Knowledge Flow, Transfer, Sharing, and Exchange

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https://hdl.handle.net/10125/102581

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    Introduction to the Minitrack on Knowledge Flow, Transfer, Sharing, and Exchange
    ( 2023-01-03) Cooper, Lynne ; Nissen, Mark ; Yasuoka, Mika
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    How does technology readiness affect the transfer of innovation between the professional domain and the private domain? A longitudinal study
    ( 2023-01-03) Stock-Homburg, Ruth Maria ; Kietzmann, Meike
    Many researchers have studied innovation in terms of either employee innovation or user innovation, but much less is known about the transfer of innovative behavior between the professional and private domains. This quantitative empirical study investigates the relationship between the development of innovations by user innovators in the private domain and the transfer of the innovation to the professional domain and vice versa. Focusing on technology readiness as a moderator on the relationship between the transfer of innovation and innovative behavior in the other domain, we address the importance of digitization for innovations. The study is relied on the spillover theory and conducted as a longitudinal online survey consists of three consecutive waves over a period of four months. The result of the study demonstrates that employee innovation in the professional domain has an impact on innovative behavior in the private domain and, in reverse causality, user innovation in the private domain has an impact on innovative behavior in the professional domain. The relationship between these spillover effects and innovative behavior is strengthened by the technology readiness of innovators.
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    A Method for Assessing Knowledge Flow Efficiency, Cost and Performance
    ( 2023-01-03) Nissen, Mark
    Knowledge is key to competitive advantage, and organization leaders and managers are called to implement, maintain and enhance key knowledge management systems and processes. However, knowledge is inherently invisible, intangible, indefinite and resistant to quantification. Hence assessing investments in such systems and processes remains fundamentally challenging. The research described in this article builds upon a growing stream of knowledge visualization, measurement and dynamics work to develop a method for assessing knowledge flow efficiency, cost and performance in the organization. Results from application to archetypical organization systems and processes are highly promising, and they elucidate a novel decision support capability.