The purpose of this study was to analyse knowledge management research trends to understand the development of the field using a combination of scientometric, bibliometric, and visualisation techniques, subsequently developing a normative framework of knowledge management from the results.282 articles between the years 2010–2015 were retrieved, analysed, and visualised to produce the state of knowledge management during the selected timeframe. The results of this study provide a visualisation of the current research trends to understand the development of the knowledge management discipline. There are signals that the literature about knowledge management is progressing towards academic maturity. This study is one of the first studies to combine bibliometric and scientometric methods to assess productivity along with visualisation, and subsequently provide a knowledge management framework drawing from the results of these methods.
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Insider ethnographic analysis is used to analyze change processes in an engineering department. Distributed leadership theory is used as conceptual framework.
In the literature about web survey methodology, significant e orts have been made to understand the role of time-invariant factors (e.g. gender, education and marital status) in (non-)response mechanisms. Time-invariant factors alone, however, cannot account for most variations in (non-)responses, especially fluctuations of response rates over time. This observation inspires us to investigate the counterpart of time-invariant factors, namely time-varying factors and the potential role they play in web survey (non-)response. Specifically, we study the effects of time, weather and societal trends (derived from Google Trends data) on the daily (non-)response patterns of the 2016 and 2017 Dutch Health Surveys. Using discrete-time survival analysis, we find, among others, that weekends, holidays, pleasant weather, disease outbreaks and terrorism salience are associated with fewer responses. Furthermore, we show that using these variables alone achieves satisfactory prediction accuracy of both daily and cumulative response rates when the trained model is applied to future unseen data. This approach has the further benefit of requiring only non-personal contextual information and thus involving no privacy issues. We discuss the implications of the study for survey research and data collection.
The overall purpose of this consultancy was to support the activities under the Environmental Monitoring and Assessment Programme of the UN Economic Commission for Europe (UNECE) in developing the 7th pan-European environmental assessment, an indicator based and thematic assessment, implemented jointly with the United Nations Environment Programme (UNEP) and in support of the 2030 Agenda for Sustainable Development. The series of environmental assessments of the pan-European region provide up to-date and policy-relevant information on the interactions between the environment and society. This consultancy was to:> Draft the input on drivers and developments to chapter 1.2 of the assessment related to the environmental theme “4.2 Applying principles of circular economy to sustainable tourism”.> Suggest to UNECE and UNEP the most policy relevant indicators from UNECE-environmental, SDG indicators and from other indicator frameworks such as EEA or OECD for the environmental theme for the sub-chapter 4.2.> Assess the current state, trends and recent developments and prepare the substantive part of sub-chapter 4.2 (summary - part I) and an annex (part II) with the detailed analysis and findings.
