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Using Crowd Funding for Idea Assessment inside Organizations : Lessons Learned from a Market Engineering Perspective

Title data

Feldmann, Niels ; Gimpel, Henner ; Kohler, Marc ; Weinhardt, Christof:
Using Crowd Funding for Idea Assessment inside Organizations : Lessons Learned from a Market Engineering Perspective.
2013
Event: IEEE 3rd International Conference on Cloud and Green Computing , 30 Sept.-2 Oct. 2013 , Karlsruhe, Germany.
(Conference item: Conference , Paper )
DOI: https://doi.org/10.1109/CGC.2013.88

Official URL: Volltext

Abstract in another language

Idea assessment is a critical activity in organizations' innovation management. In recent years, Wisdom of the Crowd mechanisms, such as prediction markets, have received increasing awareness as a means to improve idea assessment. Currently, crowd funding is becoming increasingly popular amongst people seeking funding for implementing their ideas, as well as others potentially willing to invest in those. While first companies are already starting to apply crowd funding for internal idea assessment, knowledge on how to design crowd funding approaches inside the enterprise is almost non-existent. In this work-in-progress paper we contribute to building a body of knowledge for this new topic by analyzing the structural overlap between crowd funding and prediction markets. We strive to provide a basis for a decision on how far transfer of existing knowledge from the latter to the design of organization internal crowd funding mechanisms is possible. For this, we assign the characteristics of crowd funding mechanisms, derived from literature and an assessment of 13 platforms, to an established market engineering framework and compare them to current implementations of prediction markets for idea assessment. We find similarities, as well as distinct differences and outline areas of future research.

Further data

Item Type: Conference item (Paper)
Refereed: Yes
Keywords: crowdsourcing; crowd funding; crowd investing; prediction markets; idea markets; market engineering
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 14 Sep 2018 07:16
Last Modified: 17 Oct 2019 09:39
URI: https://eref.uni-bayreuth.de/id/eprint/45793