Using Human Resource Data to Track Innovation Summary of a Workshop (2002) / Chapter Skim
Currently Skimming:
Appendix C: 'Using Human Resource Data to Illuminate Innovation and Research Utilization' by Paula Stephen
Appendix C: 'Using Human Resource Data to Illuminate Innovation and Research Utilization' by Paula Stephen
Pages 43-68
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 43... ...
One consequence of these changes is that traditional measures, such as patent counts and research and development expenditure data, are increasingly unable to illuminate R&D activity in the United States. "Without substantial change in the content and coverage of data collection, our portrait of innovative activity in the U.S.
|
From page 44... ...
Section II summarizes changing patterns of research and development and comments on gaps in our ability to measure innovative activity. Section III defines what is meant by human resource data and describes the data that are readily available.
|
From page 45... ...
This is largely a result of increased spending on health-related R&D, primarily through the National Institutes of Health. Changes in the Industrial Mix of R&D The most striking change in the industrial mix of innovation in the United States is the increased role played by the service sector.
|
From page 46... ...
Because these changes contribute to the growing inadequacy of traditional measures to describe innovative activity, we examine each in some detail. The trend toward increased reliance on external R&D is undeniable.2 Firms outsource R&D to other firms or, in a more aggressive mode, acquire R&D through acquisitions.3 Cisco Systems is an oft-cited example of the latter, acquiring start-up companies as an R&D strategy.
|
From page 47... ...
256~. Organizational changes have also occurred within the firm as some firms have shifted away from the central R&D lab model choosing not only to outsource research but in many instances to locate research activities at the plant level.
|
From page 48... ...
46~. Creative uses of human resource data could illuminate industries that have high technology absorption capacities and could aid in our understanding of the strong performance enjoyed by a number of industrial sectors in recent years.
|
From page 49... ...
In short, the changes outlined above result in a blurring of boundaries and a blurring of roles. Measures of innovation designed when firms were discrete firms and universities were strictly universities fail to portray these changes adequately.8 Even without the changes noted above the traditional measures of innovative activity, namely patent counts and R&D expenditures, reveal little to investors and analysts concerning the knowledge base of firms.
|
From page 50... ...
The data capture individuals trained as scientists and engineers who are working outside their field of training as well as, until quite recently, individuals with doctoral degrees outside SHE. Thus the linguist who received a PhD in English but is now working in an information tech-nology field was included in the survey until financial considerations recently led National Endowment for the Humanities (NEH)
|
From page 51... ...
The sampling frame for the NSCG is drawn from all college-educated individuals in the most recent decennial census regardless of occupation reported in the census. Follow-up biennial surveys include college-educated individuals trained and/or working in science and engineering.
|
From page 52... ...
Data are released at the aggregated level. Broadly speaking, from the six sources described above we are able to obtain information on the training and deployment of individuals working in S&E occupations as well as individuals trained in S&E occupations.
|
From page 53... ...
We exclude individuals reporting military employment and those who report that they are retired or out of the labor force.
|
From page 54... ...
SOURCE: Survey of Doctorate Recipients, NSF, 1973-1993.
|
From page 55... ...
The sectors supposedly excluded from "other" across all periods are construction, manufacturing, mining, transportation, communication and utilities, wholesale and retail trade, and finance, insurance, and real estate. In 1991 the industrial classification was no longer done by coders but instead by the respondent.
|
From page 56... ...
Many of the changes noted above, however, undoubtedly reflect changes in the deployment of this portion of the workforce and we could undoubtedly learn something about these changes if these data were readily available by geographic location. The blurring of boundaries between industry and academe and the extent of knowledge spillovers from academe to industry and vice versa make
|
From page 57... ...
Not only do new PhDs bring new ideas, but they help to build and maintain effective networks between industry and academe. This raises the question of whether data on PhDs can shed light on changing patterns of deployment of new PhDs.
|
From page 58... ...
We have little information on non-salary components of income, including stock options. More importantly, we have no indication of the respondents' productivity, as measured either by article counts and the citations associated with these articles or by patent counts.22 Neither do we have information on the productivity of the firm for which the in-dividual works, as measured by traditional indicators of firm per-formance.
|
From page 59... ...
SECTION IV. LESSONS LEARNED FROM THE STUDY OF BIOTECHNOLOGY By far the best example of what can be learned by examining linkages based on human resource data comes from the study of biotechnology firms.
|
From page 60... ...
· The higher the quality of the star, the shorter is the time that the star remains at a university before moving into the biotechnology industry, other things being equal (Zucker et al., 1997~. Stephan's research focused on biotechnology firms that made an initial public offering during the hot market of the early 1990s.
|
From page 61... ...
The work of Zucker and Darby and of Stephan shows the richness of results that can be obtained by linking data on scientists to indicators of their productivity such as citations and then linking this information either directly or by geographic indicator to firm data. No other industry appears to have garnered such attention and for no other industry have such intricate linkages based on human resource data been constructed.24 SECTION V
|
From page 62... ...
papers to 41 percent. Increased intersectoral collaboration is occurring in the United States as well (National Science Board, 1998, pp.
|
From page 63... ...
address rose from 9 to 16 percent during the period 1981-1995 (National Science Board, 1998, Table 5-53~. Bibliometric research holds remarkable promise for using human resource data to study innovation if links can be made between biblio-metric information and data collected in such surveys as the SDR with files from funding agencies concerning the amount and source of research support.
|
From page 64... ...
More recently, Narin collaborated with Deng and Lev (Deng et al., 1999) to demonstrate how the use of patent citation information adds to our understanding of the performance of firms in capital markets using such measures as stock returns and market-to-book ratios.
|
From page 65... ...
The latter change reflects an increased reliance on external R&D, increased collaboration in the development of new products and processes, a decentralization of in-house R&D activities, and the movement of innovative activities to functions in the firm typically not thought of as being drivers of innovation. These changes mean that traditional indicators of R&D as well as the traditional unit of analysis, the firm, are less relevant to the study of innovation than they once were.
|
From page 66... ...
For example, the deployment data show a change in industrial mix that R&D data support but fail to fully capture. These trends could be more clearly discerned if the firm address were carefully coded.3~ We also find that the HR data provide insight into the movement of innovative activities to non-A&D functions in the firm.
|
From page 67... ...
1991. "Research Productivity Over the Life Cycle: Evidence for Academic Scientists." American Economic Review, 81: 114-32.
|
From page 68... ...
1998. The Role of Firm Capabilities in the Evolution of the Laser Industry.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.