The crowdsourcing data for innovation

Does it Matter?

Keywords: creativity, project management, data-driven design, innovation, social media, IT-management

Abstract

Purpose – to explore a crowdsourcing data-driven approach to construct crowdknowledge databases for innovation through supporting creative idea generation. In the approach, social media will be used as platforms to crowdsource knowledge for producing the databases.

Findings. Creativity is an essential element of innovation, but producing creative ideas is often challenging in design. Many computational tools have become available recently to support designers in producing creative ideas that are new to individuals. As a standard feature, most of the tools rely on the databases employed, such as ConceptNet and the US Patent Database. This study highlighted that the limitations of these databases have constrained the capabilities of the tools and, thereby, new computational databases supporting the generation of new ideas to a crowd or even history are needed. Crowdsourcing outsources tasks conventionally performed in-house to a crowd and uses external knowledge to solve problems and democratize innovation. Social media is often employed in crowdsourcing for a crowd to create and share knowledge.

Originality/value/scientific novelty of the research. This paper proposes a novel approach employing social media to crowdsource knowledge from a crowd for constructing crowd knowledge databases.

Practical importance of the research. The crowd knowledge database is expected to be used by the current computational tools to support designers producing highly creative ideas that are new to the crowd, in new product design, and ultimately to innovation.

Research limitations/Future research. In this study to provide insights and potential directions for future research are discussed that challenges of employing described approach.  

Paper type – theoretical.

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Author Biographies

Zainal Ilmi, Mulawarman Univesity, Indonesia

Senior Lecturer, Dr, Department of Management, Faculty of Economics and Business, Mulawarman Univesity, Indonesia

Adi Wijaya, Mulawarman Univesity, Indonesia

Senior Lecturer, Department of Economics, Faculty of Economics and Business, Mulawarman Univesity, Indonesia

 

Jati Kasuma, Universiti Teknologi Mara Sarawak, Malaysia

Assoc. Prof., Faculty of Business and Management, Universiti Teknologi Mara Sarawak, Universiti Teknologi Mara Sarawak, Malaysia

Dio Caisar Darma, Sekolah Tinggi Ilmu Ekonomi Samarinda, Indonesia

Researcher, Department of Management, Sekolah Tinggi Ilmu Ekonomi Samarinda, Indonesia

 

References

Abrahamson, S., Ryder, P., & Unterbeg, B. (2013). Crowdstorm: the future of innovation, ideas, and problem-solving. New Jersey: John Wiley & Sons.

Ackerman, S. (2013). This Is the Million-Dollar Design for Darpa's Crowdsourced Swimming Tank. Retrieved July 17, 2020 from https://bit.ly/3Ak5WtK.

Akshay, R. K., & Walter, S. L. (2018). Plexiglass: Multiplexing passive and active tasks for more efficient crowdsourcing. Sixth AAAI Conference on Human Computation and Crowdsourcing.

Altshuller, G. S. (1984). Creativity as an exact science: The theory of the solution of inventive problems. Amsterdam: Gordon and Breach Publishers.

Amabile, T. M. (1983). The social psychology of creativity. New York: Springer-Verlag.

Bertola, P., & Teixeira, J. C. (2003). Design as a knowledge agent. Design Studies, 24(2), 181–194. https://doi.org/10.1016/s0142-694x(02)00036-4.

Boden, M. A. (2004). The creative mind: Myths and mechanisms (Vol. 2). London: Routledge.

Brabham, D. C. (2008). Crowdsourcing as a Model for Problem Solving: An Introduction and Cases. Convergence, 14(1), 75-90.

Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s mechanical turk: A new source of inexpensive, yet high-quality, data?”. Perspectives on psychological science, 6(1), 3–5. https://doi.org/10.1177/1745691610393980.

Cash, P., & Štorga, M. (2015). Multifaceted assessment of ideation: using networks to link ideation and design activity. Journal of Engineering Design, 26(10-12), 391-415. https://doi.org/10.1080/09544828.2015.1070813.

Charalabidis, Y. N., Loukis, E., Androutsopoulou, A., Karkaletsis, V., & Triantafillou, A. (2014). Passive crowdsourcing in government using social media. Transforming Government: People, Process and Policy, 8(2), 283-308. https://doi.org/10.1108/tg-09-2013-0035.

Chen, K. T., Wu, C. C., Chang, Y. C., & Lei, C. L. (2009). A crowdsourceable QoE evaluation framework for multimedia content. Proceedings of the 17th ACM international conference on Multimedia (pp. 491-500). ACM.

Colleoni, E., Rozza, A., & Arvidsson, A. (2014). Echo chamber or public sphere? Predicting political orientation and measuring political homophily in Twitter using big data. Journal of Communication, 64(2), 317-332. ttps://doi.org/10.1111/jcom.12084.

Corp, G. (2001). The goldcorp challenge winners. Retrieved July 11, 2020 from https://bit.ly/3AeJ3Yy.

Cullina, E., Conboy, K., & Morgan, L. (2016). Choosing the right crowd: An iterative process for crowd specification in crowdsourcing initiatives. System Sciences (HICSS) 49th Hawaii International Conference (pp. 4355-4364). IEEE.

Daly, S. R., Yilmaz, S., Christian, J. L., Seifert, C. M., & Gonzalez, R. (2012). Design heuristics in engineering concept generation. Journal of Engineering Education, 101(4), 601-629. https://doi.org/10.1002/j.2168-9830.2012.tb01121.x.

Di Gangi, P. M., & Wasko, M. (2009). Steal my idea! organizational adoption of user innovations from a user innovation community: A case study of dell idea storm. Decision Support Systems, 48(1), 303–312. ttps://doi.org/10.1016/j.dss.2009.04.004.

Dodgson, M., Gann, D., & Salter, A. (2006). The role of technology in the shift towards open innovation: the case of Procter & Gamble. R&D Management, 36(3), 333-346. https://doi.org/10.1111/j.1467-9310.2006.00429.x.

Dubois, E., & Blank, G. (2018). The echo chamber is overstated: the moderating effect of political interest and diverse media. Information, Communication & Society, 21(5), 729-745. https://doi.org/10.1080/1369118x.2018.1428656.

Feng, L., Yanqing, H., Baowen, L. H., Eugene, S., Shlomo, H., & Braunstein, L. A. (2015). Competing for Attention in Social Media under Information Overload Conditions. PloS One, 10(7), e0126090. https://doi.org/10.1371/journal.pone.0126090.

Forbes, H. L., & Schaefer, D. (2018). Crowdsourcing in product development: Current state and future research directions. Proceedings of the DESIGN 2018 15th International Design Conference. Dubrovnik, Croatia: The Design Society.

Forbes, H., Han, J., & Schaefer, D. (2019). Exploring a Social Media Crowdsourcing Data-Driven Approach for Innovation. Proceedings of the International Conference on Systematic Innovation. The 2019 International Conference on Systematic Innovation. Liverpool, UK.

Garimella, K., Gionis, A., Parotsidis, N., & Tatti, N. (2017). Balancing information exposure in social networks. 31st Conference on Neural Information Processing Systems (NIPS 2017). Long Beach, CA, USA.

Gerth, R. J., Burnap, A., & Papalambros, P. (2012). Crowdsourcing: A primer and its implications for systems engineering. Michigan University Ann Arbor.

Goldschmidt, G. (2001). Visual Analogy - a Strategy for Design Reasoning and Learning. In G. Goldschmidt, Design Knowing and Learning: Cognition in Design Education (pp. 199-219). Oxford: Elsevier Science.

Goucher-Lambert, K., & Cagan, J. (2019). Crowdsourcing inspiration: Using crowd-generated inspirational stimuli to support designer ideation. Design Studies, 61(1), 1-29. https://doi.org/10.1016/j.destud.2019.01.001.

Han, J., Forbes, H., & Schaefer, D. (2019). An Exploration of the Relations between Functionality, Aesthetics and Creativity in Design. Proceedings of the Design Society: International Conference on Engineering Design, 1(1), 259-268. https://doi.org/10.1017/dsi.2019.29.

Han, J., Shi, F., Chen, L., & Childs, P. R. (2018). A computational tool for creative idea generation based on analogical reasoning and ontology. Artificial Intelligence for Engineering Design, 32(4), 462-477. ttps://doi.org/10.1017/s0890060418000082.

Han, J., Shi, F., Chen, L., & Childs, P. R. (2018). The Combinator – a computer-based tool for creative idea generation based on a simulation approach. Design Science, 4, e11. https://doi.org/10.1017/dsj.2018.7.

Howard, T. J., Culley, S., & Dekoninck, E. A. (2011). Reuse of ideas and concepts for creative stimuli in engineering design. Journal of Engineering Design, 22(8), 565-581. https://doi.org/10.1080/09544821003598573.

Howe, J. (2006). The rise of crowdsourcing. Wired Magazine, 14(6), 1-4.

Iyer, G., & Zsolt, K. (2015). Competing for attention in social communication markets. Management Science, 62(8), 2304-2320. https://doi.org/10.1287/mnsc.2015.2209.

Janssen, M., Konopnicki, D., Snowdon, J. L., & Ojo, A. (2017). Driving public sector innovation using big and open linked data (BOLD). Information systems frontiers, 19(2), 189-195. https://doi.org/10.1007/s10796-017-9746-2.

Jonson, B. (2005). Design ideation: the conceptual sketch in the digital age. Design Studies, 26(6), 613-624. ttps://doi.org/10.1016/j.destud.2005.03.001.

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53(1), 59-68. https://doi.org/10.1016/j.bushor.2009.09.003.

Kemp, S, Hootsuite. (2019). Digital Report 2019: Essential Insights into How People Around the World Use the Internet Mobile Devices. Retrieved July 8, 2020 from https://bit.ly/3zd4isB.

Keshwani, S., & Chakrabarti, A. (2017). Towards automatic classification of description of analogies into SAPPhIRE constructs. Research into Design for Communities, 2, 643-655. https://doi.org/10.1007/978-981-10-3521-0_55.

Kittur, A., Smus, B., & Khamkar, S. K. (2011). Crowdforge: Crowdsourcing complex work. Proceedings of the 24th annual ACM symposium on User interface software and technology (pp. 43-52). ACM.

Liu, S. B. (2014). Crisis crowdsourcing framework: Designing strategic configurations of crowdsourcing for the emergency management domain. Computer Supported Cooperative Work, 23(4-6), 389-443. https://doi.org/10.1007/s10606-014-9204-3.

McCaffrey, T., & Spector, L. (2017). An approach to human–machine collaboration in innovation. Artificial Intelligence for Engineering Design, 32(1), 1-15. https://doi.org/10.1017/s0890060416000524.

Mount, M., & Martinez, M. G. (2014). Social Media: A Tool for Open Innovation. California Management Review, 56(4), 124-143. https://doi.org/10.1525/cmr.2014.56.4.124.

Nijstad, B. A., & Stroebe, W. (2006). How the Group Affects the Mind: A Cognitive Model of Idea Generation in Groups. Personality and Social Psychology Review, 10(3), 186-213. https://doi.org/10.1207/s15327957pspr1003_1.

Niu, X. J., Qin, S. F., Vines, J., Wong, R., & Lu, H. (2019). Key crowdsourcing technologies for product design and development. International Journal of Automation and Computing, 16(1), 1-15. https://doi.org/10.1007/s11633-018-1138-7.

Panchal, J. H. (2015). Using crowds in engineering design–Towards a holistic framework. Proceedings of the 20th International Conference on Engineering Design (ICED 15), 8: Innovation and Creativity, pp. 041-050. Milan, Italy.

Paulus, P. B., & Dzindolet, M. (2008). Social influence, creativity and innovation. Social Influence, 3(4), 228-247. https://doi.org/10.1080/15534510802341082.

Paulus, P. B., Dzindolet, M., & Kohn, N. W. (2012). Chapter 14 - Collaborative Creativity: Group Creativity and Team Innovation. In Handbook of Organizational Creativity. San Diego: Academic Press.

Romero, Mauricio, D., Meeder, B., Barash, V., & Kleinberg, J. (2011). Maintaining ties on social media sites: The competing effects of balance, exchange, and betweenness. Proceedings of the Fifth International Conference on Weblogs and Social Media. Barcelona, Spain.

Sarkar, P., & Chakrabarti, A. (2011). Assessing design creativity. Design Studies, 32(4), 348-383. https://doi.org/10.1016/j.destud.2011.01.002.

Shi, F., Chen, L., Han, J., & Childs, P. (2017). A Data-Driven Text Mining and Semantic Network Analysis for Design Information Retrieval. Journal of Mechanical Design, 139(11), 111402-111414. https://doi.org/10.1115/1.4037649.

Siddharth, L., & Chakrabarti, A. (2018). Evaluating the impact of Idea-Inspire 4.0 on analogical transfer of concepts. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 32(4), 431–448. https://doi.org/10.1017/s0890060418000136.

Speer, R., Chin, J., & Havasi, C. (2017). ConceptNet 5.5: an open multilingual graph of general knowledge. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. San Francisco, California.

To, H., & Shahabi, C. (2018). Location privacy in spatial crowdsourcing. In Handbook of Mobile Data Privacy (pp. 167-194). Springer, Cham.

Ullman, D. G. (2010). The mechanical design process: Part 1. New York: McGraw-Hill.

Yilmaz, S., Daly, S. R., Seifert, C. M., & Gonzalez, R. (2016). Evidence-based design heuristics for idea generation. Design Studies, 46, 95–124. https://doi.org/10.1016/j.destud.2016.05.001.

Zhan, L., Sun, Y., Wang, N., & Zhang, X. (2016). Understanding the influence of social media on people’s life satisfaction through two competing explanatory mechanisms. Aslib Journal of Information Management, 68(3), 347–361. https://doi.org/10.1108/ajim-12-2015-0195.

Published
2020-06-25
How to Cite
Ilmi, Z., Wijaya, A., Kasuma, J., & Darma, D. C. (2020). The crowdsourcing data for innovation: Does it Matter?. European Journal of Management Issues, 28(1-2), 3-12. https://doi.org/10.15421/192001