A digital transformation-enabled framework and strategies for public health risk response and governance: China's experience
| DOI | https://doi.org/10.1108/IMDS-01-2022-0008 |
| Published date | 22 June 2022 |
| Date | 22 June 2022 |
| Pages | 133-154 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Ching-Hung Lee,Dianni Wang,Shupeng Lyu,Richard David Evans,Li Li |
A digital transformation-enabled
framework and strategies for
public health risk response and
governance: China’s experience
Ching-Hung Lee, Dianni Wang and Shupeng Lyu
School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, China
Richard David Evans
School of Computer Science, Dalhousie University, Halifax, Canada, and
Li Li
School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an, China
Abstract
Purpose –Under uncertain circumstances, digital technologies are taken as digital transformation enablers
and driving forces to integrate with medical, healthcare and emergency management research for effective
epidemic prevention and control. This study aims to adapt complex systems in emergency management. Thus,
a digital transformation-driven and systematic circulation framework is proposed in this study that can utilize
the advantages of digital technologies to generate innovative and systematic governance.
Design/methodology/approach –Aiming at adapting complex systems in emergency management, a
systematic circulation framework based on the interpretive research is proposed in this study that can utilize
the advantages of digital technologies to generate innovative and systematic governance. The framework
consists of four phases: (1) analysis of emergency management stages, (2) risk identification in the emergency
management stages, (3) digital-enabled response model design for emergency management, and (4) strategy
generation for digital emergency governance. A case study in China was illustrated in this study.
Findings –This paper examines the role those digital technologies can play in responding to pandemics and
outlines a framework based on four phases of digital technologies for pandemic responses. After the phase-by-
phase analysis, a digital technology-enabled emergency management framework, titled “Expected digital-
enabled emergency management framework (EDEM framework)”was adapted and proposed. Moreover, the
social risks of emergency management phases are identified. Then, three strategies for emergency governance
and digital governance from the three perspectives, namely “Strengthening weaknesses for emergency
response,”“Enhancing integration for collaborative governance,”and “Engaging foundations for emergency
management”that the government can adopt them in the future, fight for public health emergency events.
Originality/value –The novel digital transformation-driven systematic circulation framework for public
health risk response and governance was proposed. Meanwhile, an “Expected digital-enabled emergency
management framework (EDEM model)”was also proposed to achieve a more effective empirical response for
public health risk response and governance and contribute to studies about the government facing the COVID-
19 pandemic effectively.
Keywords Digital transformation, Emergency management process, Public health, COVID-19,
Risk identification, Social digital governance
Paper type Research paper
Strategies for
public health
risk response
133
This research is partially supported by the Xi’an Jiaotong University [grant number: 7121192301] and
the National Natural Science Foundation of China [grant number:72174168], Xi’an Science and
Technology Plan [grant number: 2021-0035], Shaanxi Province Innovation Capacity Support Project
[grant number: 2017KRM011], and National Social Science Foundation of China [grant number:
21BZZ079].
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 6 January 2022
Revised 27 March 2022
5 May 2022
27 May 2022
Accepted 27 May 2022
Industrial Management & Data
Systems
Vol. 123 No. 1, 2023
pp. 133-154
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-01-2022-0008
1. Introduction
The COVID-19 outbreak was first detected in Wuhan, China, near the end of 2019, and it has
spread throughout the world. Unlike the three traditional types of emergencies: natural
disasters, accidents, and social security (Rosenthal et al., 1989;Rosenthal et al., 2001a,b;Pan
and Meng, 2016;Christensen et al., 2016;Majchrzak, 2016), public health emergencies, as a
highly uncertain risk event, are frequently influenced by their suddenness, variability, and
transient nature (Hewitt and Kenneth, 1983;Harrison and Johnson, 2019). The bureaucratic
governance system poses substantial obstacles (Panagiotopoulos et al., 2014;Reddy et al.,
2009). The overall social risks, harm, and destructiveness have extended from public health,
emergency management, transportation, and public safety areas to the macroeconomy due to
the COVID-19 epidemic’s massive impact (Hart et al., 1989;Rosenthal et al., 2001a,b;Boin,
2009). As the epidemic crosses geographical boundaries, social risks gradually upgrade to
various fields such as national institutions and mechanisms (Goodsell, 2015;Pellegata and
Memoli, 2016;Selby and Desouza, 2018), international trade and economy (Weible and
Nohrstedt, 2020), national ideology (Jones, 2008;Carayannopoulos and George, 2017), and
traditional culture (Gelfand, 2012;Yan et al., 2020). The COVID-19 epidemic has brought
systemic shocks to the governance systems of countries and regions. Chia’s top-down
national emergency management system has unique characteristics and advantages for
preventing and defusing social risks. The emergency management department could
effectively coordinate the promotion of emergency preparedness, epidemic prevention and
control, and restore productivity and economic vitality (Hart et al., 1989;Boin et al., 2005;Boin
and Hart, 2010). After the outbreak, the Emergency Management Department in China makes
the best efforts to prepare for emergency rescue during the prevention and control of the
epidemic, from the aspects of emergency plans, command mechanisms, rescue forces, news
and social media trust, and the daily life guarantees (McConnell, 2003;Bynander and
Nohrstedt, 2019;Weible and Nohrstedt, 2020;Tian et al., 2020).
This fight against the disease is also a natural and significant test for China’s emergency
response system. Many problems in China’s emergency management system have been
exposed in the process: (1) the original emergency management system design for primary
social security is imperfect, lacking the consideration of public health emergencies.
Emergency response to public health epidemics is not included and it is well-designed in
the unified dispatches of the emergency management department. (2) regulations and
organizations do not clarify the coordination chain. The linkage mechanism between the up-
down and the left-right is not sound enough. The emergency response mechanism is not
sensitive. (3) various emergency preparedness and dispatches have shortcomings and
insufficient capabilities to be resolved urgently. Fortunately, in recent years, emerging
technologies have been developing in the advent of the information age (Woo et al., 2016;
H€
ochtl et al., 2016; Desjardins, 2020; Turchin and Denkenberger, 2020). The Internet of
Things, artificial intelligence, big data, blockchain, and cloud computing are bringing new
opportunities (Lee et al., 2021a) in the new scenarios of public health emergency events.
Simultaneously, it has also spawned many intelligent governance tools, providing the right
technology for establishing a better smart governance model for innovative government risk
management.
For example, governments and society depend on social media platforms (e.g. Twitter,
WeChat, QQ, etc.) and search engines to gain vital records to screen tendencies of the
epidemic in real-time and visualize the transferring paths of validated cases. Furthermore,
artificial brain (AI) technology effectively assists in medical diagnosis. Huawei launched an
AI-assisted medical picture analysis service to check the development of COVID-19. Cloud
computing is used for gene sequencing. Nucleic acid takes a look at reagent development, and
in particular, pills and vaccines. The clever disinfection robot of Keen efficaciously reduces
the route of virus transmission (Lee et al., 2021b;Wei et al., 2021).
IMDS
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