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Essays on Consumer Heterogeneity and Personalized Discounts in an Online Market
No full textPh.D.This thesis delves into consumer heterogeneity in an online marketplace from an empirical lens on business practices. Furthermore, it evaluates the welfare consequences of employing personalized discounts as a strategic marketing approach.The first chapter utilizes comprehensive consumer clickstream data to construct and refine demand models for smartphones on an e-commerce platform. The narrative unfolds through the exploration of increasing levels of consumer heterogeneity, built upon the conditional logit framework. The last model directly leverages consumer historical clickstreams with a recurrent neural network (RNN), offering detailed individual-level preferences and realistic product substitution patterns. This model excels by outperforming other models in both in-sample and out-of-sample fit.
The second chapter, building upon the demand model established in the first, conducts a counterfactual analysis that enables the issuance of personalized discounts tailored to individual consumer preference parameters. Using a numerically stable algorithm, this chapter presents empirical evidence that highlights the welfare implications. The findings illuminate a mutually beneficial scenario for firm profitability and consumer welfare, in conditional expected terms
Investigating the Neural and Behavioral Processes Involved in Learning Ordered Abstract Symbols
No full textPh.D.Abstract symbols, such as numerals (e.g., 1, 2, 3…), are core components of human thinking, enabling activities such as from keeping track of time and advanced mathematics. Understanding precisely how symbols are acquired and utilized is fundamental to deciphering the functional organization of the human brain. On one hand, symbols may be derived by the learning environment (i.e., the learning context). Alternatively, symbols may be influenced by the context in which they are embedded (i.e., the processing context). Across three studies, the present dissertation aims to disentangle the role of the learning context and processing context in symbolic representations. All three studies use data from an fMRI training dataset, in which participants were taught a sequence of artificial (i.e., novel) ordered symbols using either an associative (i.e., learning the order of the symbols using symbol-to-symbol relationships) or positional (i.e., learning the order of the symbols using the spatial layout) learning paradigm. In study 1, I investigated the learning trajectories and patterns of performance for associative and positional training, with results showing distinct patterns of acquisition and anchoring. In study 2, I evaluated group and task differences in the brain using fMRI data. Results showed that the neural representation of artificial symbols depends on the processing, but not the learning context. Study 3 extends these findings to show the significant role of processing context extends to overlearned numerals. Combined, the findings from this dissertation provide strong evidence for the importance of processing context for representing abstract symbols. Conversely, this research demonstrates the robustness of neural coding to different learning contexts. Overall, this research suggests the human brain is organized in a dynamic manner, able to rapidly activate neural representations specific to the processing context, regardless of symbolic format
Natural Killer Cells in the Pancreatic Ductal Adenocarcinoma Tumor Microenvironment
No full textPh.D.Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer. PDAC’s poor prognosis and resistance to chemo- and immunotherapies are attributed in part to its dense, fibrotic tumor microenvironment (TME), which is known to inhibit immune cell infiltration. Our laboratory recently determined that PDAC patients with higher natural killer (NK) cell content and activation have better survival rates. However, NK cell interactions in the PDAC TME have yet to be fully defined. Here, I used in vitro, in vivo, and multi-omics approaches to characterize NK cell interactions in the PDAC TME. I used spatial proteomics to assess NK cell content, spatial localization, and interactions in previously untreated human PDAC samples and found that active NK cells are present effector cells, both associate and interact with malignant epithelial cells, and that fibroblast-rich, desmoplastic epithelial-ductal regions limit NK cell infiltration in the PDAC TME. I then used single cell RNA sequencing (scRNA-seq) analysis, of a previously published human PDAC scRNA-seq dataset, to infer ligand-receptor (L-R) interactions and identified that the CD44 receptor on NK cells interacts with PDAC extracellular matrix (ECM) components such as collagens, fibronectin (FN1) and laminins expressed by fibroblasts and malignant epithelial cells. This led me to hypothesize that these interactions play roles in regulating NK cell motility in desmoplastic PDAC TMEs. Using 2D and 3D in vitro models, I found that CD44 neutralization significantly increased NK cell invasion through matrix. These findings demonstrate that NK cells are relevant in PDAC, and that targeting CD44-based or other receptors mediating ECM-immune cell interactions, such as LAIR-1, may increase NK cell invasion in the PDAC TME. Lastly, I used spatial transcriptomics to further contextualize gene signatures in CAF-high versus CAF-low epithelial-ductal regions and found that CAF-high epithelial-ductal regions are highly enriched for genes associated with epithelial-to-mesenchymal transition. These findings highlight the heterogeneity of the PDAC TME where further characterization of NK cell interactions in PDAC may identify additional potential therapeutic targets to increase NK cell-mediated anti-tumor immune responses
Knowledge Suppliers: Interest Groups and Local Affordable Housing Policy
No full textPh.D.How do local governments make policy choices? This dissertation advances the theory that elected officials make choices based on a pool of knowledge shaped by the local interest group environment for the relevant policy subsystem. This provides an avenue for influence for local interest groups, who use credibility and knowledge as political resources. I analyze the role of interest groups in producing local affordable housing policy to empirically test this theory. Using IRS data on nonprofit organi- zations, I quantify the strength of six housing interest group categories across 128 cities from 1995 to 2022. I also use a combination of clustering and latent variable methods to describe local affordable housing policy mixes across the same sample. My results show an association between local housing interest group environments and the latent traits of local affordable housing policy mixes. I also analyze data from 31 semi-structured interviews with policymakers and stakeholders in the city of Washington, D.C. to provide evidence for knowledge as an important mechanism by which interest groups influence local policy choices. This dissertation demonstrates the importance of interest groups to local politics and reveals knowledge as a critical political resource
Under One Roof: The Relationship Between Grandparent Co-Residence and Adolescent Mental Health
No full textM.P.P.Multigenerational living is on the rise in the United States, with more children living in multigenerational households than in previous decades. However, the bulk of the literature on multigenerational living focuses on the financial and health impacts for adult generations. The outcomes of children in multigenerational households are not well-documented, despite the fact that 10% of children under 18 resided in multigenerational households in 2023. Mental health outcomes among children and youth are of particular concern in the United States, where the prevalence of depression among adolescents has been increasing at a faster rate than any other age group since 2009. This study investigates the relationship between living in a multigenerational household and depression among children using a sample of 4,834 middle and high school survey respondents from Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Grandparent co-residence is measured in Wave 1 (1994-95) and measures of depression incidence and symptom severity are constructed from Wave 2 (1996) responses to Center for Epidemiologic Studies Depression Scale (CES-D) instrument questions. I estimate the association between living with one or more grandparents and depression incidence and symptomatology using regression analysis in which I control for demographics, parental relationships, household structure, violence exposure and religiosity. I find no statistically significant relationship between grandparent co-residence and depression in this sample, although results indicate an inverse association between strength of parental relationships and depression incidence and symptomatology. Future research should involve a larger sample of longitudinal data in order to further shed light on the relationship between household structure and adolescent mental health
Activation of Estrogen Related Receptor γ by Calcium and Cadmium and the Influence of Estradiol Treatment on Breast Cancer Cell
No full textPh.D.Estrogen related receptor γ (ERRγ) is a metabolic regulator with no identified physiological ligands. This study investigates whether calcium is an ERRγ ligand that mediates the effects of glucagon and whether cadmium disrupts metabolism through ERRγ. In HepG2 cells, treatment with glucagon, calcium, or cadmium re-localized ERRγ to the cell nucleus, recruited ERRγ to estrogen related response elements, and induced the expression of ERRγ regulated genes that was blocked by an ERRγ antagonist. In MCF-7 cells and HEK293T cells transfected with ERRγ, similar treatments induced the expression of the metabolic genes. Mutational analysis identified S303, T429, and E452 in the ligand binding domain as interaction sites. Molecular dynamics simulations showed that calcium induced changes in ERRγ similar to an ERRγ agonist. The results suggest that calcium is a ligand of ERRγ that mediates the effects of glucagon and cadmium, which mimics the effects of calcium, disrupts metabolism through ERRγ. In MCF-7 and HepG2 cells, treatment with calcium also induced the expression of ERRγ regulated lipogenesis genes suggesting that calcium can activate ERRγ and its downstream lipogenesis genes.Recent studies suggest that estrogen treatment inhibits breast cancer cell growth in estrogen deprived patients. This study investigates whether estradiol treatment of estrogen independent breast cancer cells inhibits growth and define the mechanism of inhibition. Treatment of the estrogen independent breast cancer cells MCF-7-2A and MCF-7-RR with estradiol inhibited growth. Treatment with estradiol also increased the expression of calcium channels such as TRPA1 and CACNA1I and increased the concentration of intracellular calcium to concentrations associated with apoptosis. Together, the results suggest that estradiol treatment inhibits estrogen independent breast cancer cell growth, in part, due to an increase in intracellular calcium
At the Intersection of Cultural Cosmopolitanism and Spatial Literary Studies
No full textReview article - Geo-Spatiality in Asian and Oceanic Literature and Culture: Worlding Asia in the
Anthropocene, ed. by Shiuhhuah Serena Chou, Soyoung Kim, and Rob Sean Wilson. Cham, Switzerland: Palgrave Macmillan, 2022, 323 p., ISBN: 978-3-031-04046-7 Spatiality at the Periphery in European Literatures and Visual Arts, ed. by Kathryn Everly, Stefano Giannini, and Karina von Tippelskirch. Cham, Switzerland: Palgrave Macmillan, 2023, 212 p., ISBN: 978-3-031-30311-1 Spatial Literary Studies: Interdisciplinary Approaches to Space, Geography, and the Imagination, ed. by Robert T. Tally Jr. New York: Routledge, 2020, 352 p., ISBN: 978-1-003-05602-7https://doi.org/10.57928/qnq4-5k1
Exploring Variation in Cash Assistance: How Lump Sum versus Regular Payments Relate to Families’ Food Insecurity and Psychological Well-Being
No full textPh.D.Income is one of the strongest predictors of child development, with insufficient funds for basic needs undermining the well-being of children and parents alike. In the context of high child poverty rates in the U.S. and soaring rates of food insecurity during the COVID-19 pandemic, it is essential to explore ways to mitigate the harmful sequelae of low-income. Cash assistance represents one promising solution; however, questions remain regarding the best way to deliver cash to families. A lump sum payment, which delivers a large amount of money at once, could reduce the economic and psychological hardships associated with being low-income immediately, but these effects would likely fade as the money is spent. In contrast, a series of smaller payments delivered regularly may have smaller initial effects on family well-being but would likely last longer. This dissertation investigates how the lump sum, economic stimulus payments and monthly, Child Tax Credit (CTC) payments delivered during the pandemic relate to two indicators of family well-being, food insecurity and psychological distress, in the months following receipt.I find that both forms of cash predicted lower food insecurity; stimulus payments were associated with reductions in severe food insecurity that faded over time, whereas CTC payments inconsistently predicted declines within and across months. I also find that both payment forms were associated with decreases in parents’ psychological distress, though again these findings were more consistent with stimulus checks. Moreover, reductions in parent distress were partially mediated by food insecurity, with more consistent mediation evidence for stimulus checks. Children’s psychological distress, conversely, was largely unaffected by cash receipt and was instead explained by changes in COVID-related restrictions. Overall, these results suggest that a lump sum allows families to address a wider breadth of economic needs, which is psychologically relieving to parents, while regular payments need to be large enough to have consistent longer-term effects. Accordingly, policymakers should consider using lump sums during times of intense economic need and regular payments during times of relative economic stability. In doing so, we can optimally use limited government dollars in ways that maximize the well-being of low-income children and families