McCoy College of Business

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    Deep Vision for Breast Cancer Classification and Segmentation
    (Multidisciplinary Digital Publishing Institute, 2021-10) Fulton, Lawrence V.; McLeod, Alexander; Dolezel, Diane; Bastian, Nathaniel; Fulton, Christopher P.
    (1) Background: Female breast cancer diagnoses odds have increased from 11:1 in 1975 to 8:1 today. Mammography false positive rates (FPR) are associated with overdiagnoses and overtreatment, while false negative rates (FNR) increase morbidity and mortality. (2) Methods: Deep vision supervised learning classifies 299 × 299 pixel de-noised mammography images as negative or non-negative using models built on 55,890 pre-processed training images and applied to 15,364 unseen test images. A small image representation from the fitted training model is returned to evaluate the portion of the loss function gradient with respect to the image that maximizes the classification probability. This gradient is then re-mapped back to the original images, highlighting the areas of the original image that are most influential for classification (perhaps masses or boundary areas). (3) Results: initial classification results were 97% accurate, 99% specific, and 83% sensitive. Gradient techniques for unsupervised region of interest mapping identified areas most associated with the classification results clearly on positive mammograms and might be used to support clinician analysis. (4) Conclusions: deep vision techniques hold promise for addressing the overdiagnoses and treatment, underdiagnoses, and automated region of interest identification on mammography.
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    Increasing Access to Care for the Underserved: Voices of Riders, Drivers, and Staff of a Rural Transportation Program
    (Multidisciplinary Digital Publishing Institute, 2022-10) Schwartz, Abby; Richman, Alice; Scott, Mallary; Liu, Haiyong; White, Weyling; Doherty, Caroline
    The qualitative data presented in this paper was part of a larger concurrent mixed methods study evaluating the effectiveness of a transportation program (Project TRIP) for low-income residents in rural eastern North Carolina. Twenty stakeholders involved in TRIP were interviewed, including riders (n = 12) of which 83% were over 50 years old, program staff including the program coordinator and 5 case managers (n = 6), and transportation providers (n = 2). Due to the COVID-19 pandemic, interviews were completed by phone with each participant. Themes from the qualitative data included the: (1) Emotional, health, & financial impacts of TRIP, (2) Changes that should be implemented into TRIP when replicating the program, and (3) Unique aspects of how TRIP operates that could inform other rural transportation programs. Thematic analysis was used to analyze the transcript data. The findings are couched in the context of how TRIP potentially defrays the impacts of cumulative disadvantage that residents experience over the life course by increasing access to healthcare.
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    Waves of Disruption: Professional Selling
    (2022-01) West, Vicki
    This is an open access text on professional selling and new sales technology.
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    Predictors of Business Return in New Orleans after Hurricane Katrina
    (Public Library of Science, 2012-10) Lam, Nina S. N.; Arenas, Helbert; Pace, R. Kelley; LeSage, James P.; Campanella, Richard
    We analyzed the business reopening process in New Orleans after Hurricane Katrina, which hit the region on August 29, 2005, to better understand what the major predictors were and how their impacts changed through time. A telephone survey of businesses in New Orleans was conducted in October 2007, 26 months after Hurricane Katrina. The data were analyzed using a modified spatial probit regression model to evaluate the importance of each predictor variable through time. The results suggest that the two most important reopening predictors throughout all time periods were the flood depth at the business location and business size as represented by its wages in a logarithmic form. Flood depth was a significant negative predictor and had the largest marginal effects on the reopening probabilities. Smaller businesses had lower reopening probabilities than larger ones. However, the nonlinear response of business size to the reopening probability suggests that recovery aid would be most effective for smaller businesses than for larger ones. The spatial spillovers effect was a significant positive predictor but only for the first nine months. The findings show clearly that flood protection is the overarching issue for New Orleans. A flood protection plan that reduces the vulnerability and length of flooding would be the first and foremost step to mitigate the negative effects from climate-related hazards and enable speedy recovery. The findings cast doubt on the current coastal protection efforts and add to the current debate of whether coastal Louisiana will be sustainable or too costly to protect from further land loss and flooding given the threat of sea-level rise. Finally, a plan to help small businesses to return would also be an effective strategy for recovery, and the temporal window of opportunity that generates the greatest impacts would be the first 6∼9 months after the disaster.
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    Business Return in New Orleans: Decision Making Amid Post-Katrina Uncertainty
    (Public Library of Science, 2009-08) Lam, Nina S. N.; Pace, R. Kelley; Campanella, Richard; LeSage, James P.; Arenas, Helbert
    Background: Empirical observations on how businesses respond after a major catastrophe are rare, especially for a catastrophe as great as Hurricane Katrina, which hit New Orleans, Louisiana on August 29, 2005. We analyzed repeated telephone surveys of New Orleans businesses conducted in December 2005, June 2006, and October 2007 to understand factors that influenced decisions to re-open amid post-disaster uncertainty. Methodology/Principal Findings: Businesses in the group of professional, scientific, and technical services reopened the fastest in the near term, but differences in the rate of reopening for businesses stratified by type became indistinguishable in the longer term (around two years later). A reopening rate of 65% was found for all businesses by October 2007. Discriminant analysis showed significant differences in responses reflecting their attitudes about important factors between businesses that reopened and those that did not. Businesses that remained closed at the time of our third survey (two years after Katrina) ranked levee protection as the top concern immediately after Katrina, but damage to their premises and financing became major concerns in subsequent months reflected in the later surveys. For businesses that had opened (at the time of our third survey), infrastructure protection including levee, utility, and communications were the main concerns mentioned in surveys up to the third survey, when the issue of crime became their top concern. Conclusions/Significance: These findings underscore the need to have public policy and emergency plans in place prior to the actual disaster, such as infrastructure protection, so that the policy can be applied in a timely manner before business decisions to return or close are made. Our survey results, which include responses from both open and closed businesses, overcome the “survivorship bias” problem and provide empirical observations that should be useful to improve micro-level spatial economic modeling of factors that influence business return decisions.
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    A Heuristic Storage Location Assignment Based on Frequent Itemset Classes to Improve Order Picking Operations
    (Multidisciplinary Digital Publishing Institute, 2021-02) Li, Yue; Mendez-Mediavilla, Francis A.; Temponi, Cecilia; Kim, Junwoo; Jimenez, Jesus
    Most large distribution centers’ order picking processes are highly labor-intensive. Increasing the efficiency of order picking allows these facilities to move higher volumes of products. The application of data mining in distribution centers has the capability of generating efficiency improvements, mainly if these techniques are used to analyze the large amount of data generated by orders received by distribution centers and determine correlations in ordering patterns. This paper proposes a heuristic method to optimize the order picking distance based on frequent itemset grouping and nonuniform product weights. The proposed heuristic uses association rule mining (ARM) to create families of products based on the similarities between the stock keeping units (SKUs). SKUs with higher similarities are located near the rest of the members of the family. This heuristic is applied to a numerical case using data obtained from a real distribution center in the food retail industry. The experiment results show that data mining-driven developed layouts can reduce the traveling distance required to pick orders.
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    The Effect Mechanism of Tie Strength of Supply Networks on Risk Sharing: Based on the Empirical Data of China’s Automobile Manufacturing Industry
    (Multidisciplinary Digital Publishing Institute, 2021-04) Ma, Lina; Wan, Min; Du, Yushen
    Based on the research perspective of the cooperation risk and opportunistic risk between supply network enterprises, this article investigates the mechanism of how tie strength between manufacturers and suppliers influences risk sharing among enterprises from two dimensions of tie strength: structural strength and relational strength. In particular, we introduce how asymmetry of dependence moderates the relationship between tie strength and risk sharing. We surveyed China’s domestic auto OEMs and their first-tier suppliers in China through 260 questionnaires and used a hierarchical regression model as a research method to carry out the empirical analysis and test. We found an inverted U-shaped relationship between tie strength and risk sharing among enterprises, and asymmetry of dependence has a significant negative adjustment function on relational strength of the tie and risk-sharing relationship, while there is no significant adjustment function on the structural strength of it. Our findings suggest that keeping moderate tie strength among enterprises is conducive to achieving risk sharing. Moreover, trust and reciprocity is inhibitory regarding the adjustment effect of asymmetry of the dependence influencing relational strength and risk-sharing relationship. However, the structural strength and risk-sharing relationship are not interfered with by the adjustment function of asymmetry of dependence; that is, structural strength plays a decisive role in risk sharing.
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    Has China’s Belt and Road Initiative Intensified Bilateral Trade Links between China and the Involved Countries?
    (Multidisciplinary Digital Publishing Institute, 2020-08) Yu, Chunjiao; Zhang, Ren; An, Lian; Yu, Zhixing
    The Belt and Road Initiative (BRI) is designed to intensify reciprocal trade preferentiality between China and the Belt-Road countries. However, there has been little research empirically examining the policy effects on the trade links between China and the involved countries. This paper attempts to evaluate the BRI effects quantitatively by constructing a new bilateral revealed trade preference index to measure the bilateral trade preferentiality between China and its 114 trading partners. Using a difference in differences model, we show that the trade of China with the Belt-Road countries has become more preferentially linked since the implementation of the BRI. In particular, the bilateral revealed trade preference index between China and the Belt-Road countries has grown approximately 8% faster than has that with the non-Belt-Road countries. We further show that the BRI effects are heterogeneous across different regions. The bilateral trade links have been more significantly intensified in the regions of the China–Indochina Peninsula Economic Corridor, the China–Pakistan Economic Corridor, the China–Central Asia–West Asia Economic Corridor and the Bangladesh–China–India–Myanmar Economic Corridor. The findings strongly indicate that BRI has been acting as a catalyst for intensifying bilateral trade preferentiality between China and the Belt-Road countries.
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    Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence
    (Multidisciplinary Digital Publishing Institute, 2019-07) Lee, Jaehun; Suh, Taewon; Roy, Daniel; Baucus, Melissa
    Artificial intelligence (AI) has been altering industries as evidenced by Airbnb, Uber and other companies that have embraced its use to implement innovative new business models. Yet we may not fully understand how this emerging and rapidly advancing technology influences business model innovation. While many companies are being made vulnerable to new competitors equipped with AI technology, this study attempts to focus on the proactive side of the use of AI technology to drive business model innovation. Describing AI technology as the catalyst of business model innovation, this study sheds light on contingent factors shaping business model innovation initiated by the emerging technology. This study first provides a brief overview of AI, current issues being tackled in developing AI and explains how it transforms business models. Our case study of two companies that innovated their business models using AI shows its potential impact. We also discuss how executives can create an innovative AI-based culture, which rephrases the process of AI-based business model innovation. Companies that successfully capitalize on AI can create disruptive innovation through their new business models and processes, enabling them to potentially transform the global competitive landscape.
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    Positive Disposition in the Prediction of Strategic Independence among Millennials
    (Multidisciplinary Digital Publishing Institute, 2017-11) Konopaske, Robert; Kirby, Eric G.; Kirby, Susan L.
    Research on the dispositional traits of Millennials (born in 1980–2000) finds that this generation, compared to earlier generations, tends to be more narcissistic, hold themselves in higher regard and feel more entitled to rewards. The purpose of this intragenerational study is to counter balance extant research by exploring how the positive dispositional traits of proactive personality, core self-evaluation, grit and self-control predict strategic independence in a sample of 311 young adults. Strategic independence is a composite variable measuring a person’s tendency to make plans and achieve long-term goals. A confirmatory factor analysis and hierarchical regression found evidence of discriminant validity across the scales and that three of the four independent variables were statistically significant and positive predictors of strategic independence in the study. The paper discusses research and practical implications, strengths and limitations and areas for future research.
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    The Biggest Myth in Spatial Econometrics
    (Multidisciplinary Digital Publishing Institute, 2014-12) LeSage, James P.; Pace, R. Kelley
    There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based on the true partial derivatives for a well-specified spatial regression model. We conclude that this myth may have arisen from past applied work that incorrectly interpreted the model coefficients as if they were partial derivatives, or from use of misspecified models.
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    Monetary Transfers in the U.S.: How Efficient Are Tax Rebates?
    (Multidisciplinary Digital Publishing Institute, 2013-11) Vacaflores, Diego E.
    Recent debate on the effectiveness of tax rebates has concentrated on the degree to which they can affect economic activity, which depends on the methodology, the state of the economy, and the underlying assumptions. A better approach to assess the effectiveness of these monetary transfers is by comparing this method to alternative policies—like the traditional monetary injections through the financial intermediaries. A limited participation model calibrated to the U.S. economy is used to show that the higher the proportion of the monetary injection channeled through the consumers—instead of banks—leads to a less vigorous recovery of output but softens the detrimental effect on the utility of the representative household from the inherent inflationary pressure. This result is robust to the relative importance of the injection (utilization of resources) and alternative utility functions.
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    Women's Reasons for Leaving the Engineering Field
    (Frontiers Media, 2017-06) Fouad, Nadya A.; Chang, Wen-Hsin; Wan, Min; Singh, Romila
    Among the different Science, Technology, Engineering, and Math fields, engineering continues to have one of the highest rates of attrition (Hewlett et al., 2008). The turnover rate for women engineers from engineering fields is even higher than for men (Frehill, 2010). Despite increased efforts from researchers, there are still large gaps in our understanding of the reasons that women leave engineering. This study aims to address this gap by examining the reasons why women leave engineering. Specifically, we analyze the reasons for departure given by national sample of 1,464 women engineers who left the profession after having worked in the engineering field. We applied a person-environment fit theoretical lens, in particular, the Theory of Work Adjustment (TWA) (Dawis and Lofquist, 1984) to understand and categorize the reasons for leaving the engineering field. According to the TWA, occupations have different "reinforcer patterns," reflected in six occupational values, and a mismatch between the reinforcers provided by the work environment and individuals' needs may trigger departure from the environment. Given the paucity of literature in this area, we posed research questions to explore the reinforcer pattern of values implicated in women's decisions to leave the engineering field. We used qualitative analyses to understand, categorize, and code the 1,863 statements that offered a glimpse into the myriad reasons that women offered in describing their decisions to leave the engineering profession. Our results revealed the top three sets of reasons underlying women's decision to leave the jobs and engineering field were related to: first, poor and/or inequitable compensation, poor working conditions, inflexible and demanding work environment that made work-family balance difficult; second, unmet achievement needs that reflected a dissatisfaction with effective utilization of their math and science skills, and third, unmet needs with regard to lack of recognition at work and adequate opportunities for advancement. Implications of these results for future research as well as the design of effective intervention programs aimed at women engineers' retention and engagement in engineering are discussed.
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    Meta-Analysis of Coefficient Alpha for Scores on the Narcissistic Personality Inventory
    (Public Library of Science, 2018-12) Miller, Brian K.; Nicols, Kay M.; Clark, Silvia; Daniels, Alison; Grant, Whitney
    The Narcissistic Personality Inventory (NPI) has greatly facilitated the scientific study of trait narcissism. However, there is great variability in the reported reliability of scores on the NPI. This study meta-analyzes coefficient alpha for scores on the NPI and its sub-scales (e.g. entitlement) with transformed alphas weighted by the inverse of the variance of alpha. Three coders evaluated 1213 individual studies for possible inclusion and determined that 1122 independent samples were suitable for coding on 12 different characteristics of the sample, scale, and study. A fourth author cross-coded 15 percent of these samples resulting in 85 percent overall agreement. In the independent samples, comprised of 195,038 self-reports, the expected population coefficient alpha for the NPI was .82. The population value for alpha on the various sub-scales ranged from .48 for narcissistic self-sufficiency to .76 for narcissistic leadership/authority. Because significant heterogeneity existed in coded study alphas for the overall NPI, moderator tests and an explanatory model were also conducted and reported. It was found that longer scales, the use of a Likert response scale as opposed to the original forced choice response format, higher mean scores and larger standard deviations on the scale, as well as the use of samples with a larger percentage of female respondents were all positively related to the expected population alpha for scores on the overall NPI. These results will likely aid researchers who are concerned with the reliability of scores on the NPI in their research on non-clinical subjects.
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    Thickness Measurement of Multilayer Film Stackin Perovskite Solar Cell Using Spectroscopicellipsometry
    (AIP Publishing, 2019-12) Hasan, Mehedhi; Lyon, Kevin; Trombley, Lauren; Smith, Casey; Zakhidov, Alex
    The rapid surge in perovskite solar cell efficiency has necessitated the development of viable metrology techniques during device integration, paving the way for commercialization. Ellipsometry is considered the most appropriate technique for fast and accurate thickness measurement for large scale production. However, a precise and well-calibrated model is a prerequisite for this technique. While ellipsometry of individual device layers has been reported in recent perovskite literature, a comprehensive multilayer modeling approach is thus far unavailable. Perovskite optoelectronic devices generally consist of a six-layer film stack with three transparent layers required for optical absorption in the perovskite layer. Spin casted thin films, now common in this line of research, impart their own difficulties into ellipsometric modeling. Roughnesses at each heterointerface, similarities in optical spectra of transparent layers, and anomalous dispersion of perovskite are just a few of such challenges. In this work, we report the process of building an ellipsometry model from scratch for thickness measurement of methylammonium lead iodide (MAPI) perovskite and indium tin oxide (ITO)/hole transport layer (HTL) bilayer thin film stacks on a glass substrate. Three promising representatives of HTLs (CuI, Cu2O, and PEDOT:PSS) were studied. The models were extended to measure the individual layer thicknesses of the MAPI/HTL/ITO film stack on a glass substrate using the models developed for individual layers. Optical constants of all the representative thin films were thus extracted for a wide wavelength range (300 nm–900 nm).
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    SWT and San Marcos: Economic Impact Study, 1999
    (Southwest Texas State University, 1999-01) Southwest Texas State University
    No abstract prepared.
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    SWT and San Marcos: An Economic Impact Analysis, 1990
    (Southwest Texas State University, 1990-01) Savage, V. Howard; Kishan, Ruby P.
    At the request of President Robert Hardesty of Southwest Texas State University, the economic relationship between Southwest Texas State University, the economic relationship between Southwest Texas State University and San Marcos was studied for fiscal year 1985. This study was carried out through the use of the Caffrey-Isaacs cash flow model. In the 1985 fiscal year the university dominated the local economy.
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    Southwest Texas State University and the San Marcos Community: An Economic Impact Analysis
    (Southwest Texas State University, 1985-01) Southwest Texas State University
    No abstract prepared.
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    Economic Base: San Marcos, Hays County, Texas (1959-1971)
    (Southwest Texas State University, 1972-01) Savage, V. Howard; Morgan, Celia A.; Yeargan, Howard R.
    No abstract prepared.
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    Measurement Invariance Tests of Revisions to Archaically Worded Items in the Mach IV Scale
    (Public Library of Science, 2019-10) Miller, Brian K.; Nicols, Kay M.; Konopaske, Robert
    The Machiavellian IV [1] instrument, developed almost 50 years ago to measure trait Machiavellianism and still in wide use in personality research, uses item wording that is not gender-neutral, makes use of idiomatic expressions, and includes archaic references. In this two-sample study, exploratory factor analysis (EFA) was conducted on one sample to examine the structure of responses to the Mach IV. In an independent second sample the resulting EFA structure was analyzed using confirmatory factor analysis-based measurement equivalence/invariance (ME/I) tests in a control group with the original archaic items and a treatment group with eight items rewritten in a more modern vernacular. Specific model testing steps [2] and statistical tests [3] were applied in a bottom-up approach [4] to ME/I tests on these two versions of the Mach IV. The two versions were found to have equal form, equal factor loadings, but unequal indicator error variances. Subsequent item-by-item tests of error invariance resulted in substantial decrements to fit for three revised items suggesting that the error associated with these items was not equal across the two versions.