On electronic word-of-mouth diffusion in social networks: curiosity and influence

Abstract

The rapid proliferation of social networking sites (SNSs) provides marketers with ample opportunities to explore advertising strategies based on electronic word-of-mouth (eWOM). With that in mind, this study aims to understand the influence of the eWOM diffusion process on SNSs. We propose a theoretical framework to investigate the roles of curiosity and influence in SNS users’ decisions to adopt eWOM and to pass it along to their contact groups. Two forms of curiosity, specific and diversive, are proposed to initiate specific exploration (consistency checking and knowledge-based validation) and diversive exploration (referral visit behavior), and eventually, adoption and pass-along behavior. In addition, SNS influence, formed by maven, persuasiveness, and connectivity, is proposed as a moderator affecting information diffusion. The proposed framework is empirically validated using the data collected from online surveys of 590 Facebook users. Implications for theory and practice are also discussed.

Keywords:

• social network
• word-of-mouth
• curiosity
• influence
• exploration

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. http://www.kpmg.com/us/en/topics/2014-outlook-surveys/pages/2014-retail-industry-outlook-survey.aspx, Accessed date Dec. 27, 2014.

2. http://www.ninthdecimal.com/wp-content/uploads/2014/06/ND_Insights_Q2_2013.pdf, Accessed December 27, 2014.

3. http://www.nielsen.com/content/dam/corporate/us/en/reports-downloads/2012-Reports/global-trust-in-advertising-2012.pdf, Accessed December 27, 2014.

4. We defined and explained specific curiosity and diversive curiosity in Curiosity and exploration section.

5. Note that there is no theoretical reason to link specific exploration (functional view) to pass-along behavior on SNSs. No hypotheses were put forth between consistency-checking, knowledge-based validation, and pass-along behavior.

6. Note that we rename the term of ‘influence’ to ‘SNS influence’ to better depict such self-influence on SNS.

7. Note that there is no theoretical reason to expect a receiver's level of influence to predict the extent of his/her eWOM adoption on SNSs. No hypothesis was put forth between SNS influence and eWOM adoption.

8. Internet World Stats 2015, http://www.internetworldstats.com/stats3.htm, Accessed April 20, 2016.

9. Note that further analysis is not necessary given that H8b was not supported.

10. Note that an alternative model with specific and diversive curiosity as mediators between SNS influence and eWOM adoption and pass-along behavior performed worse than the direct-link model (GoF of 0.42 and R² of 0.336). Since the direct links between curiosity and pass-along behavior remain insignificant, discussion of this alternative model is not necessary.

11. Virtual reality, https://en.wikipedia.org/wiki/Virtual_reality, Accessed September 22, 2016.

Additional information

Funding

National Science Council of Taiwan, ROC [grant number NSC-101-2410-H-004-013-MY2].

Notes on contributors

Yu-Hui Fang

Yu-Hui Fang is an associate professor in the Department of Accounting at the Tamkang University, Taiwan. She received the PhD degree in information management from National Central University and MS degree in accounting from University of Houston. Her research interests include electronic commerce, social media, and virtual communities. Her research has appeared in International Journal of Electronic Commerce, Journal of the Association for Information Systems, Information Systems Journal, Psychology & Marketing, Telematics and Informatics, Internet Research, Service Business, Online Information Review, Human Systems Management, Computers in Human Behavior, etc.

E-mail: [email protected]

Kwei Tang

Kwei Tang is university chair professor and dean of College of Commerce at National Chengchi University, Taipei, Taiwan. Prior to the current position, he was the Allison and Nancy Schleicher Chair of Management and the associate dean for Academic Affairs at the Krannert School of Management, Purdue University. He received his PhD degree from Purdue University. He is a recipient of the 1988 U.S. Presidential Young Investigator Award, and the 1998 Distinguished Alumni Award from National Chiao Tung University. He is a fellow of the Decision Sciences Institute and his current research interests include big data analytics and data mining.

E-mail: [email protected]

Chia-Ying Li

Chia-Ying Li is an associate professor in the Department of Business Administration at the National TaiChung University of Science and Technology, Taiwan. She received her PhD degree in business administration from National Cheng Kung University. Her research interests are in electronic commerce, strategic marketing management and social media. She has published articles in Service Business, Journal of Service Theory and Practice, Asia Pacific Management Review, Computers in Human Behavior, International Journal of Information Management, Journal of Information Science, Expert Systems with Applications, International Journal of Human Resource Management, Industrial Management and Data System, Human Systems Management, and elsewhere.

E-mail: [email protected]

Chia-Chi Wu

Chia-Chi Wu is a senior engineer at Institute for Information Industry in Taiwan. He received his PhD degree in information management from National Central University and MS degree in management information systems from National Chengchi University. His research interests include data mining and artificial intelligence. Currently, he is focusing on social media and text mining.

E-mail: [email protected]