Development of a competitive technology intelligence methodology to identify technology dynamics: the case of M-health for diabetes

Abstract

The unprecedented development of technological advances brings new challenges and opportunities to create competitive advantages. It is necessary the effective use of technology as a facilitator to bring better products and services in all sectors such as industry, business, education, healthcare, and government. An adequate assessment of science and technology is fundamental to impact present and future Research and Development (R&D) and innovation decisions. Diverse disciplines based on metrics analysis have emerged to facilitate science and technology understanding, such as scientometrics, patentometrics, and altmetrics. They offer fundamental theoretical and methodological contributions to quantify scientific research literature, patents, scholarly activities on social networks and websites, aiming to reveal the process of scientific and technology development. However, the current accelerated technological advances require researchers to implement a superior approach to detect continuous changes in the external environment identifying opportunities and vulnerabilities to strengthen the decision-making process regarding R&D and innovation. Organizations can increase their advantages by systematically analyzing the external environment, identify movements of competitors and detect opportunities for growth. In this context, Competitive Technology Intelligence (CTI) offers a strategic approach where information is transformed into opportunities for an actionable result. This research proposes a CTI methodology of eight steps that incorporates experts feedback, a scientometrics and a word distribution analysis into a process to provide a broader scope to science and technology. This thesis provides a more robust analytical approach than traditional scientometric analysis where indicators as relevant authors, institutions, countries, citations, and impactful articles are identified. In this context, this thesis goes further since current hotspots and landscape of main research topics are also determined as well as technological trends, gaps, and opportunity areas to research, evolving the traditional scientometric approach. To demonstrate the methodology proposed, a case study was carried out around diabetes m-Health which is particularly relevant given the worldwide increase in diabetes prevalence. Identifying its technological dynamics can facilitate the adoption of effective technologies that enhance patients' quality of life. As a result of all this process, three scientific publications were developed and published in Q1, and Q2 journals. In the first publication (2021) the proposed CTI methodology is VII presented, while in the second publication (2024) the methodology is applied through a scientometric analysis where current hotspots on diabetes m-Health are determined. Finally, the third publication (2024) provides a landscape of main research topics in diabetes m-Health, and technological trends and opportunity areas to research are identified. These studies aim to contribute researchers, decision makers, and policy makers to prioritize R&D efforts, consolidate areas of interest and explore new research topics.