. International Journal of Retail & Distribution Man-agement 34(2) 172–184.
Rascher, D. A., C. D. McEvoy, M. Nagel, M. T. Brown. 2007. Variable ticket pricing in major league baseball. Journal of Sport Management, Forthcoming .
Rosen, S., A. M. Rosenfield. 1997. Ticket pricing 1. The Journal of Law and Economics 40(2) 351–376.
Sezen, B. 2004. Expected profit approach used in discount pricing decisions for perishable products. International Journal of Retail & Distribution Management 32(4) 223–229.
Shapiro, S. L., J. Drayer. 2012. A new age of demand-based pricing: An examination of dynamic ticket pricing and secondary market prices in Major League Baseball. Journal of Sport Management 26 532–546.
Tseng, Y. C. 2016. The influence of herd behavior on sales volume and inventory in online shopping. Department of Internet Business, Chung Yuan Christian University 1–122.
Tsiros, M., C. M. Heilman. 2005. The effect of expiration dates and perceived risk on purchasing behavior in grocery store perishable categories. Journal of marketing 69(2) 114–129.
Watts, D. J. 2002. A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences 99(9) 5766–5771.
Weatherford, L. R., S. E. Bodily. 1992. A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing. Opera-tions Research 40(5) 831–844.
Welch, I. 2000. Herding among security analysts. Journal of Financial economics 58(3) 369–396.
You, P. S. 1999. Dynamic pricing in airline seat management for flights with multiple flight legs. Transportation Science 33(2) 192–206.
Zhao, W., Y. S. Zheng. 2000. Optimal dynamic pricing for perishable assets with nonho-mogeneous demand. Management science 46(3) 375–388.