Analysing the change management process for digital transformation involving citizens using textual analysis techniques

Caihua Liu; Quangui Wan; Zhaonian Sun; Shufeng Kong

doi:10.4025/actascitechnol.v47i1.71028

Authors

Caihua Liu Guilin University of Electronic Technology
Quangui Wan Guilin University of Electronic Technology
Zhaonian Sun Guilin University of Electronic Technology
Shufeng Kong Sun Yat-sen University

DOI:

https://doi.org/10.4025/actascitechnol.v47i1.71028

Keywords:

Digital Transformation, Citizen Engagement, Change Management Process, Textual Analysis

Abstract

The irreversible trend of digitalisation is reshaping our society, capturing citizens’ attention by delivering high-quality, real-time digital services across various domains. Prior research has primarily concentrated on addressing concerns and challenges related to utilising digital platforms for citizen engagement. This research aims to improve understanding of change management process for digital transformation involving citizens for prioritising problem handling and devising appropriate solutions at different stages of the process. Firstly, content and thematic analysis techniques were employed to identify and analyse the characteristics of the change management process from 33 relevant studies in a systematic review. Subsequently, a change management process model was developed, including five stages: determining a change initiative, developing a change plan, communicating changes resulting from digital transformation, monitoring the progress of changes, and learning from past lessons. This model was then applied to analyse the change management process in a case study using text clustering technique based on online news released by the Shanghai government in 2023, allowing to gain insights into challenges/problems and strategies used to address them at each stage in the process. The findings show the utility of the model for analysing the change management processes. Implications for academia and practitioners are also discussed.

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