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Forecasting invention in the pharmaceutical industry

机译:预测制药行业的发明

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This dissertation empirically examines temporal relationships among variables thought to influence a firm's propensity to invent. The endogenous variable, invention, is operationalized and measured as the number of annual patents a firm is granted. Exogenous variables serving as leading indicators of invention are research and development expenditures, net sales, profit, net assets, and number of employees. All independent variables are measured annually. As constructs, they represent respectively, investment in invention, market activity, profitability, wealth, and human capital. Using these variables, time series models are estimated and evaluated to determine the extent to which invention can be forecast for individual firms.;The sample cohorts consists of nineteen large U.S. pharmaceutical companies. Sample data are analyzed for the time period 1964 to 1985, inclusive. The majority of the statistical analysis employs Box-Jenkins ARIMA methodology for single series estimation and State Space methodology for multiple series estimation. A statistical model of invention is estimated for each firm. Quantitative information criteria are used to select the best statistical model for each firm. Various measures of model adequacy are also reported. Additionally, the annual data are pooled for the twenty-two year period and an industry model of invention is estimated and evaluated.;Each firm's model of invention is then regressed on the industry model and appropriate significant levels are determined for each firm's model. Results from these tests signify the extent to which each of the nineteen firms follow the aggregated industry model of invention. Three general groups result: those firms which essentially define the industry; firms that are significantly related; and firms which deviate markedly from the industry model. Three principal conclusions are drawn. First, it is possible to forecast through time a firm's inventive output. Second, results indicate this procedure provides a viable alternative to current methods of strategic group analysis, especially, for technology dependent industries. Finally, it is suggested that a firm's performance on the dimension of invention is an alternative measure of strategic performance.
机译:本文从经验上考察了影响企业发明倾向的变量之间的时间关系。内生变量发明是作为企业每年授予的专利数量进行操作和衡量的。用作发明领先指标的外生变量是研发支出,净销售额,利润,净资产和员工人数。所有自变量均每年进行测量。作为结构,它们分别表示对发明的投资,市场活动,盈利能力,财富和人力资本。使用这些变量,对时间序列模型进行估算和评估,以确定可以预测单个公司的发明范围。;样本组由19家大型美国制药公司组成。分析了1964年至1985年(含)的样本数据。大多数统计分析采用Box-Jenkins ARIMA方法进行单序列估计,并使用State Space方法进行多序列估计。为每个公司估计发明的统计模型。定量信息标准用于为每个公司选择最佳的统计模型。还报告了各种模型充分性的度量​​。此外,汇总22年期间的年度数据,并估算和评估发明的行业模型。然后,将每个公司的发明模型回归到行业模型上,并为每个公司的模型确定适当的重要水平。这些测试的结果表明,十九家公司中的每家公司在何种程度上遵循了汇总的发明产业模型。结果由三个大类组成:本质上定义行业的公司;有重大关系的公司;和明显偏离行业模式的公司。得出三个主要结论。首先,有可能随着时间的推移预测公司的发明产出。其次,结果表明该程序为当前的战略集团分析方法提供了一种可行的替代方法,尤其是对于依赖技术的行业。最后,建议公司在发明方面的绩效是战略绩效的另一种衡量标准。

著录项

  • 作者

    Crossland, Philip Paul.;

  • 作者单位

    The University of Nebraska - Lincoln.;

  • 授予单位 The University of Nebraska - Lincoln.;
  • 学科 Management.;Pharmaceutical sciences.
  • 学位 Ph.D.
  • 年度 1987
  • 页码 353 p.
  • 总页数 353
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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