2016
DOI: 10.1080/0144929x.2016.1212932
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A picture is worth a thousand words: an empirical study on the influence of content visibility on diffusion processes within a virtual world

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Cited by 22 publications
(12 citation statements)
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References 88 publications
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“…Hamari & Keronen 2016 for a review), the related quantitative literature has commonly focused on more abstract psychological constructs rather than being concerned with possible purchase motivations that stem from how the game has been designed. This vein of literature has been interested in predicting virtual good or in-game content (re-)purchases from perspectives of different affective experiences in the game (Chou & Kimsuwan 2013;Hamari 2015;Luo et al 2011), customer lifetime value (Hanner & Zarnekov 2015), content visibility (Jankowski et al 2016), cultural and demographic aspects (Lee & Wohn 2012;Wohn 2014), tele/social presence (Animesh et al 2011), playfulness (Han & Windsor 2013), flow/cognitive involvement (Huang 2012;Liu & Shiue 2014), transaction cost theory (Guo & Barnes 2011;, satisfaction (Kim 2012), perceived value (Chou & Kimsuwan 2013;Park & Lee 2011), critical reception (Alha et al 2016), technology acceptance (Cha 2011;Domina et al 2012;Hamari & Keronen 2016), theories of planned behavior and reasoned action (Gao 2014;Kaburuan et al 2009), and expectancy-disconfirmation model (Wang & Chang 2013;. Qualitative efforts mapping the phenomenon, on the other hand, have been more successful in identifying concrete purchase motivations that pertain to the nature of the business models and its related effect on game design (Hamari & Lehdonvirta 2010;Hamari 2011;Hamari & Järvinen 2011;Zagal et al 2013), user experiences (Alha et al 2014;Cleghorn & Griffiths 2015;Lin & Sun 2011;Paavilainen et al 2013), and features of virtual goods (Lehdonvirta 2009).…”
Section: Introductionmentioning
confidence: 99%
“…Hamari & Keronen 2016 for a review), the related quantitative literature has commonly focused on more abstract psychological constructs rather than being concerned with possible purchase motivations that stem from how the game has been designed. This vein of literature has been interested in predicting virtual good or in-game content (re-)purchases from perspectives of different affective experiences in the game (Chou & Kimsuwan 2013;Hamari 2015;Luo et al 2011), customer lifetime value (Hanner & Zarnekov 2015), content visibility (Jankowski et al 2016), cultural and demographic aspects (Lee & Wohn 2012;Wohn 2014), tele/social presence (Animesh et al 2011), playfulness (Han & Windsor 2013), flow/cognitive involvement (Huang 2012;Liu & Shiue 2014), transaction cost theory (Guo & Barnes 2011;, satisfaction (Kim 2012), perceived value (Chou & Kimsuwan 2013;Park & Lee 2011), critical reception (Alha et al 2016), technology acceptance (Cha 2011;Domina et al 2012;Hamari & Keronen 2016), theories of planned behavior and reasoned action (Gao 2014;Kaburuan et al 2009), and expectancy-disconfirmation model (Wang & Chang 2013;. Qualitative efforts mapping the phenomenon, on the other hand, have been more successful in identifying concrete purchase motivations that pertain to the nature of the business models and its related effect on game design (Hamari & Lehdonvirta 2010;Hamari 2011;Hamari & Järvinen 2011;Zagal et al 2013), user experiences (Alha et al 2014;Cleghorn & Griffiths 2015;Lin & Sun 2011;Paavilainen et al 2013), and features of virtual goods (Lehdonvirta 2009).…”
Section: Introductionmentioning
confidence: 99%
“…As a result, premium content that had been advertised using mass announcements within the virtual world resulted in a spike in purchase activity that quickly dissipated. To address this issue, several viral marketing campaigns aimed at stimulating interest in a new form of premium content were initiated and discussed in our earlier work [31]. It showed the potential of increasing interest in virtual goods with the use of viral mechanics.…”
Section: Resultsmentioning
confidence: 99%
“…The experimental study is based on data from the virtual world and the use of avatars within the platform [25,26]. The introduced dataset covers information from 195 items included in the form of user avatars.…”
Section: Dataset Description and Participantsmentioning
confidence: 99%