Shuyang Li

Dr. Shuyang Li

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 May 2021 in Information Systems Frontiers
Verified
Journal Article
Open access
PDF file
JZJun Zhang
Jun Zhang
SLShuyang Li
Shuyang Li
YWYichuan Wang
Yichuan Wang
The smart transportation system (STS) leverages ubiquitous and networked computing to improve the efficiency of urban mobility. Whilst existing IS work has explored various factors influencing STS development, there is a lack of consideration of how value can be created for building a more sustainable STS. Drawing upon the value co-creation theory and stakeholder theory, we seek to understand the socio-technical shaping of the STS ecosystem and how government, firms and citizens collaboratively create sustainable value for designing and implementing STS initiatives. To reach this aim, we carry out a longitudinal case study over 2016–2018 in Shijiazhuang, China. We offer both theoretical and practical explanations on (i) key value facets with regard to sustainable STS design and implementation; and (ii) a holistic view of iterative value co-creation process pushed by key stakeholders. This study makes particular contributions to the IS, marketing and transportation literature by offering a critical understanding of the social dynamics for shaping a big data-driven STS ecosystem.

10 June 2019 in Industrial Management & Data Systems
Verified
Journal Article
Closed access
SLShuyang Li
Shuyang Li
GPGuochao Peng
Guochao Peng
FXFei Xing
Fei Xing
Purpose: Big data is a key component to realise the vision of smart factories, but the implementation and usage of big data analytical tools in the smart factory context can be fraught with challenges and difficulties. The purpose of this paper is to identify potential barriers that hinder organisations from applying big data solutions in their smart factory initiatives, as well as to explore causal relationships between these barriers.Design/methodology/approach: The study followed an inductive and exploratory nature. Ten in-depth semi-structured interviews were conducted with a group of highly experienced SAP consultants and project managers. The qualitative data collected were then systematically analysed by using a thematic analysis approach.Findings: A comprehensive set of barriers affecting the implementation of big data solutions in smart factories had been identified and divided into individual, organisational and technological categories. An empirical framework was also developed to highlight the emerged inter-relationships between these barriers.Originality/value: This study built on and extended existing knowledge and theories on smart factory, big data and information systems research. Its findings can also raise awareness of business managers regarding the complexity and difficulties for embedding big data tools in smart factories, and so assist them in strategic planning and decision making.

5 August 2021 in Symmetry
Verified
Journal Article
Open access
PDF file
CLCaihua Liu
Caihua Liu
GPGuochao Peng
Guochao Peng
YKYongxin Kong
Yongxin Kong
SLShuyang Li
Shuyang Li
SCSi Chen
Si Chen
Recent years have seen a growing call for use of big data analytics techniques to support the realisation of symmetries and simulations in digital twins and smart factories, in which data quality plays an important role in determining the quality of big data analytics products. Although data quality affecting big data analytics has received attention in the smart factory research field, to date a systematic review of the topic of interest for understanding the present state of the art is not available, which could help reveal the trends and gaps in this area. This paper therefore presents a systematic literature review of research articles about data quality affecting big data analytics in smart factories that have been published up to 2020. We examined 31 empirical studies from our selection of papers to identify the research themes in this field. The analysis of these studies links data quality issues toward big data analytics with data quality dimensions and methods used to address these issues in the smart factory context. The findings of this systematic review also provide implications for practitioners in addressing data quality issues to better use big data analytics products to support digital symmetry in the context of smart factory.

19 April 2024 in JMIR Formative Research
Verified
Journal Article
Open access
JAJake Alan Allcock
Jake Alan Allcock
MZMengdie Zhuang
Mengdie Zhuang
SLShuyang Li
Shuyang Li
XZXin Zhao
Xin Zhao
Background: In England, digital technologies are exploited to transform the way health and social care is provided and encompass a wide range of hardware devices and software that are used in all aspects of health care. However, little is known about the extent to which health care providers differ in digital health technology capabilities and how this relates to geographical and regional differences in health care capacities and resources. Objective: This paper aims to identify the set of digital technologies that have been deployed by the National Health Services clinical commissioning groups (NHS CCGs) in England. In doing this, we respond to calls to shed light on the internal dynamics and variation in the form of digital capability in England in terms of health service regional differences and health diversity, equity, and inclusion. Methods: We collected 135 annual reports that belong to 106 NHS CCGs in England, comprising more than 18,000 pages in total, released from 2020 to 2021. Using this data set, we identified 2163 pages related to digital technologies and labeled them using content analysis. We follow the construct taxonomy used by digital options theory, a theory from the management information systems field analyzing organizational resource investment choices, in classifying observed technologies according to digital themes—inherent design patterns that we identified and explained. We then used a hierarchical clustering method to extract groups of NHS CCGs that implement similar technology themes. Results: We found 31 technologies from the reports and grouped them into 9 digital themes. The 9 themes were further assigned to 1 of the 3 constructs of digital options theory, the identification of patients’ requirements (we identified information portals [76/106], digital health engagement [67/106], and digital inclusion support [45/106]), the development of new work patterns (we identified telehealth [87/106], telemedicine [35/106], and care home technologies [40/106]), the realization of improvements in efficiency and public accessibility (we identified online booking [26/106], online triage [104/106], and digital mental health services [74/106]). The 3 clusters of CCGs are identified based on the 8 themes (Hopkins=0.9914, silhouette=0.186), namely (1) digitally disengaged, (2) digitally engaged, and (3) digital torchbearer. Conclusions: Our findings show prominent digital themes within each construct group, namely information portals, telehealth, and online triage, covering people’s fundamental health information needs. Almost half of CCGs fell into the digitally disengaged group, and all London CCGs (5/106) belonged to this group. We propose that practitioners should offer specialized assistance to regions with limited digital engagement, emphasizing digital health literacy, inclusion support, and ongoing evaluation, rather than concentrating solely on technical advancements.

1 January 2021
Verified
Conference Paper
Closed access
YZYizi Zhou
Yizi Zhou
JLJiyin Liu
Jiyin Liu
Rupal MandaniaRupal Mandania
Rupal Mandania
SLShuyang Li
Shuyang Li
KCKai Chen
Kai Chen
RXRongjun Xu
Rongjun Xu

15 August 2023 in JMIR Preprints
Verified
Preprint
Open access
JAJake Alan Allcock
Jake Alan Allcock
MZMengdie Zhuang
Mengdie Zhuang
SLShuyang Li
Shuyang Li
XZXin Zhao
Xin Zhao
BACKGROUND In England, digital technologies are exploited to transform the way health and social care is provided and encompass a wide range of hardware devices and software that are used in all aspects of health care. However, little is known about the extent to which health care providers differ in digital health technology capabilities and how this relates to geographical and regional differences in health care capacities and resources. OBJECTIVE This paper aims to identify the set of digital technologies that have been deployed by the National Health Services clinical commissioning groups (NHS CCGs) in England. In doing this, we respond to calls to shed light on the internal dynamics and variation in the form of digital capability in England in terms of health service regional differences and health diversity, equity, and inclusion. METHODS We collected 135 annual reports that belong to 106 NHS CCGs in England, comprising more than 18,000 pages in total, released from 2020 to 2021. Using this data set, we identified 2163 pages related to digital technologies and labeled them using content analysis. We follow the construct taxonomy used by digital options theory, a theory from the management information systems field analyzing organizational resource investment choices, in classifying observed technologies according to digital themes—inherent design patterns that we identified and explained. We then used a hierarchical clustering method to extract groups of NHS CCGs that implement similar technology themes. RESULTS We found 31 technologies from the reports and grouped them into 9 digital themes. The 9 themes were further assigned to 1 of the 3 constructs of digital options theory, the identification of patients’ requirements (we identified information portals [76/106], digital health engagement [67/106], and digital inclusion support [45/106]), the development of new work patterns (we identified telehealth [87/106], telemedicine [35/106], and care home technologies [40/106]), the realization of improvements in efficiency and public accessibility (we identified online booking [26/106], online triage [104/106], and digital mental health services [74/106]). The 3 clusters of CCGs are identified based on the 8 themes (Hopkins=0.9914, silhouette=0.186), namely (1) digitally disengaged, (2) digitally engaged, and (3) digital torchbearer. CONCLUSIONS Our findings show prominent digital themes within each construct group, namely information portals, telehealth, and online triage, covering people’s fundamental health information needs. Almost half of CCGs fell into the digitally disengaged group, and all London CCGs (5/106) belonged to this group. We propose that practitioners should offer specialized assistance to regions with limited digital engagement, emphasizing digital health literacy, inclusion support, and ongoing evaluation, rather than concentrating solely on technical advancements.