Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/338028 
Year of Publication: 
2025
Citation: 
[Journal:] Digital Business [ISSN:] 2666-9544 [Volume:] 5 [Issue:] 2 [Article No.:] 100157 [Year:] 2025 [Pages:] 1-28
Publisher: 
Elsevier, Amsterdam
Abstract: 
This study develops a structured framework for advancing theory-driven research on the application of Internet of Things (IoT) technologies in the healthcare sector. Despite the growing body of empirical research, prior studies lack a systematic analysis of the research questions posed and the theoretical frameworks applied. Addressing this gap, the study conducts a rigorous Systematic Literature Review (SLR) of 75 peer-reviewed articles indexed in Scopus and Web of Science. It identifies 85 distinct research questions and 36 theories used in empirical investigations, classifying them into five thematic areas: technology adoption, performance improvement, social and cultural aspects, cognitive processes, and decision-making. To enhance theoretical precision and applicability, the study introduces a decision matrix based on the framework of Hanafizadeh and Alipour (2025), which enables the alignment of research questions with suitable theories through an analysis of contextual and conceptual fit. Using this approach, the study proposes 113 alternative theories to address existing questions and introduces 38 new research questions, supported by 48 relevant theoretical frameworks. The original contribution of this research lies in its systematic mapping of theory-question relationships and the introduction of a structured model for guiding future research in IoT and healthcare. By bridging theoretical gaps and extending conceptual understanding, the study offers a valuable resource for scholars seeking to conduct more robust, theory-informed investigations in the rapidly evolving field of smart healthcare systems.
Subjects: 
Healthcare
IoT
Theory
Persistent Identifier of the first edition: 
Creative Commons License: 
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Document Type: 
Article
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