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Factors influencing the decision to crowdsource: A systematic literature review

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Abstract

Crowdsourcing is currently attracting much attention from organisations for its competitive advantages over traditional work structures regarding how to utilise skills and labour and especially to harvest expertise and innovation. Prior research suggests that the decision to crowdsource cannot simply be based on perceived advantages; rather multiple factors should be considered. However, a structured account and integration of the most important decision factors is still lacking. This research fills the gap by providing a systematic literature review of the decision to crowdsource. Our results identify nine factors and sixteen sub-factors influencing this decision. These factors are structured into a decision framework concerning task, people, management, and environmental factors. Based on this framework, we give several recommendations for managers making the crowdsourcing decision.

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Notes

  1. Preliminary results of the review were reported in a conference paper that appeared in Springer’s Lecture Notes in Computer Science, vol. 8224.

References

  • Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review, 37(3), 355–375.

    Article  Google Scholar 

  • Allahbakhsh, M., Benatallah, B., Ignjatovic, A., Motahari-Nezhad, H. R., Bertino, E., & Dustdar, S. (2013). Quality control in crowdsourcing systems: issues and directions. Internet Computing, IEEE, 17(2), 76–81.

    Article  Google Scholar 

  • Alonso, O., & Baeza-Yates, R. (2011). Design and implementation of relevance assessments using crowdsourcing. In P. Clough, C. Foley, C. Gurrin, G. F. Jones, W. Kraaij, H. Lee, & V. Mudoch (Eds.), Advances in information retrieval. LNC (Vol. 6611, pp. 153–164). Berlin Heidelberg: Springer.

    Chapter  Google Scholar 

  • Baesens, B., Setiono, R., Mues, C., & Vanthienen, J. (2003). Using neural network rule extraction and decision tables for credit-risk evaluation. Management Science, 49(3), 312–329.

    Article  Google Scholar 

  • Bai, C., & Sarkis, J. (2013). Green information technology strategic justification and evaluation. Information Systems Frontiers, 15(5), 831–847.

    Article  Google Scholar 

  • Benbasat, I., & Zmud, R. W. (1999). Empirical research in information systems: the practice of relevance. MIS Quarterly, 23(11), 3–16.

    Article  Google Scholar 

  • Boughzala, I., De Vreede, T., Nguyen, C., & De Vreede, G. J. (2014). Towards a Maturity Model for the Assessment of Ideation in Crowdsourcing Projects 47th Hawaii International Conference on System Sciences (HICSS) (pp. 483–490): IEEE.

  • Brabham, D. C. (2008). Crowdsourcing as a model for problem solving: an introduction and cases. Convergence: The International Journal of Research into New Media Technologies, 14(1), 75–90.

    Google Scholar 

  • Brabham, D. C. (2009). Crowdsourcing the public participation process for planning projects. Planning Theory, 8(3), 242–262.

    Article  Google Scholar 

  • Brabham, D. C. (2010). Moving the crowd at threadless. Information, Communication & Society, 13(8), 1122–1145.

    Article  Google Scholar 

  • Brabham, D. C. (2012a). A model for leveraging online communities. In A. Delwiche & J. Henderson (Eds.), The participatory cultures handbook. New York: Routledge.

    Google Scholar 

  • Brabham, D. C. (2012b). Motivations for participation in a crowdsourcing application to improve public engagement in transit planning. Journal of Applied Communication Research, 40(3), 307–328.

    Article  Google Scholar 

  • Brabham, D. C. (2013). Crowdsourcing. Canbridge: The MIT Press.

    Google Scholar 

  • Buecheler, T., Sieg, J. H., Füchslin, R. M., & Pfeifer, R. (2010). Crowdsourcing, open innovation and collective intelligence in the scientific method: a research agenda and operational framework. Proceedings of the twelfth international conference on the synthesis and simulation of living systems. Denmark: Odense.

    Google Scholar 

  • Burger-Helmchen, T., & Pénin, J. (2010). The limits of crowdsourcing inventive activities: What do transaction cost theory and the evolutionary theories of the firm teach us. Paper presented at the workshop on open source innovation. France: Strasbourg.

    Google Scholar 

  • Chanal, V., & Caron-Fasan, M. L. (2010). The difficulties involved in developing business models open to innovation communities: the case of a crowdsourcing platform. Management, 13(4), 318–340.

    Google Scholar 

  • Corney, J., Torres-Sanchez, C., Jagadeesan, A. P., Yan, X., Regli, W., & Medellin, H. (2010). Putting the crowd to work in a knowledge-based factory. Advanced Engineering Informatics, 24(3), 243–250.

    Article  Google Scholar 

  • Curran, S., Feeney, K., Schaler, R., & Lewis, D. (2009). The management of crowdsourcing in business processes. Paper presented at the Integrated Network Management-Workshops, IM apos.

  • De Roover, W., & Vanthienen, J. (2011). On the relation between decision structures, tables and processes. In R. Meersman, D. Tharam & H. Pilar (Eds.), On the Move to Meaningful Internet Systems: OTM 2011 Workshops. LNCS (Vol. 7046, pp. 591–598): Springer Berlin Heidelberg.

  • De Vreede, T., Nguyen, C., De Vreede, G. J., Boughzala, I., Oh, O., & Reiter-Palmon, R. (2013). A Theoretical Model of User Engagement in Crowdsourcing. In P. Antunes, M. Gerosa, A. Sylvester, J. Vassileva, & G. J. De Vreede (Eds.), Collaboration and Technology. LNCS (Vol. 8224, pp. 94–109). Berlin Heidelberg: Springer.

    Chapter  Google Scholar 

  • Dibbern, J., Goles, T., Hirschheim, R., & Jayatilaka, B. (2004). Information systems outsourcing: a survey and analysis of the literature. ACM SIGMIS Database, 35(4), 6–102.

    Article  Google Scholar 

  • Djelassi, S., & Decoopman, I. (2013). Customers’ participation in product development through crowdsourcing: Issues and implications. Industrial Marketing Management, 42(5), 683–692.

    Article  Google Scholar 

  • Doan, A., Ramakrishnan, R., & Halevy, A. Y. (2011). Crowdsourcing systems on the world-wide web. Communications of the ACM, 54(4), 86–96.

    Article  Google Scholar 

  • Dow, S., Kulkarni, A., Bunge, B., Nguyen, T., Klemmer, S., & Hartmann, B. (2011). Shepherding the crowd: managing and providing feedback to crowd workers. Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems, 1669–1674.

  • Erickson, L. B., & Trauth, E. M. (2013). Getting work done: evaluating the potential of crowdsourcing as a model for business process outsourcing service delivery. Proceedings of the 2013 annual conference on computers and people research, 135–140.

  • Estellés-Arolas, E., & González-Ladrón-de-Guevara, F. (2012). Towards an integrated crowdsourcing definition. Journal of Information Science, 38(2), 189–200.

    Article  Google Scholar 

  • Feller, J., Finnegan, P., Hayes, J., & O’Reilly, P. (2012). ‘Orchestrating’sustainable crowdsourcing: a characterisation of solver brokerages. The Journal of Strategic Information Systems, 21(3), 216–232.

    Article  Google Scholar 

  • Freyne, J., Coyle, L., Smyth, B., & Cunningham, P. (2010). Relative status of journal and conference publications in computer science. Communications of the ACM, 53(11), 124–132.

    Article  Google Scholar 

  • Gassenheimer, J. B., Siguaw, J. A., & Hunter, G. L. (2013). Exploring motivations and the capacity for business crowdsourcing. AMS Review, 3(4), 205–216.

    Article  Google Scholar 

  • Geiger, D., Seedorf, S., Schulze, T., Nickerson, R. C., & Schader, M. (2011). Managing the crowd: towards a taxonomy of crowdsourcing processes. Proceedings of the Seventeenth Americas Conference on Information Systems.

  • Geiger, D., Rosemann, M., Fielt, E., & Schader, M. (2012). Crowdsourcing Information Systems - Definition, Typology, and Design. Proceedings of the 33rd International Conference on Information Systems.

  • Heimerl, K., Gawalt, B., Chen, K., Parikh, T., & Hartmann, B. (2012). CommunitySourcing: engaging local crowds to perform expert work via physical kiosks. Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems, 1539–1548.

  • Hetmank, L. (2013). Components and Functions of Crowdsourcing Systems–A Systematic Literature Review. Paper presented at the 11th International Conference on Wirtschaftsinformatik, Leipzig, Germany.

  • Hirth, M., Hoßfeld, T., & Tran-Gia, P. (2011). Anatomy of a crowdsourcing platform-using the example of microworkers. com. Paper presented at the Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), Seoul

  • Holley, R. (2010). Crowdsourcing: How and Why Should Libraries Do It? D-Lib Magazine. Retrieved from http://dlib.org/dlib/march10/holley/03holley.html

  • Hoßfeld, T., Keimel, C., Hirth, M., Gardlo, B., Habigt, J., Diepold, K., & Tran-Gia, P. (2013). Best practices for QoE crowdtesting: QoE assessment with crowdsourcing. IEEE Transactions on Multimedia, 16(2), 541–558.

    Article  Google Scholar 

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

    Google Scholar 

  • Huston, L., & Sakkab, N. (2006). Connect and develop. Harvard Business Review, 84(3), 58–66.

    Google Scholar 

  • Huysmans, J., Dejaeger, K., Mues, C., Vanthienen, J., & Baesens, B. (2011). An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models. Decision Support Systems, 51(1), 141–154.

    Article  Google Scholar 

  • Hwang, Y. C., Yuan, S. T., & Weng, J. H. (2011). A study of the impacts of positive/negative feedback on collective wisdom—case study on social bookmarking sites. Information Systems Frontiers, 13(2), 265–279.

    Article  Google Scholar 

  • Ipeirotis, P. G., Provost, F., & Wang, J. (2010). Quality management on amazon mechanical turk. Proceedings of the ACM SIGKDD workshop on human computation, 64–67.

  • Kannangara, S. N., & Uguccioni, P. (2013). Risk Management in Crowdsourcing-Based Business Ecosystems. Technology Innovation Management Review (December 2013: Living Labs and Crowdsourcing).

  • Kärkkäinen, H., Jussila, J., & Multasuo, J. (2012). Can crowdsourcing really be used in B2B innovation? Proceeding of the 16th International Academic MindTrek Conference, 134–141.

  • Katz, R., & Allen, T. J. (1982). Investigating the Not invented here (NIH) syndrome: a look at the performance, tenure, and communication patterns of 50 R & D project groups. R&D Management, 12(1), 7–20.

    Article  Google Scholar 

  • Kazman, R., & Chen, H. M. (2009). The metropolis model a new logic for development of crowdsourced systems. Communications of the ACM, 52(7), 76–84.

    Article  Google Scholar 

  • King, W. R., & He, J. (2005). Understanding the role and methods of meta-analysis in is research. Communications of the Association for Information Systems, 16, 665–686.

    Google Scholar 

  • Kingston, A. (2013). “Choir attempted that beautiful anthem “Oh, radiant morn” – made a hash of it” - making a hash of the adkin diary transcriptions (Workshop on Crowdsourcing for the Digital Humanities and Cultural Heritage Sector. [PowerPoint slides]). New Zealand: Wellington.

    Google Scholar 

  • Kitchenham, B. (2007). Guidelines for performing systematic literature reviews in software engineering Version 2.3 EBSE Technical Report: Keele University and University of Durham.

  • Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic literature reviews in software engineering–a systematic literature review. Information and Software Technology, 51(1), 7–15.

    Article  Google Scholar 

  • Kittur, A., Nickerson, J., Bernstein, M., Gerber, E., Shaw, A., Zimmerman, J., . . . Horton, J. (2013). The Future of Crowd Work. Proceedings of the 2013 Conference on Computer Supported Cooperative Work.

  • Kucherbaev, P., Tranquillini, S., Daniel, F., Casati, F., Marchese, M., Brambilla, M., & Fraternali, P. (2013). Business processes for the crowd computer. In M. L. Rosa & P. Soffer (Eds.), Business process management workshops (pp. 256–267). Berlin Heidelberg: Springer.

    Chapter  Google Scholar 

  • Lee, H., & Seo, S. (2013). What Determines an Agreeable and Adoptable Idea? A Study of User Ideas on MyStarbucksIdea. com 46th Hawaii International Conference on System Sciences (HICSS) (pp. 3207–3217): IEEE.

  • Leimeister, J. M., Huber, M., Bretschneider, U., & Krcmar, H. (2009). Leveraging crowdsourcing: activation-supporting components for IT-based ideas competition. Journal of Management Information Systems, 26(1), 197–224.

    Article  Google Scholar 

  • Levy, Y., & Ellis, T. J. (2006). A systems approach to conduct an effective literature review in support of information systems research. Informing Science: International Journal of an Emerging Transdiscipline, 9, 181–212.

    Google Scholar 

  • Lloret, E., Plaza, L., & Aker, A. (2012). Analyzing the capabilities of crowdsourcing services for text summarization. Language Resources and Evaluation, 47(2), 337–369.

    Article  Google Scholar 

  • Lo, J. (2015). The information technology workforce: a review and assessment of voluntary turnover research. Information Systems Frontiers, 17(2), 387–411.

    Article  Google Scholar 

  • Lofi, C., Selke, J., & Balke, W. T. (2012). Information extraction meets crowdsourcing: a promising couple. Datenbank-Spektrum, 12(2), 109–120.

    Article  Google Scholar 

  • Lu, B., Hirschheim, R., & Schwarz, A. (2015). Examining the antecedent factors of online microsourcing. Information Systems Frontiers, 17(3), 601–617.

    Article  Google Scholar 

  • Lüttgens, D., Pollok, P., Antons, D., & Piller, F. (2014). Wisdom of the crowd and capabilities of a few: internal success factors of crowdsourcing for innovation. Journal of Business Economics, 84(3), 339–374.

    Article  Google Scholar 

  • Maiolini, R., & Naggi, R. (2011). Crowdsourcing and SMEs: Opportunities and challenges. In A. D’Atri, M. Ferrara, J. F. George & P. Spagnoletti (Eds.), Information Technology and Innovation Trends in Organizations (pp. 399–406): Physica-Verlag HD.

  • Malone, T. W., Laubacher, R., & Dellarocas, C. (2010). The collective intelligence genome. IEEE Engineering Management Review, 38(3), 38–52.

    Article  Google Scholar 

  • Marjanovic, S., Fry, C., & Chataway, J. (2012). Crowdsourcing based business models: in search of evidence for innovation 2.0. Science and Public Policy, 39(3), 318–332.

    Article  Google Scholar 

  • Martens, B., & Teuteberg, F. (2012). Decision-making in cloud computing environments: a cost and risk based approach. Information Systems Frontiers, 14(4), 871–893.

    Article  Google Scholar 

  • Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s mechanical Turk. Behavior Research Methods, 44(1), 1–23.

    Article  Google Scholar 

  • Mingers, J. (2003). The paucity of multimethod research: a review of the information systems literature. Information Systems Journal, 13(3), 233–249.

    Article  Google Scholar 

  • Muhdi, L., Daiber, M., Friesike, S., & Boutellier, R. (2011). The crowdsourcing process: an intermediary mediated idea generation approach in the early phase of innovation. International Journal of Entrepreneurship and Innovation Management, 14(4), 315–332.

    Article  Google Scholar 

  • Muntés-Mulero, V., Paladini, P., Manzoor, J., Gritti, A., Larriba-Pey, J. L., & Mijnhardt, F. (2013). Crowdsourcing for industrial problems. In J. Nin & D. Villatoro (Eds.), Citizen in sensor networks. LNCS (Vol. 7685, pp. 6–18). Berlin Heidelberg: Springer.

    Chapter  Google Scholar 

  • Naroditskiy, V., Jennings, N. R., Van Hentenryck, P., & Cebrian, M. (2013). Crowdsourcing dilemma. arXiv preprint arXiv:1304.3548.

  • Nickerson, R. C., Varshney, U., & Muntermann, J. (2012). A method for taxonomy development and its application in information systems. European Journal of Information Systems, 22(3), 336–359.

    Article  Google Scholar 

  • Okoli, C., & Schabram, K. (2010). A guide to conducting a systematic literature review of information systems research. Sprouts: Working Papers on Information Systems, 10(26).

  • O’Neill, J., Roy, S., Grasso, A., & Martin, D. (2013). Form digitization in BPO: from outsourcing to crowdsourcing? Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 197–206.

  • Pedersen, J., Kocsis, D., Tripathi, A., Tarrell, A., Weerakoon, A., Tahmasbi, N., . . . De Vreede, G. J. (2013). Conceptual Foundations of Crowdsourcing: A Review of IS Research. 46th Hawaii International Conference on System Sciences (HICSS), 579–588.

  • Ranade, G., & Varshney, L. R. (2012). To Crowdsource or not to Crowdsource? Paper presented at the AAAI Workshop Human Comput. (HCOMP’12).

  • Rouse, A. C. (2010). A preliminary taxonomy of crowdsourcing. Proceedings of the 21st Australasian Conference on Information Systems, 1–10.

  • Sakamoto, Y., Tanaka, Y., Yu, L., & Nickerson, J. V. (2011). The crowdsourcing design space. In D. Schmorrow & C. Fidopiastis (Eds.), Foundations of augmented cognition. Directing the future of adaptive systems. LNCS (Vol. 6780, pp. 346–355). Berlin Heidelberg: Springer.

    Chapter  Google Scholar 

  • Saxton, G. D., Oh, O., & Kishore, R. (2013). Rules of crowdsourcing: models, issues, and systems of control. Information Systems Management, 30(1), 2–20.

    Article  Google Scholar 

  • Schenk, E., & Guittard, C. (2011). Towards a characterization of crowdsourcing practices. Journal of Innovation Economics, 7(1), 93–107.

    Article  Google Scholar 

  • Seltzer, E., & Mahmoudi, D. (2013). Citizen participation, open innovation, and crowdsourcing challenges and opportunities for planning. Journal of Planning Literature, 28(1), 3–18.

    Article  Google Scholar 

  • Sharma, A. (2010). Crowdsourcing Critical Success Factor Model: Strategies to Harness the Collective Intelligence of the Crowd. Working paper. Retrieved May 2014, from http://www.crowdsourcing.org/document/crowdsourcing-critical-success-factor-model-strategies-to-harness-the-collective-intelligence-of-thecrowd/3167

  • Simula, H. (2013). The Rise and Fall of Crowdsourcing? 46th Hawaii International Conference on System Sciences (HICSS) (pp. 2783–2791): IEEE.

  • Smith, M., Busi, M., Ball, P., & Van Der Meer, R. (2008). Factors influencing an organisation’s ability to manage innovation: a structured literature review and conceptual model. International Journal of Innovation Management, 12(04), 655–676.

    Article  Google Scholar 

  • Souza, L., Ramos, I., & Esteves, J. (2009). Crowdsourcing Innovation: A Risk Management Approach. MCIS 2009 Proceedings.

  • Stoodley, I., Bruce, C., & Edwards, S. (2010). Expanding ethical vistas of IT professionals. Information Systems Frontiers, 12(4), 379–387.

    Article  Google Scholar 

  • Sun, J., & Qu, Z. (2014). Understanding health information technology adoption: A synthesis of literature from an activity perspective. Information Systems Frontiers, 1–14.

  • Surowiecki, J. (2004). The wisdom of crowds: Why the many Are smarter than the Few and How collective wisdom shapes business. New York: Doubleday.

    Google Scholar 

  • Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2), 237–246.

    Article  Google Scholar 

  • Thuan, N. H., Antunes, P., & Johnstone, D. (2014). Toward a nexus model supporting the establishment of business process crowdsourcing. In T. K. Dang, R. Wagner, E. Neuhold, M. Takizawa, J. Küng, & N. Thoai (Eds.), FDSE 2014. LNCS (Vol. 8860, pp. 136–150). Heidelberg: Springer.

    Google Scholar 

  • Thuan, N. H., Antunes, P., Johnstone, D., & Ha, X. S. (2015). Building an Enterprise Ontology of Business Process Crowdsourcing: A Design Science Approach. PACIS 2015 Proceedings, Paper 112.

  • Thuan, N. H., Antunes, P., & Johnstone, D. (2013). Factors Influencing the Decision to Crowdsource. In P. Antunes, M. Gerosa, A. Sylvester, J. Vassileva & G. J. De Vreede (Eds.), CRIWG 2013. LNCS (Vol. 8224, pp. 110–125): Springer Berlin Heidelberg

  • Tokarchuk, O., Cuel, R., & Zamarian, M. (2012). Analyzing crowd labor and designing incentives for humans in the loop. IEEE Internet Computing Magazine, 16(5), 45.

    Article  Google Scholar 

  • Trompette, P., Chanal, V., & Pelissier, C. (2008). Crowdsourcing as a way to access external knowledge for innovation. Paper presented at the 24 th EGOS Colloquium, Amsterdam, France.

  • Tung, Y. H., & Tseng, S. S. (2013). A novel approach to collaborative testing in a crowdsourcing environment. Journal of Systems and Software, 86(8), 2143–2153.

    Article  Google Scholar 

  • Vanthienen, J., & Wets, G. (1993). Building intelligent systems for management applications using decision tables. Proceedings of The Fifth Annual Conference on Intelligent Systems in Accounting, Finance and Management, Stanford, 16.

  • Vicente, K. J. (1999). Cognitive work analysis: Toward safe, productive, and healthy computer-based work: CRC Press.

  • Vukovic, M. (2009). Crowdsourcing for enterprises. Paper presented at the 2009 World Conference on Services-I, Los Angeles, CA.

  • Vukovic, M., & Bartolini, C. (2010). Towards a research agenda for enterprise crowdsourcing. In T. Margaria & B. Steffen (Eds.), Leveraging applications of formal methods, verification, and validation. LNCS (Vol. 6415, pp. 425–434): Springer Berlin Heidelberg.

  • Vukovic, M., Lopez, M., & Laredo, J. (2010). PeopleCloud for the globally integrated enterprise. In A. Dan, F. Gittler & F. Toumani (Eds.), Service-Oriented Computing. ICSOC/ServiceWave 2009 Workshops. LNCS (Vol. 6275, pp. 109–114): Springer Berlin Heidelberg.

  • Wang, A., Hoang, C. D. V., & Kan, M.-Y. (2013). Perspectives on crowdsourcing annotations for natural language processing. Language Resources and Evaluation, 47(1), 9–31.

    Article  Google Scholar 

  • Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: writing a literature review. MIS Quarterly, 26(2), xiii-xxiii.

  • Westpac. (2013). Westpac New Zealand to crowdsource mobile banking apps. Retrieved October, 2013, from http://www.westpac.co.nz/who-we-are/newsroom/media-releases-2013/westpac-new-zealand-to-crowdsource-mobile-banking-apps/

  • Wexler, M. N. (2011). Reconfiguring the sociology of the crowd: exploring crowdsourcing. International Journal of Sociology and Social Policy, 31(1/2), 6–20.

    Article  Google Scholar 

  • Whitla, P. (2009). Crowdsourcing and its application in marketing activities. Contemporary Management Research, 5(1).

  • Whitmore, A., Agarwal, A., & Da Xu, L. (2015). The internet of things—a survey of topics and trends. Information Systems Frontiers, 17(2), 261–274.

    Article  Google Scholar 

  • Yang, H., & Tate, M. (2012). A descriptive literature review and classification of cloud computing research. Communications of the Association for Information Systems, 31, 35–60.

    Google Scholar 

  • Yue, P., & Blevis, E. (2011). A survey of crowdsourcing as a means of collaboration and the implications of crowdsourcing for interaction design. In International conference on collaboration technologies and systems (CTS) (pp. 397–403).

    Google Scholar 

  • Zhao, Y., & Zhu, Q. (2014). Evaluation on crowdsourcing research: current status and future direction. Information Systems Frontiers, 16(3), 417–434.

    Article  Google Scholar 

  • Zheng, H., Li, D., & Hou, W. (2011). Task design, motivation, and participation in crowdsourcing contests. International Journal of Electronic Commerce, 15(4), 57–88.

    Article  Google Scholar 

  • Zogaj, S., Bretschneider, U., & Leimeister, J. M. (2014). Managing crowdsourced software testing: a case study based insight on the challenges of a crowdsourcing intermediary. Journal of Business Economics, 84(3), 375–405.

    Article  Google Scholar 

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  1. School of Information Management, Victoria University of Wellington, PO Box 600, Wellington, 6140, New Zealand

    Nguyen Hoang Thuan, Pedro Antunes & David Johnstone

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  1. Nguyen Hoang Thuan
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  2. Pedro Antunes
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Correspondence to Nguyen Hoang Thuan.

Appendix A

Appendix A

Table 7 List of Reviewed Articles
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1.1 Appendix B Coding Form

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Thuan, N.H., Antunes, P. & Johnstone, D. Factors influencing the decision to crowdsource: A systematic literature review. Inf Syst Front 18, 47–68 (2016). https://doi.org/10.1007/s10796-015-9578-x

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