• The student should be able to define a real crowdsourcing and/or prediction sourcing challenge in collaboration with an external partner.
• The student should be able to relate the challenge to relevant theories and discuss the strengths and weaknesses in those theories.
• The student should be able to analyze and present the results of the analysis as well as use sound arguments to support findings and draw convincing conclusions based on evidence from the analysis.
• The student should integrate both crowd predictions and crowdsourcing mechanisms.

The study of Collective Intelligence; Crowdsourcing for Firm Innovation and Predictions is essentially the study of collective intelligence and ‘bottom-up’ information aggregation from the organization's important stakeholders (both internal and external "global" crowds) for advancing firm creativity, innovation and predictions of uncertainties.

The course builds students’ ability to set up and run ongoing crowdsourcing activities with the purpose of aggregating and using knowledge and collective intelligence from the firms’ important stakeholder groups such as employees, customers and suppliers for use in effective strategic decision making and innovation management. That is, the course builds students’ ability to analyze, select and develop innovation strategies by introducing  'crowdsourcing of innovation',  'prediction markets', 'prediction without markets' as emergent business information aggregation tools to assess changes in the firm’s internal and external environments.

The course starts with the premise that business strategy is a dynamic process which is both reactive and proactive in dealing with ongoing changes and innovation processes within the firm. The course analyzes the phenomenon of collective intelligence and cover various crowdsourcing and prediction mechanisms. That is, the course presents various tools and methods to crowdsource for innovation, creativity and predictive purposes that can be used to modify, adapt, and change new service designs and other business initiatives that can positively affect the firm’s strategic outcomes.

Crowdsourcing for firm innovation highlights the role of users and “crowds” as an important external source of innovation and will include various open innovation and crowdsourcing strategies including search mechanisms, motivational aspects, platform assessment and crowdsourcing methods. The course will also include hand-on workshops on how crowds can be used for strategic funding decisions through crowdfunding.

Crowdsourcing of predictions includes 'prediction markets', 'wisdom of crowds' and 'crowd predictions without markets' that involve the assessment of uncertainties in environmental and operational conditions. We will cover voting dynamics; risk management; strategic issue management; prediction of promising projects and in forecasting of performance metrics, product success and scenarios, natural disasters, terror and highly uncerrain (fuzzy) events such as changes in customer, employee satisfaction and brand reputation.

There is not a single text for the course. Instead, the lectures will be based on material from updated and published papers, downloadable from CBS Library databases that will be made available on CBS Canvas.