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EXPLORING THE VALUE OF PURCHASING ONLINE GAME ITEMS

Bong-Won Park, Kun Chang Lee Computers in Human Behavior. EXPLORING THE VALUE OF PURCHASING ONLINE GAME ITEMS. Group 6 Chap Yuen Kwan, Rachel (11007931) Choi Man Hei , Vivien (11002417) Leung Chui Ting, Irene Lo Sin Hei , Alistair (11009322). Agenda. Introduction Research objective

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EXPLORING THE VALUE OF PURCHASING ONLINE GAME ITEMS

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  1. Bong-Won Park, Kun Chang Lee Computers in Human Behavior EXPLORING THE VALUE OF PURCHASING ONLINE GAME ITEMS Group 6 Chap Yuen Kwan, Rachel (11007931) Choi Man Hei, Vivien (11002417) Leung Chui Ting, Irene Lo Sin Hei, Alistair (11009322)

  2. Agenda • Introduction • Research objective • Research model and its application • Hypotheses • Measurement and data collection • Internal consistency, reliability, validity, structural model • Results and implication

  3. Introduction (1/3) • Online game market has expanded dramatically in terms of both market size and number of gamers, as a result of rapid development of the Internet • Need to have business models to reflect gamers’ changing preferences

  4. Introduction (2/3) • Two kinds of business models • Subscription-based model: gamers pay fixed subscription fee on a monthly basis • Free-to-play model: the games are free-of-charge; but are required to purchase additional game items, e.g. clothing, swords, and guns to enhance power and appearance of character

  5. Introduction (3/3) • Previous studies have revealed motivation for free-to-play gamers to purchase game items • BUT there is NO research to explore why game users purchase online game items in the free-to-play game market

  6. Objectives of Research (1/1) • Understanding the value of purchasing game items • Identifying relevant factors affecting game users’ intentions to purchase game items

  7. Research Model (1/1) • The theory of consumption values (TCV) developed by Sheth, Newman, and Gross (1991)

  8. Theory of consumption value (TCV)(1/3) • Functional value: “the utility that is perceived to possess criteria salient to physical or functional purposes” • Social value: “derived from its association with one or more distinctive social groups”

  9. Theory of consumption value (TCV)(2/3) • Emotional value: “derived from feelings or affective states” • Epistemic value: “capacity to provide novelty, arouse curiosity, and/or satisfy knowledge-seeking aspirations

  10. Theory of consumption value (TCV)(3/3) • Conditional value: “capacity to provide temporary functional or social value in the context of a specific and transient set of circumstances or contingencies

  11. Application of TCV (1/3) • Review of literature • Common features associated with purchase of virtual goods

  12. Application of TCV (2/3) • Enjoyment value (similar to emotional value in TCV): increase the fun associates with playing the game • Character competency value (associated with functional value in TCV): purchase game items to increase strength and power in the game context

  13. Application of TCV (3/3) • Visual authority value (includes social value in TCV): purchase game items to adorn their characters, or to increase their social status in the context of the game • Monetary value (not mentioned in TCV): cost-effective and reasonably priced • Epistemic value, conditional value in TCV: not applicable

  14. Hypothesis

  15. Hypothesis • H1. The integrated consumption value of an online game item (including the four values) is positively related with a user’s intentions to purchase that item. Enjoyment Character competency Integrated value of purchasing game item Game item purchase intention H1 Visual Authority DV IV (1) Monetary

  16. Hypothesis • H2. Character identification is positively related to the intention to purchase game items. Character identification Game item purchase intention H2 DV IV (2)

  17. Hypothesis • H3. Satisfaction about game is positively related to the intention to purchase game items. Satisfaction about game Game item purchase intention H3 DV IV (3)

  18. Measurement and Data Collection • Data collection method: Survey • Survey procedure:

  19. Measurement and Data Collection • Population: online game users is about 18M • Non-probability sample, self-selection • Data collection: Survey • Initial: 384 participants (83 incomplete) • 26 students responded further • 327 valid questionnaires

  20. Demographic information of respondents

  21. Questionnaire Items

  22. Development of questionnaire • Pilot study  finalize the questionnaire • 20 Korean university students & revised some vague items on the questionnaire • PLS (partial least squares) approach • To find & understand existing relationships • To analyze descriptive & predictive relationships

  23. Partial Least Squares (1/1) • The first step to find and understand existing relationships • A powerful analytical tool in various areas • (Rosipal & Krämer, 2006) • Used to estimate relationships between observed and latent variables in IT research • (Gefen & Straub, 2005; Geri &Naor-Elaiza, 2008; Lee & Chung, 2009; Lee, Pi, Kwok, & Huyhn, 2003) • Useful in analyzing descriptive and predictive relationships • (Sellin & Keeves, 1997)

  24. Internal Consistency (1/1) Values > 0.7  moderate

  25. Reliability (1/1) • Composite reliability > 0.7 • AVE > 0.5 • (Fornell & Larcker, 1981; Fornell, Tellis, & Zinkhan, 1982)  Satisfied

  26. Validity (1/3) • Principal components analysis

  27. Validity (2/3) • Factor loadings ≥ 0.6 • No cross-loading ≥ 0.4 • ( Hair, Anderson, Tatham, & Black, 1998) • Correlation between two factors < square root of AVE values • ( Fornell & Larcker, 1981; Fornell et al., 1892)

  28. Validity (3/3) • Variables are valid

  29. Structural Model (1/1)

  30. Result and Implication (1/3) • The results of the PLS analysis indicate:- • Valuable Game items • their intention to purchase these game items in the future increases • Play online games just for fun • Show off through various values that the game items provide • Visual authority value

  31. Result and Implication (2/3) • Character Identification • Game companies could offer more items for purchase • Make users more unique and powerful in the gaming world • Design game characters that appear more realistic • E.g. Free Style, FIFA Online • Leads game users to become immersed in the game because they identify with the characters

  32. Result and Implication (3/3) • Regardless of Satisfaction • Users do not necessarily intend to purchase game items • Conventional wisdom: Satisfaction leads to increased intention. • However, this does not applyto the purchase of game items • Want more game items = Pay more • Pricing is important

  33. Conclusion (1/1) • In the online game business: • Subscription-based • Free-to-play • Markets in Korea, Japan, and Taiwan • This study is one of the first of its kind in its focus on free-to-play online games. • Online game users experience character competency, enjoyment, visual authority, and monetary value from using and purchasing online game items.

  34. Limitation (1/1) • Sample: Mainly of young male game users • Only included game users who previously purchased online game items • Could be extended in several ways:- • Adopt technology adoption model and task/ technology • Other factors such as social influence and the effectiveness of purchasing game items

  35. END OF PRESENTATION

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