The
pervasiveness of the Internet provides organizations with
new opportunities to access a global network made up of
millions of people. In recent years, a multitude of business
models and platforms have emerged, which revolve around the
idea of tapping into the knowledge, creativity, and
innovative power of ‘crowds’. These phenomena are
commonly described as ‘crowdsourcing’, which generally
refers to harnessing the potential of open, large groups of
people. Crowdsourcing approaches are applied in a wide range
of contexts such as collective intelligence, open
innovation, problem solving, human computation,
user-generated content, creative design, social engagement,
knowledge aggregation, and prediction markets, among others.
As
crowdsourcing and related fields such as open innovation and
collective intelligence are rapidly gaining importance in
research and practice, new questions and challenges arise
that require a deeper understanding of these phenomena from
an Information Systems (IS) perspective. Today,
organizations apply a large variety of crowdsourcing
concepts and methods to gain access to more capabilities,
realize new business models, and drive innovation. For the
effective adoption of these new capabilities, however,
organizations will require theoretically grounded decision
frameworks, governance processes, and supporting tools.
While
research on crowdsourcing is multidisciplinary, this track
focuses on the role of IS in realizing crowdsourcing
approaches and achieving the aspired outcomes. In the
process of crowdsourcing, information systems are used to
interconnect organizations and globally distributed
contributors. Related research brings together theories and
fundamentals from fields such as human-computer interaction,
machine learning, innovation, marketing, law, sociology,
psychology, business administration, and economics. The aim
of crowdsourcing research in the IS discipline is to adapt
these different research directions to move from special
aspects and applications to general, multi-disciplinary
knowledge, insights, and theory. This track encourages
submissions based on a variety of research methods,
including explanatory/theoretical research, empirical
studies (action research, case studies, surveys,
experiments), and design science.
SUGGESTED
TOPICS
Topics
of interest include but are not limited to the following:
-
Crowdsourcing ecosystems and markets
- Open
innovation and idea generation processes
- Collective
intelligence and crowd wisdom
- Human
computation
- Microtasks
and cloud labor (e.g., Amazon Mechanical Turk)
- Platforms,
tools, and technologies
- Design of
workflows and processes
- Task
characteristics and task design
- Quality
assurance mechanisms and metrics
-
Contributor motivation and incentive structures
- Economics
of crowdsourcing and open innovation
- Adoption
of crowdsourcing business models
-
Cross-cultural differences in participants
- Taxonomies
and classifications
- Innovative
projects and implementations