Clute Institute: Journals
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    A Study Of The Use Of Financial Ratios In Smaller Business Enterprises

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    Entrepreneurs should be aware of the currently high rate of failure for small business firms and the consequent need for well-formulated and strategic planning, implementation and evaluation of the smaller business firm. Many of these basic forms of analysis can be derived from financial statement and reporting disclosures for the smaller business firm. These tools for management planning and decision-making are increasingly available with the use of electronic data processing (EDP) systems in the creation of financial data for a business organization.Recognizing the need for systematic use and evaluation of these financial data by small business owners, this study focused upon the use of a set of widely discussed financial ratios by a sample group of small business owners in the Chicago metropolitan area

    The Wage Gap And Comparable Worth

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    The issue of equal pay for equal work between males and females, although not in political vogue, is an issue with merit and need of resolution

    Comparison Of The Performance Of Several Data Mining Methods For Bad Debt Recovery In The Healthcare Industry

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    The healthcare industry, specifically hospitals and clinical organizations, are often plagued by unpaid bills and collection agency fees. These unpaid bills contribute significantly to the rising cost of healthcare. Unlike financial institutions, health care providers typically do not collect financial information about their patients.  This lack of information makes it difficult to evaluate whether a particular patient-debtor is likely to pay his/her bill.  In recent years, the industry has started to apply data mining tools to reduce bad-debt balance. This paper compares the effectiveness of five such tools - neural networks, decision trees, logistic regression, memory-based reasoning, and the ensemble model in evaluating whether a debt is likely to be repaid. The data analysis and evaluation of the performance of the models are based on a fairly large unbalanced data sample provided by a healthcare company, in which cases with recovered bad debts are underrepresented. Computer simulation shows that the neural network, logistic regression, and the combined model produced the best classification accuracy. More thorough interpretation of the results is obtained by analyzing the lift and receiver operating characteristic charts. We used the models to score all “unknown” cases, which were not pursued by a company. The best model classified about 34.8% of these cases into “good” cases. To collect bad debts more effectively, we recommend that a company first deploy and use the models, before it refers unrecovered cases to a collection agency.   &nbsp

    Teaching Characteristics Of Successful College Professors

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    During the past several years, the authors have devoted a great deal of time and energy in the pursuit of becoming effective college professors.  After observing a number of excellent professors (and a number of less-than-excellent ones), the authors would like to share some of their observations and ideas.Although this article focuses specifically on effective classroom performance in a traditional lecture-based setting, many of the principles discussed can be applied to alternative styles of teaching such as seminar settings, individualized instruction, etc.


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