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2013/2014  BA-HAS_PMCI  Prediction Markets and Crowdsourcing for Firm Innovation

English Title
Prediction Markets and Crowdsourcing for Firm Innovation

Course information

Language English
Exam ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Quarter
Course period Third Quarter
The course is offered from spring 2015
Time Table Please see course schedule at e-Campus
Study board
Study Board for BSc in Service Management
Course coordinator
  • Carina Antonia Hallin - Department of International Economics and Management (INT)
Main academic disciplines
  • Innovation and entrepreneurship
  • Management of Information and Knowledge Management
  • Statistics and mathematics
  • Corporate and Business Strategy
Last updated on 15-08-2013
Learning objectives
This course builds students’ ability to set up and run ongoing prediction markets and crowdsourcing with the purpose of aggregating collective intelligence from the firms’ important stakeholder groups 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 prediction markets and crowdsourcing as emergent business information aggregation tools to assess changes in the firm’s internal and external environments. The students will learn about the dynamics of stakeholder sensing of the internal and external firm environments and how such sensing activities may be utilized in strategic decision processes for strategic outcomes that can contribute to the development of sustainable competitive advantage. Students will learn basic theories of collective intelligence, environmental sensing, judgmental predictions, prediction markets, crowdsourcing and dynamic strategic decision making with a focus on responsiveness and innovative behaviors. The course provides a framework for analyzing the competitive environment and potential effects of important stakeholder interactions.
Course prerequisites
English language skills equal to B2 level (CEFR) and math skill equal to Danish level B are recommended.
Prediction Markets and Crowdsourcing for Firm Innovation:
Examination form Home assignment - written product
Individual or group exam Group exam, max. 4 students in the group
Size of written product Max. 20 pages
Assignment type Written assignment
Duration 7 days to prepare
Grading scale 7-step scale
Examiner(s) Internal examiner and second internal examiner
Exam period Spring Term
Make-up exam/re-exam
Same examination form as the ordinary exam
Description of the exam procedure
The exam is a written group project of max. 20 pages.  Eksamen består af et skriftlig gruppeprojekt (max. 20 sider). Max. 4 students in each group.
The product is a case combined with fieldwork.
Course content and structure

The study of Prediction Markets and Crowdsourcing is essentially the study of ‘bottom-up’ information processes among firm stakeholders as they sense changes in the firms’ environmental spheres for use in strategic decision making and innovation processest. Prediction markets and crowdsourcing in businesses can be used in relation to operational risk management, business portfolio management, and strategic planning by assessing operating capabilities, identifying most promising projects, and evaluating the likelihood of meeting key performance metrics and strategic goals. 
This 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 phenomena of environmental sensing by employees, suppliers and customers and presents various tools to aggregate such information for predictive purposes that can be used to modify, adapt, and change new service designs and other business initiatives that affect the firm’s strategic outcomes.  

Teaching methods
The teaching sessions will normally be divided between lectures and class discussion. The sessions have been designed to facilitate as much active class participation as possible using classroom clickers, student presentations and the proportion of time allocated to lecture although discussions will vary somewhat in intensity week by week.
Expected literature
There is not a single text for the course. Instead, the lectures will be based on material from published papers, downloadable from CBS Library databases or to be made available on Learn, and the following textbook, several copies of which will be on reserve in the Library.
Oracles: How Prediction Markets Turn Employees into Visionaries, Harvard Business Review Press, 1st Edition by Donald N. Thompson
Predictocracy: Market Mechanisms for Public and Private Decision Making, Yale University Press, 1st Edition by Michael Abramowicz.
Last updated on 15-08-2013