Technological Scanning for Foresight: The case of Metaverse applications for Healthcare

Abstract

The process of foresight, which allows companies and organizations to build scenarios and inform the creation and sustainment of their competitive advantage, relies on the integration of several steps. Scanning is a crucial step of foresight, as it informs and influences the results of the whole process and, thus, the strategic decision-making of the company. Sources and methods of scanning for foresight analysis can be diverse and lead to different results, although few studies investigate such differences: more specifically, the informative power of academic and non-academic articles and reports has not been assessed yet. This study aims to shed novel light on how the different analysis methods of full reading of records and text mining analysis isolate and gather forces of change differently, based on the source analyzed. The study’s empirical context is the metaverse and its application in healthcare. We find that each source and method by itself is unable to fully gather the whole set of forces of change; however, each source presents some topics that are specific to the target readers of the source, and each methodology presents some advantages as well as some limitations. From the comparison of the results, theoretical and managerial implications are drawn.