As a Master at the China Academy of Information and Communications Technology (CAICT), Justin Zhang has held executive positions at many world’s best companies such as Sun Microsystems, IBM, and Accenture. He has published several books on “Information Lifecycle Management” and “Future Ready Information Systems Architecture” during his career life.
He defended his Executive Doctorate of Business Administration (EDBA) in March 2025, on the theme “An Empirical Study on Realization of Data Value: Key Drivers and Challenges of Data Monetization in the Chinese Healthcare Industry” under the supervision of Prof Jean-Fabrice Lebraty, iaelyon School of Management, Université Lyon 3, France.
Thesis Direction
Prof Lebraty Jean-Fabrice
Thesis Title
An empirical study on realization of data value: key drivers and challenges of data monetization in the Chinese Healthcare Industry
Abstract
1: Introduction and Background
The purpose of this thesis is to study the realization of data value in the process of data factor flow and analyze the various favorable and unfavorable factors that promote or hinder the realization of data value.
The reason for choosing this topic is that China and even the whole world expects the flow of data elements, but in practice, there are many factors such as policy, technology, process and law that make it difficult to carry out this work, so it is necessary to systematically analyze the root causes and propose solutions.
2: Issues
In the process of data value realization, there are many favorable and hindering factors, and it is necessary to find a suitable theoretical framework to systematically sort out the relationship between various factors and quantify them, so as to persuade various decision makers and theoretical researchers in the ecological chain of data element circulation to design the correct policy and legal framework, finally to recognize and solve the problems from the top.
The DeLone and McLean model has not been used in the existing literature to analyze and solve the problems in the flow of data elements and AI automation process.
3: Objectives and Contributions
The goal of this dissertation is to use the DeLone and McLean model as a theoretical framework to investigate which elements of policy, law, technology, and process in the flow of data elements play the most significant or decisive role in determining the value of data.
In the process of analysis, the DeLone and McLean model is very systematic and valuable, but this model was invented in the era of information technology, and it needs to be enriched and optimized in the digital era to adapt to the era of digitization and artificial intelligence, which is also the academic value of this thesis.
4: Methodology
The research methodology used in this paper includes a combination of seminars, questionnaires, qualitative analysis and quantitative analysis.
5: Main Results
When using DeLone and McLean model to analyze and sort out all the key elements affecting the process of realizing the value of data, through the interviews with CIOs of more than 50 hospitals and health care institutions, it was found that the key role in the assessment of the value of data is the treatment of data ownership, and the paper proposes to replace the treatment of ownership with the right to use, the right to process and the right to benefit from the data, which can solve the legal problems. This would solve the legal issues and thus simplify the problem, which is a managerial contribution.
Meanwhile, the DeLone and McLean model is optimized and many new elements are added to make the D&M model continue to play a greater role in the digital era.
6: Implications
The value of this thesis to policy makers and theoretical researchers in the field of data elements is that it identifies the key problems in China’s data domain, especially in healthcare industry, finally the solutions are provided.
The total solution is systematic, comprehensive, high level and deep, and very actionable.
7: Conclusion and Outlook
The main conclusion of the thesis is that the road to realize the value of data element circulation is very long, but after systematic analysis, the risk and difficulties in the journey have been identified.
Recognized and valued by China’s data management authorities, and also reached a consensus with many theoreticians, the biggest contribution of this thesis to the Chinese industry is the thesis draw a whole picture of data circulation in China.
The next step is to extend this theoretical research framework to other fields besides the healthcare industry, so that the research methodology and conclusions can be generalized into a universal model.