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This paper introduces the Swedish BERT ("KB-BERT") developed by the KBLab for data-driven research at the National Library of Sweden (KB). Building on recent efforts to create transformer-based BERT models for languages other than English, we explain how we used KB's collections to create and train a new language-specific BERT model for Swedish. We also present the results of our model in comparison with existing models-chiefly that produced by the Swedish Public Employment Service, Arbetsförmedlingen, and Google's multilingual M-BERT-where we demonstrate that KB-BERT outperforms these in a range of NLP tasks from named entity recognition (NER) to part-of-speech tagging (POS). Our discussion highlights the difficulties that continue to exist given the lack of training data and testbeds for smaller languages like Swedish. We release our model for further exploration and research here: https://github.com/Kungbib/swedish-bert-models.

Public organizations increasingly rely on management consultants to access expertise, impose reforms, and drive organizational change, and spend large sums each year on their services. Despite this, we know little about the antecedents of public organizations' use of management consulting services. Drawing on upper echelon theory, a longitudinal hypothesis‐testing study of the hiring of management consultants in 72 Swedish public organizations, and interviews with Swedish chief executives (CEs), we find an inverted U‐shaped relationship between CE tenure and public organizations' use of management consulting services. We also find that this relationship is moderated by CEs' previous experience and managerial discretion. These findings contribute to theorizing on the use of management consulting services and the influence of CEs in public organizations.