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During the COVID-19 pandemic, knowledge workers worked from home (WFH) and had to share knowledge mainly online. Studies show that remote work influence knowledge sharing. Beyond the pandemic, several studies report that companies expect more people to work partly or fully from home or anywhere. Therefore, we investigate how knowledge workers experience working from home (WFH), full or part-time, and how it affects their work and knowledge sharing. We conducted an online survey at six different time points between May 2020 and November 2021, allowing us to analyse different working from home situations for the first time. Our survey included 23 questions covering positive and negative experiences from WFH and demographics. Data was collected from 3406 knowledge workers in Denmark working fully or partly from home. The answers were analysed by fitting proportional odds logistic regressions. During the lockdown around February 2021, when Danish restrictions were high, knowledge workers reported that they could focus less on their work at home than at other points of time when they were allowed back in the office. Furthermore, they missed seeing their colleagues more during the lockdown period than at times when the society was completely open again, as they felt a lack of discussion and creative problem-solving. Despite using software solutions for collaboration and communication, knowledge workers missed opportunities for knowledge sharing when WFH. In general, during the whole period, female respondents reported that they got more time to focus on their work when WFH than males did. Finally, older respondents experienced more time to focus on work than the young respondents did when WFH. The results show the differences in the situation of knowledge workers, whether it is enforced or flexible/voluntary to work from home. Thus, this study contributes to a better understanding of the challenges when knowledge workers WFH, which groups of knowledge workers can gain from WFH regarding efficiency and knowledge sharing needs. Beyond the pandemic, when companies want to offer more flexibility to WFH, this study provides conclusions on which conditions to be aware of to ensure efficient knowledge sharing.

 Users may download and print one copy of any publication from the public portal for the purpose of private study or research.  You may not further distribute the material or use it for any profit-making activity or commercial gain  You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Daily scheduling of surgical operations is a complicated and recurrent problem in the literature on health care optimization. In this study, we present an often overlooked approach to this problem that incorporates a rolling and overlapping planning horizon. The basis of our modeling approach is a Markov decision process, where patients are scheduled to a date and room on a daily basis. Acknowledging that both state and action space are only partially observable, we employ our model using a simulation-based method, where actions are derived from a heuristic search procedure.We test the potential of using this modeling approach on the resulting hospital costs and number of patients that are outsourced to avoid violating constraints on capacity. Using data from a Danish hospital, we find a distinct improvement in performance when compared with a policy that resembles a manual planner. Further analysis shows that substantial improvements can be attained by employing other simple policies.

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7Providing patients with the best possible care is the most essential function of any hospital. In an 8 increasing number of countries, hospitals are governed by the number of patients they are able to attract 9 and the corresponding services they provide for patients. One such service, which is often of significant 10 importance for patients, is the option to choose their room type. 11Hospital decision makers would benefit from a strategic method for optimizing the configuration of room 12 types among nursing wards by distinguishing between patients who prefer private rooms and those who 13 have no preference concerning whether they are assigned to a private or shared room. Such a decision 14 support method is currently non-existent, therefore the goal of this study is to provide a methodology for 15 hospital management. Specifically, a mixed modeling approach is proposed which evaluates the patient 16 flow behavior by applying a Continuous-Time Markov Chain within a heuristic search procedure. This 17 procedure recursively improves a configuration of rooms among the wards by sampling from a gradually 18 improved interpolation of an objective function. 19 Based on patient data obtained from both a Danish and Belgian hospital, the performance and robustness 20 of the proposed approach is validated through various numerical experiments, demonstrating that solutions 21 within a relative gap of 1% from the optimum are attained in most cases.22

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