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
- 特岗教师招聘语文备考重点之常见文言虚词(二)
- 2015特岗教师招考“化学与生活”单元测试题(1)
- 2015特岗教师招聘语文文言虚词强化练习题(2)
- 特岗教师招聘生物“基因的本质”知识点详解(三)
- 2015特岗教师招聘语文文言虚词强化练习题(3)
- 2015特岗招考音乐备考:西方音乐史之中世纪音乐(一)
- 2015特岗教师招聘“学校体育学”名词解释专项练习(2)
- 2015特岗教师招聘“学校体育学”名词解释专项练习(1)
- 特岗招考历史备考:“科学技术与思想文化”考点梳理(二)
- 2015特岗教师招聘体育《运动训练学》综合练习试题(4)
- 特岗教师招聘生物“基因的本质”知识点提炼及典例精析(二)
- 2015特岗教师招聘初中物理“液体的压强”精选习题(一)
- 2015特岗教师招考英语备考:状语从句专项练习及详解(8)
- 2015特岗教师招考化学“盐化肥”单元测试题(3)
- 2015特岗教师招聘体育《运动训练学》综合练习试题(3)
- 2015特岗教师招聘历史“科学技术与思想文化”测试题(2)
- 特岗教师招考化学知识点精讲:化学与生活(二)
- 2015特岗教师招聘历史“科学技术与思想文化”测试题(1)
- 特岗教师招聘语文备考重点之常见文言虚词(四)
- 特岗教师招考化学知识点精讲:化学与生活(一)
- 特岗教师招聘语文备考重点之常见文言虚词(一)
- 2015特岗教师招考化学“盐化肥”单元测试题(2)
- 2015特岗教师招聘《信息技术基础知识》章节练习题(2)
- 特岗教师招聘生物“基因的本质”知识点提炼及典例精析(一)
- 2015特岗招考语文备考——古代诗歌中常见的情感
- 2015特岗招考音乐备考:西方音乐史之古希腊音乐
- 2015特岗招考语文备考——常见诗歌的题材分类
- 特岗教师招聘生物“基因的本质”知识点详解(二)
- 2015特岗招考音乐备考:西方音乐史之古罗马音乐
- 2015特岗招考音乐备考:西方音乐史之中世纪音乐(二)
网友关注视频
- 外研版英语三起5年级下册(14版)Module3 Unit1
- 【获奖】科粤版初三九年级化学下册第七章7.3浓稀的表示
- 第五单元 民族艺术的瑰宝_15. 多姿多彩的民族服饰_第二课时(市一等奖)(岭南版六年级上册)_T129830
- 冀教版小学英语五年级下册lesson2教学视频(2)
- 每天日常投篮练习第一天森哥打卡上脚 Nike PG 2 如何调整运球跳投手感?
- 沪教版牛津小学英语(深圳用) 四年级下册 Unit 4
- 冀教版小学数学二年级下册第二单元《租船问题》
- 冀教版小学英语四年级下册Lesson2授课视频
- 北师大版数学四年级下册3.4包装
- 七年级下册外研版英语M8U2reading
- 冀教版小学数学二年级下册1
- 化学九年级下册全册同步 人教版 第25集 生活中常见的盐(二)
- 外研版英语七年级下册module3 unit2第一课时
- 第五单元 民族艺术的瑰宝_16. 形形色色的民族乐器_第一课时(岭南版六年级上册)_T1406126
- 沪教版牛津小学英语(深圳用) 四年级下册 Unit 7
- 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
- 19 爱护鸟类_第一课时(二等奖)(桂美版二年级下册)_T502436
- 七年级英语下册 上海牛津版 Unit9
- 第8课 对称剪纸_第一课时(二等奖)(沪书画版二年级上册)_T3784187
- 8.练习八_第一课时(特等奖)(苏教版三年级上册)_T142692
- 《小学数学二年级下册》第二单元测试题讲解
- 沪教版牛津小学英语(深圳用) 六年级下册 Unit 7
- 冀教版小学数学二年级下册第二周第2课时《我们的测量》宝丰街小学庞志荣
- 河南省名校课堂七年级下册英语第一课(2020年2月10日)
- 三年级英语单词记忆下册(沪教版)第一二单元复习
- 第五单元 民族艺术的瑰宝_16. 形形色色的民族乐器_第一课时(岭南版六年级上册)_T3751175
- 8.对剪花样_第一课时(二等奖)(冀美版二年级上册)_T515402
- 沪教版八年级下册数学练习册21.4(1)无理方程P18
- 七年级英语下册 上海牛津版 Unit3
- 沪教版牛津小学英语(深圳用) 四年级下册 Unit 3
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