and their effect on player bases

An investigation in the price

determinants of video games

and their effect on player bases

A Master thesis by Redmer Nijboer

Content

Dutch gaming industry:

• 11.5% growth in revenue between 2015 and 2018.

• In the same period, job growth of 10%.

United States gaming industry:

• 35.7% growth in revenue between 2014 and 2016.

• Larger than the box office revenues. • Achieving exponential growth over the

last years.

Yet….

• Bankruptcy rates are high among game developers and publishers. • Substantial increase in the amount

of released games.

• How will these two trends affect the market (i.e. prices and

consumption) of video games?

Background and literature

• Academic research efforts into the video gaming industry have been rather sparse.

• Mostly qualitative analyses. (Marchand et al. (2013); Rysman (2009)). • Quantitative analyses are meagre (e.g. aggression effects)(Shankar et al.

(2003); Dill et al. (1998)).

• Dynamic processes of the gaming industry have not been conducted.

Background and literature

• Generally speaking, the entertainment suffers from this problem.

• In the entertainment industry, CDs and DVDs are most similar to video games.

• For these products, prices have been the most straightforward quantifiable variables.

• For factors driving prices:

• CD: digital retailers are cheaper than brick-and-mortar stores (Rabinovich et al. (2008)). No real literature on the effect of CD characteristics.

• DVD: genres, studios, ratings, seasonality, popularity affect WTP consumers (Mukherjee & Kadiyali (2018); Li & Tang (2011))

Background and literature

• Summed up: pricing (dynamics) in the entertainment industry have rarely been investigated.

• Video gaming industry in particular.

• The same holds for the number of consumers.

• Best research assesses proxies (e.g. box office revenues)(Terry et al. 2011; Pangarker & Smit (2013))

Background and literature

• Therefore, in this thesis we investigate the relation between prices and number of players. In particular:

Hypotheses

From the literature we set the following hypotheses. • H1: Prices of the same genre are affected equally.

• H2: Popular video game titles are priced more highly than less popular titles.

• H3: Prices are affected equally due to a market trend.

• H4: Prices of different genres are set independently of the country they are sold in.

Research goals

In addition, we set the following goals for the analysis.

1. Global evaluation of price development and trends of video games between countries and genres (hypothesis testing).

2. Assess the relative influence of different factors on the prices of video games (i.e. decomposition of the variance).

Research framework

• Affect all games in the market.

• Genre level effect G.

• Allows for quantification of

asymmetries in genre level consumer preferences.

• Country level effect C.

• Accounts for disparities for country level consumer preferences.

Research framework

hierarchical factor model (DHFM) to analyse

dynamics of prices.

• Hierarchy levels: market-wide (1), genre level (4), country (5), prices

Research framework

• The extracted factors from the DHFM will be used for vector autoregressive models.

• Particular interest in the impulse response functions for number of players.

Data

• Prices/players/Twitch viewer data obtained from Steamdb.info.

• Minimum prices per week. Mean number of players/TV per week.

• Top 100 grossing PC games of 2016.

• Divided into four groups: platina, gold, silver, bronze.

• Qualitative measure of popularity.

• Two year period. • Data provide…

• A sufficient length of sample period.

• Sufficient amount of variation in the prices.

Data

• Genres identification from within sample.

• Top five ‘user tags’ on the Steamdb website.

• Hierarchical cluster analysis (Ward’s method)

• Four genres identified:

• Action/AAA

• RPG/Action/Adventure • Indie

Data

• Countries selected based

upon PC gaming market size. • NOTE: Europe is not a

country but a region.

• Prices are exchange rate corrected.

Country Market size in millions USD Currency

China 13,100 Chinese Renminbi (RMB) United States 5,300 US Dollar (USD)

Data

Data

Data

• Preliminary evidence of different price dynamics between genres.

• Not so much between countries.

• DHFM estimation for relative shares.

• Variance decomposition

Estimation results

Genre 2: RPG/Action/Adventure

- Most notable variance decomposition stems from Japan.

- Generally, the factors contribute rather similarly across countries for this genre.

Genre 4: Simulation/Strategy

- Market wide factor plays a minor role in explaining prices. - Idiosyncratic component is

rather large.

Top panel: Genre 1 (Action/AAA) and genre 2 (RPG/Action/Adventure). Bottom panel: Genre 3 (Indie) and genre 4 (Simulation/Strategy).

Estimation results

• Vector autoregressive analyses’ impulse response functions for the number of players of a genre.

• Only conducted for genre one (Action/AAA) and two (RPG/Action/Adventure).

• General findings:

• Some signs of endogeneity among the models (country block level factors). • Effects are mostly similar for each country.

Estimation results

Estimation results

Conclusion

• H1: Prices of the same genre are affected equally. → Rejected • H2: Popular video game titles are priced more highly than less

popular titles. → Accepted

• H3: Prices are affected equally due to a market trend. → Accepted • H4: Prices of different genres are set independently of the country

they are sold in. → Partially accepted

• H5: Indie video games will have a lower mean and higher variance →

Conclusion

• Prices exhibit different pricing patterns, dependent on the genre and the country.

• Suggestive of different demand structures.

• Market forces have significant, substantial and lasting impact on the amount of players of a game.

• Discount seasons are highly influential.

• Genre and country forces also have an impact, albeit to a lesser degree.

• Evidence of network effects of games.

Implications and discussion

• Centralized marketplaces like Steam possess significant power. • Players are likely await discount seasons.

• Video game publishers are subject to prisoner’s dilemma.

• To increase profits, publishers can consider offering different video games.

• Simulation/Strategy games have the largest idiosyncratic component.

• Marketeers should find balance between marketing and sales.

Discussion

• DHFM relevant for analysing differentiated products’ pricing.

• Yet, video games remain unique

• Generalizability of results

• Other marketplaces (e.g. EA Origin) • Console gaming

• Other industries (CD & DVD)

• Marketing/business perspective

• Video game making process

• Quality of experience measurement

References

• Shankar, V., & Bayus, B. L. (2003). Network effects and competition: An empirical analysis of the home video game industry. Strategic Management

Journal, 24(4), 375-384.

• NU.nl. 2019. Omzet Nederlands game-industrie stijgt flink. https://www.nu.nl/economie/5956392/omzet-nederlandse-game-industrie-stijgt-flink.html, accessed on 30th of June 2019

• Entertainment Software Association. 2019. 2019 Essential Facts About the Computer and Video Game Industry. https://www.theesa.com/wp-content/uploads/2019/05/ESA_Essential_facts_2019_final.pdf, accessed on 30th of June 2019

• Statista. 2019. Number of games released on steam worldwide from 2004 to 2018. https://www.statista.com/statistics/552623/number-games-released-steam/, accessed on 30th of June 2019

• Marchand, A., & Hennig-Thurau, T. (2013). Value creation in the video game industry: Industry economics, consumer benefits, and research opportunities. Journal of Interactive Marketing, 27(3), 141-157.

• Rysman, M. (2009). The economics of two-sided markets. Journal of economic perspectives, 23(3), 125-43.

• Dill, K. E., & Dill, J. C. (1998). Video game violence: A review of the empirical literature. Aggression and violent behavior, 3(4), 407-428.

• Rabinovich, E., Maltz, A., & Sinha, R. K. (2008). Assessing markups, service quality, and product attributes in music CDs' Internet retailing. Production and Operations Management, 17(3), 320-337.

• Mukherjee, A. & Kadiyali, V. 2018. The Competitive Dynamics of New DVD Releases. Management Science 64(8):3536-3553.

https://doi.org/10.1287/mnsc.2017.2795

• Li, B. Tang, F. 2011. Online pricing dynamics in Internet retailing: The case of the DVD market. Electronic Commerce Research and Applications Volume 10, Issue 2, March–April 2011, Pages 227-236

References

• Ataman, M. B., Van Heerde, H. J., & Mela, C. F. (2010). The long-term effect of marketing strategy on brand sales. Journal of Marketing Research, 47(5), 866-882.

• Kopalle, P. K., Mela, C. F., & Marsh, L. (1999). The dynamic effect of discounting on sales: Empirical analysis and normative pricing implications. Marketing Science, 18(3), 317-332.

• Terry, N., Butler, M., & De’Armond, D. A. (2011). The determinants of domestic box office performance in the motion picture industry. Southwestern Economic Review, 32, 137-148.

• Pangarker, N.A. Smit, E.M. 2013. The determinants of box office performance in the film industry revisited. South African Journal of Business Management, 44(3)