Analysis of the Factors that Affect the Number of Positive Reviews in an Idea Crowdsourcing Community ——An ELM Perspective

Abstract

Abstract: Using second-hand data from an idea crowdsourcing community and drawing on Elaboration Likelihood Model(ELM), this study focuses on how the quality (the potential and the feasibility of a creative idea) and the format (the number of words in a creative idea, whether other users can vote and the number of negative affective words in a creative idea) of a creative idea affect the number of positive reviews towards the idea, and the moderating effect of a creative idea's format on the relationship between the quality of the creative idea and the number of positive reviews towards the idea. The results show that the potential of a creative idea positively affects the number of positive reviews towards this idea, while the feasibility of a creative idea does not significantly affect the number of positive reviews towards this idea. Both the number of words in a creative idea and the authority of voting to the idea positively influence the number of positive reviews towards the idea. Furthermore, when the number of words in a creative idea is small or when community members can vote on an idea, the potential of the creative idea has a greater impact on the number of positive reviews; otherwise, it is the feasibility of the creative idea that has a significant impact on the number of positive reviews.

Key words: Elaboration Likelihood Model, positive reviews, the quality of a creative idea, the format of a creative idea

Ma Yongbin, Xu Qing. Analysis of the Factors that Affect the Number of Positive Reviews in an Idea Crowdsourcing Community ——An ELM Perspective[J]. Management Review, 2020, 32(11): 140-150.

References

[1] Huang Y., Vir S. P., Srinivasan K. Crowdsourcing New Product Ideas under Consumer Learning[J]. Management Science, 2014,60(9):2138-2159
[2] Mollick E., Nanda R. Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the Arts[J]. Management Science, 2015,62(6):1533-1553
[3] Kornish L. J., Ulrich K. T. The Importance of the Raw Idea in Innovation:Testing the Sow's Ear Hypothesis[J]. Journal of Marketing Research, 2014,51(1):14-26
[4] Franke N., Keinz P., Schreier M. Complementing Mass Customization Toolkits with User Communities:How Peer Input Improves Customer Self-Design[J]. Journal of Product Innovation Management, 2008,25(6):546-559
[5] Hildebrand C., Häubl G., Herrmann A., et al. When Social Media Can Be Bad for You:Community Feedback Stifles Consumer Creativity and Reduces Satisfaction with Self-Designed Products[J]. Information Systems Research, 2013,24(1):14-29
[6] 唐方成,蒋沂桐. 虚拟品牌社区中顾客价值共创行为研究[J]. 管理评论, 2018,30(12):131-141
[7] 校亮,厉洋军. 虚拟品牌社区知识贡献意愿研究:基于动机和匹配的整合视角[J]. 管理评论, 2018,30(10):82-94
[8] 严建援,乔艳芬,秦凡. 产品创新社区不同级别顾客的价值共创行为研究——以MIUI社区为例[J]. 管理评论, 2019,31(2):58-70
[9] Acar O. A. Harnessing the Creative Potential of Consumers:Money, Participation, and Creativity in Idea Crowdsourcing[J]. Marketing Letters, 2018,29(2):177-188
[10] Sun Y., Dong X., McIntyre S. Motivation of User-generated Content:Social Connectedness Moderates the Effects of Monetary Rewards[J]. Marketing Science, 2017,36(3):329-337
[11] Tam K. Y., Ho S. Y. Web Personalization as a Persuasion Strategy:An Elaboration Likelihood Model Perspective[J]. Information Systems Research, 2005,16(3):271-291
[12] Kitchen P. J., Kerr G. E., Schultz D., et al. The Elaboration Likelihood Model:Review, Critique and Research Agenda[J]. European Journal of Marketing, 2014,48(11-12):2033-2050
[13] Daft R. L., Lengel R. H. Information Richness:A New Approach to Managerial Behavior and Organizational Design[J]. Research in Organizational Behavior, 1984,6(1):191-233
[14] Sussman S. W., Siegal W. S. Informational Influence in Organizations:An Integrated Approach to Knowledge Adoption[J]. Information Systems Research, 2003,14(1):47-65
[15] Magnusson P. R., Wästlund E., Netz J. Exploring Users' Appropriateness as a Proxy for Experts When Screening New Product/Service Ideas[J]. Journal of Product Innovation Management, 2016,33(1):4-18
[16] Lüthje C. Characteristics of Innovating Users in a Consumer Goods Field:An Empirical Study of Sport-Related Product Consumers[J]. Technovation, 2004,24(9):683-695
[17] Chatterji A. K., Fabrizio K. How do Product Users Influence Corporate Invention?[J]. Organization Science, 2012,23(4):971-987
[18] Berger J. Word-of-mouth and Interpersonal Communication:An Organizing Framework and Directions for Future Research[J]. Journal of Consumer Psychology, 2014,24(4):586-607
[19] Chevalier J. A., Dover Y., Mayzlin D. Channels of Impact:User Reviews When Quality Is Dynamic and Managers Respond[J]. Marketing Science, 2018,37(5):688-709
[20] Pisano G. P., Verganti R. Which Kind of Collaboration Is Right for You?[J]. Harvard Business Review, 2008,86(12):78-86
[21] Poetz M. K., Schreier M. The Value of Crowdsourcing:Can Users Really Compete with Professionals in Generating New Product Ideas?[J]. Journal of Product Innovation Management, 2012,29(2):245-256
[22] 王婷婷. 创新价值链视角下企业开放式创新平台创意管理研究[D]. 山东大学博士学位论文, 2018
[23] 郭琴. 创新源分散化条件下开放式创新社区创意价值识别研究[D]. 广西大学硕士学位论文, 2017
[24] 殷国鹏. 消费者认为怎样的在线评论更有用?——社会性因素的影响效应[J]. 管理世界, 2012,(12):115-124
[25] 邬溪羽,郭斌,周莎莎,等. 在线评论如何影响消费者:基于社会影响视角的整合框架[J]. 西安电子科技大学学报(社会科学版), 2015,25(1):1-18
[26] Sidali K. L., Schulze H., Spiller A. The Impact of Online Reviews on the Choice of Holiday Accommodations[A]. In Höpken W., Gretzel U., Law R. (Eds.). Information and Communication Technologies in 2009[C]. New York, NY:Springer Wien, 2009
[27] Kruger J., Wirtz D., van Boven L., et al. The Effort Heuristic[J]. Journal of Experimental Social Psychology, 2004,40(1):91-98
[28] Molm L. D. The Structure of Reciprocity[J]. Social Psychology Quarterly, 2010,73(2):119-131
[29] Cabral L., Li L. A Dollar for Your Thoughts:Feedback-Conditional Rebates on eBay[J]. Management Science, 2015,61(9):2052-2063
[30] Yin D., Bond S., Zhang H. Anxious or Angry? Effects of Discrete Emotions on the Perceived Helpfulness of Online Reviews[J]. MIS Quarterly, 2014,38(2):539-560
[31] Keltner D., Haidt J. Social Functions of Emotions at Four Levels of Analysis[J]. Cognition & Emotion, 1999,13(5):505-521
[32] Dahl D. W., Fuchs C., Schreier M. Why and When Consumers Prefer Products of User-Driven Firms:A Social Identification Account[J]. Management Science, 2014,61(8):1978-1988
[33] Baumeister R. F., Bratslavsky E., Finkenauer C., et al. Bad Is Stronger Than Good[J]. Review of General Psychology, 2001,5(4):323-370
[34] Berger J., Milkman K. L. What Makes Online Content Viral?[J]. Journal of Marketing Research, 2012,49(2):192-205
[35] Agarwal A., Xie B., Vovsha I., et al. Sentiment Analysis of Twitter Data[C]. Proceedings of the Workshop on Language in Social Media (LSM 2011), 2011
[36] Salminen J., Yoganathan V., Corporan J., et al. Machine Learning Approach to Auto-tagging Online Content for Content Marketing Efficiency:A Comparative Analysis between Methods and Content Type[J]. Journal of Business Research, 2019,101:203-217
[37] 刘波,马永斌. 网络环境中用户努力与创新观点质量——在线互动和评论版块异质性的调节作用[J]. 消费经济, 2016,32(5):73-81
[38] Diedrich J., Benedek M., Jauk E., et al. Are Creative Ideas Novel and Useful?[J]. Psychology of Aesthetics, Creativity & the Arts, 2015,9(1):35-40
[39] Dean D. L., Hender J. M., Rodgers T. L., et al. Identifying Quality, Novel, and Creative Ideas:Constructs and Scales for Idea Evaluation[J]. Journal of the Association for Information Systems, 2006,7(10):646-699
[40] Roberts J. A., Hann I. H., Slaughter S. A. Understanding the Motivations, Participation, and Performance of Open Source Software Developers:A Longitudinal Study of the Apache Projects[J]. Management science, 2006,52(7):984-999