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  • Writer's pictureT. (Ned) Choungprayoon

In Conversation with Simon Blanchard: His Perspectives on Prediction, Mixed Methods, and Peer Review

Updated: May 9

Written By T. (Ned) Choungprayoon, Ph.D. Candidate at Stockholm School of Economics



This may seem like just another interview with an area editor of IJRM for our newsletter readers. But this is not “any other piece of Meet-the-AE” for me. As I am leaving academia and joining the financial services industry (whether you would call it the dark side or not), this might be one of my last articles for the IJRM newsletter, but probably one of the most inspiring interviews I have had. Simon Blanchard is the AE I picked to interview this time. Before interviewing, I typically ask around and gather useful background information. When it comes to Simon, one of my favorite things I heard about him is that “he is awfully cute and a great AE”. After the interview, I nodded to myself “Simon is awfully cute, inspiring, knowledgeable, open-minded and I wish to have him as an AE for whatever paper I may submit.”


Transitioning to the industry and finishing my PhD, I couldn’t help myself ranting about my personal view on the industry obsession over prediction, the difficulty in choosing the right methods for research, and my not-so-great experience with reviewer(s). During the interview, Simon changed my views and turned me from a grumpy graduating PhD to a prospective banker who wants to keep one foot in academia.


“As you progress in your careers, even in the industry, the ability to stay connected to academia can be valuable. Maintaining a foot in is not something I would discourage; just work on things you like or even finish what you start. You can keep your mind fresh, and it can also be really fun.”

- Simon Blanchard -


From Information Systems to Digital Marketing


Simon began his academic journey in information systems and a research master’s in analytics in the early 2000s. Back then, he worked on prediction problems like anomaly detection using models like support vector machines and logical analysis of data (LAD). Later in his PhD, he developed an interest in where information systems meets psychology: psychometrics, in which he tried to understand how survey data can be transformed into models that explain consumer decision-making. Throughout his tenure at Georgetown, his work has moved towards practical applications, from consumer reactions to sales to consumer finance. Today, Simon’s research involves the confluence of digital marketing and financial technology, where he applies his theoretical and methodological expertise.


Simon started as a quant student but loved his CB seminars, so he attempted switching to a consumer behavior student. To the dismay of his incoming advisor, he requested to switch to CB. “I was a PhD student in consumer behavior and developed a paper that ended up in Psychological Science as my first summer project. It focused on methods for understanding psychological processes. But over the years I struggled to find a good behavioral research question worthy of a dissertation. As I still really enjoyed the quantitative aspects, I ended up being fairly pragmatic, returning on the quant side and focusing more on psychometrics”, recalls Simon.


Not just a prediction


When I mentioned industry priority in predictive analytics for decision-making, Simon pointed out that there could be a lot of really interesting questions about prediction. Unlike economics and marketing whose focus is primarily on causation, his background in information and operational research leads him to place a strong emphasis on prediction as well. For instance, his work on predicting consumer financial vulnerability and propensity to share fake news not only helps businesses inform managerial decisions but also helps governments in designing policy intervention.


“If your goal is prediction, say that and show me that you predict better, and then convinced me that the better prediction will enable some kind of policy or marketing outcomes in ways that would not be possible before.” 

- Simon Blanchard -


Mixed Method is great, but what about Mixed Results?


In our conversation, I shared my difficulty during my PhD as an empirical modeler in reconciling results between experimental data and field/observational data. Simon agreed that mixed-method research, while powerful, often introduces complex discrepancies that can be intellectually and methodologically challenging. He stressed the importance of embracing these differences as opportunities for deeper understanding rather than mere complications. He shared that the key to leveraging mixed methods is to clearly define the contribution of each data source. This clarity not only helps in aligning the research with theoretical expectations but also in communicating the findings to a broader audience. Researchers should focus on how each methodological component — whether experimental or observational — complements the other, and how their interplay might reveal new dimensions of a research question that were not previously apparent.

 

“I have this result from the lab, it works really great, and I replicated it a bunch of times. I move to the field, and it doesn't work. How can you think about what's different in a way that helps you identify either why your effects in the lab will never generalize to the field, or if there is anything in the field that you need to do differently to find the effect from the lab." 

- Simon Blanchard -


Simon Blanchard as a Reviewer and an AE


Writing the newsletter about a good reviewer but experiencing not-so-great reviewer(s) myself, I asked Simon what makes him an outstanding reviewer. Simon shared that it is important to be both thorough and constructive to help the AEs and editors make decisions easier. A good review should assume that the paper will be invited for revision, hence, points out issues but also suggests feasible improvements, transforming what could be demotivating feedback into actionable advice. This practice of nurturing rather than merely critiquing not only aids authors but also enhances the quality of submitted academic articles. As an AE, Simon likes to invite junior scholars for the review. This inclusive approach not only diversifies the perspectives within the review process but also provides a learning experience for these junior researchers.

 

“I'll pick more junior reviewers that I know they are going to do a thorough job, and also because I can give them feedback in ways that I can't do at other journals that are double-blinded. So for IJRM, I invite the reviewers and then I can give them feedback on how to do better.." 

- Simon Blanchard -



 

Meet Simon J. Blanchard

 

Simon J. Blanchard

Provost's Distinguished Associate Professor and Dean's Professor at Georgetown University


What drives you to do the research / work you do?

“I do it for two reasons. First, it’s curiosity. I just really want to know, like there's something that makes me wanna know and try to find the answer. Second is the ability to help others achieve goals. I wanna help junior faculty or PhD students get jobs. I find that it is really rewarding and fulfilling knowing that the paper that I work with the junior co-author could help them get tenure.”



If you were not an academic, what would you be?

“If I weren't in academia right now, I would work with a few fintech startups or consumer finance-oriented companies doing head of research in practice. I also really like to work within marketing research and marketing policy development.”


 

This article was written by

T. (Ned) Choungprayoon

Ph.D. Candidate at the Stockholm School of Economics (Sweden)







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