Student Spotlight: Sanaz Kakavand

Sanaz Kakavand is a PhD candidate in Business Technology Management at the University of Calgary, focusing on user data privacy and the economic effects of privacy regulations on online content monetization. 

Her work examines consent-based monetization strategies, including Consent-or-Pay and subscription-based strategies. Additionally, her work examines the economics of blockchain-based platforms, particularly the emerging field of Move-to-Earn (M2E) gaming models. She explores how blockchain-enabled financial incentives, asset ownership, and governance structures influence user motivation and engagement. She is supervised by Dr. Hooman Hidaji.  

When did you start your program at HSB?

I applied to the Haskayne School of Business Ph.D. program in January 2021. At the time, I was not in Calgary. I had recently completed my master’s degree in Iran. I officially began the Ph.D. program in Fall 2021.

What is your Ph.D. dissertation topic?

My Ph.D. dissertation examines how different monetization models influence user behavior, motivation, and welfare across online services. The dissertation consists of three chapters.

The first chapter focuses on blockchain systems and token-based economies. Using STEPN as the empirical setting, I analyze how a Move-to-Earn model, where users buy NFT sneakers, earn tokens by running, and interact within a tokenized economy, shapes motivation and participation. This chapter uses blockchain transaction data to study how users respond to price fluctuations, why motivations shift over time, and how these dynamics contribute to instability in token economies.

The second chapter studies the welfare implications of consent-based monetization used by online publishers under privacy regulations such as the GDPR. I study publishers who must operate under strict privacy rules such as the GDPR. These rules limit the use of personal data, so publishers increasingly rely on several alternative revenue approaches. Some continue with advertising, some use subscription or paywall models, and many now use consent-based payment systems like “Consent-or-Pay,” where users can either accept tracking or pay a fee. In this project, I focus on how these different designs work from an economic point of view: what kind of choice they present to users, and how they affect the publisher’s ability to fund content.

The third chapter is not finalized yet, but it will continue examining data privacy within the context of relevant privacy regulations.

What are some of the insights you have gained about your research goals during your Ph.D. program?

During my Ph.D., I have gained a much clearer understanding of what I want my research to accomplish. The insight I have gained is that my research goals are not only about analyzing models or outcomes, but also about explaining why people react the way they do under different scenarios. 

I have also learned that my broader goal is to produce research that helps publishers, policymakers, and designers understand the unintended consequences of the decisions they make. Whether the system involves tokens, payments, or consent choices, the structure of the model can create incentives that are very different from what was originally intended.

Are there any experiences from your program that stand out for you?

One experience that stands out for me is the process of developing my dissertation direction. Early in the program, I explored several topics without knowing exactly where they would lead. Over time, through discussions with my advisor and a lot of trial and error, I learned how to turn a broad interest into a focused research agenda. That experience taught me how to identify the core questions I truly care about and how to build a coherent dissertation around them. It was a turning point in understanding what kind of researcher I want to become.

Another meaningful experience has been learning how to navigate long, complex projects with patience and confidence. Working on multi-chapter research taught me that progress is rarely linear: sometimes a model has to be rebuilt, a dataset needs a new approach, or an idea has to be reframed entirely. Instead of seeing these moments as setbacks, I began seeing them as part of the research process. This experience helped me develop resilience, better work habits, and a clearer sense of ownership over my work. It also made me more comfortable with uncertainty, which I now see as a natural and even productive part of doing research at the Ph.D. level.