Essays on Operations Management
Creators: Ding, Likang
Publisher: name: University of Alberta Library
Year: 2024

<p>This dissertation consists of three separate essays on operations management. Essay 1 is on sports analytics and Essays 2 and 3 are on queueing theory. The abstracts of the three essays are as follows:</p>

<pre><code>Essay 1: The hot-hand theory posits that an athlete who has performed well in the recent past performs better in the present. We use multilevel logistic regression to test this theory for National Hockey League playoff goaltenders, controlling for a variety of shot-related and game-related characteristics. Our data consists of $48,431$ shots for 93 goaltenders in the 2008--2016 playoffs. Using a wide range of shot-based windows to quantify recent save performance, we find no evidence for the hot-hand theory, and some evidence that good recent save performance negatively impacts the next-shot save probability. We use a permutation test to rule out a regression to the mean explanation for our findings.

Essay 2: Recent empirical studies suggest that human behavior in queues causes workload-dependent service times.  We investigate the translation of empirical service times into state-dependent queueing models. To this end, we identify two types of state-dependent models: service time and service rate models.  For each model type, we discuss behavioral mechanisms that are consistent with the model assumptions and we indicate how empirical service time findings can be translated into model input parameters.  We illustrate how translating service times into service rate models can result in invalid service rates, which provides evidence against this model type and the mechanisms associated with it.  For service rate models, we find that mean service times are in general not the inverse of service rates, the directional change in service rates is not always the opposite of the directional change in mean service times, and workload measurement timing can drastically impact mean service time patterns. We provide closed-form equations to convert service times into service rates and vice versa, and find conditions under which monotonic mean service times imply monotonic service rates and vice versa. Our results provide guidelines for researchers to select and specify an appropriate state-dependent queueing model from service time data, and expand the scope of previously published analytical results.

Essay 3: Empiricists are often interested in analyzing drivers causing human behaviors in queues, which requires understanding the data-generating process. They use statistical tools to estimate the causal impact, but a rigorous analysis of the causal structure among variables is often missing. We propose to use causal analysis through Pearl&#39;s Structural Causal Models in analyzing queueing data, combined with knowledge of queueing dynamics. Focusing on two canonical directed acyclic graphs, we use this approach to determine sufficient sets of control variables and construct instrumental variable estimations. We show that including all available control variables is not always appropriate, and similar queueing systems may lead to different model specifications. In addition, we compare the commonly used 2-stage linear least square model with a 2-stage generalized additive model and demonstrate that the former may be overly restrictive.
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