Maturity of the Internet of Things Research Field: Or Why Choose Rigorous Keywords

Periodically researchers examine the maturity of their research fields against a set of maturity criteria including the types of theories and methods used within the field. Keyword metadata was used to locate relevant research articles, which were manually read, summarised, and compared against field maturity criteria. This study used data extracted from three academic databases to examine the maturity of the Internet of Things (IoT) research field using keyword metadata analysis alone. The metadata analysis was proposed to reduce analysis time, and allowed for testing of a much larger sample of articles. Findings indicated that the IoT research field was immature, with experimental methods dominating research outputs. Difficulties with keyword metadata including synonyms, abbreviations, poor accuracy, and method and theory not being included in metadata, made this research challenging. To relieve these problems in the future a keyword schema is suggested. This should also assist researchers in locating relevant literature

A “Look” into the IS Discipline through the Lens of MIS Quarterly: A Visual Examination of Scholar Characteristics

Academic disciplines naturally form their own knowledge cultures. This research examines characteristics of knowledge creators by investigating a subset of information systems (IS) researchers, namely those who have published in one of the field’s premier journals – MIS Quarterly. Author characteristics (pedigree, gender, various location data, etc.) are examined and reported on. Additionally, with the aid of modern visualization tools such as Tableau and/or Microsoft Power BI, influential scholarly foci (knowledge centers) are analyzed. Findings suggest an increase of women, international scholars, and locations over time, are adding to the richness and diversity of the IS field. Furthermore, this research presents some discussion and presentation of the migratory pattern of IS researchers utilizing dynamic mapping visualizations