My research falls along three lines of inquiry: sustainable energy transitions, corporate sustainability, and artificial intelligence (AI) and cyber-physical systems. Specifically, I investigate the policy and market transformations of sustainable energy transitions, the changes in corporate sustainability dynamics, and the regulatory and sustainability challenges caused by AI and cyber-physical systems. In researching these topics, I extensively use digital data (i.e., web-scraped data), and data science (i.e., simulation and advanced quantitative methods, such as social network analysis and GIS).




My scholarship focuses on global environmental change, with an emphasis on sustainable energy transitions. I investigate how state and non-state actors react to sustainable energy transition and how the existing infrastructures and policies encourage or hinder further developments of sustainable energy and energy decentralization.


I have published in leading interdisciplinary journals on issues of energy transitions and organizational behavior. In a paper published in Environmental Innovation and Societal Transitions (impact factor 8.4), I supervised a group of undergraduate research assistants who helped me to collect relevant news articles in order to how investor owned utilities and stakeholders’ framings on solar energy changed over time. The findings showed that investor owned utilities, civil society actors, government agencies, and other solar and community developers tend to change the frequency and framing of their arguments on solar transition depending on political climate. The paper also suggested that solar programs face several challenges from many actors, as the market for solar continues to grow.


Moreover, I also have a publication in Renewable and Sustainable Energy Reviews (impact factor: 12.1), a leading energy journal. This study discussed the social and political structures that inhibit sustainable energy transitions, focusing on community choice aggregation, and community solar in California and New York. The paper found that the success of these community level sustainable energy programs is largely determined by state level government regulations and the existing energy market structures.


I envision further developing my scholarship on environmental policy focusing on international sustainable energy transitions. Building onto my existing projects, my future research will focus on the economic and social structures that encourage or inhibit international sustainable energy production and consumption. So far, my scholarship has focused on sustainable energy transitions in the United States. I plan to expand the research area by conducting a cross country study on how economic and social structures affect sustainable energy transitions. Focusing on countries in Asia, Europe, and North America, I will collect and analyze survey data on economic and market structures, democracy processes, social and political participation in energy decentralization movements. I hypothesize that energy transitions are more feasible in (1) countries with policies that directly and indirectly promote and fund energy decentralization projects, (2) markets that encourage competition among investor owned utilities, and (3) social structures that allow consumer engagements in energy decentralization processes.


I study the changing dynamics of private governance and corporate sustainability. My dissertation focused on the application of the United Nations Sustainable Development Goals (SDGs) to corporate sustainability behavior. The SDGs have had significant global implications in state level environmental actions. However, there has been limited research on directly applying the SDGs to corporations. The first research chapter of my dissertation constructed a new corporate sustainability index using the SDGs. The scholarly significance of this index is twofold. First, it incorporated one the of most important international goals into quantifiable measures for corporations, and second, it also allowed for granular data analysis by providing a corporate score for each goal. Using data from Bloomberg, ASSET4, and the Carbon Disclosure Project, this study identified the corporate leaders and laggards for each SDG. This study is currently going through the revise and resubmit process in Environmental Sociology.


The second research topic used data from the U.S. Securities Exchange Commission and other sources to assess whether central corporations’ behavior on CSR differs from less central corporations. This paper utilized social network analysis, Bayesian multiple imputation, and linear regression analysis to empirically show that central corporations score higher in SDGs compared to less central corporations, showing a greater SDG compliance. This study is theoretically important because it combined the theories of corporate sustainability and corporate interlocks. Moreover, it also showed the significance of corporate networks in determining the success of global environmental governance. This paper is currently under review in the Journal of Business Ethics.


The third research topic used institutional logics theory to investigate the extent to which the logic of profit and the logic of sustainability can coexist. Here, the logic of sustainability is measured using the SDG scores. Using structural equation modeling, this paper constructed the two logics as latent variables and showed that in smaller and non-consumer facing companies, the environmental logic and the profit logic do not coexist. However, regarding the social logic and profit logic, there was evidence of coexistence in all types of companies: larger, smaller, consumer facing, and non-consumer facing. This paper suggested that companies can pursue both goals, profit and sustainability. In other words, it showed that corporations do not have to sacrifice profitability in following global environmental governance.


In the future, I plan to further continue this line of research by focusing on which types of corporations and board composition lead to a better environmental performance. In particular, I am interested in board tenure and CEO duality. The existing literature does not have an overarching conclusion on the impact of board membership on corporate sustainability. Nevertheless, I hypothesize that the power structure of the board has a significant impact on initiatives and practices of SDGs. I plan to hire several research assistants for this project to help with the management of the data. Consequently, this project will provide hands-on research opportunities for students.



To briefly define cyber-physical systems, the concept refers to the technologies or systems that are controlled or monitored by computer-based algorithms and AI. My research on cyber-physical systems focuses on smart technologies in the energy and transportation industries: transactive energy and connected and automated vehicles (CAVs, self-driving vehicles). I analyze how these new and emerging technologies are regulated and governed in international settings and how they contribute to the existing issues of sustainability and equity.


My scholarship has extensively focused on the importance of data reporting and the issues around privacy in the energy and transportation industries. I have a publication in Transportation Research Part A: Policy and Practice (impact factor: 4.0), which examined the safety and liability regulatory challenges of CAVs. With a wider spread of CAV testing, this paper provided safety guidelines for conducting on-road testing of CAVs, and it showed that data reporting and collection are crucial components in ensuring CAV safety. Similarly, my co-author and I have a paper under review in Utilities Policy that directly addressed the issues of digital data in the energy industry. In this paper, my co-author and I assessed privacy regulatory challenges for personal energy consumption data and data management, and we proposed the ways to improve privacy while maintaining the benefits that come with energy automation.


I am also interested in the economic transformations that cyber-physical systems are currently making. I have a paper forthcoming in The Electricity Journal. This study focused on the challenges proposed by transactive energy transitions. Automating load management and energy use in real time, transactive energy is considered as one of the promising ways to reduce energy demand. However, it also creates significant privacy issues around the energy consumption data, which is transmitted to the utilities as often as every five minutes. The findings of this study indicated that the expected energy reduction from the adoption of transactive energy may not be significant. Therefore, to further test this finding, I am currently working on a paper on simulating the energy demand when solar and transactive energy systems are adopted. Using Python and an energy simulation program, GridLAB-D, a group of computer scientists and I are estimating the energy use by creating a virtual community that adopts solar energy and transactive energy. The preliminary findings indicate there is a significant energy reduction in solar transitions but not in transactive energy transitions.


I plan to further develop this area of research by investigating how social scientists can collaborate with computer scientist and engineers in the development of the discourse, responsible innovation. I am currently working on a paper that identifies the challenges proposed by AI and cyber-physical systems in the transportation and energy industries, particularly concerning sustainability, equity, and data security. I plan to further develop this project and quantitatively analyze and simulate the impact of AI technologies in these two industries. Some of the key research questions will be “how much greenhouse gas emission do self-driving cars reduce” and “how do energy automation technologies contribute to equity and what is the simulated value that energy automation brings per household.”




My research also uses extensively utilizes digital data and strives for data-driven communication. I have a minor in quantitative methods, through which I have gained a number of advanced methods training, including but not limited to Bayesian statistics, structural equation modeling, latent growth curve modeling, social network analysis, categorical data analysis, and multilevel analysis. I have used my skills in digital data management and statistical analysis to evaluate economic and environmental issues.


I have used digital media data for a quantitative analysis of solar energy transition in a paper published in a leading sustainability transitions journal, Environmental Innovation and Societal Transitions (SSCI, SCIE, impact factor 8.4). In this paper, I had a group of undergraduate research assistants who helped me to collect relevant news articles in order to assess whether different social and economic actors’ positions on solar energy changed over time. Using inferential statistics, my co-author and I found that investor owned utilities and other relevant social actors tend to change the frequency and framing of their arguments on solar transition depending on political climate.


In the future, I envision merging my two research interests, namely corporate sustainability and AI and new technologies. The literature on CSR is highlighting the importance of smaller vendors, developers, and small and medium size enterprises. Combining this with the literature on AI and new technologies, I plan to investigate how AI is changing the frameworks of corporate sustainability. In this project, I plan to rely on two digital datasets: (1) the data that I have collected, cleaned, and analyzed for my dissertation as the foundational data; and (2) large-scale survey that investigates how smaller companies are investing in AI and cyber-physical systems in comparison to larger companies. For the survey data, the questions will focus not only on AI’s impacts on CSR discourses but also on whether smaller companies’ approaches to AI and cyber-physical systems are different from the larger transnational companies. I predict that smaller companies’ approach to the development of AI and cyber-physical systems are more sustainable and ethical compared to the larger companies, particularly in the energy industry. This project will successfully combine the two main research interests of mine, corporate sustainability and AI and emerging technologies.

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