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Robert E Kraut - One of the best experts on this subject based on the ideXlab platform.

  • distributed analogical Idea Generation with multiple constraints
    Conference on Computer Supported Cooperative Work, 2016
    Co-Authors: Lixiu Yu, Robert E Kraut, Aniket Kittur
    Abstract:

    Previous work has shown the promise of crowdsourcing analogical Idea Generation, where distributing the stages of analogical processing across many people can reduce fixation, identify inspirations from more diverse domains, and lead to more creative Ideas. However, prior work has only considered problems with a single constraint, while many real-world problems involve multiple constraints. This paper contributes a systematic crowdsourcing approach for eliciting multiple constraints inherent in a problem and using those constraints to find inspirations useful in solving it. To do so we identify methods to elicit useful constraints at different levels of abstraction, and empirical results that identify how the level of abstraction influences creative Idea Generation. Our results show that crowds find the most useful inspirations when the problem domain is represented abstractly and constraints are represented more concretely.

  • distributed analogical Idea Generation inventing with crowds
    Human Factors in Computing Systems, 2014
    Co-Authors: Lixiu Yu, Aniket Kittur, Robert E Kraut
    Abstract:

    Harnessing crowds can be a powerful mechanism for increasing innovation. However, current approaches to crowd innovation rely on large numbers of contributors generating Ideas independently in an unstructured way. We introduce a new approach called distributed analogical Idea Generation, which aims to make Idea Generation more effective and less reliant on chance. Drawing from the literature in cognitive science on analogy and schema induction, our approach decomposes the creative process in a structured way amenable to using crowds. In three experiments we show that distributed analogical Idea Generation leads to better Ideas than example-based approaches, and investigate the conditions under which crowds generate good schemas and Ideas. Our results have implications for improving creativity and building systems for distributed crowd innovation.

  • CHI - Distributed analogical Idea Generation: inventing with crowds
    Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI '14, 2014
    Co-Authors: Lixiu Yu, Aniket Kittur, Robert E Kraut
    Abstract:

    Harnessing crowds can be a powerful mechanism for increasing innovation. However, current approaches to crowd innovation rely on large numbers of contributors generating Ideas independently in an unstructured way. We introduce a new approach called distributed analogical Idea Generation, which aims to make Idea Generation more effective and less reliant on chance. Drawing from the literature in cognitive science on analogy and schema induction, our approach decomposes the creative process in a structured way amenable to using crowds. In three experiments we show that distributed analogical Idea Generation leads to better Ideas than example-based approaches, and investigate the conditions under which crowds generate good schemas and Ideas. Our results have implications for improving creativity and building systems for distributed crowd innovation.

Lixiu Yu - One of the best experts on this subject based on the ideXlab platform.

  • distributed analogical Idea Generation with multiple constraints
    Conference on Computer Supported Cooperative Work, 2016
    Co-Authors: Lixiu Yu, Robert E Kraut, Aniket Kittur
    Abstract:

    Previous work has shown the promise of crowdsourcing analogical Idea Generation, where distributing the stages of analogical processing across many people can reduce fixation, identify inspirations from more diverse domains, and lead to more creative Ideas. However, prior work has only considered problems with a single constraint, while many real-world problems involve multiple constraints. This paper contributes a systematic crowdsourcing approach for eliciting multiple constraints inherent in a problem and using those constraints to find inspirations useful in solving it. To do so we identify methods to elicit useful constraints at different levels of abstraction, and empirical results that identify how the level of abstraction influences creative Idea Generation. Our results show that crowds find the most useful inspirations when the problem domain is represented abstractly and constraints are represented more concretely.

  • CHI - Distributed analogical Idea Generation: inventing with crowds
    Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI '14, 2014
    Co-Authors: Lixiu Yu, Aniket Kittur, Robert E Kraut
    Abstract:

    Harnessing crowds can be a powerful mechanism for increasing innovation. However, current approaches to crowd innovation rely on large numbers of contributors generating Ideas independently in an unstructured way. We introduce a new approach called distributed analogical Idea Generation, which aims to make Idea Generation more effective and less reliant on chance. Drawing from the literature in cognitive science on analogy and schema induction, our approach decomposes the creative process in a structured way amenable to using crowds. In three experiments we show that distributed analogical Idea Generation leads to better Ideas than example-based approaches, and investigate the conditions under which crowds generate good schemas and Ideas. Our results have implications for improving creativity and building systems for distributed crowd innovation.

  • distributed analogical Idea Generation inventing with crowds
    Human Factors in Computing Systems, 2014
    Co-Authors: Lixiu Yu, Aniket Kittur, Robert E Kraut
    Abstract:

    Harnessing crowds can be a powerful mechanism for increasing innovation. However, current approaches to crowd innovation rely on large numbers of contributors generating Ideas independently in an unstructured way. We introduce a new approach called distributed analogical Idea Generation, which aims to make Idea Generation more effective and less reliant on chance. Drawing from the literature in cognitive science on analogy and schema induction, our approach decomposes the creative process in a structured way amenable to using crowds. In three experiments we show that distributed analogical Idea Generation leads to better Ideas than example-based approaches, and investigate the conditions under which crowds generate good schemas and Ideas. Our results have implications for improving creativity and building systems for distributed crowd innovation.

  • an internet scale Idea Generation system
    Ksii Transactions on Internet and Information Systems, 2013
    Co-Authors: Lixiu Yu, Jeffrey V Nickerson
    Abstract:

    A method of organizing the crowd to generate Ideas is described. It integrates crowds using evolutionary algorithms. The method increases the creativity of Ideas across Generations, and it works better than greenfield Idea Generation. Specifically, a design space of internet-scale Idea Generation systems is defined, and one instance is tested: a crowd Idea Generation system that uses combination to improve previous designs. The key process of the system is the following: A crowd generates designs, then another crowd combines the designs of the previous crowd. In an experiment with 540 participants, the combined designs were compared to the initial designs and to the designs produced by a greenfield Idea Generation system. The results show that the sequential combination system produced more creative Ideas in the last Generation and outperformed the greenfield Idea Generation system. The design space of crowdsourced Idea Generation developed here may be used to instantiate systems that can be applied to a wide range of design problems. The work has both pragmatic and theoretical implications: New forms of coordination are now possible, and, using the crowd, it is possible to test existing and emerging theories of coordination and participatory design. Moreover, it may be possible for human designers, organized as a crowd, to codesign with each other and with automated algorithms.

Aniket Kittur - One of the best experts on this subject based on the ideXlab platform.

  • distributed analogical Idea Generation with multiple constraints
    Conference on Computer Supported Cooperative Work, 2016
    Co-Authors: Lixiu Yu, Robert E Kraut, Aniket Kittur
    Abstract:

    Previous work has shown the promise of crowdsourcing analogical Idea Generation, where distributing the stages of analogical processing across many people can reduce fixation, identify inspirations from more diverse domains, and lead to more creative Ideas. However, prior work has only considered problems with a single constraint, while many real-world problems involve multiple constraints. This paper contributes a systematic crowdsourcing approach for eliciting multiple constraints inherent in a problem and using those constraints to find inspirations useful in solving it. To do so we identify methods to elicit useful constraints at different levels of abstraction, and empirical results that identify how the level of abstraction influences creative Idea Generation. Our results show that crowds find the most useful inspirations when the problem domain is represented abstractly and constraints are represented more concretely.

  • distributed analogical Idea Generation inventing with crowds
    Human Factors in Computing Systems, 2014
    Co-Authors: Lixiu Yu, Aniket Kittur, Robert E Kraut
    Abstract:

    Harnessing crowds can be a powerful mechanism for increasing innovation. However, current approaches to crowd innovation rely on large numbers of contributors generating Ideas independently in an unstructured way. We introduce a new approach called distributed analogical Idea Generation, which aims to make Idea Generation more effective and less reliant on chance. Drawing from the literature in cognitive science on analogy and schema induction, our approach decomposes the creative process in a structured way amenable to using crowds. In three experiments we show that distributed analogical Idea Generation leads to better Ideas than example-based approaches, and investigate the conditions under which crowds generate good schemas and Ideas. Our results have implications for improving creativity and building systems for distributed crowd innovation.

  • CHI - Distributed analogical Idea Generation: inventing with crowds
    Proceedings of the 32nd annual ACM conference on Human factors in computing systems - CHI '14, 2014
    Co-Authors: Lixiu Yu, Aniket Kittur, Robert E Kraut
    Abstract:

    Harnessing crowds can be a powerful mechanism for increasing innovation. However, current approaches to crowd innovation rely on large numbers of contributors generating Ideas independently in an unstructured way. We introduce a new approach called distributed analogical Idea Generation, which aims to make Idea Generation more effective and less reliant on chance. Drawing from the literature in cognitive science on analogy and schema induction, our approach decomposes the creative process in a structured way amenable to using crowds. In three experiments we show that distributed analogical Idea Generation leads to better Ideas than example-based approaches, and investigate the conditions under which crowds generate good schemas and Ideas. Our results have implications for improving creativity and building systems for distributed crowd innovation.

Jens Dibbern - One of the best experts on this subject based on the ideXlab platform.

  • HICSS - Supporting Joint Idea Generation with Software Prototypes in Offshore-Outsourced Software Development Projects
    2016 49th Hawaii International Conference on System Sciences (HICSS), 2016
    Co-Authors: Maike A. E. Winkler, Thomas Huber, Jens Dibbern
    Abstract:

    Joint Idea Generation is vital in software development projects requiring team members with different knowledge specializations to exchange and integrate multiple perspectives into Ideas to improve the software product. While joint Idea Generation is generally difficult to achieve, it is even more challenging in offshore-outsourced settings. Our goal was to understand the process of how software prototypes can support joint Idea Generation over the life of a 16 month offshore-outsourced software development project. Based on an in-depth, ethnographic case study, we reveal three joint Idea Generation modes building on and stimulating each other: from diverging, to exploring and advancing. These joint Idea Generation modes were closely interwoven with the software prototype. We find that as the software prototype evolved, new possibilities for engaging in various joint Idea Generation modes emerged. Our research has important implications for literature and practice.

  • Supporting Joint Idea Generation with Software Prototypes in Offshore-Outsourced Software Development Projects
    2016 49th Hawaii International Conference on System Sciences (HICSS), 2016
    Co-Authors: Maike Winkler, Thomas Huber, Jens Dibbern
    Abstract:

    Joint Idea Generation is vital in software development projects requiring team members with different knowledge specializations to exchange and integrate multiple perspectives into Ideas to improve the software product. While joint Idea Generation is generally difficult to achieve, it is even more challenging in offshore-outsourced settings. Our goal was to understand the process of how software prototypes can support joint Idea Generation over the life of a 16 month offshore-outsourced software development project. Based on an in-depth, ethnographic case study, we reveal three joint Idea Generation modes building on and stimulating each other: from diverging, to exploring and advancing. These joint Idea Generation modes were closely interwoven with the software prototype. We find that as the software prototype evolved, new possibilities for engaging in various joint Idea Generation modes emerged. Our research has important implications for literature and practice.

Graham Horton - One of the best experts on this subject based on the ideXlab platform.

  • The Structure of Idea Generation Techniques: Three Rules for Generating Goal-Oriented Ideas
    Advances in Human and Social Aspects of Technology, 2020
    Co-Authors: Stefan Werner Knoll, Graham Horton
    Abstract:

    Idea Generation techniques play an important role in the innovation process. Until recently, the space of techniques has been unstructured, and no clear guidelines have been available for the selection of an appropriate technique for a given innovation goal. This chapter uses an engineering approach to study and develop Idea Generation techniques with the aim of obtaining more structured and rigorous guidelines for generating Ideas. One element of this approach was to identify and understand the fundamental mental principles underlying an Idea Generation technique. In this chapter, three such principles suffice to cover a large range of published Idea Generation techniques and can be used to improve the utility of Idea Generation within the innovation process.

  • supporting initial trust in distributed Idea Generation and Idea evaluation
    International Conference on Supporting Group Work, 2012
    Co-Authors: Jana Schumann, David Redmiles, Patrick C. Shih, Graham Horton
    Abstract:

    Previous research has shown that diversity within distributed collaborative teams can lead to innovation, but trust must exist for the open expression of innovative Ideas and establishment of Idea credibility. Initial trust is pivotal for distributed teams where team members have never met face-to-face and have only a very limited time to accomplish a task. Our goal is to determine if knowing specific information about other team members could enhance initial trust and improve productivity and satisfaction in Idea Generation and Idea evaluation sessions. In an experiment, we showed that cognitive and affective trust could be successfully enhanced by presenting relevant information elements, such as domain expertise and personal hobbies, and could have positive effects on the quality and quantity of Ideas in Idea Generation sessions as well as the satisfaction of the participants with the rating result in Idea evaluation sessions. However, participants receiving personal information often misconstrue this as professional competency. We also describe gender differences observed in the Idea Generation sessions and discuss how to better design future systems for supporting Idea Generation and Idea evaluation activities.

  • GROUP - Supporting initial trust in distributed Idea Generation and Idea evaluation
    Proceedings of the 17th ACM international conference on Supporting group work - GROUP '12, 2012
    Co-Authors: Jana Schumann, David Redmiles, Patrick C. Shih, Graham Horton
    Abstract:

    Previous research has shown that diversity within distributed collaborative teams can lead to innovation, but trust must exist for the open expression of innovative Ideas and establishment of Idea credibility. Initial trust is pivotal for distributed teams where team members have never met face-to-face and have only a very limited time to accomplish a task. Our goal is to determine if knowing specific information about other team members could enhance initial trust and improve productivity and satisfaction in Idea Generation and Idea evaluation sessions. In an experiment, we showed that cognitive and affective trust could be successfully enhanced by presenting relevant information elements, such as domain expertise and personal hobbies, and could have positive effects on the quality and quantity of Ideas in Idea Generation sessions as well as the satisfaction of the participants with the rating result in Idea evaluation sessions. However, participants receiving personal information often misconstrue this as professional competency. We also describe gender differences observed in the Idea Generation sessions and discuss how to better design future systems for supporting Idea Generation and Idea evaluation activities.