Determinants of the application of the Evidence – Based Management concept for explaining ontological entities in management and quality sciences

„Kwartalnik Nauk o Przedsiębiorstwie“ 4 (2024), p. 115–135. https://doi.org/10.33119/KNoP.2024.74.4.8

We are pleased to invite you to explore our latest scientific article, which delves into the key determinants of studying ontological entities in quality management sciences through the lens of the Evidence Based Practice concept. This article provides an in-depth critical analysis of previous studies, highlighting the cognitive gap and emphasizing the significance of systematic literature reviews, meta-analyses, and other methodologies in advancing our understanding of ontological entities within management and quality sciences.

Summary: The article aims to identify the primary determinants of studying ontological entities in quality management sciences using the Evidence Based Practice concept. The research draws on critical analyses of prior studies to elucidate the current status and knowledge gaps in this field. Our findings demonstrate the effective application of research methodologies such as systematic literature reviews and meta-analyses, adapted from the medical industry, in the management and quality sciences. These methodologies provide a broader scientific understanding compared to traditional literature reviews. Moreover, the article addresses the challenges posed by managers' limited knowledge of ontological entities and the ontological significance of their decisions in business. The increasing availability of large sets of scientific data enhances the understanding and utilization of evidence-based management practices.

We believe that this article will offer valuable insights and contribute to the ongoing discourse in management and quality sciences. We look forward to your feedback and engagement with our research.

Tematyka: Big Data In Decision Making, Business Decision Support, Data Driven Decisions, Evidence-Based Management, our research, Scientific Management