Experimental research setting in management

The current issue of the CERN IdeaSquare Journal of Experimental Innovation displays the plurality of levels of analysis for experimental research in management leaving only the policy level investigations untouched

Open laboratories for everyone wishing to experiment with the future

publishedVersionNon peer reviewe

Reply to Comment on Saku et al. : Reasons and risk factors for ninety day re-admission following primary total knee arthroplasty in a high-volume centre

Non peer reviewe

A Consultation Phone Service for Patients With Total Joint Arthroplasty May Reduce Unnecessary Emergency Department Visits

Background: Different measures for reducing costs after total joint arthroplasty (TJA) have gained attention lately. At our institution, a free-of-charge consultation phone service was initiated that targeted patients with TJA. This service aimed at reducing unnecessary emergency department (ED) visits and, thus, potentially improving the cost-effectiveness of TJAs. To our knowledge, a similar consultation service had not been described previously. We aimed at examining the rates and reasons for early postdischarge phone calls and evaluating the efficacy of this consultation service. Methods: During a 2-month period, we gathered information on every call received by the consultation phone service from patients with TJAs within 90 days of the index TJA procedure. Patients were followed for 2weeks aftermaking a call to detectmajor complications and self-initiated EDvisits. Datawere collected fromelectronic medical charts regarding age, gender, type of surgery, date of discharge, and length of hospital stay. Results: We analyzed 288 phone calls. Calls were mostly related to medication (41%), wound complications (17%), and mobilization issues (15%). Most calls were resolved in the phone consultation. Few patients (13%) required further evaluation in the ED. The consultation service failed to detect the need for an ED visit in 2 cases (0.7%) that required further care. Conclusion: The consultation phone service clearly benefitted patients with TJAs. The service reduced the number of unnecessary ED visits and functioned well in detecting patients who required further care. Most postoperative concernswere related to prescribed medications, wound complications, and mobilization issues. (c) 2017 Elsevier Inc. All rights reserved.Peer reviewe

Advancing Reproducibility and Accountability of Unsupervised Machine Learning in Text Mining : Importance of Transparency in Reporting Preprocessing and Algorithm Selection

Machine learning (ML) enables the analysis of large datasets for pattern discovery. ML methods and the standards for their use have recently attracted increasing attention in organizational research; recent accounts have raised awareness of the importance of transparent ML reporting practices, especially considering the influence of preprocessing and algorithm choice on analytical results. However, efforts made thus far to advance the quality of ML research have failed to consider the special methodological requirements of unsupervised machine learning (UML) separate from the more common supervised machine learning (SML). We confronted these issues by studying a common organizational research dataset of unstructured text and discovered interpretability and representativeness trade-offs between combinations of preprocessing and UML algorithm choices that jeopardize research reproducibility, accountability, and transparency. We highlight the need for contextual justifications to address such issues and offer principles for assessing the contextual suitability of UML choices in research settings.publishedVersionPeer reviewe

Advancing Reproducibility and Accountability of Unsupervised Machine Learning in Text Mining: Importance of Transparency in Reporting Preprocessing and Algorithm Selection

Machine learning (ML) enables the analysis of large datasets for pattern discovery. ML methods and the standards for their use have recently attracted increasing attention in organizational research; recent accounts have raised awareness of the importance of transparent ML reporting practices, especially considering the influence of preprocessing and algorithm choice on analytical results. However, efforts made thus far to advance the quality of ML research have failed to consider the special methodological requirements of unsupervised machine learning (UML) separate from the more common supervised machine learning (SML). We confronted these issues by studying a common organizational research dataset of unstructured text and discovered interpretability and representativeness trade-offs between combinations of preprocessing and UML algorithm choices that jeopardize research reproducibility, accountability, and transparency. We highlight the need for contextual justifications to address such issues and offer principles for assessing the contextual suitability of UML choices in research settings

Using mergers and acquisitions to prepare for disruption

Industry incumbents often encounter significant troubles in the face of disruptive innovations. These types of innovations erode the existing capabilities and resources of the firm, forcing them to seek out new capabilities outside their own organization in order to remain competitive and survive. Exploitation and exploration, organizational learning strategies utilized to develop incremental and radical innovations, respectively, are considered common drivers for mergers and acquisitions (MA) among firms. MA's enable the firm to obtain new capabilities and competencies in order to respond to the threat of substitution of their current ones by disruptive innovations and new entrants employing them. According to the research, firms' operative actions are more strongly linked to preparing for disruption than strategic ones in the motives for acquisitions.acceptedVersionPeer reviewe

Editorial: Experimental projects in the special circumstances of the COVID-19 era

This editorial marks the end of fourth year in the history of the CERN IdeaSquare Journal of Experimental Innovation (CIJ). The collection of articles in this issue highlights the special circumstances of experimental projects during the global COVID-19-related restrictions.publishedVersionNon peer reviewe

Editorial: Tackling challenges of the future with new approaches

The special circumstances of the post-COVID-19 situation emphasise the importance of innovating new solutions with cross-disciplinary approaches and these manuscripts in their part also have shown interesting ways towards the future of innovating. We hope that these manuscripts will inspire new approaches and experiments in tackling challenges of the future globally.publishedVersionNon peer reviewe