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Decision Space: Collective Intelligence

In: Crowd-Based Business Models

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  • Rajagopal

    (Tecnologico de Monterrey)

Abstract
There are two-way and three-way decision spaces that involve multiple information taxonomy. In the three-way decision spaces, three basic elements: decision measurement, decision conditions, and decision evaluation functions are unified. The major challenges with collective intelligence are the screening, modeling, and measurement of information to make appropriate business decisions. This chapter discusses the ways of collective information decision process by involving the stakeholders and managers. The importance of stakeholder management and business governance in the decision process, interactive planning and governance, value chain management, and the pattern of market competition and growth in the crowd-based business ecosystems have been discussed in this chapter. Business governance, scaling, and performance management have been discussed in this chapter in the context of transformative relationship between data and people, which creates new forms of collective search for solutions and decision-making. This chapter argues that the crowd-based business model has emerged as voluntary open collaboration in the development of creative solutions that mobilizes experience-led paradigms to improve the business performance of global–local firms.

Suggested Citation

  • Rajagopal, 2021. "Decision Space: Collective Intelligence," Springer Books, in: Crowd-Based Business Models, chapter 0, pages 101-132, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-77083-9_4
    DOI: 10.1007/978-3-030-77083-9_4
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    Cited by:

    1. Davies, Jennifer & Sharifi, Hossein & Lyons, Andrew & Forster, Rick & Elsayed, Omar Khaled Shokry Mohamed, 2024. "Non-fungible tokens: The missing ingredient for sustainable supply chains in the metaverse age?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).

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