Doctor of Philosophy, The Ohio State University, 2024, Theatre

This dissertation project uses a phenomenological approach to better understand the aural experience of audiences in theatrical productions and to advance the study of the art of sound design beyond the level of technical manuals. The arrangement of the audience within the theatre space is an often-overlooked variable that affects how the audience listens to and contextualizes the performance. In addition to aural framing, this dissertation explores the concepts of noise, silence, aural intimacy, mediatization, immersive audio, audience reception, and the communal experience of listening in thrust, arena, proscenium, and immersive stages.

Committee: Stratos Constantinidis (Advisor); Beth Kattelman (Committee Member); Alex Oliszewski (Committee Member) Subjects: Theater; Theater History; Theater Studies

MFA, Kent State University, 2023, College of Communication and Information

The combination of variable fonts and digital signage presents a unique and practical solution to the various challenges wayfinding systems face. These challenges include issues with readability, monolingual signage, low visibility, minimal readership, material waste, and limited adaptability to environmental conditions and space functionality. Variable fonts, on the other hand, are incredibly versatile and adaptive. They can be easily modified, and their display methods can be customized for any resolution or medium, static or digital. With new infrastructures and spaces emerging, typographic and display technologies are continually evolving. Designers must capitalize on and leverage these advancements to instill a better experience for those interacting with them. This investigation examines the directional attributes of a partially formed typeface to ascertain whether typography alone can aid users in navigating a given space. The findings of this investigation set the foundation for shaping the future of environmental graphic design and type design.

Committee: David Middleton (Advisor); Aoife Mooney (Committee Member); Jessica Barness (Committee Member) Subjects: Communication; Design; Instructional Design; Technology

MDES, University of Cincinnati, 2020, Design, Architecture, Art and Planning: Design

Older adults are increasingly socially isolated as they age, which is detrimental to their overall health and wellbeing. Retirement communities often promote passive forms of leisure that do not contribute to older adults forming social relationships, or feelings of self-esteem and purpose. Museum programing is proven to provide significant social and health benefits for this population— however, access to such programs widely varies due to physical barriers, socioeconomic status, and geographic location. Designers have the opportunity to rethink `leisure' and bridge the gap between museums and isolated older adults. Designers can transform unused spaces in retirement communities into inclusive environments that empower residents to be more engaged in active leisure and lead healthier and more social lives. Using the theoretical framework of co-design, this thesis proposes a set of criteria for how to design portable, multi-sensory interactive tools that support active engagement and bring the museum experience to retirement communities.

Committee: Claudia Rebola Ph.D. (Committee Chair); Ming Tang M.Arch. (Committee Member) Subjects: Design

PhD, University of Cincinnati, 2019, Education, Criminal Justice, and Human Services: Educational Studies

Multilevel study designs are well suited for research in hierarchically structured educational settings. However, this structure, limited resources, and complex theories of teaching and learning limit the ability of educational researchers to feasibly conduct adequate studies. This three-article dissertation increases the feasibility of multilevel studies through improvements in study design and advancements in analytic approaches. The totality of this work expands the capacity of educational researchers to conduct multilevel studies. First, I extend the partial posterior predictive distribution method (p3 method) to test multilevel mediation. A variety of inferential tests are available for single and multilevel mediation but most come with notable limitations that balance tradeoffs between power and Type I error. The p3 method is a contemporary resampling-based composite approach specifically suited for complex null hypotheses. I develop the p3 method and investigate its performance within the context of two-level cluster-randomized multilevel mediation studies. The p3 method performed well relative to other mediation tests because it provides a more judicious balance of the Type I error rate and power. The method serves as a powerful alternative tool for researchers investigating multilevel mediation. Next, I investigate the robustness of statistical power under an optimal sampling framework to misspecified parameter values in cluster-randomized designs with cluster- or individual-level mediators. When planning cluster-randomized studies probing mediation, effective and efficient sample allocation is governed by several parameters. In the design stage, these parameters are typically approximated using information from prior research and these approximations are likely to deviate from the true values eventually realized in the study. The results suggest that estimates of statistical power are robust to misspecified parameter values across a variet (open full item for complete abstract)

Committee: Benjamin Kelcey Ph.D. (Committee Chair); Amy Farley Ph.D. (Committee Member); Jessaca Spybrook Ph.D. (Committee Member); Christopher Swoboda Ph.D. (Committee Member) Subjects: Psychological Tests

Doctor of Philosophy, The Ohio State University, 2018, Psychology

Conditional process models are commonly used in many areas of psychology research as well as research in other academic fields (e.g., marketing, communication, and education). Conditional process models combine mediation analysis and moderation analysis. Mediation analysis, sometimes called process analysis, investigates if an independent variable influences an outcome variable through a specific intermediary variable, sometimes called a mediator. Moderation analysis investigates if the relationship between two variables depends on another. Conditional process models are very popular because they allow us to better understand how the processes we are interested in might vary depending on characteristics of different individuals, situations, and other moderating variables. Methodological developments in conditional process analysis have primarily focused on the analysis of data collected using between-subjects experimental designs or cross-sectional designs. However, another very common design is the two-instance repeated-measures design. A two-instance repeated-measures design is one where each subject is measured twice; once in each of two instances. In the analysis discussed in this dissertation, the factor that differentiates the two repeated measurements is the independent variable of interest. Research on how to statistically test mediation, moderation, and conditional process models in these designs has been minimal. Judd, Kenny, and McClelland (2001) introduced a piecewise method for testing for mediation, reminiscent of the Baron and Kenny causal steps approach for between-participant designs. Montoya and Hayes (2017) took this piecewise approach and translated it to a path-analytic approach, allowing for a quantification of the indirect effect, more sophisticated methods of inference, and the extension to multiple mediator models. Moderation analysis in these designs has been described by Judd, McClelland, and Smith (1996), Judd et al. (2001), and Montoya (open full item for complete abstract)

Committee: Andrew Hayes (Advisor); Jolynn Pek (Committee Member); Paul De Boeck (Committee Member) Subjects: Applied Mathematics; Behavioral Sciences; Biostatistics; Experimental Psychology; Psychology; Quantitative Psychology; Statistics

Doctor of Philosophy, The Ohio State University, 2014, Statistics

In early research, computer experiments were assumed to have been performed by a single powerful, but expensive, computer. With the availability of cheaper, powerful computers, it is now more common to run simulations simultaneously on several computers, and we consider the possibility of using multiple computers. In such cases, computer experiments need to be run in specific batches of runs, one run per computer, with the batch size determined by the number of computers. Various methods to perform these simulations in batches have been proposed. Here, we investigate batch methods that make use of a combination of expected improvement and space filling criteria in order to construct efficient experimental designs for sequentially-adaptive computer experiments problems. These methods select the site with the highest expected improvement, with the rest of the batch sites selected through various methods that balance high expected improvement with being space filling. These methods are tested on various problem types, and the results are compared and contrasted with each other, as well as with one-at-a-time methods and other batch methods in the literature, to determine the effectiveness of the proposed methods for sampling in batches. We conclude that some of the proposed batch methods have advantages over existing methods.

Committee: William Notz (Advisor); Christopher Hans (Committee Member); Matthew Pratola (Committee Member) Subjects: Statistics

MFA, Kent State University, 2014, College of Communication and Information / School of Visual Communication Design

Strategies, systems, experiences and services are part of the new challenges faced today by design students and designers. These challenges include shifting audiences with specific needs due to the broad offer of services and products that often create new needs. These needs include limited resources, sustainable solutions with low environmental impact, and production costs. Besides, there is a great demand for multidisciplinary designers that are able to generate and perform ideas in a co-creation environment. An approach to meeting these challenges can include an open-ended, scaffolded brainstorming process. This might involve design students and designers, instead of advancing towards potential solutions from an unstructured ideation process. Structured methods have many benefits such as collaboration between teammates, ordered and constructive creative sessions as well as increased efficiency. One structured method that has found a place inside classrooms across the world is the Deconstructive discourse, in the areas of philosophy, linguistics, architecture, and others. This paper describes the process, and findings of building a creative framework based on the Deconstructive discourse and its implications in the learning process of design students. Deconstruction provides a structured way of analyzing complex problems. An example of successful application of Deconstructionist theories in design education is the academic work of Cranbrook Academy of Art. In the late 1980 and early 1990s under the direction of Katherine McCoy, Graphic Design students explored the semantics and syntax of their. This demonstrated the importance and the value of the Deconstructive discourse in the studio classroom. As a result, its use as a critical tool it exposed the gap between sign and meaning in the context of culture. This research follows the definition of Deconstruction as a mode of questioning stereotypes, traditional ideas and popular views by comparing them and exploit (open full item for complete abstract)

Committee: Sanda Katila MFA (Advisor); Tameka Ellington PhD (Committee Member); Gretchen Rinnert MFA (Committee Member); Jessica Barness MFA (Committee Member) Subjects: Design; Education; Linguistics

Master of Fine Arts, The Ohio State University, 2011, Industrial, Interior Visual Communication Design

The roles of Designers and Researchers are blending together and each one is trying to work in and improve on the other's domain. This represents an important shift for both fields, but it is fundamental that the next steps are taken by studying and acquiring more knowledge across both fields. Thus, this study aims to adapt Experimental Design as a method to be used by Designers. The use of experiments as a method for Design Research is a relatively unexplored domain within the field of Design that has implications for positive and useful applications. With the application of rigorous methods of experimental study, results can be generalized to broader situations. Scientific methods address concern of bias, replication, and disclosure of the problem and findings. Experimentally-based findings will be well respected not only by Designers, but also by the Scientific community. The experiment consisted of interviews with ninety people who were asked to associate the presented smells with words. Quantitative analysis was done using statistical tests to understand whether people's responses did or did not occur by chance. This helped support, scientifically, the findings. Additionally, qualitative analysis was done by creating different types of visualizations of the data. These visualizations helped to reveal patterns and to create unique “fingerprints” for the smells. The sense of smell was chosen as a medium for the Experimental Design. In Psychology or Neuroscience it is easy to find information about how the sense of smell works. It is a sense that hits us directly through the limbic system, which supports a variety of functions including emotion, behavior and long-term memory. Therefore, our associations with smells are incredibly strong, emotional, and cognitively bonded to memory, which shows opportunities for Design explorations. However, there are not a clear understanding about people's psychological perceptions and associations to the odors. Understanding thi (open full item for complete abstract)

Committee: Peter Chan (Committee Chair); Elizabeth Sanders (Committee Member); Carolina Gill (Committee Member) Subjects: Design

Doctor of Philosophy, The Ohio State University, 2006, Statistics

The problems of combinatorial and geometric equivalence of symmetric factorial experiments, as well as characterization and ranking of two-level Split-plot and Split-lot designs are considered. Two fractional factorial symmetric designs with qualitative factors are said to be combinatorially equivalent if one can be obtained from the other by reordering the runs, relabeling the factors and relabeling factor levels. If the only permissible relabeling of factors levels is reversal of symbols, geometric equivalence is obtained. Existing criteria for detecting combinatorial and geometric equivalence or non-equivalence of symmetric factorial designs are described and evaluated via computer algorithms. Some new necessary and sufficient criteria for both types of equivalence are presented. All results generalize to designs with factors having different number of levels. A characterization method for two-level Split-plot and Split-lot designs based on nonregular fractional factorial designs is given. As an application, a new ranking method is proposed for general two-level Split-plot and Split-lot designs which suggests that existing ranking criteria overlook some aspects of the designs.

Committee: Angela Dean (Advisor) Subjects: Statistics

Doctor of Philosophy, The Ohio State University, 2024, Industrial and Systems Engineering

This dissertation introduces a groundbreaking data-driven approach to optimize the placement and quantity of facilities relevant across various industries and supply chains, such as warehouses, charging stations, and hand sanitizer dispensers. Addressing a critical challenge in operational efficiency, this research seeks to significantly impact industry practices, public health, and environmental sustainability. In our preliminary analysis working with a major provider of Alcohol-Based Hand Sanitizer dispensers, we discovered that up to 80% of dispenser facilities are underutilized, underscoring a widespread issue in resource allocation with profound implications for manufacturers and public health. This dissertation aims to rectify such inefficiencies by proposing the first-ever data-driven methodology for facility placement, rooted in optimally designed experiments and optimally placed facilities. We investigate relevant optimal experimental design, a key component of scientific research that ensures precise data collection while minimizing costs. This research pioneers the development of efficient, optimal experimental design methods for the relevant type of linear models to facility location problems which we argue are generalized linear models that address period-specific response cross-correlations. Time periods in which facilities are configured are termed a type of “whole plot” in that responses at the facilities correlate within the period. Related experimental planning leads to a new type of optimal split designs which account for terms including “network effects” associated with the specific configuration of facilities, including co-location. In our split plot formulation, we also include “market presence” effects relating to the total number of facilities within a local region. The coordinate-exchange algorithm, initially proposed by Meyer and Nachtsheim in 2005, is enhanced to cater to scenarios where the proximity of physical locations influences d (open full item for complete abstract)

Committee: Theodore Allen (Advisor); Susan O'Hara (Committee Member); Samantha Krening (Committee Member) Subjects: Industrial Engineering

PhD, University of Cincinnati, 2023, Engineering and Applied Science: Civil Engineering

The constant growth of population and urbanization in conjunction with the demand for enhanced building services and comfort have led to a substantial increase in energy consumption in the building sector accounting for up to 40% in developed countries. Among the several end uses in buildings, heating, ventilation, and air conditioning (HVAC) systems consume the largest quantity of energy. Therefore, energy efficiency in these systems has become a prime objective for building standards and energy policies. The variable air volume (VAV) systems that are the most commonly used HVAC systems in the USA offer some advantages to achieve energy efficiency in buildings but also have some inherent limitations that can increase the energy consumption and cost of the systems. In response, this dissertation proposes an optimal design and control of the VAV systems that aims to achieve both energy and cost benefits in buildings, taking the existing systems' attributes into account. In this research, (i) a new configuration of dual duct systems named the ‘Dual VAV' system is proposed that has the characteristics of existing single and dual duct VAV systems to utilize their benefits while eliminating the shortcomings, (ii) a new sequence of control is designed for the dual VAV system after several iterations that largely varies from the standard control sequence of the VAV systems for the effective control and operation of the proposed system, (iii) a modeling strategy is developed for dual VAV and three other existing systems for the building simulation purposes as the specific AHU arrangement is not available in any simulation platforms, (iv) a small multizone office building is simulated with the model and control sequence at first and later a large four story multizone office building is simulated for the evaluation of annual heating, cooling and fan power consumption for the proposed system, (v) two optimization strategies for supply air temperature reset and outdoor (open full item for complete abstract)

Committee: Nabil Nassif (Committee Chair); Munir Nazzal Ph.D. (Committee Member); Hazem Elzarka Ph.D. (Committee Member); Pravin Bhiwapurkar Ph.D. (Committee Member) Subjects: Civil Engineering

Master of Science (M.S.), University of Dayton, 2023, Aerospace Engineering

There has been a recent surge in the need for unmanned aerial vehicles (UAVs), drones, and air taxis for a variety of commercial, entertainment, and military applications. New aircraft designs put forth by companies have shown to feature multiple lift producing surfaces and rotors acting in proximity to each other. These configuration choices are primarily informed by the “compactness” requirement in the design. For this reason, configurational choices are being considered that would otherwise not receive attention. Multi-wing configurations or distributed lift systems become a compelling choice in conceptual design of future UAVs and private air vehicles (PAVs) that complements the vertical takeoff and landing capabilities of the design. For multi-wing configurations to be considered in the early conceptual design process, the reliability of traditional lower order aerodynamic methods in predicting these aerodynamic effects must be determined. However, the nature of a highly distributed lift configuration, with 10 or more lifting surfaces in close proximity, does not lend itself to rapid or accurate viscous numerical solution. Moreover, highly distributed lift configurations drive individual lifting surface Reynolds numbers into a range where viscous interactions could have a profound effect on aerodynamic performance. As such, the degree of dependence of wing-wing interactions due to viscous effects could be determined in a first iteration through a reductionist approach. Focusing specifically on the three-dimensional viscous interactions and the aerodynamic forces on the upstream and downstream wings allows for a direct determination of the importance and isolated contribution of these effects. Proximity effects due to wing-wing interactions were experimentally quantified as a function of gap and stagger across a wide range of different relative angles of attack (decalage). The proximity effects and the zone of influence at different gap and stagger locations wer (open full item for complete abstract)

Committee: Sidaard Gunasekaran (Committee Chair); Aaron Altman (Committee Member); Michael Mongin (Committee Member); Markus Rumpfkeil (Committee Member) Subjects: Aerospace Engineering; Engineering; Mechanical Engineering

PhD, University of Cincinnati, 2022, Education, Criminal Justice, and Human Services: Educational Studies

The purpose of this dissertation is to develop principles and strategies for and identify limitations of multisite cluster randomized trials in the context of partially and fully nested designs. In the first study, I develop principles of estimation, sampling variability, and inference for studies that leverage multisite designs within the context of partially nested structures. In the second study, I further advance multisite partially nested designs by developing expressions to predict the statistical power with which these types of designs can detect main effects and their heterogeneity across sites, as well as expressions to identify optimal sampling plans. In the third study, I examine the impact (and sensitivity) of misspecifying the site-by-treatment variance parameter value on the power and efficiency of multisite cluster-randomized designs with fully nested data.

Committee: Benjamin Kelcey Ph.D. (Committee Member); Christopher Swoboda Ph.D. (Committee Member); Youn Seon Lim Ph.D. (Committee Member); Ying Guo Ph.D. (Committee Member) Subjects: Educational Evaluation

Doctor of Philosophy, The Ohio State University, 2022, Psychology

Formal theories of human categorization have been a focus of research in psychology and bolster more than a century's worth of studies. In this process, many theories have been proposed, evaluated, and compared through the development of computational models. An assumption shared among these studies is the existence of a psychological stimulus space that encodes stimuli. Traditionally, the field has modeled this space through low-dimensional artificial stimuli designed for the laboratory setting. While this paradigm grants a high degree of control over experiments, the ecological validity of this assumption is a major point of criticism. After all, stimuli in the natural world are often complex and unlikely to be fully represented in a low-dimensional space. Thus, studies in the field must address this representational gap for results to be generalizable. In the present thesis, we study this representational gap by reexamining the debate between exemplar and prototype models of categorization in an experiment that utilizes highly realistic stimuli and a high-dimensional stimulus space. In doing so, we propose a framework for experimentation based on using Generative Adversarial Networks (GANs) to model the psychological feature space. This framework also showcases several techniques that address the unique challenges of utilizing high-dimensional stimuli that have prevented their adoption in the past. We employed our framework in two experiments comparing prototype and exemplar models in different settings and found a consistent advantage for prototype models contrary to the dominant view in the field. We then theorize an explanation for this advantage by discussing the effects of increasing the dimensionality of the feature space on each type of model, arguing that prototype models are more robust in these scenarios. These observations suggest that previously found advantages for exemplar models might have been an artifact of using low-dimensional stimuli. The (open full item for complete abstract)

Committee: Jay Myung Myung (Advisor); Keith Redmill (Committee Member); Brandon Turner (Committee Member); Mark Pitt (Advisor) Subjects: Cognitive Psychology; Computer Science; Psychobiology

Doctor of Philosophy, The Ohio State University, 2022, Agricultural, Environmental and Developmental Economics

US restaurant industry employs nearly 14 million people and contributes as much as 4% to national GDP. With heightened global attention and effort on promoting sustainability, creating a more sustainable and resilient business model in restaurant operations is become increasingly pertinent in both academic and industry discourse. However, gaps exist in our current understanding of this process. The first chapter utilizes both quantitative and qualitative survey data on back of house food waste to differentiate the causes of waste and amount of waste across different food categories. We then categorize the waste into actionable and non-actionable waste to provide practical recommendations for food waste reduction interventions. We find 40% of back of respondents reported a non-actionable cause for house food waste and attributed 50% of total back of house food waste to such cause. With the intention to allow practitioners to prioritize on actionable waste, we also propose several practices aiming to control the non-actionable portion of restaurant food waste. Technologies such as food waste management systems have been introduced in recent years and proven effective in reducing back of house food waste. It is important to investigate how restaurateurs value such systems. The second chapter examines the way independent restauranteurs make trade-offs between implementation cost and a variety of attributes associated with such food waste management systems. This is achieved by analyzing data obtained from a discrete choice experiment (DCE) administered in a nationally distributed online survey. The results suggest that most restaurateurs see value is such management systems. The cost of operating the system is negatively associated with restaurateur's willingness to adopt. Also, large variation in restaurateurs' preferences exists for various non-price attributes. This chapter offers a case demonstrating that restaurateur-specific opinions matter for the endorsement (open full item for complete abstract)

Committee: Wuyang Hu (Advisor); Brian Roe (Advisor); Wuyang Hu (Committee Chair); Frederick Michel (Other); Brent Sohngen (Committee Member); Andrew Hanks (Committee Member); Brian Roe (Committee Co-Chair) Subjects: Behavioral Sciences; Economics

PhD, University of Cincinnati, 2022, Engineering and Applied Science: Mechanical Engineering

The characterization of the viscoelastic response of polymers and soft tissue is significant in several areas like biomedical engineering and material processing. Computational modeling of and experimentation with such rheological materials are complex due to their time- and temperature-dependent nature. There is a critical need for reliable computational models that account for the inherent variability in experimental data. Rheological constitutive models characterize the viscoelastic response of materials using discrete or continuous relaxation spectra. The spectra are characterized by parameters (time constants, elastic and shear moduli) representing the relaxation process, and contain information about the molecular structure of polymers and soft materials. We can estimate the viscoelastic model parameters from stress relaxation experiments, but several challenges exist. For discrete spectra, a challenge is a finite number of model parameters. In the case of continuous spectra, challenges include ill-posedness, the curse of dimensionality, parameter identifiability, as well as correlated and heteroscedastic data. For modeling temperature-dependent material behavior, the challenges include model complexity and limited availability of experimental data. To address these challenges, we aim to develop rigorous stochastic approaches. Bayesian methods offer a rigorous stochastic foundation and have gained significant interest due to the increasing availability of computational resources. The specific aims of this work are: Aim 1: Employ an information-theoretic approach, namely Fisher information, to develop criteria for evaluating experimental data to obtain an ideal range of parameters. Aim 2: Develop a hierarchical Bayesian (HB) approach to L2 regularization for inferring continuous spectra while considering heteroscedasticity. This approach applies to the general linear inverse problems involving regularization, and is not limited to (open full item for complete abstract)

Committee: Kumar Vemaganti Ph.D. (Committee Member); Gowtham Atluri Ph.D. (Committee Member); Sandeep Madireddy Ph.D. (Committee Member); Manish Kumar Ph.D. (Committee Member); Woo Kyun Kim Ph.D. (Committee Member) Subjects: Mechanical Engineering

Master of Science, The Ohio State University, 2022, Mechanical Engineering

The major shift in the mobility industry towards electric vehicles requires the development of safer energy storage systems (ESS). Li-ion ESS has been at the forefront of automotive, aerospace, and stationary ESS for power backup applications, albeit it suffers from thermal instability issues, which prompts investigation into the thermal behavior of these systems. Thermal modeling of Li-ion batteries is an essential practice to understand the mechanisms behind heat generation and distribution, and cognizance of the thermal behavior is crucial to developing safer Li-ion batteries and optimal thermal management solutions. However, one of the most significant challenges associated with developing thermal models is parameter identification due to the unique layered construction of a Li-ion cell. The simplest thermal model for a Li-ion battery can require the identification of ten or more unknown parameters. The accuracy of the model depends on the accuracy of the parameter identification process. Thermal models also require electrical models to predict heat generation in the cell, which requires a plethora of unknown parameters to be identified to simulate the electrical behavior of the cell. The overall accuracy of predicted temperature and thermal distribution is dependent on the accuracy of both the electrical and thermal models. The parameter identification for thermal modeling requires extensive experimentation, with its challenges, such as heat propagation to the experimental setup and power cables connecting the cell to the battery cycler. The goal of the research presented in this thesis is to develop an innovative experimental setup, test procedures, and calibration strategy for a lumped-parameter thermal model with the aim of accurately estimating the temperature of the cell and the cell tabs. The research aims at developing a test bench capable of minimizing the heat transfer from the cell to the power cables and the ambient. Two thermal exper (open full item for complete abstract)

Committee: Marcello Canova (Advisor); Kim Jung Hyun (Committee Member); Matilde D’Arpino (Advisor) Subjects: Mechanical Engineering

Doctor of Philosophy, The Ohio State University, 2022, Consumer Sciences

Solo dining is on the rise, yet the existing hospitality and tourism literature offers little guidance regarding how to market solo diners. By conducting three studies, the current dissertation focuses on three marketing strategies—service robots, consumption rituals, and nostalgic ads—and examines how they affect solo (vs. group) diners' decision-making. Study 1 focuses on the online booking context and examines how service robot type (i.e., non-humanoid vs. humanoid) influences solo (vs. group) diners' responses, including attitude toward the restaurant, visit intention, and e-WOM intention. Results from Study 1 suggest that group diners exhibit more favorable attitudes and behavioral intentions toward restaurants featuring humanoid (vs. non-humanoid) service robots, whereas solo diners respond more favorably to restaurants featuring non-humanoid (vs. humanoid) service robots. Furthermore, anticipated psychological comfort is revealed as driver of the congruency effects between robot type and diner type. Study 2 focuses on the tourism dining context and investigates the impact of consumption rituals (i.e., absence vs. presence) on solo (vs. group) diners' responses, including food evaluation and purchase intention. Results from Study 2 show that for group diners who travel with others, the presence (vs. absence) of consumption rituals leads to more favorable food evaluation and greater purchase intention, whereas the presence (vs. absence) of consumption rituals backfires and results in less favorable responses among solo diners who travel alone. Furthermore, anticipated pleasure is identified as the underlying mechanism explaining these effects. Study 3 focuses on the restaurant advertising context and explores how advertisement type (i.e., nostalgic vs. non-nostalgic) influences solo (vs. group) diners' responses, including food evaluation and purchase intention. Results from Study 3 show that for group diners, the nostalgic (vs. non-nostalgic) ad gen (open full item for complete abstract)

Committee: Stephanie Q Liu (Advisor); Jay Kandampully (Committee Member); Caezilia Loibl (Committee Member); Laurie Wu (Committee Member) Subjects: Experimental Psychology; Marketing

Doctor of Philosophy, University of Toledo, 2021, Educational Research and Measurements

The present study explores the use of Student Evaluations of Teaching (SETs) within higher education institutions. In particular, bias associated with student ratings was explored in several ways. An experimental study design, using an advanced measurement framework was employed. Eight faculty participants from four ethnic-identity groups, and two gender-identity groups offered short 3-minute lectures to students within a fictitious “Great Cities of the Americas” course. Students were asked to watch each and complete both a cognitive quiz and a uniquely developed SET. Three research questions were asked: (1) Are student ratings of instructional effectiveness influenced by the perceived gender- or ethnic-identity of the instructor under experimental conditions?, (2) Are student ratings of items related to instructional effectiveness subject to Differential Item Functioning (DIF) under experimental conditions?, and (3) Can a Multi-faceted Rasch Modeling approach account and adjust for biases in SETs detected relative to faculty characteristics? The Rasch Rating Scale model (RSM), Multi-faceted Rasch model (MFRM), Differential Item Functioning (DIF) analyses, and inferential statistical tests were used to answer the three research questions.   Results from the study demonstrated significant differences based on the gender- and ethnic-identity of faculty. Female-identifying were rated significantly higher than male-identifying faculty and White-identifying faculty were rated significantly higher than the non-White-identifying faculty. Among the non-White faculty, Asian faculty were rated significantly lower than the Black and Latinx faculty. MFRM analyses and statistical testing showed that this difference was not explained by student variables including student gender, ethnicity, location, age, college, nationality, and school year. Conclusions suggest that SETs as they currently exist are at best inadequate representations of effectiveness, and at worse, biased and in (open full item for complete abstract)

Committee: Gregory Stone (Committee Chair); Noela Haughton (Committee Member); Snejana Slantcheva- Durst (Committee Member); Toni Sondergeld (Committee Member) Subjects: Educational Evaluation; Gender; Higher Education

Doctor of Philosophy, The Ohio State University, 2021, Consumer Sciences

Recently, consumers are becoming more health-conscious and increasingly seeking healthful menu options. To understand consumers' decision-making about healthy food choices, the current dissertation explores marketing strategies that effectively promote healthy food within restaurant settings in a series of three experimental studies. Study 1 used a between-subjects experiment to investigate how expressive aesthetics influence consumer evaluations of organic food (vs. conventional food). The findings reveal that the expressive aesthetics strategy is effective for marketing conventional, non-organic food; however, such a strategy decreases consumers' purchase intention when the food is described as organic. Furthermore, an investigation into the underlying psychological mechanism uncovers that anticipated pleasure and food temptation serially mediate the impact of expressive aesthetics and food type on purchase intention. Study 2 investigated the effectiveness of assertive ad language in persuading consumers to purchase organic food. The findings indicate that restaurants advertise organic food with assertive language will lead to more favorable responses, but not conventional food. In addition, perceived brand competence is the psychological mechanism that mediates the effect of ad language on consumers' purchase intention. Study 3 further explored how pricing strategy influences consumer purchase intention toward small plates. The findings demonstrate that small plates using nonrounded pricing will lead to a higher level of purchase intention, and such iii an effect is attenuated for regular-sized food. Price fairness is the underlying mechanism explaining the pricing strategy for small plates. Theoretical and managerial contributions are discussed.

Committee: Qing Liu (Advisor); Jay Kandampully (Committee Member); Yunzhang Zhu (Committee Member); Milos Bujisic (Committee Member) Subjects: Behavioral Sciences; Experiments; Marketing