Identification of research trends in emerging technologies implementation on public services using text mining analysis

【Author】 Rodriguez Bolivar, Manuel Pedro; Alcaide Munoz, Laura

【Source】INFORMATION TECHNOLOGY & PEOPLE

【影响因子】4.481

【Abstract】Purpose This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery. Design/methodology/approach VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services. Findings The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the "electronic administration" stage, the "technological baseline" stage, the "managerial" stage and the "disruptive technological" stage. Practical implications The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services. Social implications The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services. Originality/value Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens' quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

【Keywords】Emerging technologies; Public services; Text mining; Clustering analysis; Science mapping

【发表时间】

【收录时间】2022-05-07

【文献类型】综述

【主题类别】

区块链应用-实体经济-公共管理