Exploring the forward citation patterns of patents based on the evolution of technology fields. Issue 4 (November 2019)

• Record Type: Journal Article
• Authors: Jee, Su Jung; Kwon, Minji; Ha, Jung Moon; Sohn, So Young
• Is Part Of: Journal of informetrics. Volume 13:Issue 4(2019)
• Publication Date: 2019-11
• Subjects: Forward citation patterns of patents -- Dynamic field effects -- Technology diffusion -- Technology value -- Evolutionary perspective; Library statistics -- Periodicals; Information science -- Statistical methods -- Periodicals; Bibliometrics -- Periodicals; Bibliothèques -- Statistiques -- Périodiques; Sciences de l'information -- Méthodes statistiques -- Périodiques; Bibliométrie -- Périodiques; 020.727
• DOI: 10.1016/j.joi.2019.100985
• Languages: English
• ISSNs: 1751-1577

Abstract

Highlights: A dynamic approach is used to understand patterns of patent forward citation. Four different aspects of technology field evolution are employed. Patents across heterogeneous industries and within an industry are considered. The proposed approach is applied to the IT and healthcare industries. Implications are suggested for those who exploit patent citation information. Abstract: Forward citations of patents have been used extensively to capture the impact of technological knowledge. However, our understanding of the factors shaping patent citation patterns remains limited. One of the main limitations is the lack of scholarly attention paid to the dynamic influences arising from the evolution of technology fields. From an evolutionary perspective, technological impact is not simply determined by the static attributes of a technology itself; it is also dynamically affected by changes in the external conditions. Drawing on this viewpoint, this study suggests a model for understanding patent citation patterns by reflecting the evolution of the technology fields to which each patent belongs. Four such factors are explored: technology cycle time, potential of technological convergence, popularity of the technology field, and technological novelty. Based on the proposed model, we show how expected citation patterns can change as a result of different scenarios for technology field evolution. We conduct a case study of patents in the information technology and healthcare industries to show citation patterns of patents across heterogeneous industries as well as those within an industry. Contributions to the innovation literature and research investment decisions are discussed.