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About: About


     Rongen (Sophia) Zhang is an assistant professor in the Information Systems and Business Analytics Department at Baylor University. She earned her Ph.D. in Computer Information Systems at Georgia State University. 
   Her research interests center on the fundamental impact and behavioral implications brought by digital innovations, such as distributed ledger technologies and explainable artificial intelligence. For example, blockchain governance and incentive mechanisms in the context of healthcare, supply chain, and online communities. Her research has been accepted for publication by respected journals, such as Information Systems Journal, the Journal of Medical Internet Research, Frontiers in Neuroinformatics, and ACM Transactions on Management Information Systems. 

    Though she strives to explore emerging phenomena with a methodology-agnostic view, her ongoing projects adopt case studies, econometric analysis, qualitative comparative analysis, and mixed methods approach. 

    She values teaching as an opportunity to inspire and support students' success as wholesome individuals through engaging learning experiences. 



Investigating Decentralization, Incentives, and Configurations of Emerging Blockchain Technology

(Platform Level | PoW)

Drawing from the distributed computing literature and sequential decentralization theory from political science literature, we conceptualize and operationalize three different dimensions of decentralization: physical, development, and pecuniary dimensions, and their effects on blockchain platform growth, which is operationalized as the market capitalization of platforms. Furthermore, we theorize the mechanism of decentralization’s effect through governance activity decentralization (improvement proposal quantity and diversity).


(Platform Level | Delegated PoS)

The objective of this study is to understand how cryptocurrency incentives impact user engagement in blockchain-based online communities. We conduct a longitudinal empirical study at Steemit, a major blockchain-based online community. Drawing on elite theory, we hypothesize power dynamics between “whales” (rich and influential users) and “minnows” (impoverished and inconspicuous users). Moreover, we conceptualize two different kinds of cryptocurrencies: liquid cryptocurrency (which represents a stake in the platform and can be converted to fiat currency immediately, however, does not grant voting rights) and vested cryptocurrency (which represents a voting stake in the platform that can only be withdrawn over a certain period), respectively.

(Platform level | Design choices)

The third essay of my dissertation, Blockchain Governance Design Elements and Generative Governance Engagement: A Configurational Perspective, sheds light on how to configure different design elements to enhance users' generative governance engagement. Given the innate nature of decentralization, it is especially crucial to engage users in governing decentralized platforms. We draw on IT governance, platform governance, and emerging blockchain governance literature to conceptualize equifinal configurations of blockchain design elements. Adopting a fuzzy-set qualitative comparative analysis (fsQCA) approach, we examine the complex relationships between blockchain governance configurations and user generative governance engagement to identify the ideal types of platform design choices. [It is forthcoming in the QCA special issue at ISJ].

About: Dissertation Research
Anchor:Research Pipeline


Refereed Publications and Conference Proceedings

Zhang, R., Ramesh, B. “A Configurational Perspective on Design Elements and User Governance Engagement in Blockchain Platforms” (Forthcoming) Information Systems Journal (ABS 4)

Blockchain technology offers the potential to create an open, decentralized governance structure that empowers stakeholders to participate in decentralized engagement. However, how blockchain platforms configure their design elements to establish and maintain decentralized systems with high levels of user governance engagement requires further research. This study investigates the key design elements of blockchain platforms and their ideal configurations for promoting user governance engagement. Due to the complex and interdependent nature of the design elements, we adopt a configurational perspective accompanied by a fuzzy set qualitative comparative analysis (fsQCA) to uncover complex nonlinear relationships among key conditions that are relevant to decentralized governance. Our research identifies five key design elements that facilitate distributed governance (Access to decision rights, Process visibility, Protocol automation, Incentives for developers/miners, and Incentives for other stakeholders) based on existing blockchain governance literature. We analyze 14 unique blockchain platform cases that adopted on-chain governance. Our fsQCA results reveal three ideal types of blockchain governance configurations that are sufficient for high generative user governance engagement: Centralized incentive model, Impartial incentive model, and Automation-driven model, whereas achieving high evaluative governance engagement requires the presence of all the design elements (Comprehensive model). Also, we found Access to decision rights and Protocol automation are necessary conditions for generative governance engagement, and Access to decision rights together with Process visibility is a combined necessary condition for evaluative governance engagement. Relevant theoretical and practical implications for platform designers as well as methodological implications for applying QCA to emerging IS phenomena are discussed.

Werder, K., Ramesh, B., Zhang, R. (2021) “Establish Data Provenance for Responsible Artificial Intelligence SystemsACM Transactions on Management Information Systems

Zhang R., George A., Kim J., Johnson V., Ramesh B. (2019) "Benefits of Blockchain Initiatives for Value-Based Care: Proposed Framework" Journal of Medical Internet Research;21(9):e13595 

Zhang, R., Park, J., Cirrelio, R.  (2019) The Differential Effects of Cryptocurrency Incentives in Blockchain Social Networks” Proceedings of Pre-ICIS SIGBPS Workshop on Blockchain and Smart Contract

Zhang, R., Park, J., Ciriello, R., and Thatcher, J.B. (2021). “Digital Class Struggle? Incentivizing User Engagement in a Blockchain-based Online Community”  Proceedings of the 3rd Multidisciplinary International Symposium on Disinformation in Open Online Media. The Oxford Internet Institute.

Ellis, C., Zhang, R., Carbajal, D., Miller, R., Calhoun, V., Wang, M. (2021) “Explainable Sleep Stage Classification with Multimodal Electrophysiology Time-series” 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society 

Ellis, C., Carbajal, D., Zhang, R., Miller, R., Calhoun, V., Wang, M. "An Explainable Deep Learning Approach for Multimodal Electrophysiology ClassificationIEEE-EMBS International Conference on Biomedical and Health Informatics (2021)

Ellis, C., Carbajal, D., Zhang, R., Miller R., Calhoun, V., and Wang, D. (2021) “A Gradient-based Approach for Explaining Multimodal Deep Learning Classifiers”, IEEE International Conference on BioInformatics and BioEngineering,

Working Papers

Johnson V, Ramesh B, Kim J, George A, Zhang R. “Value co-creation with double loop learning in blockchain systems: a study in supply chain management

The potential of blockchain technology to achieve strategic goals, such as value-based care, is increasingly being recognized by both researchers and practitioners. However, current research and practices lack comprehensive approaches for evaluating the benefits of blockchain applications. The goal of this study was to develop a framework for holistically assessing the performance of blockchain initiatives in providing value-based care by extending the existing balanced scorecard (BSC) evaluation framework. Based on a review of the literature on value-based health care, blockchain technology, and methods for evaluating initiatives in disruptive technologies, we propose an extended BSC method for holistically evaluating blockchain applications in the provision of value-based health care.

Zhang, R., Park, J., Xue, L. "Digital Class Struggle? Incentivizing User Engagement in a Blockchain-based Online Community"


Working Paper

Park, J., Xue, L., Zhang, R. "Myopic Behaviors in Evaluative Governance Engagement of Cryptocurrency-incentivized Online Community"


Under Review

Final Preparation for Submission 


MIS 4344/5342 Business Intelligence

Business Intelligence (BI) is the discovery of patterns and relationships hidden in large amounts of data. This hands-on course is designed to provide practical analytical skills that can be applied in almost any workplace. The course explores analytical techniques for making intelligent business decisions in data-rich organizations. Specifically, this course introduces the basics of data manipulation, exploratory visualization, and common analytical algorithms using the R programming language. In class, students will learn to use R to analyze a variety of different data sets to address business questions and discover insights to inform strategic and operational decisions.


Over 90 percent of digital data is unstructured – much of which is locked away across a variety of different data stores, in different locations and in varying formats. This course will discuss various issues and challenges in unstructured data management. At the same time, this course will introduce the best practices, underlying principles, and emerging technologies in storing, retrieving, and analyzing unstructured data.

About: Teaching
About: Service
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Practicing Servant Leadership


  • MIS Quarterly

  • Decision Support Systems

  • Information Systems Journal

  • European Journal of Information Systems (EJIS)

  • Journal of Medical Internal Research (JMIR)

  • International Conference on Information Systems (ICIS)


  • MISQ Insider (2021 - Present)

  • Dan Robey's Workshop (2021-2023)



  • Baylor Bible Bear (BBB) Fellowship (2022 - Present)

  • Blockchain Collaborative (2023 - Present)

About: Contact


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"Alone we can do so little; together we can do so much."

                               - Helen Keller

Thanks for connecting!

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