Idea selection and adoption by users – a process model in an online innovation community

References

• Ali, A., W. Bahadur, N. Wang, A. Luqman, and A. N. Khan. 2020. “Improving Team Innovation Performance: Role of Social Media and Team Knowledge Management Capabilities.” Technology in Society 61: 1–41. doi:10.1016/j.techsoc.2020.101259.
   Web of Science ®Google Scholar
• Allison, T. H., B. C. Davis, J. W. Webb, and J. C. Short. 2017. “Persuasion in Crowdfunding: an Elaboration Likelihood Model of Crowdfunding Performance.” Journal of Business Venturing 32 (6): 707–725. doi:10.1016/j.jbusvent.2017.09.002.
   Web of Science ®Google Scholar
• Bayus, B. L. 2013. “Crowdsourcing new Product Ideas Over Time: an Analysis of the Dell Ideastorm Community.” Management Science 59 (1): 226–244. doi:10.1287/mnsc.1120.1599.
   Web of Science ®Google Scholar
• Blohm, I., J. M. Leimeister, and H. Krcmar. 2013. “Crowdsourcing: How to Benefit from Many Great Ideas.” MIS Quarterly Executive 12 (4): 199–211.
   Web of Science ®Google Scholar
• Brem, A., V. Bilgram, and A. Marchuk. 2019. “How Crowdfunding Platforms Change the Nature of User Innovation-from Problem Solving to Entrepreneurship.” Technological Forcasting and Social Change 144 (7): 348–360. doi:10.1016/j.techfore.2017.11.020.
   Google Scholar
• Brem, A., and V. Utikal. 2019. “How to Manage Creativity Time? Results from a Social Psychological Time Model Lab Experiment on Individual Creative and Routine Performance.” Creativity and Innovation Management 28 (3): 291–305.
   Web of Science ®Google Scholar
• Brem, A., and E. Viardot. 2015. “Adoption of Innovation: Balancing Internal and External Stakeholders in the Marketing of Innovation.” In Adoption of Innovation, 1–10. Cham: Springer.
   Google Scholar
• Cacioppo, J. T., and R. E. Petty. 1984. “The Elaboration Likelihood Model of Persuasion.” Advances in Consumer Research 11 (1): 673–675.
   Google Scholar
• Chaiken, S. 1980. “Heuristic Versus Systematic Information Processing and the Use of Source Versus Message Cues in Persuasion.” Journal of Personality and Social Psychology 39 (5): 752–766. doi:10.1037/0022-3514.39.5.752.
   Web of Science ®Google Scholar
• Chang, H. H., and S. Chuang. 2011. “Social Capital and Individual Motivations on Knowledge Sharing: Participant Involvement as a Moderator.” Information and Management 48 (1): 9–18. doi:10.1016/j.im.2010.11.001.
   Web of Science ®Google Scholar
• Chang, Y. T., H. J. Yu, and H. P. Lu. 2015. “Persuasive Messages, Popularity Cohesion, and Message Diffusion in Social Media Marketing.” Journal of Business Research 68 (4): 777–782. doi:10.1016/j.jbusres.2014.11.027.
   Web of Science ®Google Scholar
• Cheng, V. H., and H. Y. Ho. 2015. “Social Influence’s Impact on Reader Perceptions of Online Reviews.” Journal of Business Research 68 (4): 883–887. doi:10.1016/j.jbusres.2014.11.046.
   Web of Science ®Google Scholar
• Clevinger, A. 2014. “Test Performance: The Influence of Cognitive Load on Reading Comprehension.” ScholarWorks@Georgia State University.
   Google Scholar
• Conway, S. 1995. “Informal Boundary-Spanning Communication in the Innovation Process: An Empirical Study.” Technology Analysis & Strategic Management 7 (3): 327–342. doi:10.1080/09537329508524216.
   Web of Science ®Google Scholar
• Di Gangi, P. M., and M. Wasko. 2009. “Steal My Idea! Organizational Adoption of User Innovations from a User Innovation Community: A Case Study of Dell IdeaStorm.” Decision Support Systems 48 (1): 303–312. doi:10.1016/j.dss.2009.04.004.
   Web of Science ®Google Scholar
• Di Gangi, P. M., M. Wasko, and R. Hooker. 2010. “Getting Customers’ Ideas to Work for You: Learning from Dell How to Succeed with Online User Innovation Communities.” MIS Quarterly Executive 9 (4): 213–228.
   Web of Science ®Google Scholar
• Eppler, M. J., and J. Mengis. 2004. “The Concept of Information Overload: A Review of Literature from Organization Science, Accounting, Marketing, MIS, and Related Disciplines.” Information Society 20 (5): 325–344. doi:10.1080/01972240490507974.
   Web of Science ®Google Scholar
• Fedorowicz, J., and J. L. Gogan. 2010. “Reinvention of Interorganizational Systems: A Case Analysis of the Diffusion of a Bio-Terror Surveillance System.” Information Systems Frontiers 12 (1): 81–95. doi:10.1007/s10796-009-9167-y.
   PubMed Web of Science ®Google Scholar
• Fleming, L., and D. M. Waguespack. 2007. “Brokerage, Boundary Spanning, and Leadership in Open Innovation Communities.” Organization Science 18 (2): 165–180. doi:10.1287/orsc.1060.0242.
   Web of Science ®Google Scholar
• Fuller, Steve. 2006. “Intelligent Design Theory: A Site for Contemporary Sociology of Knowledge.” The Canadian Journal of Sociology 31 (3): 277–289. doi:10.1353/cjs.2006.0054.
   Web of Science ®Google Scholar
• Ghose, A., and P. G. Ipeirotis. 2011. “Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics.” IEEE Transations On Knowledge And Data Engineering 23 (10): 1498–1512. doi:10.1109/tkde.2010.188.
   Web of Science ®Google Scholar
• Hau, Y. S., B. Kim, H. Lee, and Y. G. Kim. 2013. “The Effects of Individual Motivations and Social Capital on Employees’ Tacit and Explicit Knowledge Sharing Intentions.” International Journal of Information Management 33 (2): 356–366. doi:10.1016/j.ijinfomgt.2012.10.009.
   Web of Science ®Google Scholar
• Hiltz, S. R., and M. Toroff. 1985. “Structuring Computer-Mediated Communication Systems to Avoid Information Overload.” Communications of the Acm 28 (7): 680–689. doi:10.1145/3894.3895.
   Web of Science ®Google Scholar
• Ho, S. Y., and D. Bodoff. 2014. “The Effects of web Personalization on User Attitude and Behavior: An Integration of the Elaboration Likelihood Model and Consumer Search Theory.” Journal of Polymer Science Part B: Polymer Physics 52 (2): 1476–1489. doi:10.1002/polb.23587.
   Google Scholar
• Hossain, M., and K. M. Z. Islam. 2015. “Ideation through Online Open Innovation Platform: Dell IdeaStorm.” Journal of the Knowledge Economy 6 (3): 611–624. doi:10.1007/s13132-015-0262-7.
   Web of Science ®Google Scholar
• Huang, Y., and G. Kou. 2014. “A Kernel Entropy Manifold Learning Approach for Financial Data Analysis.” Decision Support Systems 64 (8): 31–42. doi:10.1016/j.dss.2014.04.004.
   Google Scholar
• Huang, Y., P. V. Singh, and K. Srinivasan. 2014. “Crowdsourcing New Product Ideas under Consumer Learning.” Management Science 60 (9): 2138–2159. doi:10.1287/mnsc.2013.1879.
   Web of Science ®Google Scholar
• Jones, Q., G. Ravid, and S. Rafaeli. 2004. “Information Overload and the Message Dynamics of Online Interaction Spaces: A Theoretical Model and Empirical Exploration.” Information Systems Research 15 (2): 194–210. doi:10.1287/isre.1040.0023.
   Web of Science ®Google Scholar
• Kirsh, D., J. Hollan, and E. Hutchins. 2000. “Distributed Cognition: Toward a New Foundation for Human-Computer Interaction Research.” ACM Transactions on Computer Human Interaction 7 (6): 174–196. doi:10.1145/353485.353487.
   Google Scholar
• Kohn, N. W., and S. M. Smith. 2011. “Collaborative Fixation: Effects of Others’ Ideas on Brainstorming.” Applied Cognitive Psychology 25 (3): 359–371. doi:10.1002/acp.1699.
   Web of Science ®Google Scholar
• Law, K. K., A. Chan, and M. Ozer. 2017. “Towards an Integrated Framework of Intrinsic Motivators, Extrinsic Motivators and Knowledge Sharing.” Journal of Knowledge Management 21 (21): 1486–1502. doi:10.1108/JKM-03-2016-0119.
   Google Scholar
• Li, C. 2013. “Persuasive Messages on Information System Acceptance: A Theoretical Extension of Elaboration Likelihood Model and Social Influence Theory.” Computers in Human Behavior 29 (1): 264–275. doi:10.1016/j.chb.2012.09.003.
   Web of Science ®Google Scholar
• Li, M., A. Kankanhalli, and S. H. Kim. 2016. “Which Ideas Are More Likely to be Implemented in Online User Innovation Communities? An Empirical Analysis.” Decision Support Systems 84 (4): 28–40. doi:10.1016/j.dss.2016.01.004.
   Google Scholar
• Magnusson, P. R. 2010. “Exploring the Contributions of Involving Ordinary Users in Ideation of Technology-Based Services.” Journal of Product Innovation Management 26 (5): 578–593. doi:10.1111/j.1540-5885.2009.00684.x.
   Web of Science ®Google Scholar
• Mahr, D., and A. Lievens. 2012. “Virtual Lead User Communities: Drivers of Knowledge Creation for Innovation.” Research Policy 41 (1): 167–177. doi:10.1016/j.respol.2011.08.006.
   Web of Science ®Google Scholar
• Martínez-Torres, M. R. 2014. “Analysis of Open Innovation Communities from the Perspective of Social Network.” Technology Analysis & Strategic Management 26 (4): 435–451. doi:10.1080/09537325.2013.851378.
   Web of Science ®Google Scholar
• Miller, G. A. 1994. “The Magical Number Seven, Plus or Minus Two: Some Limits on Our Capacity for Processing Information.” Psychological Review 101 (2): 343–352. doi:10.1037/0033-295X.101.2.343.
   PubMed Web of Science ®Google Scholar
• Nambisan, S., and R. A. Baron. 2009. “Virtual Customer Environments: Testing a Model of Voluntary Participation in Value Co-Creation Activities.” Journal of Product Innovation Management 26 (4): 388–406. doi:10.1111/j.1540-5885.2009.00667.
   Web of Science ®Google Scholar
• Nel, J., and C. Boshoff. 2017. “Development of Application-Based Mobile-Service Trust and Online Trust Transfer: An Elaboration Likelihood Model Perspective.” Behavior &Information Technology 36 (8): 809–826. doi:10.1080/0144929x.2017.1296493.
   Web of Science ®Google Scholar
• Park, D. H., J. Lee, and I. Han. 2007. “The Effect of on-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement.” International Journal of Electronic Commerce 11 (4): 125–148. doi:10.2753/JEC1086-4415110405.
   Web of Science ®Google Scholar
• Perry-Smith, J. E., and C. E. Shalley. 2003. “The Social Side of Creativity: A Static and Dynamic Social Network Perspective.” The Academy of Management Review 28 (1): 89–106. doi:10.2307/30040691.
   Web of Science ®Google Scholar
• Petty, R. E., and J. T. Cacioppo. 1986. “The Elaboration Likelihood Model of Persuasion.” Advances in Experimental Social Psychology 19 (1): 123–205. doi:10.1016/S0065-2601(08)60214-2.
   Google Scholar
• Piezunka, H., and L. Dahlander. 2015. “Distant Search, Narrow Attention: How Crowding Alters Organizations’ Filtering of Suggestions in Crowdsourcing.” Academy of Management Journal 58 (3): 856–880. doi:10.5465/amj.2012.0458.
   Web of Science ®Google Scholar
• Rogers, E. M. 2003. Difussion of Innovations. New York: Free Press.
   Google Scholar
• Schemmann, B., A. M. Herrmann, M. M. H. Chappin, and G. J. Heimeriks. 2016. “Crowdsourcing Ideas: Involving Ordinary Users in the Ideation Phase of New Product Development.” Research Policy 45 (6): 1145–1154. doi:10.1016/j.respol.2016.02.003.
   Web of Science ®Google Scholar
• Schweisfurth, T. G., and C. Raasch. 2018. “Absorptive Capacity for Need Knowledge: Antecedents and Effects for Employee Innovativeness.” Research Policy 47 (4): 687–699. doi:10.1016/j.respol.2018.01.017.
   Web of Science ®Google Scholar
• Shi, C. L., L. L. Yu, N. Wang, B. Y. Cheng, and X. F. Cao. 2020. “Effect of Social Media Overload on Academic Performance: A Stressor-Strain-Outcome Perspective.” Asian Journal of Communication 30 (2): 179–197. doi:10.1080/01292986.2020.1748073.
   Web of Science ®Google Scholar
• Sussman, S. W., and W. S. Siegal. 2003. “Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption.” Information Systems Research 14 (1): 47–65. doi:10.1287/isre.14.1.47.14767.
   Web of Science ®Google Scholar
• Tsai, K., C. Chou, and J. Kuo. 2008. “The Curvilinear Relationships Between Responsive and Proactive Market Orientations and new Product Performance: A Contingent Link.” Industrial Marketing Management 37 (8): 884–894. doi:10.1016/j.indmarman.2007.03.005.
   Web of Science ®Google Scholar
• Tushman, M. L., and T. J. Scanlan. 1981. “Boundary Spanning Individuals: Their Role in Information Transfer and Their Antecedents.” Academy of Management Journal 24 (2): 289–305. doi:10.2307/255842.
   Web of Science ®Google Scholar
• Wisdom, J. P., K. H. B. Chor, K. E. Hoagwood, and S. M. Horwitz. 2014. “Innovation Adoption: A Review of Theories and Constructs.” Administration and Policy in Mental Health and Mental Health Services Research 41 (1): 480–502. doi:10.1007/s10488-013-0486-4.
   PubMedGoogle Scholar
• Xiao, L., and J. Mou. 2019. “Social Media Fatigue-Technological Antecedents and the Moderating Roles of Personality Traits: The Case of WeChat.” Computers in Human Behavior 101 (8): 297–310. doi:10.1016/j.chb.2019.08.001.
   Google Scholar
• Xiong, Y., Z. Cheng, E. Liang, and Y. Wu. 2018. “Accumulation Mechanism of Opinion Leaders’ Social Interaction Ties in Virtual Communities: Empirical Evidence from China.” Computers in Human Behavior 82: 81–93. doi:10.1016/j.chb.2018.01.005.
   Web of Science ®Google Scholar
• Yang, X., and G. Li. 2016. “Factors Influencing the Popularity of Customer-Generated Content in a Company-Hosted Online co-Creation Community: A Social Capital Perspective.” Computers in Human Behavior 64 (11): 760–768. doi:10.1016/j.chb.2016.08.002.
   Google Scholar
• Zhang, X., S. Liu, X. Chen, and Y. Gong. 2017a. “Social Capital, Motivations, and Knowledge Sharing Intention in Health Q and A Communities.” Management Decision 55 (7): 1536–1557. doi:10.1108/md-10-2016-0739.
   Web of Science ®Google Scholar
• Zhang, W., and S. Watts. 2008. “Online Communities as Communities of Practice: A Case Study.” Journal of Knowledge Management 12 (4): 55–71. doi:10.1108/13673270810884255.
   Google Scholar
• Zhang, D., F. Zhang, M. Lin, and H. S. Du. 2017b. “Knowledge Sharing among Innovative Customers in a Virtual Innovation Community: The Roles of Psychological Capital, Material Reward and Reciprocal Relationship.” Online Information Review 41 (5): 691–709. doi:10.1108/oir-08-2016-0226.
   Web of Science ®Google Scholar
• Zhao, L., B. Detlor, and C. E. Connelly. 2016. “Sharing Knowledge in Social QandA Sites: The Unintended Consequences of Extrinsic Motivation.” Journal of Management Information Systems 33 (1): 70–100. doi:10.1080/07421222.2016.1172459.
   Web of Science ®Google Scholar
• Zhou, Z. Y., X. L. Jin, and Y. L. Fang. 2014. “Moderating Role of Gender in the Relationships Between Perceived Benefits and Satisfaction in Social Virtual World Continuance.” Decision Support Systems 65 (1): 69–79. doi:10.1016/j.dss.2014.05.004.
   Google Scholar