Knowing What We Know: Where to Now?

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https://hdl.handle.net/10125/72263

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    Research Method Classification with Deep Transfer Learning for Semi-Automatic Meta-Analysis of Information Systems Papers
    ( 2021-01-05) Anisienia, Anna ; Mueller, Roland M. ; Kupfer, Anna ; Staake, Thorsten
    This paper presents an artifact that uses deep transfer learning methods for the multi-label classification of research methods for an Information Systems corpus. The artifact can support researchers with frequently performed yet time-consuming classification and structure-seeking tasks that are often part of literature analyses. We use a corpus of 5,388 papers from AIS journals and conferences, of which 1,766 have been manually labelled with up to five research methods. The unlabelled papers are used for finetuning the language model, whereas the labelled data are used for training and testing. Our approach outperforms state of the art research method classification that deploy SVM. We show that deep transfer learning models can lead to a better recognition of research methods than shallower word embedding approaches like word2vec or GloVe. The results illustrate the potential of establishing semi-automated methods for meta-analysis.
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    Organizational Robustness and Information Systems
    ( 2021-01-05) Desouza, Kevin ; Xie, Yancong
    The concept of robustness is critically analyzed. Although robustness has been widely adopted across scientific disciplines, no comprehensive and systematic conceptualization on robustness exists. This paper develops a framework to conceptualize organizational robustness. The framework outlines mechanisms of organizational robustness in three layers – strategical mechanisms, functional mechanisms, and infrastructure mechanisms. The complex role of information systems for organizational robustness is also discussed.
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    An Open-Ended Work System Knowledge Model for Visualizing, Organizing, and Accessing Knowledge about Information Systems in Organizational Settings
    ( 2021-01-05) Alter, Steven
    This essay presents a new approach for visualizing and organizing IS-related knowledge and expanding that knowledge. It mentions other possibly relevant approaches and then proposes a new approach that combines ideas from two sources, a taxonomy of “knowledge objects” (KOs) and the work system perspective (WSP), including several new extensions of work system theory (WST). Its contribution is the rationale and structure of a work system knowledge model (WSKM) that is potentially useful for organizing a significant fraction of knowledge related to IS
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    Introduction to the Minitrack on Knowing What We Know: Where to Now?
    ( 2021-01-05) Mueller, Benjamin ; Hovorka, Dirk