People-Driven, ICT-Enabled Innovation: Crowdsourcing

Crowdsourcing reflects the idea that a firm or a person, in an effort to solve specific problem(s), seeks voluntary help from the general public via an open call, by utilizing the available information and communication technologies (ICT). Such description accentuates two central assumptions. Firstly, while recent advances in ICT have enabled novel and innovative applications of crowdsourcing; it is by no means a post-Web phenomenon. In fact, examples of inviting unknown crowds to participate in solving a challenge have been around for centuries. Secondly, crowdsourcing is a multi-faceted and complex phenomenon where social, technological and economic forces are at play; and as such, any attempt at understanding crowdsourcing while ignoring such complexity can be misleading. The objective of this dissertation is to contribute to the accumulating body of knowledge on crowdsourcing, both at organizational and individual levels of analysis, with the following broad questions in mind. How has complexity research aided organization scholars to theorize about innovation in general, and what could crowdsourcing researchers learn from this line of research? To what extent does the crowd represent a threat to professionalism, and to what extent could organizations exploit this threat as a source of opportunity? What factors motivate the crowd to repeatedly participate in crowdsourcing services? And as the time passes, what makes them discontinue their participation? These four questions, respectively, have guided the research efforts reported in the four articles included in this dissertation. Together, these four articles provide a holistic and multi-perspective understanding of crowdsourcing. From an organizational perspective, articles I and II – predominantly conceptual (theoretical) in nature – identify the key characteristics of organizations as complex adaptive systems, and provide a theoretical foundation for crowdsourcing as a sourcing strategy that enhances organizational survival chances. Then, from an individual perspective, articles III and IV provide an interpretive understanding of the use lifecycle of crowdsourcing systems. Based on a longitudinal empirical investigation of a popular crowdsourcing platform, these two articles report on: a) the key factors responsible for attracting members of the crowd to adopt the said technology; b) the key factors responsible for driving them to continuously use it for extended periods of time; and c) the key factors responsible for them to discontinue using it. The thesis concludes with a discussion of the key theoretical and practical contributions, as well as the limitations and directions for future research