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Why Are the Largest Social Networking Services Sometimes Unable to Sustain Themselves?

Yong Joon Hyoung (), Arum Park () and Kyoung Jun Lee ()
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Yong Joon Hyoung: Department of Social Network Science, Kyung Hee University, Seoul 02447, Korea
Arum Park: School of Management, Kyung Hee University, Seoul 02447, Korea
Kyoung Jun Lee: Department of Social Network Science, Kyung Hee University, Seoul 02447, Korea

Sustainability, 2020, vol. 12, issue 2, 1-23

Abstract: The sustainability of SNSs (social networking services) is a major issue for both business strategists and those who are simply academically curious. The “network effect” is one of the most important theories used to explain the competitive advantage and sustainability of the largest SNSs in the face of the emergence of multiple competitive followers. However, as numerous cases can be observed when a follower manages to overcome the previously largest SNS, we propose the following research question: Why are the largest social networking services sometimes unable to sustain themselves? This question can also be paraphrased as follows: When (under what conditions) do the largest SNSs collapse? Although the network effect generally enables larger networks to survive and thrive, exceptional cases have been observed, such as NateOn Messenger catching up with MSN Messenger in Korea (Case 1), KakaoTalk catching up with NateOn in Korea (Case 2), Facebook catching up with Myspace in the USA (Case 3), and Facebook catching up with Cyworld in Korea (Case 4). To explain these cases, hypothesis-building and practice-oriented methods were chosen. While developing our hypothesis, we coined the concept of a “larger population social network” (LPSN) and proposed an “LPSN effect hypothesis” as follows: The largest SNS in one area can collapse when a new SNS grows in another larger population’s social network. For the validity and reliability of our case studies, we used an evidence chain and case study protocol with a publicly-accessible LPSN index to determine which SNS is better for participating in or adding offline social networks to their platform.

Keywords: network effect; larger population social network; social network; business sustainability; network sustainability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2020
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