Designing a Field Experiment to Provide Insights on Problem Complexity in Open Innovation
Abstract
There presently exists a renewed recognition of open innovation methodologies within the U.S. government and private industry. This includes their application as a source for ideas, solutions, and increased efficiency. Their... [ view full abstract ]
There presently exists a renewed recognition of open innovation methodologies within the U.S. government and private industry. This includes their application as a source for ideas, solutions, and increased efficiency. Their use ranges from the generation of new ideas, to the development of complex systems, and even to the measurement or creation of new market opportunities. This research is a collection and analysis of new data that may support the increased understanding of additional applications with the government and industry.
The comprehensive “toolset” for open innovation is, increasingly, credited as a prime alternative source or method in conducting business. As a consequence, organizations are motivated to apply the methods to a wider set of systems and problems. This, in turn, necessitates users of these tools to more fully understand the implications, applications, and limitations of their use. This research contributes new and unique data to enhance the understanding of the intersection between systems engineering and open innovation methodology. The new data presented include measurements and analysis of the relationship between open innovation, problem complexity and the attributes of solvers and proposed solutions. The research provides insights for organizations to assist in determining how the complexity of a problem can impact external solvers and the solutions they provide.
There is an emphasis to expand the application of open innovation methods by pushing the boundaries beyond the simple problems, user-driven innovation, and market stimulation efforts that have been demonstrated and studied to date.
Systems may be described as the summation of many smaller parts and interactions among them. In fact, one of the most common methods of dealing with such complex systems is the use of decomposition. This involves the breakdown of the larger, complex system into smaller parts with well-understood and minimized interactions between them.
In this research we use a systematic approach to collect and analyze the dependent variables, which include the attributes of solvers and the attributes of the corresponding solutions. In addition, we have sought to gain insights into the process and/or sources of the solver-knowledge used for generating the solutions to the problems. This systematic approach to an enhanced understanding of these dependent variables has utilized the method of varying the independent variable. The independent variable in this study is the complexity of the problems posed to the potential solvers over a diverse range of complexity. Problems are defined as the elements that make up a larger, complex system; they, themselves, have a measure of complexity. Problems have structure and interaction effects that are based on the manner in which the larger, complex system is decomposed into a given set of elements.
Our experiment incudes a diverse set of these problems to capture a diverse response for the measured dependent variables. The diverse sets of problems are elements and element combinations of a common medium complexity system arranged to ensure a population across the scale of complexity. The medium complexity model system we are using to achieve this diverse set of problems is a robotic arm that is a part of a new free flying robot being built for the International Space Station at NASA. The robotic arm provides a real model system that has a number of known solutions and we know those existing solutions have varying degrees of complexity. We are generating the potential elements and element combinations through the efforts of internal and external decomposition and will select to ensure a diverse set of varying complexity problems.
To date there exist only minimal and limited on such a set of varying complexity problems posed to an external set of solvers. The existing collection of dependent variable data is equally limited to simple systems and elements, user innovation, and fully integrated complex systems.
The external solvers are accessing through the platform Freelancer.com. This platform allows for a consistent method to access and interact with external solvers. The platform has over 17 million registered users who claim expertise across a wide set of disciplines.
The understanding of the effect that problem complexity produces upon solvers, solutions, and the process/source of solver methods will enable insights into how to expand the application of open innovation methods in a more systematic manner, which extends beyond the currently understood applications.
Authors
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Jason Crusan
(George Washington University)
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Zoe Szajnfarber
(George Washington University)
Topic Area
Contests, Crowdsourcing and Open Innovation
Session
MATr2B » Contests, Crowdsourcing & Open Innovation (Papers & Posters) (15:45 - Monday, 1st August, Room 112, Aldrich Hall)
Paper
2016_05_13_JasonCrusan_OUI_Paper.pdf
Presentation Files
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