Matching Items (394)
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Customers today, are active participants in service experiences. They are more informed about product choices, their preferences and tend to actively influence customer and firm related outcomes. However, differences across customers become a significant challenge for firms trying to ensure that all customers have a `delightful' consumption experience. This dissertation

Customers today, are active participants in service experiences. They are more informed about product choices, their preferences and tend to actively influence customer and firm related outcomes. However, differences across customers become a significant challenge for firms trying to ensure that all customers have a `delightful' consumption experience. This dissertation studies customers as active participants in service experiences and considers three dimensions of customer participation -- in-role performance; extra-role performance-citizenship and elective behavior; and information sharing -- as its focal dependent variables. This study is grounded in services marketing, customer co-production and motivation literatures. The theoretical model proposes that customer behaviors are goal-directed and different consumers will have different reactions to the service quality because they have different assessments of progress towards their goals and (consequently) different levels of participation during the service experience. Customer role clarity and participation behavior will also influence the service experience and firm outcomes. A multi-step process was adopted to test the conceptual model, beginning with qualitative and quantitative pretests; followed by 2 studies (one cross-sectional and other longitudinal in nature). Results prove that customer participation behaviors are influenced by service quality directly and through the mediated path of progress towards goals. Assessment of progress towards goals directly influences customer participation behaviors cross-sectionally. Service quality from one service interaction influences customer in-role performance and information sharing in subsequent service interactions. Information sharing influences service quality in subsequent service interactions. Role-clarity influences in-role and extra-role performance cross-sectionally and influences these behaviors longitudinally only in the early stages of the customer-firm relationship. Due to multi-collinearity, the moderating effect of customer goals on assessment of progress towards goals could not be tested. The study findings contribute to the understanding of customer participation behaviors in service interactions for both academics and managers. It contributes to the literature by examining consumption during the service interaction; considering customers as active participants; explaining differences in customer participation; integrating a forward-looking component (assessment of progress towards goals) and a retrospective component (perceptions of service quality) to explain customer participation behaviors over time; defining and building measures for customer participation behavior.
ContributorsSaxena, Shruti (Author) / Mokwa, Michael (Thesis advisor) / Bitner, Mary Jo (Committee member) / Bolton, Ruth N (Committee member) / Olsen, Grant D (Committee member) / Arizona State University (Publisher)
Created2010
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Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find

Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
Description

In the early years of the National Football League, scouting and roster development resembled the wild west. Drafts were held in hotel ballrooms the day after the last game of regular season college football was played. There was no combine, limited scouting, and no salary cap. Over time, these aspects

In the early years of the National Football League, scouting and roster development resembled the wild west. Drafts were held in hotel ballrooms the day after the last game of regular season college football was played. There was no combine, limited scouting, and no salary cap. Over time, these aspects have changed dramatically, in part due to key figures from Pete Rozelle to Gil Brandt to Bill Belichick. The development and learning from this time period have laid the foundational infrastructure that modern roster construction is based upon. In this modern day, managing a team and putting together a roster involves numerous people, intense scouting, layers of technology, and, critically, the management of the salary cap. Since it was first put into place in 1994, managing the cap has become an essential element of building and sustaining a successful team. The New England Patriots’ mastery of the cap is a large part of what enabled their dynastic run over the past twenty years. While their model has undoubtedly proven to be successful, an opposing model has become increasingly popular and yielded results of its own. Both models center around different distributions of the salary cap, starting with the portion paid to the starting quarterback. The Patriots dynasty was, in part, made possible due to their use of both models over the course of their dominance. Drafting, organizational culture, and coaching are all among the numerous critical factors in determining a team’s success and it becomes difficult to pinpoint the true source of success for any given team. Ultimately, however, effective management of the cap proves to be a force multiplier; it does not guarantee that a team will be successful, but it helps teams that handle the other variables well sustain their success.

ContributorsBolger, William (Author) / Eaton, John (Thesis director) / Mokwa, Michael (Committee member) / Department of Marketing (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Especially during the current COVID-19 pandemic and age of social unrest in the United States, there has been an increasing need for comfort, yet the idea of comfort is quite vague and rarely elaborated upon. To simplify the idea of comfort and communicate the ideas around it effectively, I am

Especially during the current COVID-19 pandemic and age of social unrest in the United States, there has been an increasing need for comfort, yet the idea of comfort is quite vague and rarely elaborated upon. To simplify the idea of comfort and communicate the ideas around it effectively, I am defining comfort as a subset of escapism in which a person escapes to reduce or alleviate feelings of grief or distress. As companies rush to comfort their customers in this current state of uncertainty, marketers are pressed to identify people’s insecurities and comfort them without coming off as insensitive or trite. Current comfort marketing focuses on inspiring nostalgia in its customers, having them recall previous positive experiences or feelings to comfort them. Nostalgic marketing techniques may ease mild grief in some cases, but using them to alleviate severe distress probably will not be as effective, and has contributed to several seemingly out-of-touch “COVID-19 era” commercials.<br/>When addressing comfort, marketers should understand the type and hierarchy of comfort that they are catering to. Not all comforts are equal, in that some comforts make us feel better than others and some do not comfort us at all. A better understanding of how and why comforts change among different individuals, and possibly being able to predict the comfort preference based on a product or service, will help marketers market their goods and services more effectively. By diversifying and specializing comfort marketing using this hierarchical method, marketers will be able to more significantly reach their customers during “uncertain times.”

ContributorsTarpley, Rachel Michelle (Author) / Eaton, John (Thesis director) / Mokwa, Michael (Committee member) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Cardiovascular disease is one of the most deadly outcomes of end stage renal disease. Bioelectrical impedance is a intriguing, yet unproven method of measuring fluid buildup in the heart, and is marketed as a early diagnostic tool for onset of cardiovascular disease. In this study, selenium supplements were given to

Cardiovascular disease is one of the most deadly outcomes of end stage renal disease. Bioelectrical impedance is a intriguing, yet unproven method of measuring fluid buildup in the heart, and is marketed as a early diagnostic tool for onset of cardiovascular disease. In this study, selenium supplements were given to a cohort of dialysis patients in the Phoenix metro area and their fluid tolerance was measured with thoracic biolectrical impedance. BNP was used as a correlate to see if bioelectrical impedance was correlated with heart disease. The study found no correlation between BNP and bioelectrical impedance and thus was not an accurate diagnostic tool in a medical setting.
ContributorsBrown, Patrick Michael (Author) / Johnston, Carol (Thesis director) / Orchinik, Miles (Committee member) / Tingey, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor)
Created2013-05
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The unprecedented rise of terrorist network ISIL has brought the revolutionary Salafi agenda to the forefront of global politics. This thesis provides an analysis of the ideology and an overview of ISIL. The research is comprised of reports on the organization from prominent think-tanks, books analyzing the tenets and thinkers

The unprecedented rise of terrorist network ISIL has brought the revolutionary Salafi agenda to the forefront of global politics. This thesis provides an analysis of the ideology and an overview of ISIL. The research is comprised of reports on the organization from prominent think-tanks, books analyzing the tenets and thinkers of Salafi radicalism and original source material confiscated from ISIL's predecessor al-Qaeda in Iraq (AQI). An international coalition is posited as a solution to the threat as well as the Middle Eastern terrorist threat more broadly. However, the likelihood of such international cooperation is minimal, and the commitment it would require may make it unfeasible.
Created2015-05
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Advancements in mobile technologies have significantly enhanced the capabilities of mobile devices to serve as powerful platforms for sensing, processing, and visualization. Surges in the sensing technology and the abundance of data have enabled the use of these portable devices for real-time data analysis and decision-making in digital signal processing

Advancements in mobile technologies have significantly enhanced the capabilities of mobile devices to serve as powerful platforms for sensing, processing, and visualization. Surges in the sensing technology and the abundance of data have enabled the use of these portable devices for real-time data analysis and decision-making in digital signal processing (DSP) applications. Most of the current efforts in DSP education focus on building tools to facilitate understanding of the mathematical principles. However, there is a disconnect between real-world data processing problems and the material presented in a DSP course. Sophisticated mobile interfaces and apps can potentially play a crucial role in providing a hands-on-experience with modern DSP applications to students. In this work, a new paradigm of DSP learning is explored by building an interactive easy-to-use health monitoring application for use in DSP courses. This is motivated by the increasing commercial interest in employing mobile phones for real-time health monitoring tasks. The idea is to exploit the computational abilities of the Android platform to build m-Health modules with sensor interfaces. In particular, appropriate sensing modalities have been identified, and a suite of software functionalities have been developed. Within the existing framework of the AJDSP app, a graphical programming environment, interfaces to on-board and external sensor hardware have also been developed to acquire and process physiological data. The set of sensor signals that can be monitored include electrocardiogram (ECG), photoplethysmogram (PPG), accelerometer signal, and galvanic skin response (GSR). The proposed m-Health modules can be used to estimate parameters such as heart rate, oxygen saturation, step count, and heart rate variability. A set of laboratory exercises have been designed to demonstrate the use of these modules in DSP courses. The app was evaluated through several workshops involving graduate and undergraduate students in signal processing majors at Arizona State University. The usefulness of the software modules in enhancing student understanding of signals, sensors and DSP systems were analyzed. Student opinions about the app and the proposed m-health modules evidenced the merits of integrating tools for mobile sensing and processing in a DSP curriculum, and familiarizing students with challenges in modern data-driven applications.
ContributorsRajan, Deepta (Author) / Spanias, Andreas (Thesis advisor) / Frakes, David (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human

With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human to provide it some supervisory parameters that modify the degree of autonomy or allocate extra tasks to the robot. In this regard, this thesis presents an approach to include a provision to accept and incorporate such human inputs and modify the navigation functions of the robot accordingly. Concepts such as applying kinematical constraints while planning paths, traversing of unknown areas with an intent of maximizing field of view, performing complex tasks on command etc. have been examined and implemented. The approaches have been tested in Robot Operating System (ROS), using robots such as the iRobot Create, Personal Robotics (PR2) etc. Simulations and experimental demonstrations have proved that this approach is feasible for solving some of the existing problems and that it certainly can pave way to further research for enhancing functionality.
ContributorsVemprala, Sai Hemachandra (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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We apply a Bayesian network-based approach for determining the structure of consumers' brand concept maps, and we further extend this approach in order to provide a precise delineation of the set of cognitive variations of that brand concept map structure which can simultaneously coexist within the data. This methodology can

We apply a Bayesian network-based approach for determining the structure of consumers' brand concept maps, and we further extend this approach in order to provide a precise delineation of the set of cognitive variations of that brand concept map structure which can simultaneously coexist within the data. This methodology can operate with nonlinear as well as linear relationships between the variables, and utilizes simple Likert-style marketing survey data as input. In addition, the method can operate without any a priori hypothesized structures or relations among the brand associations in the model. The resulting brand concept map structures delineate directional (as opposed to simply correlational) relations among the brand associations, and differentiates between the predictive and the diagnostic directions within each link. Further, we determine a Bayesian network-based link strength measure, and apply it to a comparison of the strengths of the connections between different semantic categories of brand association descriptors, as well as between different strategically important drivers of brand differentiation. Finally, we apply a precise form of information propagation through the predictive and diagnostic links within the network in order to evaluate the effect of introducing new information to the brand concept network. This overall methodology operates via a factorization of the joint distribution of the brand association variables via conditional independence properties and an application of the causal Markov condition, and as such, it represents an alternative approach to correlation-based structural determination methods. By using conditional independence as a core structural construct, the methods utilized here are especially well- suited for determining and analyzing asymmetric or directional beliefs about brand or product attributes. This methodology builds on the pioneering Brand Concept Mapping approach of Roedder John et al. (2006). Similar to that approach, the Bayesian network-based method derives the specific link-by-link structure among a brand's associations, and also allows for a precise quantitative determination of the likely effects that manipulation of specific brand associations will have upon other strategically important associations within that brand image. In addition, the method's precise informational semantics and specific structural measures allow for a greater understanding of the structure of these brand associations.
ContributorsBrownstein, Steven Alan (Author) / Reingen, Peter (Thesis advisor) / Kumar, Ajith (Committee member) / Mokwa, Michael (Committee member) / Arizona State University (Publisher)
Created2013
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In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints.

In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints. Developing a framework to enable cooperative behavior adoption and to sustain it for a long period of time is a major challenge. As a part of developing this framework, I am focusing on methods to understand behavior diffusion over time. Facilitating behavior diffusion with resource constraints in a large population is qualitatively different from promoting cooperation in small groups. Previous work in social sciences has derived conditions for sustainable cooperative behavior in small homogeneous groups. However, how groups of individuals having resource constraint co-operate over extended periods of time is not well understood, and is the focus of my thesis. I develop models to analyze behavior diffusion over time through the lens of epidemic models with the condition that individuals have resource constraint. I introduce an epidemic model SVRS ( Susceptible-Volatile-Recovered-Susceptible) to accommodate multiple behavior adoption. I investigate the longitudinal effects of behavior diffusion by varying different properties of an individual such as resources,threshold and cost of behavior adoption. I also consider how behavior adoption of an individual varies with her knowledge of global adoption. I evaluate my models on several synthetic topologies like complete regular graph, preferential attachment and small-world and make some interesting observations. Periodic injection of early adopters can help in boosting the spread of behaviors and sustain it for a longer period of time. Also, behavior propagation for the classical epidemic model SIRS (Susceptible-Infected-Recovered-Susceptible) does not continue for an infinite period of time as per conventional wisdom. One interesting future direction is to investigate how behavior adoption is affected when number of individuals in a network changes. The affects on behavior adoption when availability of behavior changes with time can also be examined.
ContributorsDey, Anindita (Author) / Sundaram, Hari (Thesis advisor) / Turaga, Pavan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013