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150325s1996 xx |||||o 00| ||eng c |
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|a (JST)2635050
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|a eng
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|a Cheng, Yu-Ting
|e verfasserin
|4 aut
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|a Learning the Innovation Journey: Order out of Chaos?
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|c 1996
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|a Text
|b txt
|2 rdacontent
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|a This paper examines whether the developmental process of two biomedical innovations followed either (1) an orderly periodic progression of stages or phases, (2) a random sequence of chance "blind" events, or (3) a seemingly random process of chaotic events. Various diagnostics are applied to distinguish periodic, chaotic, and random patterns in time series data on innovation development events. We find that the actions and outcomes experienced by innovation teams exhibit a chaotic pattern during the initial period of innovation development, and an orderly periodic pattern during the ending development period; however, exogenous context events exhibit a random pattern during both the beginning and ending periods of innovation development. These research findings, if substantiated in other studies, significantly alter prior views of innovation and learning processes. The two most commonly-used explanations of the innovation process, that it follows either an orderly periodic sequence of stages or a random sequence of "blind" events, are not valid where chaos is found. Chaos tells us that the innovation process consists of a nonlinear dynamical system, which is neither orderly and predictable nor stochastic and random. The findings of chaos also expand existing definitions of organizational learning. Learning in chaotic conditions can be viewed as an expanding and diverging process of discovery. Learning during more stable and periodic conditions is viewed as a narrowing and converging process of testing. Timing of transitions from chaos to periodic patterns may explain whether decision or action rationality prevails. Hence, the difference between behavioral learning theorists and cognitive learning theorists may be just a matter of time.
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|a Copyright 1996 Institute for Operations Research and the Management Sciences
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|a Learning
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|a Innovation
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|a Chaos
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|a Dynamical Systems Theory
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| 650 |
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|a Information science
|x Data products
|x Datasets
|x Time series
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| 650 |
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|a Applied sciences
|x Systems science
|x Systems theory
|x Chaos theory
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Learning
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|a Business
|x Business engineering
|x Business innovation
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|a Mathematics
|x Applied mathematics
|x Statistics
|x Applied statistics
|x Descriptive statistics
|x Correlations
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|a Economics
|x Economic disciplines
|x Labor economics
|x Employment
|x Occupations
|x Businesspeople
|x Entrepreneurs
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|a Business
|x Business economics
|x Commercial production
|x Production resources
|x Resource management
|x Logistics
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| 650 |
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|a Mathematics
|x Pure mathematics
|x Probability theory
|x Randomness
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| 650 |
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|a Business
|x Business engineering
|x Business innovation
|x Innovation management
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| 650 |
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|a Behavioral sciences
|x Psychology
|x Cognitive psychology
|x Cognitive processes
|x Learning
|x Learning theory
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|a research-article
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|a Van de Ven, Andrew H.
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Organization Science
|d Institute for Operations Research and the Management Sciences
|g 7(1996), 6, Seite 593-614
|w (DE-627)320635775
|w (DE-600)2024496-4
|x 15265455
|7 nnns
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| 773 |
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|g volume:7
|g year:1996
|g number:6
|g pages:593-614
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|u https://www.jstor.org/stable/2635050
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|d 7
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