Combining topic modeling and bibliometric analysis to understand the evolution of technological innovation adoption in the healthcare industry

Purpose - This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies. Design/methodology/approach - We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed. Findings - Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI. Research limitations/implications - The study’s sample selection focused on scientific journals included in theAcademic Journal Guideand in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry. Practical implications - ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services. Originality/value - The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.