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To Belong or to be different? Evidence from a large-scale field experiment in China

This study investigates whether individuals conform or diverge from their friends' choices on a social networking platform in China. The findings reveal that participants are more likely to diverge from the majority choice as the adoption rate increases. Females and individuals from more affluent towns also exhibit a higher likelihood of divergence. These results have implications for platforms' decision to publicize users' choices.

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To Belong or to be different? Evidence from a large-scale field experiment in China

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  1. To Belong or to be different? Evidence from a large-scale field experiment in China Monic Sun Joint with Michael Zhang and Feng Zhu

  2. Social Influence at Work • People’s buying decisions are greatly influenced by social media these days with 52% of Facebook users said their friends’ photos inspired their holiday choice and travel plans. But HOW?

  3. The research question • When surrounded by your friends, and only your friends, would you conform to or diverge from the most popular choice among them? • Fundamental tradeoff • Need to belong • Need to be different

  4. Prior studies • Individuals are very good at fitting in • Asch (1952), Deutsch and Gerard (1955) • Theyassimilatetonormsof a groupwhengroupidentityissalient • Turner (1991); Brewer (1991); Escalas and Bettman(2005); Berger and Heath (2007, 2008) • Theories on uniqueness and individuality • Snyder and Fromkin (1980), Kim and Marcus (1999), Imhoff and Erb (2009)

  5. Empirical Difficulties • Friendship structures are hard to observe • Pre-existing similarity in friends tastes • Observational learning • Presence of out-group members

  6. This Study • We identified a unique environment (kaixin001.com) to tackle the difficulties • Social network structure transparent to researchers • Field experiment helps eliminating learning and homophily • Minimizes the hawthorne effect • Traditionally regarded as a conformity driven culture

  7. Kaixin001.com (a.k.a. Happy Net) • One of the top social-networking websites in China • Launched in March 2008 • 130 million registered users (~10% Chinese population) • Registered with real names and friendship requires mutual agreement • Alexa traffic rank 49th in China

  8. “Virtual Homes”

  9. Sample Message Friend color Social message

  10. Experiment • February and March, 2011 • 4 weeks • 16,298 participants • 5440 in condition A (Friend message) • 5423 in condition B (Friend message + social message) • 5435 in condition C (Global message)

  11. Design Features • Field study • Subjects not aware of being monitored • No need for them to imagine encountering friends • Randomly generated the most popular colors • Avoiding pre-existing similarities or differences • Color only observed by friends, not by the public • No out-group • Eliminating social identity pressure to conform • Colors are standard and users can try them freely • Unlikely to have learning when choosing colors

  12. Summary Stats

  13. Likelihood to Converge A: Friend Color C: Global Color

  14. Likelihood to Converge A: Friend Color B: Friend Color + Social message

  15. Conclusion • Participants are more likely to diverge from the majority choice among their friends as the adoption rate increases • Females’ likelihood of divergence is greater than males’ by 1.7 percentage points • Subjects born in more affluent towns are more likely to diverge from their friends • It may be unprofitable for platforms to publicize the users’ choices, even among their friends.

  16. Thank you!

  17. New Possible Confounds by Experiment • Saliency Effect • The color is made salient • Warning Effect • The message may prompt the user to change • Solution: • We use the reaction to global color as a control • We examine the reactions to changes in adoption rate

  18. Typical User on Kaixin • 25-34 years old • College degree • Visit from office • Access 49 pages and spends 33 minutes on each visit

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