Zeng Li

This site uses cookies

We use necessary cookies to make our sites work. We'd also like to set additional cookies to analyse how our sites are performing, to improve the relevance of our ads and to optimise your experience. These will be set only if you accept. To learn more, view our privacy policy.

Necessary cookies

These cookies are necessary for the website to function normally and cannot be turned off. They are usually set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can block or delete them in your browser settings, but this may affect how the website functions.

Analytics cookies

These cookies allow us to monitor how our websites and services are performing by collecting data about how visitors interact with our sites. The data is collected in a way that does not directly identify anyone.

Marketing cookies

These cookies are set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant ads on other sites. If you disable this setting, you will experience less targeted advertising.

Functionality cookies

These cookies enable us to provide enhanced functionality and personalisation. They may be set by us or by third party providers whose services we have added to our pages.

Research Topic

Organisational Tensions during the Adoption of Medical AI Systems

Research
Profile

Research Summary

Zeng's research focuses on the tensions arising during the adoption of Artificial Intelligence (AI) systems in the healthcare industry, explores the evolution and dynamics of these tensions, and identifies coping strategies. Zeng is collecting qualitative data in Chinese hospitals, where medical AI technology is rapidly growing. Zeng's research will provide valuable guidance for stakeholders (hospitals, IT companies, universities, and the government) seeking to foster sustainable adoption of AI systems in healthcare organisations.

Supervisor(s)

Research Area

Entrepreneurship and Innovation

Background

Zeng is a doctoral researcher in the Entrepreneurship and Innovation Group. After acquiring foundational Computer Science knowledge during her undergraduate studies at the Beijing University of Posts and Telecommunications, Zeng developed a keen interest in Information systems, a discipline bridging engineering and management.

Following the completion of her master's degree, Zeng gained valuable experience as a research assistant at the Fudan University Innovation Institute. During this work experience, she participated in a transformative project combining Artificial Intelligence, mathematical algorithms, and medicine, which inspired her current research interests.

Zeng has reviewed papers for the British Academy of Management (BAM) and the International Conference on Information Systems (ICIS). Her paper "Applying Paradox Theory in Mapping Tensions during AI Implementation in Healthcare Organisations" won the Best Full Paper Award on the e-Business and e-Government Track at BAM2023.

Zeng’s interdisciplinary background equips her with flexible strategies to tackle complex challenges.

Education and Qualifications

Institute	Degree/Qualification	Dates
University of Leeds Business School	MSc Information Systems and Information Management (1st Class Honours)	2019-2020
Beijing University of Posts and Telecommunications	Bachelor of E-Commerce Engineering	2015-2019

Professional and Voluntary Experience

Professional

Research Assistant, Zhuhai Fudan Innovation Research Institute (2020-2021)

91����