Details

Autor(en) / Beteiligte

• Cho, S. Ray
• Lucas, Anthony F.
• Singh, Ashok K.

Titel

How do free-play offers affect gambling behavior?

Ist Teil von

• International journal of contemporary hospitality management, 2023-11, Vol.35 (12), p.4313-4329

Ort / Verlag

Bradford: Emerald Publishing Limited

Erscheinungsjahr

2023

Quelle

Emerald Management 200

Beschreibungen/Notizen

• Purpose This study aims to understand how free-play credits affect risk-seeking behavior in slot players. Extant results suggest they encourage risk aversion, counter to the primary aim of increasing spend per visit. The results inform operators as to the effectiveness of what has become the primary play incentive for casino marketers within many of the world’s markets. Design/methodology/approach Within a quasi-experimental grouped design, 365 days of player-level performance data from four different casinos were analyzed to determine whether player losses (casino revenues) and time played differed on visits that included free-play redemptions from those that did not. Hypotheses were tested via paired-samples t-tests and Mann–Whitney U tests. Findings On balance, neither player losses nor time played were significantly different on the free-play visits. Neither the house money effect nor the endowment effect was supported. The results were most consistent with the prospect-theory-with-memory editing rule. No findings indicated increased risk-seeking behavior associated with the free-play offers. Practical implications Casino operators are afforded insight related to how costly free-play campaigns affect gaming spend and playtime. Both are critical to understanding the impact of free-play on the gambler’s experience. Originality/value The 365-day samples extended existing research by analyzing the impact of free-play offers on risk-taking behaviors within the scope of a perpetual/ongoing campaign. Comparisons of observed daily behavior/outcomes were made between separate tiers of like-kind gamblers from each of four different casinos. Quasi-hedonic editing rules were applied to a multistage decision framework.