I study how customers respond to operational transparency with parcel delivery data from Cainiao Network, the logistics arm of Alibaba. The sample describes 4.68 million deliveries. Each delivery has between four and ten track-package activities, which customers can check in real time, and a...

ChatGPT rendered my old data science class obsolete, so I created a new version that leverages large language models. This paper chronicles my experiences incorporating ChatGPT into the MBA classroom. I learned that the chatbot does not blur the lines between A and B students, as I only needed...

We study a sample of data from an online platform that matches home cleaners with people who want their homes cleaned. The dataset has a key feature: it reports with high frequency the geographic distances between the cleaners and their appointed residences during both the cleaners' working...

Supply chains typically benefit from economies of scale due to market growth. However, are there any tradeoffs due to rapid market growth? In particular, what is the impact on customer experience? While it is well-established that there are diminishing returns for scale in supply chains in terms...

The bullwhip effect and production smoothing appear antithetical because their empirical tests oppose one another: production variability exceeding sales variability for bullwhip, and vice versa for smoothing. But this is a false dichotomy. We distinguish between the phenomena with a new...

We model how a judge schedules cases as a multi-armed bandit problem. The model indicates that a first-in-first-out (FIFO) scheduling policy is optimal when the case completion hazard rate function is monotonic. But there are two ways to implement FIFO in this context: at the hearing level or at...

We model a single-supplier, 73-store supply chain as a dynamic discrete choice problem. We estimate the model with transaction-level data, spanning 3,251 products and 1,370 days. We find two interrelated phenomena: the bullwhip effect and ration gaming. To establish the bullwhip effect, we show...

Rust (1997) discovered a class of dynamic programs that can be solved in polynomial time with a randomized algorithm. Insulated from the curse of dimensionality, this walled garden of tractable dynamic problems is intriguing, if not useful. Unfortunately, I find that the class is more limited...