Scalability of generative knowledge management systems: designing for individuals’ and institutions’ mutual benefit

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Abstract

Purpose: In further conceptualizing a novel generative knowledge management system (KM/KMS), this paper aims to focus on identifying and mitigating the risks related to its envisaged scaling from a prototype to an application with a rapidly growing user base. Design/methodology/approach: It follows up on prior publications using design science research (DSR) methodologies in compliance with theory effectiveness, a principle expecting system designs to be purposeful in terms of utility and communication. The KMS perspective taken prioritizes a decentralizing agenda benefiting knowledge workers while also aiming to foster a fruitful co-evolution with conventional organizational KM approaches. Findings: The utilization and further extension of the CKDT and a “scalable innovation” heuristic are assisting the detecting of potential scaling risks related to the logics and logistics, generative interoperability, technological capacitating, knowledge dynamics and value chain which further validates the viability of the proposed KM concept and system. Research limitations/implications: Although the prototype development is still in progress, the paper conforms to the DSR practice to report on early visions of technology impact on users, organizations and society but also reflects on expectations of viability, desirability and commitment, as well as the system’s prospect as a general-purpose-technology or disruptive innovation. Originality/value: In addition to the novel KM-related perspectives, the paper’s practical emphasis on the scaling of more complex systems is rarely dealt with in the literature due to the respective projects’ often large-scale collaborative nature, broad methodological scope and diverse stakeholders’ interests. In this case, the task is eased as prior DSR outputs can be referred to.

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APA

Schmitt, U. (2021). Scalability of generative knowledge management systems: designing for individuals’ and institutions’ mutual benefit. Kybernetes, 50(10), 2701–2725. https://doi.org/10.1108/K-05-2020-0324

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