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2020 | OriginalPaper | Chapter

8. Tying It All Together: A Theory of Collective Production of Innovation to Inspire Future Research

Authors : Ann Majchrzak, Arvind Malhotra

Published in: Unleashing the Crowd

Publisher: Springer International Publishing

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Abstract

Since we are interested in progressing research, we present a scholarly version of our theory of collective production of innovation in which innovating crowds consist of some participants willing to use their scant two posts to disaggregate their knowledge into creative associations of knowledge batons and others willing to take those knowledge batons and co-mingle them to stimulate creative discoveries. The disaggregation occurs as people break down their causal models, their coherent perspectives, their proposals of need-solution pairs into factual assumptions, short statements of ideas, and creative associations. Since crowds spend so little time contributing to the wicked problem, the more effective the crowd can be at eliciting each other’s disaggregated knowledge in a way that stimulates creative thought in a virtuous cycle, the more likely that the crowd will successfully produce an innovative solution. The implications for a new direction for research on innovation and new organizational forms are discussed.

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Footnotes
1
Please see endnotes for Chap. 1, which contains the references supporting these statements.
 
2
Finke, R.A., Ward, T.B., Smith, S.M. (1996) Creative Cognition: Theory, Research, and Applications. Cambridge: MIT Press.
 
3
Amabile, T. M. 1996. Creativity in Context: The Social Psychology of Creativity. Boulder, CO: Westview.
 
4
Scott Page in his Academy of Management Perspective article discusses the concept of superadditivity, when multiple perspectives are engaged so that new perspectives are created. The result is not integration or synthesis in the sense of simply accommodating to different perspectives, but rather, the creation of a new perspective. We do not use Page’s words of superadditivity and prefer co-mingling to avoid any confusion that the issues raised simply add up to a new perspective. Page, S. E. (2007). Making the difference: Applying a logic of diversity. Academy of Management Perspectives, 21(4), 6–20.
 
5
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7
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8
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9
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10
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11
Majchrzak, A. and Malhotra, A. 2016. Effect of Knowledge-sharing Trajectories on Innovative Outcomes in Temporary Online Crowds, Information Systems Research, 27(4): 685–703 are one exception to this.
 
12
Cognitive stigmergy is most comprehensively described by Christensen, L. R. 2013. Stigmergy in human practice: Coordination in construction work. Cognitive Systems Research, 21: 40–51; Marsh, L., & Onof, C. 2008. Stigmergic epistemology, stigmergic cognition. Cognitive Systems Research, 9(1–2): 136–149; Dipple, A., Raymond, K., & Docherty, M. 2014. General theory of stigmergy: Modelling stigma semantics. Cognitive Systems Research, 31: 61–92 and Ricci, A., Omicini, A., Viroli, M., Gardelli, L., & Oliva, E. 2006. Cognitive stigmergy: Towards a framework based on agents and artifacts. In D. Weyns, H.V.D. Parunak & F. Michel (Eds). International Workshop on Environments for Multi-Agent Systems (pp. 124–140). Springer, Berlin, Heidelberg.
 
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16
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17
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Majchrzak, A. and Malhotra, A. 2016. Effect of Knowledge-sharing Trajectories on Innovative Outcomes in Temporary Online Crowds, Information Systems Research, 27(4): 685–703.
 
21
Parunak, H.V.D. 2006. A survey of environments and mechanisms for human-human stigmergy In D. Weyns, H.V.D. Parunak & F. Michel (Eds). International Workshop on Environments for Multi-Agent Systems (pp. 124–140). Springer, Berlin, Heidelberg.
 
22
Malhotra, A., & Majchrzak, A. 2014. Managing crowds in innovation challenges. California Management Review, 56(4): 103–123; Ranade, G., & Varshney, L. R. 2018. The role of information patterns in designing crowdsourcing contests. In C. Tucci, A. Afuah and G. Viscusi (Ed) Creating and Capturing Value Through Crowdsourcing. Oxford Scholarship Press.
 
23
Marsh, L., & Onof, C. 2008. Stigmergic epistemology, stigmergic cognition. Cognitive Systems Research, 9(1–2): 136–149.
 
24
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25
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26
Viscusi, G. & Tucci, C.L. 2018. Three’s a Crowd. In Tucci, C. L., Afuah, A., & Viscusi, G. (Eds.) Creating and capturing value through crowdsourcing, Oxford University Press, p. 42.
 
27
Theraulaz, G. 2014. Embracing the creativity of stigmergy in social insects. Architectural Design 84(5): 54–59.
 
28
Dipple, A., Raymond, K., & Docherty, M. 2014. General theory of stigmergy: Modelling stigma semantics. Cognitive Systems Research, 31: 61–92.
 
29
Majchrzak, A. and Malhotra, A. 2016. Effect of Knowledge-sharing Trajectories on Innovative Outcomes in Temporary Online Crowds, Information Systems Research, 27(4): 685–703.
 
30
Heylighen, F. 2016. Stigmergy as a universal coordination mechanism I: Definition and components. Cognitive Systems Research, 38: 4–13; Parunak, H.V.D. 2006. A survey of environments and mechanisms for human-human stigmergy In D. Weyns, H.V.D. Parunak & F. Michel (Eds). International Workshop on Environments for Multi-Agent Systems (pp. 124–140). Springer, Berlin, Heidelberg.
 
31
Parunak, H.V.D. 2006. A survey of environments and mechanisms for human-human stigmergy In D. Weyns, H.V.D. Parunak & F. Michel (Eds). International Workshop on Environments for Multi-Agent Systems (pp. 124–140). Springer, Berlin, Heidelberg.
 
32
Heylighen, F. 2016. Stigmergy as a universal coordination mechanism I: Definition and components. Cognitive Systems Research, 38: 4–13.
 
33
Dipple, A., Raymond, K., & Docherty, M. 2014. General theory of stigmergy: Modelling stigma semantics. Cognitive Systems Research, 31: 61–92.
 
34
Dipple, A., Raymond, K., & Docherty, M. 2014. General theory of stigmergy: Modelling stigma semantics. Cognitive Systems Research, 31: 61–92.
 
35
Ricci, A., Omicini, A., Viroli, M., Gardelli, L., & Oliva, E. 2006. Cognitive stigmergy: Towards a framework based on agents and artifacts. In D. Weyns, H.V.D. Parunak & F. Michel (Eds). International Workshop on Environments for Multi-Agent Systems (pp. 124–140). Springer, Berlin, Heidelberg.
 
36
Dipple, A., Raymond, K., & Docherty, M. 2014. General theory of stigmergy: Modelling stigma semantics. Cognitive Systems Research, 31: 61–92; Parunak, H.V.D. 2006. A survey of environments and mechanisms for human-human stigmergy In D. Weyns, H.V.D. Parunak & F. Michel (Eds). International Workshop on Environments for Multi-Agent Systems (pp. 124–140). Springer, Berlin, Heidelberg.
 
37
This builds on the discussion of routines in Feldman, M. S., & Pentland, B. T. 2003. Reconceptualizing organizational routines as a source of flexibility and change. Administrative Science Quarterly, 48(1): 94–118.
 
38
And, using the defenition of emergence from Mittal, S. 2013. Emergence in stigmergic and complex adaptive systems: A formal discrete event systems perspective. Cognitive Systems Research, 21: 22–39.
 
39
Afuah, A. 2018a. Crowdsourcing: A Primer and Research Framework. In Creating and capturing value through crowdsourcing. In Tucci, C. L., Afuah, A., & Viscusi, G. (Eds.), Creating and Capturing Value through Crowdsourcing, Oxford University Press, pp. 39–57.
 
40
Viscusi, G. & Tucci, C.L. 2018. Three’s a Crowd. In Tucci, C. L., Afuah, A., & Viscusi, G. (Eds.) Creating and capturing value through crowdsourcing, Oxford University Press, pp. 39–57.
 
41
Nickerson, J. A., Wuebker, R., & Zenger, T. 2017. Problems, theories, and governing the crowd. Strategic Organization, 15(2): 275–288.
 
42
For example, Afuah, A. 2018a. Crowdsourcing: A Primer and Research Framework. In Creating and capturing value through crowdsourcing. In Tucci, C. L., Afuah, A., & Viscusi, G. (Eds.), Creating and Capturing Value through Crowdsourcing, Oxford University Press, pp. 39–57; Dahlander, L., Piezunka, H., & Jeppesen, L. 2018. How organizations manage crowds: Define, broadcast, attract and select. In J. Sydow and H. Berends (eds.) Managing Inter-organizational collaborations – Process View. Part of a series: Research in the Sociology of Organizations; Jeppesen, L. B., & Lakhani, K. R. 2010. Marginality and problem-solving effectiveness in broadcast search. Organization Science, 21(5): 1016–1033.
 
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Thank you to John Wentworth for this wonderful idea.
 
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55
Thank you to John Wentworth for this interesting idea.
 
56
This notion of the burstiness of the crowd was raised by Riedl, C., & Woolley, A. W. (2017). Teams vs. crowds: A field test of the relative contribution of incentives, member ability, and emergent collaboration to crowd-based problem solving performance. Academy of Management Discoveries, 3(4), 382–403.
 
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Majchrzak, A., Griffith, T., Reez, D., Alexy, O. 2018. Organizations Designed for Grand Challenges: Generative Dilemmas and Implications for Organization Design Theory. Academy of Management Discoveries, 4(4): 472–496.
 
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As suggested by Vedres, B., & Stark, D. 2010. Structural folds: Generative disruption in overlapping groups. American Journal of Sociology, 115(4): 1150–1190.
 
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As suggested by Tsoukas, H. 2009. A dialogical approach to the creation of new knowledge in organizations. Organization Science, 20(6): 941–957.
 
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As suggested by Nickerson, J. A., Wuebker, R., & Zenger, T. 2017. Problems, theories, and governing the crowd. Strategic Organization, 15(2): 275–288.
 
67
Dahlander, L., Piezunka, H., & Jeppesen, L. 2018. How organizations manage crowds: Define, broadcast, attract and select. In J. Sydow and H. Berends (eds.) Managing Inter-organizational collaborations – Process View. Part of a series: Research in the Sociology of Organizations; Jeppesen, L. B., & Lakhani, K. R. 2010. Marginality and problem-solving effectiveness in broadcast search. Organization Science, 21(5): 1016–1033.
 
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E.g., Dahlander, L., Piezunka, H., & Jeppesen, L. 2018. How organizations manage crowds: Define, broadcast, attract and select. In J. Sydow and H. Berends (eds.) Managing Inter-organizational collaborations – Process View. Part of a series: Research in the Sociology of Organizations; Levina and Fayard (2018).
 
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Malhotra, A., Majchrzak, A., & Niemiec, R. M. 2017. Using public crowds for open strategy formulation: mitigating the risks of knowledge gaps. Long Range Planning, 50(3): 397–410; Malhotra, A., Majchrzak, A., Kesebi, L., & Looram, S. 2017. Developing innovative solutions through internal crowdsourcing. MIT Sloan Management Review, 58(4): 73.
 
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Levina, N. & Fayard, A. L. 2018. Tapping into diversity through open innovation platforms: The emergence of boundary-spanning practices. In Tucci, C. L., Afuah, A., & Viscusi, G. (Eds.) Creating and Capturing Value through Crowdsourcing, Oxford University Press.
 
72
That Tsoukas, H. 2009. A dialogical approach to the creation of new knowledge in organizations. Organization Science, 20(6): 941–957 argues.
 
73
Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review, 37(3): 355–375; Dahlander, L., Piezunka, H., & Jeppesen, L. 2018. How organizations manage crowds: Define, broadcast, attract and select. In J. Sydow and H. Berends (eds.) Managing Inter-organizational collaborations – Process View. Part of a series: Research in the Sociology of Organizations.
 
74
Majchrzak, A., Griffith, T., Reez, D., Alexy, O. (2018) Organizations Designed for Grand Challenges: Generative Dilemmas and Implications for Organization Design Theory. Academy of Management Discoveries, 4(4), 472–496.
 
75
Lakhani KR and Panetta JA (2007) The principles of distributed innovation. Innovations 2(3): 97–112; Kornberger, M. (2017). The visible hand and the crowd: Analyzing organization design in distributed innovation systems. Strategic Organization, 15(2), 174–193.
 
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Garud, R., Jain, S., & Tuertscher, P. (2008). Incomplete by design and designing for incompleteness. Organization studies, 29(3), 351–371.
 
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Metadata
Title
Tying It All Together: A Theory of Collective Production of Innovation to Inspire Future Research
Authors
Ann Majchrzak
Arvind Malhotra
Copyright Year
2020
DOI
https://doi.org/10.1007/978-3-030-25557-2_8