Treasures @ UT Dallas
Welcome to Treasures @ UT Dallas Institutional Repository, established in 2010. Treasures is a resource for our community to showcase, organize, share, and preserve research and scholarship in an Open Access repository.
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Recent Submissions
Analytical and Empirical Analyses of Treatment Optimization and Sequential Bargaining: Applications to Opioid Prescriptions and Real Estate Markets
(2022-08) Gokcinar, Abdullah Halit; Raghunathan, Srinivasan; Cakanyildirim, Metin; Sethi, Suresh P.; Katok, Elena; Wang, Guihua; Simsek, Serdar
Analytic approaches towards individual decision-making construct a significant portion
of the operations management literature. Following its weight in our profession, my doc-
toral studies are built upon decision-making problems surrounding two major contexts;
opioid prescriptions for pain management in healthcare and price negotiations in real es-
tate markets. These studies collaborated with co-authors are presented in this dissertation
over three separate chapters.
Clinical decisions for opioid prescribing are critical since the prescribing too little can
cause patients to suffer from pain whereas prescribing too much may lead to serious
drawbacks such as dependence, addition, overdose, and even death. A chapter in this dis-
sertation is reserved for a published manuscript collaborated with co-authors, in which,
mental trade-offs of clinicians for opioid prescribing decisions are captured in an analyt-
ical pain framework. The framework is flexible to capture both acute and chronic pain
cases, and yields a minimization objective in terms of opioid prescription duration com-
bining the total pain, total discomfort from adverse effects, and the risk of drug inefficacy
due to tolerance or increased sensitivity to pain. Despite non-convexity of the objective,
a closed-form optimal prescription amount is found. Analyses over the optimal solution
show that the role of adverse effects in prescribing decisions is as critical as that of the
pain level. Interestingly, we find that the optimal prescription duration is not necessarily
increasing with the recovery time. We show that not incorporating the risk of tolerance /
increased sensitivity leads to overprescribing. Clinicians’ beliefs on this risk can be cur-
tailed at patient handovers, thus leading to overprescribing. We also show overprescrib-
ing can be mitigated by adaptive treatments. Lastly, using real-life pain and opioid use
data from two sources, we estimate the timing of tolerance / increased pain sensitivity
and discuss the proximity of our model to clinical practice. This paper has a pain man-
agement framework that leads to tractable models. These models can potentially support
balanced opioid prescribing after their validation in a clinical setting. Then, they can
be helpful to policymakers in assessment of prescription policies and of the controversy
around over(under)prescribing.
The other two chapters of the dissertation are reserved for my doctoral studies on price
negotiations in real estate markets, both of which are collaborated with co-authors. The
mainstream adoption of online marketplaces allows large-scale collection of structured
back-and-forth (sequential) bargaining data. Obtaining such data from an online real-
estate marketplace company, we empirically analyze sequential price bargains for houses
between the company (institutional seller) and individual buyers. In each bargain, par-
ties (the seller and buyer) take turns to make concessions until one of them terminates the
bargain by accepting the other’s offer or by exiting. Our analyses of concessions and ter-
minations respectively yield that parties make diminishing and absolutist (independent
of current counteroffer) concessions, whereas they make relativist terminations. These
results are robust when tested separately for different buyer and house types, except that
certain buyer types make absolutist terminations. We explain relativist (resp. absolutist)
acceptances via high (resp. low) sensitivity to the looming deal price, and relativist (resp.
absolutist) exits by scarcity (resp. multitude) of available alternatives. Moreover, we ana-
lytically show that the empirical properties of concessions apply for compromises as well.
These properties of compromises allow us to connect a party’s offers to her reservation
price via a simple offer curve. Randomizing offers around the curves, we obtain max-
imum likelihood estimates of reservation prices and bargaining powers in terms of the
buyer and house types. Providing offer, reservation price, and bargaining power estima-
tions, offer curves could lead to a decision support tool for bargaining decisions.
Stability and Bifurcation Analysis of a Delay Differential Equation Modeling the Human Respiratory System
(2022-08) Sapkota, Nirjal; Turi, Janos; Zhang, Chuanwei; Ramakrishna, Viswanath; Dabkowski, Mieczyslaw K.; Pereira, L. Felipe
The human respiratory system takes oxygen and releases carbon dioxide in air with the
help of lungs and other respiratory organs. Understanding the human respiratory system is
important for many medical conditions. There are many disorders associated with respiratory system that affect a large number of people. Thus studying this system with a good
mathematical model has far-reaching implications.
We study the two state model which describes the balance equation for carbon dioxide and
oxygen. These are nonlinear parameter dependent and because of the transport delay in
the respiratory control system, they are modeled with delay differential equation. So the
dynamics of a two state one delay model are investigated. By choosing the delay as a
parameter, the stability and Hopf bifurcation conditions are obtained. We notice that as the
delay passes through its critical value, the positive equilibrium loses its stability and Hopf
bifurcation occurs. The stable region of the system with delay against the other parameters
and bifurcation diagrams are also plotted. The three dimensional stability chart of the two
state model is constructed. We find that the delay parameter has effect on the stability but
not on the equilibrium state. The explicit derivation of the direction of Hopf bifurcation and
the stability of the bifurcation periodic solutions are determined with the help of normal
form theory and center manifold theorem to delay differential equations.
We also study the five state model with four delays numerically. We investigated the stability
of the system at several delays and stability chart near the measured values are constructed.
Finally, some numerical example and simulations are carried out to confirm the analytical
findings. The numerical simulations verify the theoretical results.
Information Design for Online Platforms
(2022-08) Kucukgul, Can; Ozer, Ozalp; Wang, Shouqiang; Nanda, Vikram; Janakiraman, Ganesh; Simsek, Serdar
In this dissertation we focus on strategic operations problems that arise within the technology-
enhanced platform economy. Particularly, we explore how online platforms such as Amazon,
Google and Facebook can improve their revenue performance by designing and controlling
the information flow in the marketplace. In that, taking the online platforms’ perspective, we
investigate the strategic interactions between online platforms and their market participants in
an information-decentralized environment. We consider novel, profit-maximizing, information
provision policies in this study, both in dynamic and static modeling environments. First, we
uncover an online platform’s optimal information strategy for a time-locked sales campaign,
whereby the platform selectively provides information about historical purchase decisions
to influence future customers’ product evaluation. Next, we study a practically relevant
problem on consumer privacy concerns. Particularly, in a setting where users can choose
whether and what personal preference information to share with the platform, we study how
the platform should design its profit-maximizing recommender system, that also strategically
persuades users about the relevance of recommended items. The characterization of the
platform’s optimal design of its provision policies permit us to draw important managerial
and regulatory insights.
Distributed Integrated Sensing and Communications Systems
(2022-08) Liu, Jiawei; Saquib, Mohammad; Gogate, Vibhav; Al-Dhahir , Naofal; Fonseka, John P.; Torlak, Murat
The continuous scaling up of the carrier frequencies and deployment of wireless communications has propelled the spectrum regulators to allow the use of the spectrum traditionally
reserved for radar (sensing) applications for commercial communications systems. As a
result, in recent years, integrated sensing and communications (ISAC) has emerged as a
promising technology to mitigate spectral congestion and efficiently utilize radio resources.
Prior research on ISAC was largely limited to colocated or centralized systems, where communications, radar, or both employed transmit/receive units placed close to each other.
However, next-generation wireless networks are envisaged to deploy a decentralized resource
management infrastructure and edge-device-centered network paradigms. Similarly, widely
distributed radars are gaining widespread usage because they offer the advantages of spatial
diversity, improved detection of stealth targets, and joint processing.
To this end, we investigate the design and performance evaluation of distributed ISAC systems. We consider a general system comprising a widely distributed multiple-input multiple-
output (MIMO) radar that operates in the same spectrum as a distributed MIMO communications network. A major challenge to co-design such an ISAC system is a unified performance metric for both communications and radar. We address this problem by proposing
a compounded weighted sum of mutual information as an objective to obtain optimized
waveforms, precoders, beamformers, and receive filters jointly for distributed sensing and
communications. Our design problem also includes various practical constraints such as link
budget, quality of service, and peak-to-average power ratios.
We then extend our formulation to in-band full-duplex (IBFD) distributed ISAC to enable
simultaneous uplink, downlink, and radar sensing transmissions. Conventional communications systems are based on either half-duplex (HD) or out-of-band full-duplex transmission for
low-complexity transceiver designs leading to reduced spectral efficiency. On the other hand,
IBFD enables concurrent transmission and reception in a single time/frequency channel to
potentially double the attainable spectral efficiency and throughput and reduce latency.
For distributed wireless systems, synchronization in time and space is a major concern.
The clocks at the radar and communications transmitters are synchronized both offline and
periodically. We use the feedback of the base station via pilot symbols to provide the radar
receivers with the clock times of uplink user equipment. Often, distributed beamforming
(DB) is employed to achieve the desired signal-to-noise and reduce power assumption by
providing a coherent beamforming gain. Further, MIMO radars may also employ DB in the
form of distributed coherent systems, wherein accurate phase synchronization is required
to obtain coherent processing gain. In this research, we show that such synchronization
techniques may also be incorporated in distributed ISAC.
Further, we develop techniques for multi-target localization in a distributed ISAC. In general,
echoes from multiple targets have different time-of-arrivals at different receivers. We solve
this association problem for the ISAC system via a mixed-integer programming framework.
Finally, we devise low-complexity design techniques, which utilize the block-coordinate descent and Barzilai-Borwein algorithms, for the aforementioned scenarios to obtain optimal
design parameters for distributed ISAC simultaneously.
Academic Advising Effects on First-generation Student Outcomes: an Evaluation Using Bourdieu’s Theory of Cultural Capital
(2022-08) Hernandez, Nora A; Harrington , James; Scotch, Richard; Li, Dong; Sabharwal, Meghna; Holmes, Jennifer S.
First-Generation students are often hindered by their limited understanding of how to
successfully navigate post-secondary institutions. They are also known to have limited access to
familial sources of support and guidance needed to succeed in completing a college degree.
Using Bourdieu’s theory of cultural capital, this study explores whether academic advising
contributes to their academic success. Current research on academic advising and cultural
capital theory suggests that institutional agents like academic advisors contribute to student
academic success by transmitting timely and relevant academic information, guidance, and
support. With the use of student-level data, this study explores the effects of academic advising
on the academic outcomes of First-Generation Students as measured by degree completion and
final cumulative GPA. This research expands the use of cultural capital theory to a higher
education setting within the context of the academic advising process. It also contributes to the
literature on educational attainment by providing support for academic advising as an
institutional factor that is associated with better educational outcomes of First-Generation
students. This study concludes with policy and program recommendations for more effective
academic advising programs aimed at First-Generation students, low-income, and traditional
minorities.