McCoy College of Business
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Item A Brief Exploration in Statistics and Quantum Mechanics(Texas State University-San Marcos, 2011-05) Blankmeyer, EricQuantum mechanics has some probabilistic or statistical features that have been considered paradoxical or exotic; at least, this impression is frequently conveyed in introductory textbooks on the subject and informal explanations of quantum theory. The often idiosyncratic treatment of statistics and probability seems unhelpful to the student and the interested layperson: it may tend to exaggerate and mystify the real differences between the microscopic and the macroscopic worlds. In this paper I try to show that some of the statistical esoterica of quantum mechanics can be made more transparent by their very close analogies to several macroscopic topics.Item A Heuristic Storage Location Assignment Based on Frequent Itemset Classes to Improve Order Picking Operations(Multidisciplinary Digital Publishing Institute, 2021-02-19) Li, Yue; Mendez-Mediavilla, Francis A.; Temponi, Cecilia; Kim, Junwoo; Jimenez, JesusMost 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.Item Business Return in New Orleans: Decision Making Amid Post-Katrina Uncertainty(Public Library of Science, 2009-08-26) Lam, Nina S. N.; Pace, R. Kelley; Campanella, Richard; LeSage, James P.; Arenas, HelbertBackground: 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.Item Deep Vision for Breast Cancer Classification and Segmentation(Multidisciplinary Digital Publishing Institute, 2021-10-27) 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.Item 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.Item Emerging Technology and Business Model Innovation: The Case of Artificial Intelligence(Multidisciplinary Digital Publishing Institute, 2019-07) Lee, Jaehun; Suh, Taewon; Roy, Daniel; Baucus, MelissaArtificial 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.Item Errors in Variables or Bad Leverage at Some Observations ?(Texas State University-San Marcos, 2011-10) Blankmeyer, EricErrors-in-variables is a long-standing, difficult issue in linear regression; and progress depends in part on new identifying assumptions. I characterize measurement error as bad-leverage points and assume that fewer than half the sample observations are heavily contaminated, in which case a high-breakdown robust estimator may be able to isolate and downweight or discard the problematic data. In simulations of simple and multiple regression where eiv affected 25% of the data and R2 was mediocre, one high-breakdown estimator had small bias, very good coverage, and precision that improved when the sample size increased.Item Has China’s Belt and Road Initiative Intensified Bilateral Trade Links between China and the Involved Countries?(Multidisciplinary Digital Publishing Institute, 2020-08-20) Yu, Chunjiao; Zhang, Ren; An, Lian; Yu, ZhixingThe 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.Item How Robust is Linear Regression with Dummy Variables ?(Texas State University-San Marcos, 2006-11) Blankmeyer, EricResearchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations. Such groups may easily contain enough outliers to break down the parameter estimates. Models with many fixed or random effects appear to be especially vulnerable to outlying data. This paper discusses the problem at an intuitive level and cites sources for the key theorems establishing bounds on the breakdown point in models with dummy variables.Item Improving the Small-sample Efficiency of a Robust Correlation Matrix: A Note(Texas State University-San Marcos, 2007-04) Blankmeyer, EricThis paper reports small-sample simulations of a correlation matrix estimated robustly by P. J. Rousseeuw's MCD algorithm. It appears that the statistical efficiency of MCD can be improved significantly if a pairwise-difference transformation is first applied to the data.Item Increasing Access to Care for the Underserved: Voices of Riders, Drivers, and Staff of a Rural Transportation Program(Multidisciplinary Digital Publishing Institute, 2022-10-19) Schwartz, Abby; Richman, Alice; Scott, Mallary; Liu, Haiyong; White, Weyling; Doherty, CarolineThe 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.Item Log-linear Indexes of Nominal Wage Rates and Employment in Eight U. S. Regions(Texas State University-San Marcos, 2008-02) Blankmeyer, EricThis paper illustrates the use of log-linear indexes to estimate and test hypotheses about interregional differences in nominal wages and employment. A two-way analysis of variance is applied to cross sections of U. S. retailing and service categories in eight regions. The robustness of the estimated indexes is examined, and a test of consistent aggregation across sectors is proposed.Item Measurement Invariance Tests of Revisions to Archaically Worded Items in the Mach IV Scale(Public Library of Science, 2019-10) Miller, Brian K.; Miller, Brian K.; Nicols, Kay M.; Nicols, Kay M.; Konopaske, Robert; Konopaske, RobertThe 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.Item Meta-Analysis of Coefficient Alpha for Scores on the Narcissistic Personality Inventory(Public Library of Science, 2018-12-04) Miller, Brian K.; Nicols, Kay M.; Clark, Silvia; Daniels, Alison; Grant, WhitneyThe 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.Item 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.Item Percentiles of an Inflation Index by Quantile Regression(Texas State University-San Marcos, 2006-06) Blankmeyer, EricThis paper gives a methodology for estimating an inflation index using the quantile regression of Bassett and Koenker. The regression, which is orthogonal in the logarithmic price changes, is computed by linear programming for each percentile of inflation. The procedure is applied to monthly data on 25 raw materials.Item Positive Disposition in the Prediction of Strategic Independence among Millennials(Multidisciplinary Digital Publishing Institute, 2017-11) Konopaske, Robert; Konopaske, Robert; Kirby, Eric G.; Kirby, Eric G.; Kirby, Susan L.; 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.Item Predictors of Business Return in New Orleans after Hurricane Katrina(Public Library of Science, 2012-10-24) Lam, Nina S. N.; Arenas, Helbert; Pace, R. Kelley; LeSage, James P.; Campanella, RichardWe 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.Item Southwest Texas State University and the San Marcos Community: An Economic Impact Analysis(Southwest Texas State University, 1985-01) Southwest Texas State UniversityNo abstract prepared.Item 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.