​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!​

The American Marketing Association's (AMA) Retail & Pricing Special Interest Group (RAPSIG) interviewed me about my research and teaching, as their incoming Vice President of Outreach. Read more here: amarapsig.org/?page_id=2324.

For the last two years, I have been tracking and sharing my data in these blog posts for 2022 and 2021. This year, I continued the tradition.

I primarily track two types of data: Work (e.g., hours logged on research, reviewing, teaching) and health (e.g., daily workouts, calories consumed).
 
Recap: In both 2021 and 2022, I spent ~900 hours working on my top 5-6 research projects based on reports generated by an app called Toggl. Of course, all this is based on the projects and hours I am able to track in Toggl subject to some measurement error. I completed over 250 hours of workouts each year, dropping 20+ lbs in 2021 then maintaining in 2022.

How does 2023 look?
@ work: This year, I exceeded my research input of the last two years. I submitted 6 new/revised submissions (relative to 4ish last two years), including a manuscript with a PhD student and a solo-authored paper. I spent 1,000+ hours on my top 4 projects with over 70% of that on one paper (phew!). 

I spent fewer hours on exploring new ideas than I have in the past -- mostly doing so in the Spring semester (no teaching). Unlike last few years, when I had to kill many new ideas, I was able to see this one through -- and moved it into a "real" project bucket to become my 2nd biggest project investment this year. 

Importantly, I noticed that my hours spent on reviewing/writing referee reports doubled compared to last year. That must be a good thing, right? I don't usually report this but will be fun to track over the long-term....

@ the gym: I  increased my focus on weightlifting and was able to achieve new PRs of 200 and 300 lbs on squats and hip thrusts in June (!!) despite several health challenges throughout the year. I incorporated more yoga (although steady state cardio and HIIT both took a hit this year for me). Yoga has been a lovely addition to my life -- and I will not attempt to capture its impact in numbers. 

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As always, quality over quantity; so I cannot end this post without mentioning some of the opportunities for growth this year that are not captured by the data. Many in-depth conversations with peers and colleagues, opportunities to visit other groups (Reichman and Tel Aviv University in Israel, Washington University in St. Louis, Michigan Ross, and INSEAD in France as well as conferences @ UT-Dallas and Temple), and to continue to push past many rejections and risky revisions. Other highlights of the year include my interactions with students, co-chairing our PhD committee, organizing mental health workshops for students, and being part of their convocation experience esp. for the iMBA graduates.

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More stats and how I track my data below:

Bonus: One new interesting comparison I plotted this year was my actual calorie intake relative to the goals I set in the MyFitnessPal app (e.g., typical goals will be between 1600-2000 calories per day). I noticed that I was mostly eating below my goal (!!):

Note: These data are combined from various sources. The project hours data come from Toggl. The workouts data come from 3 different apps - Strong, Trainerize, and my Mindbody app I use to book yoga classes. The calorie data come from MyFitnessPal which I have been using to track my food for over 900 days. Other stuff I track but don't report is my reading lists on Goodreads (made it half way to my reading goal this year) and my Italian lessons on Duolingo (proud 250 days so far). 

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If you find these posts useful, please let me know. Often, the work academics do can appear "black box" to others who can tend to feel that our only job is what we do in the classroom and that we get "summers off" (nice joke). So this is my attempt to share what we do in our job, which is more like an identity or a lifestyle rather than a job.

My plan for 2024? I might move to a more intuitive approach to health and work i.e., less tracking... But we will see. 

It’s time for the academic job market season again. I have been helping our students practice their AMA conference-style 30-minute job interviews.

Here’s some thoughts and general advice I compiled in a Twitter thread recently:

1. Use your time well. The goal is not to present every study and robustness check in this short interview format. Share the main narrative – and enough to spark interest in the topic and demonstrate the rigor and credibility of your findings.
2. State explicitly who you are and why you study what you study using the methods you use, e.g., “I study mobile and digital marketing using causal inference and machine learning. I got interested in these topics even before my PhD when I had a retail and ecommerce startup.”
3. Get to your job market paper (JMP) and research questions relatively early in the presentation. Shouldn’t take more than 1-2 slides to motivate. State your questions clearly.
4. Use the same language and terminology throughout the talk. Keep a consistent narrative. Avoid jargon and surprises. A new term on slide 12 with key results will likely confuse the audience.
5. Know who’s going to be in the audience (most departments tell you), have some idea about their work, and 1-2 specific questions you genuinely want to know about their group/department.
6. Reiterate your pipeline and overall research program in addition to the one JMP you spend most of the time on. Also be prepared to talk about teaching – courses you’ve taught and any innovative highlights, e.g., a new technology you implemented.
7. Follow up thank-you notes. I might be old-fashioned, but I still believe in these. No one is obligated to listen to your research; send an email to thank them individually for their attention and if possible, for the specific comments they gave you during the talk.

Most important, take care of yourself and be kind!

 Last year, I started tracking my data and wrote a blog post about it.

I primarily track two types of data: Work (e.g., hours logged on research, teaching) and health (e.g., daily workouts, calories consumed, body measurements).
 
2021 stats: In 2021, I spent 932 hours working on my top 6 research projects. I completed over 250 hours of workouts and lost over 20 lbs with a 5% drop in body fat.
 
It’s a bit soon to summarize 2022 and the December data aren’t in yet – but I wanted to take an early look at the year (minus December).
 
2022 stats: In 2022, so far, I spent 818 hours working on my top 5 projects with an additional 59 hours exploring 7-8 new ideas of which only 2 have continued and stuck with me. Killed 5 new project ideas this year! Taught at least twice as many classes as 2021.

Of course, all this is based on the projects and hours I am able to track subject to some measurement error. Many "new ideas" never make it to this set. ​So these numbers should be interpreted as lower bounds. 
 
My key trends @ work:

1. Expanding the pie: My total tracked hours of work in 2022 (minus December)  were 30% more (!!!) compared to 2021. I am amazed that I could continue putting in the hours towards research given that my work commitment to my teaching doubled in the 2022 calendar year; I taught 3 courses in the Spring (one carry-forward from 2021) and 2 in the Fall (with Spring 2023 off teaching) + a 4-week iMBA course!
2. Exploitation-exploration trade-off: I spent more time on fewer research projects (still too many IMO). I also more actively used a “walk away” strategy; I was more deliberate about walking away from projects early on. I used two main criteria: Is this a project I want to work on for the next 3-5 years i.e., does it align with my research interests? Is this likely to be impactful i.e., does it have a clear contribution?

 
My key trends with fitness:

With fitness, my main goal this year was maintenance. I continued to keep the 20lbs I lost in 2021 off and maintained my 250 or so workouts with lots of long runs/cardio in the first half of the year and transitioning to mostly strength workouts in the second half. 
 
Overall – what a year it’s been!

​More details below for those who love to see the data as much as I do.