外文翻译原文
Intangibles: Management, Measurement, and Reporting
R&D and the Growth of Business Enterprises
The contribution of R&D to the performance measure (profits ,sales) statistically to R&D expenditures –in the current and previous periods to allow for the delayed effect of R&D on business performance –and by controlling for the effect of other investments (physical assets ) on business performance. This statistical approach to empirically address issues concerning intangibles and their private and social impact was frequently used by economists and researchers in related areas. The empirical worked started with extensive historical case studies and proceeded to large sample (cross-sectional) analyses of R&D on firms’ productivity and growth .The research effort yielded several important findings:
---R&D expenditures contribute significantly to the productivity(value added) and output of firms ,and the estimated rates of return on R&D investment are quite high —as much as—20-35 percent annually – with the estimates varying widely across industries and over time.
--- The contribution of basic research (work aimed at developing new science and technology) to corporate productivity and growth is substantially larger than the contribution of other types of R&D ,such as product development and process R&D(where the latter is aimed at enhancing the efficiency of production processes).The estimated contribution differential of approximately three to one in favor of basic research is particularly intriguing ,given the widespread belief that public companies have been recently curtailing expenditures on basic research, in part as a response to the skepticism of many financial analysts and institutional investors about the commercialization prospects of basic research. Basic research is, of course, more risky than applied R&D (see chapter 2), but it is inconceivable that risk differentials by themselves account for a three-to-one productivity of basic research.
---The contribution of corporate-financed R&D to productivity growth is larger than corporate-based –but government-financed —R&D (granted primarily to government contractors).The fact that most contracts with the government are based
on cost-plus terms may partially explain this findings. This result should not detract from the significant contribution to the industrial and technological infrastructure of publicly funded research conducted by government agencies and in federal laboratories (such as the contribution by the National Institutes of Health to pharmaceutical and biotech companies) as well as the substantial contribution of university research to technology.
It should be noted that much of the research summarized above was based on survey data and industry aggregates, due to severe limitations in corporate published data. In fact, most of the examined variables and attributes—such as basic versus applied research and company versus government-sponsored R&D—cannot be directly estimated from information publicly disclosed to investors. Thus an important implication of these and similar findings is to suggest which kinds of currently unavailable information and data would be useful to managers, investors, and policymakers.
Alternative Output Measures: Market Value and Patent
The research presented above relates R&D inputs (intensity, capital) to firms’ productivity, sales, or profit growth, in an attempt to estimate the return on corporate investment in innovation as well as to examine macro-economic issues, such as the productivity decline in the United States in the 1970s and early 1980s. This methodological approach encounters various problems; in particular the time lag between the investment in R&D and the realization of benefits (such as sales) is often long (particularly for basic research) and generally unknown, increasing the uncertainty about the estimated R&D contribution. Furthermore, biases and distortions in reported profits—arising from firms’ attempts to ―manage‖ investors’ perceptions (see chapter 4)—might cloud the intrinsic relationship between R&D and its subsequent benefits.
These measurement difficulties have prompted a search for alternative and more reliable indicators of R&D output than reported sales and profitability measures. Two output indicators have received considerable in attention: capital market values of corporations and patents. Believers in efficient capital markets argue that stock price
and returns provide reliable signals of enterprise value and performance; hence R&D contribution can be evaluated using market values. Patents, and particularly citations in patent applications, provide an additional of the value of R&D and firms’ technology.
Concerning capital market studies, the research persuasively indicates that investors regard R&D as a significant value-increasing activity. For example, a number of event studies register a significantly positive investor reaction (stock price increases) to corporate announcements of new R&D initiatives, particularly of firms operating in high-technology sectors and using cutting edge technology. When information is available, investors distinguish among different stages of the R&D process—such as program initiation and ultimate commercialization —most significantly rewarding mature R&D projects that are close to commercialization. Furthermore, econometric studies that relate corporate market values or market-to-book ratios to R&D intensities consistently yield positive and statistically significant association estimates. Further probing of the data suggests that investors value an R&D dollar spent by large firms more highly than that spent by small firms, probably a reflection of economies of scale in R&D. For example, large companies may benefit from lessons of failed R&D projects as they pursue the development of other project.
The evidence thus indicates unequivocally that investors view R&D expenditures as on average enhancing the value of firms and that that also demonstrate some ability to differentiate the contribution of R&D across industries, firm sizes, and stages of R&D maturity. Investors’ ability to fine-tune R&D valuations is obviously hampered by the absence of detailed information on these attributes in corporate financial reports.
Data on R&D expenditures available in financial statements are crude indicators of R&D contribution and value creation: there is productive R&D and wasteful R&D (Motorola and partners’$5 billion investment in the Iridium satellite communications project, currently in bankruptcy, is an example of the latter). The R&D productivity estimates discussed above obviously averaged the good and the bad, missing
considerable information in the process. In an attempt to improve the estimation of R&D contribution, researchers experimented with patents, which can be considered an intermediate output measure of R&D (the final output measure is, of course, the benefit—sales, cost savings—generated by the R&D expenditure). Patents are only partial indicators of R&D output, since not every R&D project id patented. Yet patent research provides interesting insights.
The Findings of Patent Research
Various attributes of patents, such as the number of patents registered by a company (patent counts), patent renewal and fee data, and citations of and to patents were examined by researchers. Both patent counts and the number of innovations emerging from a company’s R&D program were found to be associated with the level of corporate investment in R&D (the higher the R&D expenditures, the larger, on average, the number of consequent patents and innovations) as well as with firms’ market values (the larger the number of patents and innovations, the higher the market value, on average). Patents are thus related to both inputs (R&D) and outputs (market values) of the innovation process and, therefore, are meaningful intermediate value measures.
It is clear, however, that patent and innovations are noisy measures of R&D contribution, due to the skewness of their value distributions—that is, the tendency of a few patents or innovations to generate substantial returns (blockbusters), while the majority turn out to be virtually worthless. Citations (references) to a firm’s patents included in subsequent patent applications (forward citations) offer a more reliable measure of R&D value, since such citations are an objective indicator of the firm’s research capabilities and the impact of its innovation activities on the subsequent development of science and technology.
Various studies show that patent citations capture important aspects of R&D value. For example, Manuel Trajtenberg reports a positive association between citation counts and consumer welfare measures for CAT scanners; Hilary Shane finds that patent counts weighted by citations (the firm’s number of registered patents divided by the number of citations by others to these patents) contribute to the
explanation of differences in Tobin’s q measures (market value over replacement cost of assets) across semiconductor companies; and Bronwyn Hall and colleagues report that citation-weighted patent counts are positively associated with firms’ market values (after controlling for R&D capital). Patents and their attributes thus reflect technological elements used by investors to value companies.
In a direct test of the usefulness of patent citation measures as indicators of value, studies have been conducted to examine the ability of various citation-based measures to predict subsequent stock returns and market-to-book values possess such predictive ability: the number of patents granted to the firm in a given year, the intensity of citations to a firm’s patent portfolio by subsequent patents, and a measure based on the number of citation in a firm’s patents (backward citations) to scientific papers (in contrast with citations to previous patents).
The third measure reflects the scientific intensity of a patent and may provide a proxy for the extent of basic research conducted by the company. The fact that patent indicators are associated with subsequent stock prices and returns suggests that investors are not fully aware of the ability of these measures to convey useful information about firms’ innovation processes and capabilities. This is of course not surprising, given the novelty of patent-related measures as indicators of enterprise value.
Patents are the intangible assets actively traded in markets (see chapter 2), in the form of licensing and sale of patents. An examination of firms’ royalties from the licensing of patents indicates that the volume of royalty income is swiftly increasing and that investors value a dollar of patent royalties (the implicit, market multiplier of royalty income) two to three times higher than a dollar of regular income. The reason for the high valuation of patent royalties probably lies in the stability of this income source (patents are usually licensed for several years) relative to other more transitory components of income. Patent royalties also impact investors’ valuation of R&D, namely the market value they assign to a dollar of R&D expenditures. The valuation of the R&D of firms with royalty income is higher than the valuation of the R&D of firms that do not license patents, probably due to investors’ belief that the quality and
下载文档
热门试卷
- 2016年四川省内江市中考化学试卷
- 广西钦州市高新区2017届高三11月月考政治试卷
- 浙江省湖州市2016-2017学年高一上学期期中考试政治试卷
- 浙江省湖州市2016-2017学年高二上学期期中考试政治试卷
- 辽宁省铁岭市协作体2017届高三上学期第三次联考政治试卷
- 广西钦州市钦州港区2016-2017学年高二11月月考政治试卷
- 广西钦州市钦州港区2017届高三11月月考政治试卷
- 广西钦州市钦州港区2016-2017学年高一11月月考政治试卷
- 广西钦州市高新区2016-2017学年高二11月月考政治试卷
- 广西钦州市高新区2016-2017学年高一11月月考政治试卷
- 山东省滨州市三校2017届第一学期阶段测试初三英语试题
- 四川省成都七中2017届高三一诊模拟考试文科综合试卷
- 2017届普通高等学校招生全国统一考试模拟试题(附答案)
- 重庆市永川中学高2017级上期12月月考语文试题
- 江西宜春三中2017届高三第一学期第二次月考文科综合试题
- 内蒙古赤峰二中2017届高三上学期第三次月考英语试题
- 2017年六年级(上)数学期末考试卷
- 2017人教版小学英语三年级上期末笔试题
- 江苏省常州西藏民族中学2016-2017学年九年级思想品德第一学期第二次阶段测试试卷
- 重庆市九龙坡区七校2016-2017学年上期八年级素质测查(二)语文学科试题卷
- 江苏省无锡市钱桥中学2016年12月八年级语文阶段性测试卷
- 江苏省无锡市钱桥中学2016-2017学年七年级英语12月阶段检测试卷
- 山东省邹城市第八中学2016-2017学年八年级12月物理第4章试题(无答案)
- 【人教版】河北省2015-2016学年度九年级上期末语文试题卷(附答案)
- 四川省简阳市阳安中学2016年12月高二月考英语试卷
- 四川省成都龙泉中学高三上学期2016年12月月考试题文科综合能力测试
- 安徽省滁州中学2016—2017学年度第一学期12月月考高三英语试卷
- 山东省武城县第二中学2016.12高一年级上学期第二次月考历史试题(必修一第四、五单元)
- 福建省四地六校联考2016-2017学年上学期第三次月考高三化学试卷
- 甘肃省武威第二十三中学2016—2017学年度八年级第一学期12月月考生物试卷
网友关注
- 健康养生市场全景评估与发展趋势研究报告
- 2014年生物制药行业薪酬现状
- UI设计培训之8个前沿的 HTML5 CSS3 效果
- 计算机硬件与网络安全的维护
- WEB QQ 3.0用的那种技术实现的解决思路
- 网页设计与制作试卷
- 基于非经常性损益的应计异象分析--来自中国A股市场的证据
- 发展航空航天的价值
- 计算机硬件组装课件
- 脐橙产业建设项目可行性研究报告
- 网页游戏中界面设计的研究和应用(论文)
- 健康养生旅游专题研究
- 4441.计算机硬件工程师维修技能实训丛书:打印机维修技能实训(第3版)(附CD-ROM光盘1张)
- 基于网页的虚拟现实及其关键技术【ppt】
- html5标签大全
- 2010年中国客车行业市场政策历史发展研究报告
- 网站内页该如何设计?
- 计算机硬件的组装实验报告
- 浙江省小额贷款公司试点方案审核规范及可持续发展政策解读
- 周边安全环境分析专题讲座
- 星狮创想:ui设计之芝麻大年夜事 (i)
- .浅谈网页设计发展之路 迎合用户敢于创新
- 51cto下载-计算机硬件组装与维护试卷a
- 界面设计项目1
- flash.cs3网站商业设计从入门到精通 第16章 flash游戏制作【课件】
- 电脑基础常识,硬件篇[教学]
- 电脑课堂之硬件维护与系统安装
- 新建小区节能评估报告
- 试论计算机组装与维护课程改革新探索
- www资源及其概念
网友关注视频
- 第19课 我喜欢的鸟_第一课时(二等奖)(人美杨永善版二年级下册)_T644386
- 沪教版牛津小学英语(深圳用) 五年级下册 Unit 12
- 冀教版小学数学二年级下册1
- 沪教版牛津小学英语(深圳用) 四年级下册 Unit 8
- 二次函数求实际问题中的最值_第一课时(特等奖)(冀教版九年级下册)_T144339
- 【部编】人教版语文七年级下册《过松源晨炊漆公店(其五)》优质课教学视频+PPT课件+教案,江苏省
- 【部编】人教版语文七年级下册《过松源晨炊漆公店(其五)》优质课教学视频+PPT课件+教案,辽宁省
- 人教版历史八年级下册第一课《中华人民共和国成立》
- 冀教版小学数学二年级下册第二单元《有余数除法的竖式计算》
- 外研版英语七年级下册module3 unit1第二课时
- 北师大版八年级物理下册 第六章 常见的光学仪器(二)探究凸透镜成像的规律
- 沪教版牛津小学英语(深圳用) 四年级下册 Unit 3
- 外研版英语三起5年级下册(14版)Module3 Unit2
- 沪教版八年级下册数学练习册一次函数复习题B组(P11)
- 【部编】人教版语文七年级下册《泊秦淮》优质课教学视频+PPT课件+教案,天津市
- 冀教版英语五年级下册第二课课程解读
- 【部编】人教版语文七年级下册《泊秦淮》优质课教学视频+PPT课件+教案,辽宁省
- 3月2日小学二年级数学下册(数一数)
- 30.3 由不共线三点的坐标确定二次函数_第一课时(市一等奖)(冀教版九年级下册)_T144342
- 沪教版牛津小学英语(深圳用) 四年级下册 Unit 4
- 沪教版八年级下次数学练习册21.4(2)无理方程P19
- 小学英语单词
- 河南省名校课堂七年级下册英语第一课(2020年2月10日)
- 19 爱护鸟类_第一课时(二等奖)(桂美版二年级下册)_T3763925
- 苏科版数学 八年级下册 第八章第二节 可能性的大小
- 飞翔英语—冀教版(三起)英语三年级下册Lesson 2 Cats and Dogs
- 外研版英语七年级下册module1unit3名词性物主代词讲解
- 苏科版数学七年级下册7.2《探索平行线的性质》
- 冀教版小学英语五年级下册lesson2教学视频(2)
- 七年级英语下册 上海牛津版 Unit5
精品推荐
- 2016-2017学年高一语文人教版必修一+模块学业水平检测试题(含答案)
- 广西钦州市高新区2017届高三11月月考政治试卷
- 浙江省湖州市2016-2017学年高一上学期期中考试政治试卷
- 浙江省湖州市2016-2017学年高二上学期期中考试政治试卷
- 辽宁省铁岭市协作体2017届高三上学期第三次联考政治试卷
- 广西钦州市钦州港区2016-2017学年高二11月月考政治试卷
- 广西钦州市钦州港区2017届高三11月月考政治试卷
- 广西钦州市钦州港区2016-2017学年高一11月月考政治试卷
- 广西钦州市高新区2016-2017学年高二11月月考政治试卷
- 广西钦州市高新区2016-2017学年高一11月月考政治试卷
分类导航
- 互联网
- 电脑基础知识
- 计算机软件及应用
- 计算机硬件及网络
- 计算机应用/办公自动化
- .NET
- 数据结构与算法
- Java
- SEO
- C/C++资料
- linux/Unix相关
- 手机开发
- UML理论/建模
- 并行计算/云计算
- 嵌入式开发
- windows相关
- 软件工程
- 管理信息系统
- 开发文档
- 图形图像
- 网络与通信
- 网络信息安全
- 电子支付
- Labview
- matlab
- 网络资源
- Python
- Delphi/Perl
- 评测
- Flash/Flex
- CSS/Script
- 计算机原理
- PHP资料
- 数据挖掘与模式识别
- Web服务
- 数据库
- Visual Basic
- 电子商务
- 服务器
- 搜索引擎优化
- 存储
- 架构
- 行业软件
- 人工智能
- 计算机辅助设计
- 多媒体
- 软件测试
- 计算机硬件与维护
- 网站策划/UE
- 网页设计/UI
- 网吧管理