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Business process crowdsourcing concerns the integration of the crowdsourcing strategy and business process management. Crowdsourcing is often an ad-hoc endeavor, e.g., allowing crowd workers to perform simple, independent tasks. Business process crowdsourcing empowers organizations to use crowdsourcing on a long-term, recurrent basis.

We defined an ontology of business process crowdsourcing, which regards crowdsourcing from a business process management perspective [1]. The ontology was built from a literature review on crowdsourcing. The ontology was evaluated against two automated ontologies generated from the same sources. These ontologies provide a holistic view over business process crowdsourcing.

We have also done an extensive literature review on business process crowdsourcing, which covers multiple fields of research. The results identify a set of fundamental factors influencing the decision to crowdsource [2], [3]. We have developed a process model of business process crowdsourcing [4], [5]. The model helps organizations establish repeated business process crowdsourcing patterns.

Based on the business process crowdsourcing ontology, we developed a tool helping organizations to make the decision to crowdsource [6]–[9]. The tool has been extensively evaluated, showing that organizations may benefit from its use [6], [8]. The major evaluation action involved about 200 participants making the decision to crowdsource [6]. The tool supporting the decision to crowdsource has been developed using the design science research paradigm [1], [10], [11]. The tool development has been extended and generalized beyond crowdsourcing to consider the support to evidence-based management [12].

In a related research stream, we researched how to bring crowdsourcing into research methodology, focusing in particular on theory testing [13]–[17].

References

[1] N. Thuan, P. Antunes, D. Johnstone, and A. Son, “Building an Enterprise Ontology of Business Process Crowdsourcing: A Design Science Approach,” Singapore, 2015. doi: http://aisel.aisnet.org/pacis2015/112.

[2] N. Thuan, P. Antunes, and D. Johnstone, “Factors Influencing the Decision to Crowdsource: A Systematic Literature Review,” Information Systems Frontiers, vol. 18, no. 1, pp. 47–68, 2016, doi: 10.1007/s10796-015-9578-x.

[3] N. Thuan, P. Antunes, and D. Johnstone, “Factors Influencing the Decision to Crowdsource,” in Collaboration and Technology, 19th International Conference, Wellington, New Zealand, vol. 8224, P. Antunes, M. Gerosa, A. Sylvester, J. Vassileva, and G. de Vreede, Eds. Heidelberg: Springer, 2013, pp. 110–125.

[4] N. Thuan, P. Antunes, and D. Johnstone, “Toward a Nexus Model Supporting the Establishment of Business Process Crowdsourcing,” in 1st International Conference on Future Data and Security Engineering. Ho Chi Minh City, Vietnam, vol. 8860, T. Dang, R. Wagner, E. Neuhold, M. Takizawa, and J. Küng, Eds. Heidelberg: Springer, 2014, pp. 136–150.

[5] N. Thuan, P. Antunes, and D. Johnstone, “A Process Model for Establishing Business Process Crowdsourcing,” Australasian Journal of Information Systems, vol. 21, pp. 1–21, 2017, doi: https://doi.org/10.3127/ajis.v21i0.1392.

[6] N. Thuan, P. Antunes, and D. Johnstone, “A Decision Tool for Business Process Crowdsourcing: Ontology, Design, and Evaluation,” Group Decision and Negotiation, vol. 27, no. 2, pp. 285–312, 2018, doi: https://doi.org/10.1007/s10726-018-9557-y.

[7] N. Thuan, P. Antunes, and D. Johnstone, “Establishing a Decision Tool for Business Process Crowdsourcing,” in 2nd International Conference on Future Data and Security Engineering. Ho Chi Minh City, Vietnam, Heidelberg, 2015, vol. 9446. doi: 10.1007/978-3-319-26135-5_7.

[8] N. Thuan, P. Antunes, and D. Johnstone, “Pilot Experiments on a Designed Crowdsourcing Decision Tool,” Nanchang, China, 2016. doi: 10.1109/CSCWD.2016.7566058.

[9] T. Antunes, P. Antunes, D. Johnstone, V. Nghia, and N. Thuan, “A Tool for Modelling Business Behaviour Using Decision Tables,” Ho Chi Minh City, Vietnam, 2019. doi: 10.1109/ISCIT.2019.8905161.

[10] N. Thuan, P. Antunes, and D. Johnstone, “A Design Science Method for Emerging Decision Support Environments,” Adelaide, Australia, 2015. doi: arXiv:1605.04725v1.

[11] N. Thuan, A. Drechsler, and P. Antunes, “Construction of Design Science Research Questions,” Communications of the Association for Information Systems, vol. 44, 2019, doi: 10.17705/1CAIS.04420.

[12] P. Antunes, D. Johnstone, N. Thuan, and G. Vreede, “Delivering Evidence-Based Management Services: Rising to the Challenge Using Design Science,” Knowledge Management Research & Practice, 2022, doi: 10.1080/14778238.2022.2064350.

[13] I. Enwereuzo, P. Antunes, and D. Johnstone, “On the Adoption of Crowdsourcing for Theory Testing,” Portsmouth, UK, 2018. doi: https://aisel.aisnet.org/ecis2018_rp/179.

[14] I. Enwereuzo, P. Antunes, and D. Johnstone, “Towards the Development of a DSS Supporting the Integration of Crowdsourcing in Theory Testing: Conceptual Framework and Model,” Hobart, Australia, 2017. doi: https://aisel.aisnet.org/acis2017/66.

[15] I. Enwereuzo, P. Antunes, and D. Johnstone, “Patterns of Testing Theory with Human Subjects: A Design Science Perspective,” Cancun, Mexico, 2019. doi: https://aisel.aisnet.org/amcis2019/systems_analysis_design/systems_analysis_design/3.

[16] I. Enwereuzo, P. Antunes, D. Johnstone, and G. de Vreede, “Design and Development of a DSS Supporting the Integration of Crowdsourcing in Theory Testing: A Design Science Perspective,” Xi’an, China, 2019. doi: https://aisel.aisnet.org/pacis2019/172.

[17] I. Enwereuzo, P. Antunes, and D. Johnstone, “Towards the Development of a DSS Supporting the Integration of Crowdsourcing in Theory Testing: Analytical Framework Design,” Cancun, Mexico, 2019. doi: https://aisel.aisnet.org/acis2017/66.