Essay from the year 2018 in the subject Computer Science - Commercial Information Technology, grade: A, University of Malta, language: English, abstract: During the early 2000s, it was argued that there was a need for ways to determine the quality of qualitative studies in medicine, and therefore, a need for developing appraisal criteria for qualitative research. Critically appraising journal articles allow one to filter out the low-quality studies and distinguish misleading information. In an attempt to apply this to the field of management, whilst reducing the possibility of flaws and classification errors, the CEBMa adapted appraisal questionnaires for specific study designs, one of which - 'Appraisal of a Case Study' - shall act the basis of this critical essay. The article in review is featured in Elsevier's 'International Journal of Project Management' and was made available online on ScienceDirect.com on the 8th of January 2016. As declared in the journal's 'Author Information Pack' document, papers by the editorial board are selected for publication based on their relevance, clarity, topicality, the extent to which they advance knowledge, and their contribution to inspiring further development and research. The information pack contains a strict and lengthy checklist of requirements and guidelines for researchers to adhere to, before submitting their research for publishing in the IJPM. Hence, a journal article undergoes a rigorous test prior to being released and therefore, at face value, one can expect this study to be trustworthy and of adequate quality. Authors, M.A. Terlizzi, F. de Souza Meirelles, and H.R.O.C. de Moraes researched under the auspices of the São Paulo School of Business Administration, a Brazilian Higher Education institution. All three are Brazilian nationals and hold considerable experience in IT, IT Governance, Business Administration, Project Management, and Academia. The researchers did not comment on their own role and any professional bias they might have possibly caused. As emphasised by Coates (2011), it is important that researchers are aware of their own preconceptions and strive to ensure that they do not allow them to bias their interpretation of the data.