SUMMER 2024: reflections and updates as an assistant professor--advice vs. reality!

Spring 2024 was a semester of many milestones across all domains of my work: research, service, and teaching.

On research, my first-ever-paper with my advisee and PhD student received a revision opportunity. I submitted two other major revisions that I * actually * thought improved the papers, which is not always the case. On service, I was invited to the editorial review boards (ERB) of two journals in marketing, including the Journal of Marketing whose new efficient review process and focus on publishing novel research I admire. I received my first ever reviewing recognition as one of the best reviewers for the Journal of the Academy of Marketing Science. Importantly, as the PhD coordinator (with Rosanna) at Gies, I got to work with PhD students on their goals more closely, including conversations about what it means to get a PhD in marketing right now. On teaching, I mentored MS teams on their mini research projects with me the entire semester that led to some cool findings! This was one of my best marketing analytics cohort since 2020.

Here are some reflections on each area of my work, and how I continued challenging common-wisdom (often even my own beliefs):

Research with PhD students and mentoring: 

Junior faculty are often given the advice to not work with PhD students, at least not as their primary advisor. It takes too much time.

In hindsight, perhaps this advice is prudent. As most things in my life, I serendipitously was matched with a student who wanted to do empirical work the year I joined Gies. I was the only empirical quant person in the group and so, I advised the student's first and second year papers; these are also the critical stages of a PhD when you can potentially get "kicked out" and so, also the time when I needed to have hard conversations with the student (and with the department). While much of the work with students is research-related, a ton of it is also decoding to them what a PhD and academic life mean, and the philosophy of it. Were there moments I wanted to give up? Sure. Was the first rejection on the paper we submitted hard? Always. Were we able to re-work it majorly and get to a revision opportunity? Gratefully, yes. In hindsight, perhaps I had to project-manage much more than I'd have liked or had ever needed my advisors to do for me. Yet, there were some rewarding moments making it worth it.

The biggest lesson I learned is to have the hard conversations and to work with the student's goals and aspirations, and not your goals and aspirations for them -- or how you would've done things if this was your PhD.

As my colleague Maria Rodas and I often discuss, working with PhD students is a service. As a pre-tenure faculty, your work with PhD students likely won't contribute a lot to your tenure. In fact, it may take up more time and effort (and emotional energy) than you can afford. But it's also a responsibility for us to move our field forward and pass on what we have learned.

Caveat: I should say that I have had to cut down mentoring MS students on research ever since my work with the PhD student scaled up. Time and priorities can be managed. I also cut down my travel from November to April, until all my major revisions were sent back in.

​Research and reviewing (and the synergies)
Junior faculty are often given the advice to review selectively, or only review for journals they hope to be on the ERBs of. It takes too much time.

Reviewing makes you a better researcher in my view. Others can perhaps give a ton more reviewing advice on how to write good reviews, but I will share 3 things that have helped me use reviewing feedback as a way to improve my own research and reviews:

1. Pay attention to the decision letter: The decision letters sent out by the Editor with the AE and review team's feedback can be used to gauge the quality of your review. Ken Wilbur, someone I consider a mentor, once shared with me that the alignment between your recommendation and the editor's decision on a paper should be going up over time. Another good indicator is how often the editor/AE may refer to your comments in their letters, and if they found it useful.
2. Get direct feedback: Sometimes, I have also reached out to the editors for direct feedback and/or thanked them for the opportunity to review. I recently ALSO had an in-person discussion with an AE I reviewed for. Sometimes you can learn very specific things they liked in your review--which is your cue to keep doing it. Not to pat-myself-on-the-back too much but one editor said: "On this one, you caught a critical confound, and gave them a way out. I appreciate your tendencies to be both constructive and critical, and this is very crucial to the development of papers."
3. Gain insights on processes and people: Reviewing is a service to others but also a service to yourself. As an author, you could be better informed now about how various editors and/or AE's write their letters and what's important to them. Otherwise, there is a huge information asymmetry especially starting out as a PhD student and junior faculty. Making the review process (and personalities!) transparent helps. I often wonder why reviewer comments and process cannot be published once the papers are out -- as a way for readers to get insight into what the papers went through. In this aspect, I highly recommend the How I wrote this podcast!

Similarly, I learned a lot from giving others feedback on their papers through tangible and intangible ways including discussing my peer and friend's Shrabastee and her co-authors work on Goodreads at UCSD recently (video, paper).

Teaching (and synergies with research and mentoring)
Junior faculty are often given the advice to not to take on too many new preps. It takes too much time.

While I have been lucky to be able to stack my teaching and get an extended 2-0 teaching load (3-0 is more common), I have never shied away from a new prep. I have taught marketing analytics to undergrads (BADM 361), marketing analytics to masters (BADM 591), two different online iMBA courses (that also have a Coursera version with over 67k learners here and here), and an advanced marketing management course to undergrads (BADM 420) that earned me the Poets&Quants' Best Undergrad Professor honor.

Again, others can offer much more teaching advice and great content (e.g., I often refer to Ken and Dan's course materials here and Avi's quant marketing PhD seminar list here among others), I want to emphasize synergies between research and teaching that have helped me:

1. Make your research known to students: In my marketing analytics course, I discuss causal and predictive models. I often devote time during class to share my (and others') research with my students and allow them to apply class concepts to the research topics. For example, I discussed Brand, Ayelet et al.'s new GPT work in my iMBA session on sources of data. Ayelet was gracious enough to share her slides with me! Similarly, I discussed political consumerism research and retailing research. I even invited Nathan to my class to speak to the students and he graciously agreed to do this.
2. Make your class topical and current: If I read an interesting paper or attend an interesting seminar in a particular week, I bring it to my students. Last month at the Haring Symposium, PK made an excellent presentation on technology's role in marketing. He had several cases on AI and influencer marketing, which were topics I was also covering in my course. Some of my MS students in their course project were studying ChatGPT's impact on youtube content. Again, PK was gracious enough to let me use some of his slides and the students loved examples he had on TikTok's role in product development, e.g., in case of Chipotle creating a Philly Cheesesteak quesadilla.
3. Raise the bar for your students: My last reflection from my teaching this semester is that we need to ask more of our students and to show them how much more they can accomplish compared to what they think they can do. When they say "I can't do it" there is a way to break it down into small chunks of tasks and ask them to get interim feedback from you or their peers to make the bigger goals less overwhelming and more attainable.

Finally, across all domains, it's helped me to SHOW UP to things, be part of a community, and help propel others as you have been helped along the way. 

​Coming soon: Next week, I will post about the exciting projects my MS students put together this semester including framing questions about collecting data to analyze topics like  how do Boeing crashes impact its stock prices and order cancellations, and how Taylor Swift's appearances in NFL games impacts the social media following of Travis Kelce and related influencers. More soon!​