An impactful crowdsourcing intermediary design - a case of a service imagery crowdsourcing system



Crowdsourcing is usually implemented using an intermediary organization or directly coordinated by solution seekers. For those using an IT-based crowdsourcing intermediary, the important factors of intermediaries that impact the crowdsourcing outcome are yet unclear. In addition, little research was conducted on how to design a crowdsourcing intermediary that can address the combined challenges of considering different cognitive demand levels of solution providers’ contributions, combining contributions and evaluating contributions. This paper identifies three important factors and provides a novel design of crowdsourcing intermediary to cope with these challenges. This study uses a case that focuses on how to assist small and medium businesses (SMBs) to develop their service imageries in triggering service innovation and designing their service experiences as to fulfill the desired outcomes of customers. Through the case, the benefits of our crowdsourcing intermediary design are demonstrated and justified. The three important factors are the crowdsourcing intermediary knowledge base, generative networks and empowerment of crowd members. This study shows that the crowdsourcing process can facilitate achieving a higher chance of attaining creative solutions for SMBs’ innovation problems when the three factors are well incorporated and managed within the crowdsourcing intermediary design. This study also presents a novel design of crowdsourcing intermediary that can address the combined challenges of coping with different cognitive demand levels of crowd members and combining and evaluating crowd members’ contributions, in order to attain impactful crowdsourcing outcome.


Crowdsourcing intermediary Service imagery Service value Information system design Open innovation 


  1. Aaker, D. A., & Biel, A. L. (Eds.) (2013). Brand equity & advertising: Advertising’s role in building strong brands. Hove: Psychology Press.Google Scholar
  2. Abrahamson, S., Ryder, P., & Unterberg, B. (2013). Crowdstorm: The future of innovation, ideas, and problem solving. Hoboken: John Wiley & Sons.Google Scholar
  3. Agafonovas, A., & Alonderienė, R. (2013). Value creation in innovations crowdsourcing. Example of creative agencies. Organizations and Markets in Emerging Economies, 4(1), 72–103.Google Scholar
  4. Barile, S., Pels, J., Polese, F., & Saviano, M. (2012). An introduction to the viable systems approach and its contribution to marketing. Journal of Business Market Management, 5(2), 54–78.Google Scholar
  5. Baudrillard, J. (2006). The System of Objects (J. Benedict, trans.). New York: Verso.Google Scholar
  6. Beach, L. R. (1990). Image theory: Decision making in personal and organizational contexts. UK: Wiley.Google Scholar
  7. Bermejo-Luque, L. (2014). The Uses of Analogies, In Systematic Approaches to Argument by Analogy (pp. 57–71). Springer International Publishing.Google Scholar
  8. Borgianni, Y., Cascini, G., & Rotini, F. (2012). Investigating the patterns of value-oriented innovations in Blue Ocean strategy. International Journal of Innovation Science, 4(3), 123–142.CrossRefGoogle Scholar
  9. Bourdieu, P. (1984). Distinction: A Social Critique of Judgment of Taste (R. Nice, trans.). Cambridge: Harvard University Press.Google Scholar
  10. Boztepe, S. (2007). User value: competing theories and models. International Journal of Design, 1(2), 55–63.Google Scholar
  11. Busquets, J. (2010). Orchestrating Network Behavior for Innovation. Frederiksberg: Samfundslitteratur. (PhD Series; Nr. 26.2010).Google Scholar
  12. Castillo, C., Mendoza, M., & Poblete, B. (2013). Predicting information credibility in time-sensitive social media. Internet Research, 23(5), 560–588.CrossRefGoogle Scholar
  13. Chan, K. W., & Mauborgne, R. (2005). Blue Ocean strategy, from theory to practice. California Management Review, 47(3), 105–121.CrossRefGoogle Scholar
  14. Choy, K., & Schlagwein, D. (2016). Crowdsourcing for a better world: on the relation between IT affordances and donor motivations in charitable crowdfunding. Information Technology & People, 29(1), 221–247.CrossRefGoogle Scholar
  15. Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268.CrossRefGoogle Scholar
  16. Doan, A., Ramakrishnan, R., & Halevy, A. Y. (2011). Crowdsourcing systems on the world-wide web. Communications of the ACM, 54(4), 86–96.CrossRefGoogle Scholar
  17. 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.CrossRefGoogle Scholar
  18. Gardner, B. B., & Levy, S. J. (1955). The product and the brand. Harvard Business Review, 33(2), 33–39.Google Scholar
  19. Haakansson, H., & Snehota, I. (1989). No business is an island: the network concept of business strategy. Scandinavian Journal of Management, 5(3), 187–200.CrossRefGoogle Scholar
  20. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information system research. MIS Quarterly, 28(1), 75–105.Google Scholar
  21. Holsapple, C. W., Whinston, A. B., Benamati, J. H., & Kearns, G. S. (1996). Decision support systems: A knowledge-based approach. St. Paul: West Publishing Company.Google Scholar
  22. Howe, J. (2006). The rise of crowdsourcing. Wired Magzine, 14(6), 1–4 Scholar
  23. Howe, J. (2009). Crowdsourcing: Why the power of the crowd is driving the future of business. New York: Crown Business Publisher.Google Scholar
  24. Hsieh, P. H., & Yuan, S. T. (2012a). Value Evolution of Service Systems: the Service Imagery Perspective. 2012 International Service Research Conference (SERVSIG-2012), Helsinki, Finland.Google Scholar
  25. Hsieh, P. H., & Yuan, S. T. (2012b). Service Value Network: the Insights from the Psychological & Evolutionary Economics Perspective. 1st International Conference on Human Side of Service Engineering, San Francisco, USA.Google Scholar
  26. Hwang, J., & Han, H. (2014). Examining strategies for maximizing and utilizing brand prestige in the luxury cruise industry. Tourism Management, 40, 244–259.CrossRefGoogle Scholar
  27. Ichatha, S., & Ellen, P. (2013). The Role of Empowerment in Crowdsourced Customer Service. In Third Annual International Conference on Engaged Management Scholarship, Atlanta, Georgia.Google Scholar
  28. Ifinedo, P. (2011). Internet/e-business technologies acceptance in Canada’s SMEs: an exploratory investigation. Internet Research, 21(3), 255–281.CrossRefGoogle Scholar
  29. Jepsen, L. B., Dell’Era, C., & Verganti, R. (2014). The contributions of interpreters to the development of radical innovations of meanings: the role of ‘pioneering projects’ in the sustainable buildings industry. R&D Management, 44(1), 1–17.CrossRefGoogle Scholar
  30. Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. The Journal of Marketing, 57(1), 1–22.CrossRefGoogle Scholar
  31. Kobayashi, S. (1991). Color image scale. Kodansha International: Tokyo.Google Scholar
  32. Kolb, P. (2008). DISCO: a multilingual database of distributionally similar words, Tagungsband der 9. Konferenz zur Verarbeitung natürlicher Sprache–KONVENS.Google Scholar
  33. Lusch, R. F., & Vargo, S. L. (2014). Service-dominant logic: Premises, perspectives, possibilities. Cambridge: Cambridge University Press.Google Scholar
  34. 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.CrossRefGoogle Scholar
  35. 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.CrossRefGoogle Scholar
  36. Miles, M., & Huberman, A. M. (1994). Qualitative data analysis. Thousand Oaks: Sage Publications.Google Scholar
  37. Norman, D. A., & Verganti, R. (2014). Incremental and radical innovation: design research vs. technology and meaning change. Design Issues, 30(1), 78–96.CrossRefGoogle Scholar
  38. Oard, D. W. (1997). The state of the art in text filtering. User Modeling and User-Adapted Interaction, 7(3), 141–178.CrossRefGoogle Scholar
  39. Oxenfeldt, A. R., & Swan, C. J. (1964). Management of the Advertising Function. Belmont: Wadsworth Pub. Co.Google Scholar
  40. Powers, D. M. W. (2011). Evaluation: from precision, recall and F-measure to ROC, Informedness, Markedness & Correlation. Journal of Machine Learning Technologies, 2(1), 37–63.Google Scholar
  41. Roy, D., & Banerjee, S. (2014). Identification and measurement of brand identity and image gap: a quantitative approach. Journal of Product & Brand Management, 23(3), 6–6.CrossRefGoogle Scholar
  42. Saldana, J. (2009). The coding Maual for qualitative researchers. Los Angeles: SAGE Publications Ltd.Google Scholar
  43. Saxton, G. D., Oh, O., & Kishore, R. (2013). Rules of crowdsourcing: models, issues, and Systems of Control. Information Systems Management, 30(1), 2–20.CrossRefGoogle Scholar
  44. Sharp, H. S. (1984). Advertising slogans of America. Metuchen: Scarecrow Press.Google Scholar
  45. Simula, H., & Ahola, T. (2014). A network perspective on idea and innovation crowdsourcing in industrial firms. Industrial Marketing Management, 43(3), 400–408.CrossRefGoogle Scholar
  46. Spohrer, J., Vargo, S. L., Caswell, N., & Maglio, P. P. (2008). The service system is the basic abstraction of service science. In Hawaii International Conference on System Sciences, Proceedings of the 41st Annual (pp. 104–104).Google Scholar
  47. Street, C. T., & Cameron, A. F. (2007). External relationships and the small business: a review of small business alliance and network research. Journal of Small Business Management, 45(2), 239–266.CrossRefGoogle Scholar
  48. Strijbos, S. (1995). How can systems thinking help us in bridging the gap between science and wisdom? Systemic Practice and Action Research, 8(4), 361–376.Google Scholar
  49. Taylor, M., & Murphy, A. (2004). SMEs and e-Business. Journal of Small Business and Enterprise Development, 11(3), 280–289.CrossRefGoogle Scholar
  50. Tessier, C., Chaudron, L., & Müller, H. J. (Eds.) (2006). Conflicting agents: Conflict Management in Multi-Agent Systems (Vol. 1). Heidelberg: Springer Science & Business Media.Google Scholar
  51. Thuan, N. H., Antunes, P., & Johnstone, D. (2015). Factors influencing the decision to crowdsource: a systematic literature review. Information Systems Frontiers, 1–22.Google Scholar
  52. TrendHunter Marketing (2012). Crowdsourced Pizza Cars. Accessed March 2016.
  53. Valerdi, R., & Nightingale, D. (2011). An introduction to the journal of Enterprise transformation. Journal of Enterprise Transformation, 1(1), 1–6.CrossRefGoogle Scholar
  54. Vargo, S. L. (2011). On marketing theory and service-dominant logic: connecting some dots. Marketing Theory, 11(1), 3–8.CrossRefGoogle Scholar
  55. Vargo, S. L., & Lusch, R. F. (2004). The four service marketing myths: remnants of a goods-based, manufacturing model. Journal of Service Research, 6(4), 324–335.CrossRefGoogle Scholar
  56. Vargo, S. L., & Lusch, R. F. (2008). Service-dominant logic: continuing the evolution. Journal of the Academy of Marketing Science, 36(1), 1–10.CrossRefGoogle Scholar
  57. Veale, T., & Hao, Y. (2007). Comprehending and generating apt metaphors: a web-driven, case-based approach to figurative language. In Proceedings of the National Conference on Artificial Intelligence (vol. 22, pp. 1471).Google Scholar
  58. Veblen, T. (2001). The theory of the leisure class. New York: The Modern Library.Google Scholar
  59. Verganti, R. (2009). Design driven innovation. Boston: Harvard Business School Press.Google Scholar
  60. Whitla, P. (2009). Crowdsourcing and its application in marketing activities. Contemporary Management Research, 5(1), 15–28.CrossRefGoogle Scholar
  61. Yang, C. Y., & Yuan, S. T. (2010). Color imagery for destination recommendation in regional tourism. The 14th Pacific Asia Conference on Information Systems, Taipei, Taiwan.Google Scholar
  62. Zogaj, S., & Bretschneider, U. (2014). Analyzing governance mechanisms for crowdsourcing information systems: a multiple case analysis. Proceedings of the European Conference on Information Systems (ECIS) 2014, Tel Aviv, Israel, June 9–11, 2014.Google Scholar
  63. 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.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Management Information SystemsNational ChengChi UniversityTaipei CityTaiwan

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