- Email: [email protected]
The vertical transfer of technological know-how in the navy research and development community
THE VERTICAL TRANSFER OF TECHNOLOGICAL KNOW-HOW IN THE NAVY RESEARCH AND DEVELOPMENT COMMUNITY CRAIG GALBRAITH* Purdue University
GREGORY MERRILL California State University
KEN CAMPBELL Naval Ocean Systems Command
This study examines a variety of organizational factors which affect the successful vertical transfer of technological know-how within the Navy defense R&D community. In particular, this study explores the “middle ground” of vertical transfer, that is, from the exploratory research stage of the innovation cycle to that of directed research and engineering for fielded systems. Analysis of data from 342 Navy research centers suggests that factors associated with both technology provider and technology user organizations influence the success of technology transfer; however, the data also suggests that the role of the technology linker may actually be counterproductive. Little evidence is provided, however, to suggest that these relationships are technology dependent.
As the global economy becomes increasingly technology driven, questions of technology management take on a new importance. This fact is certainly not lost on strategic management theorists as technology management is now considered a fundamental and inseparable principle of the modern strategic management paradigm (e.g., Van Gunsteren, 1987). As the National Research Council defines it, technology management is, “the linking of
*Direct all correspondence West Lafayette, IN.
to: Craig Galbraith,
Krannert Graduate
School of Management,
Purdue University,
The Journal of High Technology Management Research, Volume 2, Number 1, pages 15-33 Copyright 0 1991 by JAI Press Inc. All rights of reproduction in any form reserved. ISSN: 1047-8310
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engineering, science, and management disciplines to plan, develop and implement technological capabilities to shape and accomplish the strategic and operational objectives of the firm” (1987: 9). One area of special concern is technology transfer; that is, the process by which technological know-how is exchanged between various organizations and industry sectors. This study explores the importance of different organizational and technological factors in contributing to successful technology transfer. The setting for this study is the transfer of technological know-how from Navy R&D laboratories and private sector technology providers to 342 technology centers within four key Department of Defense (DOD) Naval technology user organizations. In particular, we address technology transfer at the “middle ground” of the research/development spectrum, that is, between targeted research, exploratory development, and advanced development-an area that the American Association of Engineering Societies (1987) has identified as having received the least amount of research attention during the last decade. TECHNOLOGY
TRANSFER
The Federal Council for Science and Technology defines technology transfer as, “the process by which existing research is transferred operationally into useful processes, products, or programs that fulfill actual or potential public or private needs” (1975: v). Technology transfer questions can be considered under two separate dimensions: (a) the relationship the technology provider and technology user organizations share with each other, and, (b) the mode by which the knowledge is provided to the potential technology user. Technology transfer can be either horizontal or vertical. Teece (1977) defines horizontal transfer as the transfer of (similar) technical know-how from one project to another. The scope of horizontal transfer can range from intra-organization transfer (such as from one corporate division to another) to inter-sectoral (such as from the public sector to the private sector or vice versa). Of particular interest to many researchers and governments alike is the process of international horizontal technology transfer, especially between technically advanced countries and those less developed. In contrast, vertical transfer is the transfer of know-how between the various stages of the innovation cycle, for example, from basic research to applied research to engineering. An often asked question related to the vertical transfer of technology is, “How do we get technological know-how from the research lab into viable commercial applications ?,’ Similarly, vertical transfer issues can range from intra-organizational, such as transferring knowledge from a firm’s R&D lab to its engineering department, to inter-sectoral, such as the transfer of basic university research to the private sector for possible introduction into the marketplace. The mode by which technical know-how is passed to the recipient is an additional consideration. Knowledge can be passed to the recipient “passively,” “semi-actively,” or “actively” (Mogavero & Shane, 1982; Talaysum, 1985; Weijo, 1987). The passive mode of technology transfer is essentially a user-driven approach to the technology adoption process where the potential user must seek-out relevant information. Typical mechanisms supporting the passive mode are published research articles, technical reports, and other archival material that are placed into the potential user’s search domain. The users,
17
The Vertical Transfer of Technological Know-How
+
Organization
q
Project
Technology User
4
-+I
i Capacity
Willingness
I
I+
I-
Reward
FIGURE
1. Composite Model of Technology Transfer (Creighton, Jolly, and Buckles, 1985)
searching various sources, hopefully locate relevant materials for their specific requirements. The underlying assumption of the passive mode is that potential users have at least some elementary familiarity and competence with the subject in order to carry on a profitable search (Dorf, 1988). While the passive mode often minimizes the cost of disseminating know-how for the technology provider, the potential user may incur substantial transactional resource costs associated with the search process (Kay, 1984; Teece, 1977, 1985). With the intervention of a transfer agent, or what has become known as a “technology linker”, the mode of transfer becomes semi-active (Mogavero & Shane, 1982). The transfer agent, who can be a member of the technology provider organization, the technology user organization, or an independent organization, screens available pertinent information, eliminates redundancies, and in some cases, may detect erroneous information. The agent then transmits this more manageable body of information to potential users, thus providing a communications conduit between technology source organizations and technology user organizations. In the active mode, however, the transfer agent goes beyond information collection and communications to actual involvement in
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technology development on the source side, or demonstrating technology solutions on the user side. Recent research attempting to identify characteristics of successful linkers suggest that they share many of the same characteristics with successful entrepreneurs (Creighton, Jolly, & Denning, 1972; Essoglou, 1985; Wolf, 1984). Based upon this, or similar paradigms, a number of authors have suggested general models of technology transfer, both at the macro-level in attempting to explain technology adoption within nations (Godkin, 1988; Karagozoglu & Brown, 1986) and between nations (Teece, 1985), and at the micro-level between sectors and organizations (Boyle, 1987; Dorf, 1988; Sirinaovakul & Czajkiewicz, 1988). Creighton, Jolly, and Buckles (1985), for example, summarize much of the prior micro-level research in suggesting a composite model of technology transfer success for the defense environment (Figure 1). In this model, the formal or procedural elements are those of organizational structure, procedures of technology project selection, quality of technical documentation, and ease of access to the physical channel of information flow. Informal factors are those of linking mechanism, technical capacity and credibility of organizations, willingness to accept innovative ideas, and the personal reward system. Creighton, Jolly, and Laner (1985) provide a review of twenty-four different research studies sponsored by the Naval Postgraduate School which directly support the positive effect of one or more of the above factors in contributing to technology transfer success within the Navy environment. Unfortunately most of these empirical studies have relied on small sample studies of single (or few) technologies. Other empirical research investigating inter-organizational technology transfer have identified a number of additional considerations such as organizational integration and size (e.g., Kimberly & Evanisko, 1981; Moth & Morse, 1977), power elites (Kanter, 1983), top management influences and technology and task-related skills (Leonard-Barton & Deschamps, 1988).
THE STUDY
CONTEXT:
NAVY DEFENSE
TECHNOLOGY
Effective technology management is critical to any nation’s defense; for the U.S. (and NATO) it takes on even greater proportions given the defense community’s stated strategy of employing technological superiority to offset Soviet numerical superiority. Yet Soviet technology is not static either. Significant recent advances have been made in a number of Soviet military technologies, such as stealth capabilities and quiet submersible propulsion. It is widely recognized that a key to future technology-based defense strategies is the need to rapidly accelerate the transfer of technology from the nation’s R&D laboratories into existing and emergent DOD systems (Defense Science Board, 1987; Schaefer, 1987). However, in spite of seemingly massive DOD and Congressional efforts to maximize the flow of technical know-how within the defense community, there is increasing evidence that serious problems exist. A recent Office of Technology Assessment (1988).study, for example, expressed concern over the apparent lengthening of time required to translate laboratory advances into fielded systems, a fact also identified in a similar Defense Science Board (1987) report. This latter report also singled out the Navy from the other military branches in that the Navy has located its technology based management and source institutions farthest from its technology user and procurement centers.
The Vertical Transfer of Technological Know-How
19
Figure 2 presents a simplified view of the process by which the DOD transforms innovative new concepts and ideas into fielded equipment and systems. This multi-stage technology flow pattern is referred to as the Defense Research, Development, Test, and Evaluation (RDT&E) process. The first stage, 6.1 research, represents the development of a store of knowledge which is generated by research in understanding and defining the laws of nature, providing fundamental knowledge upon which future development may occur. The second stage, 6.2 exploratory research, represents research that involves the development and evaluation of the feasibility and practicability of new technological concepts. The sum of 6.1 and 6.2 research constitutes what is known as the “Defense Technology Base.” Proof of design concepts and some prototyping represents the third stage, 6.3 advanced development. This stage experimentally demonstrates the workability of designs and identifies the range of necessary adjunct and supporting technologies. The fourth stage in the RDT&E process is 6.4 engineering development and 6.6 operational system development.’ This stage supports the production engineering, testing, and actual procurement of equipment and systems. Figure 3 depicts the provider/user relationships within the Navy research and development community. In general, this community can be divided into technology providers and technology users. Technology providers are generally responsible for 6.1 and 6.2 research, the Navy portion of the Defense Technology Base. Technology providers can be either “in-house,” government-owned/government-operated (GOGO) Navy laboratories, or “out-of-house” centers. In-house laboratories are the primary repository of military related scientific knowledge and technology, employing over 17,000 scientists and engineers in 1987 with a budget over $4 billion. The technical staffs of in-house laboratories provide a source of advice and consultation available to all Department of Navy managers. The primary out-of-house technology providers to the Navy are private sector contractors such as Hughes, General Electric, and General Dynamics, and universities working either under direct contract or supported by Independent Research and Development (IR&D) grants. Other non-Navy government laboratories, such as NASA, the Army and Air Force R&D laboratories, and the National Institute of Standards and Technology, provide limited amounts of technology support and are also considered out-of-house centers for the Navy. Technology users are generally responsible for execution of the advanced development, engineering development, and operational systems development stages in the RDT&E process. The primary responsibility for the incorporation of technology know-how into new equipment and systems resides within three major Navy Systems Commands: the Naval Sea Systems Command (NAVSEA), the Naval Air Systems Command (NAVAIR), and the Space and Naval Warfare Systems Command (SPAWAR). NAVSEA has development and acquisition responsibility for surface ships, submersibles, propulsion, shipboard combat systems, and explosive ordnance. NAVAIR is involved in material support needs of Naval aircraft and air-launched weapon systems, as well as associated electronic components. SPAWAR provides systems which support command, control, and communications, undersea and space surveillance, electronic warfare, and intelligence collection systems. In addition, separate from the Department of Navy, the Defense Advanced Research Projects Agency (DARPA) has been gaining increasing influence over certain phases of Navy system development-a fact indicated by recent Congressional action
Base
6.1 Research
Develop Knowledge
~Develop
Base
Technology, Concepl
6.2 Exploratory Development
Examfne
Effort
FIGURE 2. Navy Research,
Technology
-
Process
6.4 Engineering Development and 6.6 Operational Systems Development
DW3lOP Advanced systems
Test and Evaulation
6.3 Advanced Development
Demonstrate System Feasibility
Development,
+
Fielded Sys terns
FIGURE
Government
6.1 Research
Other
Technology
3. Navy Technology
6.2 Exploratory Development
Laboratories
Providers
R
6.4 Engineering Development and 6.6 Operational Systems Development
NAVSEA/NAVAI
Users
Provider and User Organizations
6.3 Advanced Development
1
Technology
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assigning DARPA as the lead agency in conceptual development of an advanced nextgeneration submarine. Under its federal charter, DARPA is actually a hybrid agency in that it operates within a broad spectrum of development (typically “high risk-high return” technologies) from basic research to advanced development and testing as designated by the Secretary of Defense. As shown by Figure 3, DARPA lies more toward the basic research end of the technology user spectrum (and in many cases infringes upon 6.2 research); SPAWAR, which tends to deal mostly with 6.3 and some 6.4 development is somewhere in the middle; while NAVSEA and NAVAIR, responsible for mostly 6.4 and 6.6 development, are more at the engineering and procurement end of the user spectrum. Essentially, Navy technology user organizations define “what” needs to be done to accomplish a particular mission or objective, while Navy and non-Navy technology provider organizations define “how.” Therefore, with the exception of perhaps some DARPA projects, the flow of technical know-how presented in Figure 3 represents vertical technology transfer, both ins-organi~tion~ (Navy labs to Navy users) and inter-organizational (Private/non-Navy Government labs to Navy users). One controversial issue, hotly debated in a variety of Congressional, academic, and defense forums, is whether or not private sector R&D laboratories are better and more efficient providers of technical know-how than public R&D laboratories-the classic “biggest bang for the buck” ~gument. While there is a large volume of literature to suggest that there are both similarities and differences between public and private organizations at the broad level (see Ring and Perry, 1985, for a review of this literature), much less is known about public/private differences in the specific area of R&D activity. In one important study addressing the technology issue, Bozeman (1987) argues that public R&D organizations probably do better at producing non-market oriented or generic technologies while private R&D organizations may do better at tangible, market oriented products. Bozeman is quick to point out, however, that a high degree of “sector blurring” has occurred in the nation’s R&D labs. As a case in point Oak Ridge National Laboratory is a government owned-contractor operated (GOCO) organization managed by the Department of Energy. In fact, when examining the source of funds for 829 public and private R&D organizations, Bozeman noted that only 40% could clearly be labelled either public or private, while the remaining 60% were actually hybrid organizations. Given the above discussion, three research questions were developed to guide the analysis in this study: (1)
Do various technology user organizations perceive any difference between private sector and public sector R&D labs in providing innovative new technologies?
(2)
What factors or ch~a~te~stics of technology provider and technology zations contribute to successful technology transfer?
(3)
Does the technology technologies?
transfer
process
differ
between
different
user organitypes
of
VARIABLES As previously mentioned, several authors have suggested models identifying various organizational factors or characteristics that they believe contribute to, or inhibit, successful
The Vertical Transfer of Technological Know-How
23
technology transfer. In general, these factors can be classified into three broad categories: characteristics of the technology provider organization, those of the technology user organization, and those of the technology. Building on work by Creighton et al. (1985), Leonard-Barton and Deschamps (1988), and Teece (1977) the following elements are examined in this study.
Technology Provider Organization 1. Credibility. Measures the perceived technical ability and reliability of the technology provider organization. Credibility is a perceived state of value; in an uncertain environment where risk is high, a provider organization lacking in technical credibility may have difficulty convincing potential users to accept and adopt innovative ideas. of the technology provider to the 2. R&D Selection. Measures the responsiveness needs of potential technology users when selecting new R&D projects. Since many defense projects are both extremely complex and specification driven, technology providers that actively incorporate the stated needs of potential users into their R&D project selection process may enhance the overall acceptance of the resulting technology by potential users. Measures the clarity of technical documents. The quality of tech3. Documentation. nical documentation has been identified in a number of studies as a critical element in the diffusion of technology. For example, if the documentation of an original piece of information is made in the language of potential users, the utilization of that know-how may be greatly facilitated. by 4. Accessibility. Measures the ease of access to the physical channels/documents which technology information flows. Technology development may require an open information exchange process between provider and user organizations; on the other hand, easy access to technology developers may actually hinder technology development if specification changes and unproductive updates are constantly demanded by the future user. Measures the degree that information sources are well defined 5. Channel/Linker. and repeatable. Related to the accessibility of information channels is the repeatability of those channels; that is, are the sources of communication in the provider organization identifiable and maintained over the long-term, or are they constantly changing in which case communication relationships may be harder to establish. In all Navy laboratories this channel is maintained, at least in part, by formal “linkers.” Technology
User Organization
1. Support. Measures the immediate informal organizational support for the investigation and use of new technologies. The level of informal support received by personnel within the user organization, such as encouragement and status, may impact upon their ability and desire to search out and acquire new technologies.
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2. Interaction. Measures the degree of interaction the research team has with other internal research personnel to exchange info~ation. Technology diffusion may not only require know-how exchange between provider and user organizations but also discussion among departments or personnel within the user organization. New ideas useful to one team’s project may be brought to their attention by members of other teams during intra-organizational discussions. 3. Ca~aci~. Measures the technical capacity and skill to absorb and understand relevant technology know-how. Just as the perceived technical capability (credibility) of the provider organization to transmit useful information is important, the technical capability of the user organization to receive that information may be equally critical to the transfer process. 4. ~ilzingness. Measures the personal desire of research team members to actively pursue or seek-out innovative technology. The greater the innovative culture, reflected by the personal desire to seek out new technologies may increase the probability that viable technologies will be found, transferred and implemented. 5. Reward. Measures the existence of a personal reward process, reflected by quicker promotions, for successful technology transfer. Related to informal organizational support, personal financial reward and promotion represents the formal element of support for innovative activity within the technology user organization. It is hypothesized that, ceteris paribus, each of the ten factors described have a positive impact on technology transfer success.
TECHNOLOGY
above will
TYPES
The Navy utilizes a formal technology classification scheme. Due to certain security requirements, however, some specific technologies are grouped together for this study. Seven different technology classes are examined. Hardware technology includes massive parallel processing, connection machines, and high-speed computations engines. Software engineering technology includes large-scale algorithmic processing, protocol communication, natural languages, artificial intelligence and expert systems. Fiberoptics technology includes fiber transmission lines, optical sources and components. Autonomous vehicle technology includes guidance and control, and automatic targeting. Space-bused systems includes surveillance and upper atmospheric weapons delivery. Command and control technology includes application of statistics and logical elements, and computer-aided systems for command decisions. Advanced sensor technology includes transducers and electromagnetic devices, and navigation sensors. DATA AND SAMPLE Questionnaires were mailed to 755 senior managers at the four primary Navy technology user organizations, NAVAIR, NAVSEA, SPAWAR, and Navy related departments at DARPA. The research was authorized by the Director of Navy Laboratories by direction
The Vedcal
Transfer of Technological Know-How
25
of the senior Commander; a letter to this effect was included with the questionnaire. A senior manager is typically responsible for a team of 5 to 20 researchers, engineers, and technicians, and has a particular, specific technology assignment. These research teams then interact with various technology providers to acquire appropriate technology for their specific assignment. Managers were identified by internal directories. Data collected on the questionnaire were: (a) frequency of contact with each of 13 different Navy technology providers: these were the David Taylor Research Center, Naval Air Development Center, Naval Civil Engineering Laboratory, Naval Coastal Systems Center, Naval Ocean Systems Center, Naval Personnel Research and Development Center, Naval Research Laboratory, Naval Surface Warfare Center, Naval Training Systems Center, Naval Underwater Systems Center, Naval Weapons Center, Office of Naval Research, and the Office of Naval Technology; (b) frequency of contact with a variety of non-Navy and private-sector laboratories; (c) technology class of primary involvement; (d) ratings of the technology user’s immediate organization on the five factors: support, interaction, capacity, willingness, and reward; (e) ratings of (i) primary Navy technology provider’s organization and (ii) primary private sector technology provider, on the following characteristics: credibility, R&D selection, documentation, accessibility, channel/linker; and (f) an assessment of (i) user’s success in acquiring “innovative” technology and (ii) the various providers’ success in supplying “innovative” technology. Content validity of the questionnaire was established by a panel of five senior managers at the Naval Ocean Systems Center (NOSC). All panel members had previous formal association with one or more of the technology user organizations. Each question was judged concerning the intended meanings of the responses at the scale extremes for that item, as well as the overall meaning of the question (Bailey, 1978). Questions dealing with items “d” through “f’ were measured in the following manner: for each item under investigation a single statement was provided which required a response on a six point scale (strongly disagree with the statement to strongly agree with the statement). For example, for the Navy R&D laboratory “accessibility” factor respondents were asked to evaluate the statement, “Navy labs allow easy access to needed technical documentation and information.“; items “a” through “c” above required responses based upon a five point scale. The completed questionnaire was then pre-tested with an additional sample of 10 technology user senior managers for clarity and improvements regarding the various items. Although the Navy technology provider and user organizations in this study are all government owned and operated (GOGO), they also all operate under the Navy Industrial Fund (NIF) accounting system. Implemented in the early 198Os, the NIF accounting system attempts to replicate a market system within the naval community by requiring Navy technology providers to identify specific Navy customers and bill for reimbursement of incurred costs. Likewise, the Navy customer is allocated a certain budget, and can therefore, with certain limitations, “shop around” for services. RESULTS Of the 755 original questionnaires, 350 were returned. However 8 stated they did not seek technology from outside sources, thus leaving 342 usable responses, or a 45%
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response. DARPA had the lowest response rate of 29%, while NAVSEA had the highest with 54%. Navy vs. Private Sector R&D Labs One interesting issue is whether technology user organizations perceived significant differences between Navy R&D technology provider laboratories and those of the private sector. Table 1 shows the user perceptions of Navy versus private sector laboratories for the five technology provider factors as well as perception of success in providing innovative technology. Ratings by each of the four technology user organizations are provided. Table 1 suggests several things. First, the three Navy technology user organizations all felt that the Navy laboratories did a much better job in providing access to technical materials and personnel. This is not surprising given the intra-government relationship that exists between the Navy technology users and the Navy laboratories; technology users can readily use internal communications to quickly discuss matters with their “counterparts over in the lab,” sometimes circumventing formal bureaucratic procedures and normal communication channels. Private sector technology providers often have a real, or at least perceived, set of security and other contractual obligations which may inhibit the free flow of information to potential and actual technology users. DARPA, however, perceived the private and public sectors about equal in accessibility which is not surprising given that DARPA has a much higher percentage of employees with previous ties to the private sector. Second, on the average, NAVSEA and NAVAIR rated Navy technology providers the highest on the five provider factors, while DARPA and SPAWAR provided the highest ratings for the private sector. A possible explanation for this phenomenon can be seen in Figure 3. Both DARPA and SPAWAR are typically more involved in the conceptual/ exploratory phase of the research cycle (and rated the private sector significantly higher on the provider factors), while NAVSEA and NAVAIR are more end product/applied development oriented (and tend to rate the public/navy labs higher on the provider factors). This is somewhat contradictory to the previously cited suggestion by Bozeman (1987); our findings might suggest that private sector technology providers are viewed more favorably in supplying non-market oriented early-stage generic technologies, whereas Navy labs are viewed more favorably by those user organizations typically concerned with well-defined and established technologies. Third, on the average, the technology users rated private sector R&D organizations most successful in providing “innovative technology” that meets the user’s needs. One possible explanation is that the different technology users interact with different sets of private sector technology suppliers. However, an examination of the list of private sector technology providers for each of the four technology users revealed, with few exceptions, all four users interacted with essentially the same set of Fortune 500 firms, and many of the smaller firms. As an exception, NAVSEA was the only user to work with one particular shipbuilding firm, and did substantially more work with Westinghouse Corporation than either NAVAIR, SPAWAR, or DARPA.
The Vertical Transfer of Technological Know-How
21
28
Factors Influencing
HIGH TECHNOLOGY
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MANAGEMENT
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Vol. ~/NO. l/1991
Transfer Success
To examine the effect various factors have upon technology transfer success a multiple regression model was estimated. The dependent variable was technology transfer success, measured by the mean of the two success questions identified under item “f” above. The predictor variables were the five technology provider factors and the five technology user factors. Because of limited sample size in some technology classes, the five provider factors were computed as a weighted average (weighted by frequency of interaction) of the ratings for Navy labs and private sector labs. Table 2 presents the intercorrelations for all variables. Regression coefficient estimates were by ordinary least squares (OLS) using the SPSS/ PC+ statistical software; all ten predictor variables were entered into the equation. Multicolinearity did not appear as a major problem (based on tolerance scores), but to minimize possible pooling problems, and to explore whether there were significant differences in the transfer process between different technologies, individual equations for each of the seven technology groups were estimated. As previously mentioned, technologies were classified as computer hardware technology (COMP), software technology (SOFT), communications technology (COMM), fiberoptics technology (OPTICS), advanced sensor technology (SENSOR), space-based systems (SPACE), and autonomous vehicle technology (AUTO). Table 2 shows the estimated unstandardized coefficients for each of the technology area regression models. With the possible exception of space-based systems technology, the various technology groups appear to share somewhat similar results.2 For the technology provider organization, the user’s perception of the provider organization’s credibility (CREDIBILITY) and, with one significant exception (that being space-based systems technology), the degree that the provider incorporates user needs into new R&D project selection (R&D SELECTION) show significant positive impacts on the successful transfer of technology to user groups. The exception found for R&D selection in the space-based systems area can possibly be explained by the fact that this technology is often ill-defined in terms of established standards, and haunted by changing legislative expectations and funding requirements. In addition, there remain nagging questions regarding launch capabilities and schedules in the U.S. space program. Under such conditions a “shotgun” approach to technology development by provider organizations may be more productive than waiting for wellorganized project specifications to flow from the various user groups. Another significant provider organization factor is the channel or linker element (CHANNEL/LINKER) which measures the repeatability of the information conduit. Interestingly, this factor consistently shows a significant negative relationship with transfer success in the regression analysis. Two, albeit somewhat related, explanations for this phenomenon were provided by several of the respondents. First, a well defined set of linker mechanisms that a user organization must work with may actually delay information transfer between organizations if too much information is being funnelled through the conduit-a type of “data bottleneck”; second, a well defined and repeatable information source will inevitably acquire a high degree of public exposure as a “gate-keeper,” and thus organizational power within the system. Any bias, whether by favoring a particular technology, project, or organization, may inhibit the broad flow of technological know-how. The negative sign on the CHANNEL/LINKER factor is consistent across the seven technology areas.
The Vertical Transfer of Technological Know-How
29
COMP
0.450 129
RZ Nb 0.480 95
0.510
0.217** -0.146% 0 209** 0:250** 0.213””
0.026 0.308*** 0.005 - 0.065 -0.170”
SOFT
0.431 84
0.124
0.246** -0.166 0.147 0.312”** 0.260***
0.122 0.044 0.125 0.113 -0.256**
COMM
0.444 39
0.906
0.197* -0.014 -0.151 0.496** 0.257X
- 0,037 - 0.085 0.236 0.006 -0.081
Technology Class oprrcs
0.474 74
0.269
0.365*** 0.035 0.122 0.076 0.173””
0.184* 0.028 - 0.056 0.120 -0.146*
SENSOR
0.528 20
-0.300
0.347* 0.069 0.192 0.207 0.093
0.490* - 0.461* - 0.259 0.285 -0.056
SPACE
0.652 36
- 1.220
0.216* 0.055 0.101 0.170 0.143*
0.420X 0.137 - 0.055 0.489** - 0.476”*
AUTO
~Unstaudardized coefficients are reported; dependent variable is “technology transfer success.” bin several cases respondents indicated they participated extensively in more than one technology class. In such situations the response was counted in each of the technology groups identified. Thus, the total sample for the regression models exceeds the 342 original responses. Two-tailed t-test (* = p < .lO; ** = p < .05; *** = p < .Ol).
0.248
0.255*** -0.165* 0.216”” 0.253”” 0.244***
0.162* 0.156* 0.108 - 0.082 -0.262***
*
Intercept
SUPPORT INTERACTION CAPACITY WILLINGNESS REWARD
~ec~~ient~actors
C~DIBILITY R&D SELECTION D~U~ENT ACCESSIBILITY CHANILINKBR
Provider Factors
Predictor Variables
TABLE 3 Contribution of Factors to Transfer Successa
The Vertical Transfer of Technological Know-How
31
The technology provider organization factors of documentation and accessibility are generally statistically insignificant in the present study; accessibility is very significant for the autonomous vehicle technology area, however. The technology user organization factors of SUPPORT, WILLINGNESS, and REWARD are all statistically significant and positively related to transfer success as hypothesized. INTERACTION, on the other hand, exhibits a slight negative relationship with success-time invested in interacting with other individuals in the same organization may actually distract from the project at hand. The model of technology transfer used in this study explains about half of the observed variance in technology transfer success with R2s ranging from 0.45 to 0.65.
CONCLUSIONS This study explores the mechanism of successful technology transfer within the Navy research and development community, and suggests several important findings. First, technology transfer success does appear to be a function of both technology provider organization factors and technology recipient organization factors. Some of the hypothesized provider organization relationships, such as the technical credibility and sensitivity in R&D project selection by the provider, appear to have a significant and positive effect on technology transfer success. Similarly, organizational support and personal reward for transfer performance by the user organization have a positive impact on the process. The major deviation from received theory in our analysis is the negative effect of the Channel/Linker element. Further investigation in this area may support our contention that the linker may, in fact, create an information bottleneck within the transfer process. Second, with the possible exception of space-based systems, the relationship between these organizational factors does not appear to be technology dependent. Finally, in general, the Navy technology user community views the private sector as being more successful at providing innovative and usable technology than the public sector. In addition, this perception becomes more apparent as the technology moves toward the exploratory end of the research cycle. It is recognized that the target population for this study represents a very specialized category of the nation’s R&D activity. The parameters within which a federal organization is free to act are well established by law or regulation. However, while acknowledging the somewhat restrictive behavior imparted on the government agencies examined in this study, the fundamental managerial and organizational characteristics discussed in this study should be relatively common between all modem technology-driven organizations involved in the “middle ground” of vertical technology transfer.
NOTES 1.
We have omitted 6.5 funding from consideration, as such funding is for management expenses,
2.
not for technology development. A Chow test comparing the pooled results against the individual technology results suggest that there are no significant differences in various model estimates (FG6477 = 0.45).
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REFERENCES American Association of Engineering Societies. 1987. Management of technology: the key to America’s competitive future, 6. Bailey, K. 1978. Methods of social research. New York: The Free Press. Boyle, K. 1987. Technology transfer between universities and the U.K. offshore industry. IEEE Transactions on Engineering Management, EM-33: 33-42. Bozeman, B. 1987. All organizations arepublic: bridging public andprivate organization theories. San Francisco: Jossey-Bass. Creighton, J., Jolly, J., & Buckles, T. 1985. The manager’s role in technology transfer. Journal of Technology Transfer, 10: 65-81. Creighton, J., Jolly, J., & Denning, S. 1972. Enhancement of research and development output utilization eficiencies: linker concept methodology in the technology transfer process. Monterey, CA: Naval Postgraduate School. Creighton, J., Jolly, J., & Laner (Eds). 1985. Technology transfer: a think tank approach to managing innovation in the public sector. Monterey, CA: Naval Postgraduate School. Defense Science Board. December 1987. Report on the defense science board 1987 summer study on technology base management. Washington DC: U.S. Government Printing Office, 22. Dorf, R. 1988. Modelsfor technology transferfrom universities and research laboratories. Technology Management Publication, TM 1: 302-312. Essoglou, M. 1985. Technology transfer for enhanced research development, test, and evaluation effectiveness. In Creighton, J., J. Jolly, & S. Laner (Eds.), Technology transfer: a think tank approach to managing innovation in the public sector, pp. 77-95. Monterey, CA: Naval Postgraduate School. Federal Council for Science and Technology. 1975. Federal technology transfer: directory of programs, resources, contact points. Washington DC: U.S. Government Printing Office, 5. Godkin, L. 1988. The university’s role of technology transfer. Technology Management Publication, TM 1: 313-324. Kanter, R. 1983. The change masters: innovation for productivity in the american corporation. New York: Simon and Schuster. Karagozoglu, N., & Brown, W. 1986. A multilevel multiphase framework for viewing technological innovation. Journal of Technology Transfer, 10: 15-32. Kay, N. 1984. The emergentfirm: knowledge, ignorance and surprise in economic organization. London: Macmillan. Kimberly, J., & Evanisko, M. 1981. Organizational innovation: The influence of individual, organizational, and contextual factors in hospital adoption of technological and administrative innovations. Academy of Management Journal, 24: 689-7 13. Leonard-Barton, D., & Deschamps, I. 1988. Managerial influence in the implementation of new technology. Management Science, 34: 1252- 1265. Moth, M., & Morse, M. 1977. Size, centralization and organizational adoption of innovations. American Sociological Review, 42: 7 16-725. Mogavero, L., & Shane, R. 1982. What every engineer should know about technology transfer and innovation. New York: Dekker. National Research Council. 1987. Management of technology: the hidden competitive advantage. Washington DC: National Academy Press, 9. Office of Technology Assessment. March 1988. The Defense technology base: a special report. Washington DC: U.S. Government Printing Office, 4. Ring, P., & Perry, J. 1985. Strategic management in public and private organization: implications of distinctive contexts and constraints. Academy of Management Review, 10: 276-286.
The Vertical Transfer of Technological Know-How
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Schaefer, S. 1987. Technology application program management (TAPM): an Air Force logistics command strategy for technology transition. IEEE 1987 National Aerospace and Electronics Conference, 4: 1182-1187. Sirinaovakul, B., & Czajkiewicz, Z. 1988. A spatial d@ision model for advanced manufacturing technology. Technology Management Publication, TM 1: 291-301. Talaysum, A. 1985. Understanding the diffusion process for technology-intensive products. Research Management, 28: 22-26. Teece, D. 1985. Multinational enterprise, internal governance, and industrial organization. American Economic Review, 75: 233-238. Teece, D. 1977. Technology transfer by multinational firms: the resource costs of transferring technological know-how. Economic Journal, 87: 242-261. Van Gunsteren, L. 1987. Planning for technology as a corporate resource: a strategic classification. Long Range Planning, 20: 51-60. Weijo, R. 1987. Strategies for promoting technology transfer to the private sector. Journal of Technology Transfer, 11: 43-65. Wolf, W. 1984. Up-grading the caliber of linkage agent performance. Journal of Technology Transfer, 9: 25-37.
GREGORY MERRILL California State University
KEN CAMPBELL Naval Ocean Systems Command
This study examines a variety of organizational factors which affect the successful vertical transfer of technological know-how within the Navy defense R&D community. In particular, this study explores the “middle ground” of vertical transfer, that is, from the exploratory research stage of the innovation cycle to that of directed research and engineering for fielded systems. Analysis of data from 342 Navy research centers suggests that factors associated with both technology provider and technology user organizations influence the success of technology transfer; however, the data also suggests that the role of the technology linker may actually be counterproductive. Little evidence is provided, however, to suggest that these relationships are technology dependent.
As the global economy becomes increasingly technology driven, questions of technology management take on a new importance. This fact is certainly not lost on strategic management theorists as technology management is now considered a fundamental and inseparable principle of the modern strategic management paradigm (e.g., Van Gunsteren, 1987). As the National Research Council defines it, technology management is, “the linking of
*Direct all correspondence West Lafayette, IN.
to: Craig Galbraith,
Krannert Graduate
School of Management,
Purdue University,
The Journal of High Technology Management Research, Volume 2, Number 1, pages 15-33 Copyright 0 1991 by JAI Press Inc. All rights of reproduction in any form reserved. ISSN: 1047-8310
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HIGH TECHNOLOGY MANAGEMENT
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engineering, science, and management disciplines to plan, develop and implement technological capabilities to shape and accomplish the strategic and operational objectives of the firm” (1987: 9). One area of special concern is technology transfer; that is, the process by which technological know-how is exchanged between various organizations and industry sectors. This study explores the importance of different organizational and technological factors in contributing to successful technology transfer. The setting for this study is the transfer of technological know-how from Navy R&D laboratories and private sector technology providers to 342 technology centers within four key Department of Defense (DOD) Naval technology user organizations. In particular, we address technology transfer at the “middle ground” of the research/development spectrum, that is, between targeted research, exploratory development, and advanced development-an area that the American Association of Engineering Societies (1987) has identified as having received the least amount of research attention during the last decade. TECHNOLOGY
TRANSFER
The Federal Council for Science and Technology defines technology transfer as, “the process by which existing research is transferred operationally into useful processes, products, or programs that fulfill actual or potential public or private needs” (1975: v). Technology transfer questions can be considered under two separate dimensions: (a) the relationship the technology provider and technology user organizations share with each other, and, (b) the mode by which the knowledge is provided to the potential technology user. Technology transfer can be either horizontal or vertical. Teece (1977) defines horizontal transfer as the transfer of (similar) technical know-how from one project to another. The scope of horizontal transfer can range from intra-organization transfer (such as from one corporate division to another) to inter-sectoral (such as from the public sector to the private sector or vice versa). Of particular interest to many researchers and governments alike is the process of international horizontal technology transfer, especially between technically advanced countries and those less developed. In contrast, vertical transfer is the transfer of know-how between the various stages of the innovation cycle, for example, from basic research to applied research to engineering. An often asked question related to the vertical transfer of technology is, “How do we get technological know-how from the research lab into viable commercial applications ?,’ Similarly, vertical transfer issues can range from intra-organizational, such as transferring knowledge from a firm’s R&D lab to its engineering department, to inter-sectoral, such as the transfer of basic university research to the private sector for possible introduction into the marketplace. The mode by which technical know-how is passed to the recipient is an additional consideration. Knowledge can be passed to the recipient “passively,” “semi-actively,” or “actively” (Mogavero & Shane, 1982; Talaysum, 1985; Weijo, 1987). The passive mode of technology transfer is essentially a user-driven approach to the technology adoption process where the potential user must seek-out relevant information. Typical mechanisms supporting the passive mode are published research articles, technical reports, and other archival material that are placed into the potential user’s search domain. The users,
17
The Vertical Transfer of Technological Know-How
+
Organization
q
Project
Technology User
4
-+I
i Capacity
Willingness
I
I+
I-
Reward
FIGURE
1. Composite Model of Technology Transfer (Creighton, Jolly, and Buckles, 1985)
searching various sources, hopefully locate relevant materials for their specific requirements. The underlying assumption of the passive mode is that potential users have at least some elementary familiarity and competence with the subject in order to carry on a profitable search (Dorf, 1988). While the passive mode often minimizes the cost of disseminating know-how for the technology provider, the potential user may incur substantial transactional resource costs associated with the search process (Kay, 1984; Teece, 1977, 1985). With the intervention of a transfer agent, or what has become known as a “technology linker”, the mode of transfer becomes semi-active (Mogavero & Shane, 1982). The transfer agent, who can be a member of the technology provider organization, the technology user organization, or an independent organization, screens available pertinent information, eliminates redundancies, and in some cases, may detect erroneous information. The agent then transmits this more manageable body of information to potential users, thus providing a communications conduit between technology source organizations and technology user organizations. In the active mode, however, the transfer agent goes beyond information collection and communications to actual involvement in
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technology development on the source side, or demonstrating technology solutions on the user side. Recent research attempting to identify characteristics of successful linkers suggest that they share many of the same characteristics with successful entrepreneurs (Creighton, Jolly, & Denning, 1972; Essoglou, 1985; Wolf, 1984). Based upon this, or similar paradigms, a number of authors have suggested general models of technology transfer, both at the macro-level in attempting to explain technology adoption within nations (Godkin, 1988; Karagozoglu & Brown, 1986) and between nations (Teece, 1985), and at the micro-level between sectors and organizations (Boyle, 1987; Dorf, 1988; Sirinaovakul & Czajkiewicz, 1988). Creighton, Jolly, and Buckles (1985), for example, summarize much of the prior micro-level research in suggesting a composite model of technology transfer success for the defense environment (Figure 1). In this model, the formal or procedural elements are those of organizational structure, procedures of technology project selection, quality of technical documentation, and ease of access to the physical channel of information flow. Informal factors are those of linking mechanism, technical capacity and credibility of organizations, willingness to accept innovative ideas, and the personal reward system. Creighton, Jolly, and Laner (1985) provide a review of twenty-four different research studies sponsored by the Naval Postgraduate School which directly support the positive effect of one or more of the above factors in contributing to technology transfer success within the Navy environment. Unfortunately most of these empirical studies have relied on small sample studies of single (or few) technologies. Other empirical research investigating inter-organizational technology transfer have identified a number of additional considerations such as organizational integration and size (e.g., Kimberly & Evanisko, 1981; Moth & Morse, 1977), power elites (Kanter, 1983), top management influences and technology and task-related skills (Leonard-Barton & Deschamps, 1988).
THE STUDY
CONTEXT:
NAVY DEFENSE
TECHNOLOGY
Effective technology management is critical to any nation’s defense; for the U.S. (and NATO) it takes on even greater proportions given the defense community’s stated strategy of employing technological superiority to offset Soviet numerical superiority. Yet Soviet technology is not static either. Significant recent advances have been made in a number of Soviet military technologies, such as stealth capabilities and quiet submersible propulsion. It is widely recognized that a key to future technology-based defense strategies is the need to rapidly accelerate the transfer of technology from the nation’s R&D laboratories into existing and emergent DOD systems (Defense Science Board, 1987; Schaefer, 1987). However, in spite of seemingly massive DOD and Congressional efforts to maximize the flow of technical know-how within the defense community, there is increasing evidence that serious problems exist. A recent Office of Technology Assessment (1988).study, for example, expressed concern over the apparent lengthening of time required to translate laboratory advances into fielded systems, a fact also identified in a similar Defense Science Board (1987) report. This latter report also singled out the Navy from the other military branches in that the Navy has located its technology based management and source institutions farthest from its technology user and procurement centers.
The Vertical Transfer of Technological Know-How
19
Figure 2 presents a simplified view of the process by which the DOD transforms innovative new concepts and ideas into fielded equipment and systems. This multi-stage technology flow pattern is referred to as the Defense Research, Development, Test, and Evaluation (RDT&E) process. The first stage, 6.1 research, represents the development of a store of knowledge which is generated by research in understanding and defining the laws of nature, providing fundamental knowledge upon which future development may occur. The second stage, 6.2 exploratory research, represents research that involves the development and evaluation of the feasibility and practicability of new technological concepts. The sum of 6.1 and 6.2 research constitutes what is known as the “Defense Technology Base.” Proof of design concepts and some prototyping represents the third stage, 6.3 advanced development. This stage experimentally demonstrates the workability of designs and identifies the range of necessary adjunct and supporting technologies. The fourth stage in the RDT&E process is 6.4 engineering development and 6.6 operational system development.’ This stage supports the production engineering, testing, and actual procurement of equipment and systems. Figure 3 depicts the provider/user relationships within the Navy research and development community. In general, this community can be divided into technology providers and technology users. Technology providers are generally responsible for 6.1 and 6.2 research, the Navy portion of the Defense Technology Base. Technology providers can be either “in-house,” government-owned/government-operated (GOGO) Navy laboratories, or “out-of-house” centers. In-house laboratories are the primary repository of military related scientific knowledge and technology, employing over 17,000 scientists and engineers in 1987 with a budget over $4 billion. The technical staffs of in-house laboratories provide a source of advice and consultation available to all Department of Navy managers. The primary out-of-house technology providers to the Navy are private sector contractors such as Hughes, General Electric, and General Dynamics, and universities working either under direct contract or supported by Independent Research and Development (IR&D) grants. Other non-Navy government laboratories, such as NASA, the Army and Air Force R&D laboratories, and the National Institute of Standards and Technology, provide limited amounts of technology support and are also considered out-of-house centers for the Navy. Technology users are generally responsible for execution of the advanced development, engineering development, and operational systems development stages in the RDT&E process. The primary responsibility for the incorporation of technology know-how into new equipment and systems resides within three major Navy Systems Commands: the Naval Sea Systems Command (NAVSEA), the Naval Air Systems Command (NAVAIR), and the Space and Naval Warfare Systems Command (SPAWAR). NAVSEA has development and acquisition responsibility for surface ships, submersibles, propulsion, shipboard combat systems, and explosive ordnance. NAVAIR is involved in material support needs of Naval aircraft and air-launched weapon systems, as well as associated electronic components. SPAWAR provides systems which support command, control, and communications, undersea and space surveillance, electronic warfare, and intelligence collection systems. In addition, separate from the Department of Navy, the Defense Advanced Research Projects Agency (DARPA) has been gaining increasing influence over certain phases of Navy system development-a fact indicated by recent Congressional action
Base
6.1 Research
Develop Knowledge
~Develop
Base
Technology, Concepl
6.2 Exploratory Development
Examfne
Effort
FIGURE 2. Navy Research,
Technology
-
Process
6.4 Engineering Development and 6.6 Operational Systems Development
DW3lOP Advanced systems
Test and Evaulation
6.3 Advanced Development
Demonstrate System Feasibility
Development,
+
Fielded Sys terns
FIGURE
Government
6.1 Research
Other
Technology
3. Navy Technology
6.2 Exploratory Development
Laboratories
Providers
R
6.4 Engineering Development and 6.6 Operational Systems Development
NAVSEA/NAVAI
Users
Provider and User Organizations
6.3 Advanced Development
1
Technology
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assigning DARPA as the lead agency in conceptual development of an advanced nextgeneration submarine. Under its federal charter, DARPA is actually a hybrid agency in that it operates within a broad spectrum of development (typically “high risk-high return” technologies) from basic research to advanced development and testing as designated by the Secretary of Defense. As shown by Figure 3, DARPA lies more toward the basic research end of the technology user spectrum (and in many cases infringes upon 6.2 research); SPAWAR, which tends to deal mostly with 6.3 and some 6.4 development is somewhere in the middle; while NAVSEA and NAVAIR, responsible for mostly 6.4 and 6.6 development, are more at the engineering and procurement end of the user spectrum. Essentially, Navy technology user organizations define “what” needs to be done to accomplish a particular mission or objective, while Navy and non-Navy technology provider organizations define “how.” Therefore, with the exception of perhaps some DARPA projects, the flow of technical know-how presented in Figure 3 represents vertical technology transfer, both ins-organi~tion~ (Navy labs to Navy users) and inter-organizational (Private/non-Navy Government labs to Navy users). One controversial issue, hotly debated in a variety of Congressional, academic, and defense forums, is whether or not private sector R&D laboratories are better and more efficient providers of technical know-how than public R&D laboratories-the classic “biggest bang for the buck” ~gument. While there is a large volume of literature to suggest that there are both similarities and differences between public and private organizations at the broad level (see Ring and Perry, 1985, for a review of this literature), much less is known about public/private differences in the specific area of R&D activity. In one important study addressing the technology issue, Bozeman (1987) argues that public R&D organizations probably do better at producing non-market oriented or generic technologies while private R&D organizations may do better at tangible, market oriented products. Bozeman is quick to point out, however, that a high degree of “sector blurring” has occurred in the nation’s R&D labs. As a case in point Oak Ridge National Laboratory is a government owned-contractor operated (GOCO) organization managed by the Department of Energy. In fact, when examining the source of funds for 829 public and private R&D organizations, Bozeman noted that only 40% could clearly be labelled either public or private, while the remaining 60% were actually hybrid organizations. Given the above discussion, three research questions were developed to guide the analysis in this study: (1)
Do various technology user organizations perceive any difference between private sector and public sector R&D labs in providing innovative new technologies?
(2)
What factors or ch~a~te~stics of technology provider and technology zations contribute to successful technology transfer?
(3)
Does the technology technologies?
transfer
process
differ
between
different
user organitypes
of
VARIABLES As previously mentioned, several authors have suggested models identifying various organizational factors or characteristics that they believe contribute to, or inhibit, successful
The Vertical Transfer of Technological Know-How
23
technology transfer. In general, these factors can be classified into three broad categories: characteristics of the technology provider organization, those of the technology user organization, and those of the technology. Building on work by Creighton et al. (1985), Leonard-Barton and Deschamps (1988), and Teece (1977) the following elements are examined in this study.
Technology Provider Organization 1. Credibility. Measures the perceived technical ability and reliability of the technology provider organization. Credibility is a perceived state of value; in an uncertain environment where risk is high, a provider organization lacking in technical credibility may have difficulty convincing potential users to accept and adopt innovative ideas. of the technology provider to the 2. R&D Selection. Measures the responsiveness needs of potential technology users when selecting new R&D projects. Since many defense projects are both extremely complex and specification driven, technology providers that actively incorporate the stated needs of potential users into their R&D project selection process may enhance the overall acceptance of the resulting technology by potential users. Measures the clarity of technical documents. The quality of tech3. Documentation. nical documentation has been identified in a number of studies as a critical element in the diffusion of technology. For example, if the documentation of an original piece of information is made in the language of potential users, the utilization of that know-how may be greatly facilitated. by 4. Accessibility. Measures the ease of access to the physical channels/documents which technology information flows. Technology development may require an open information exchange process between provider and user organizations; on the other hand, easy access to technology developers may actually hinder technology development if specification changes and unproductive updates are constantly demanded by the future user. Measures the degree that information sources are well defined 5. Channel/Linker. and repeatable. Related to the accessibility of information channels is the repeatability of those channels; that is, are the sources of communication in the provider organization identifiable and maintained over the long-term, or are they constantly changing in which case communication relationships may be harder to establish. In all Navy laboratories this channel is maintained, at least in part, by formal “linkers.” Technology
User Organization
1. Support. Measures the immediate informal organizational support for the investigation and use of new technologies. The level of informal support received by personnel within the user organization, such as encouragement and status, may impact upon their ability and desire to search out and acquire new technologies.
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2. Interaction. Measures the degree of interaction the research team has with other internal research personnel to exchange info~ation. Technology diffusion may not only require know-how exchange between provider and user organizations but also discussion among departments or personnel within the user organization. New ideas useful to one team’s project may be brought to their attention by members of other teams during intra-organizational discussions. 3. Ca~aci~. Measures the technical capacity and skill to absorb and understand relevant technology know-how. Just as the perceived technical capability (credibility) of the provider organization to transmit useful information is important, the technical capability of the user organization to receive that information may be equally critical to the transfer process. 4. ~ilzingness. Measures the personal desire of research team members to actively pursue or seek-out innovative technology. The greater the innovative culture, reflected by the personal desire to seek out new technologies may increase the probability that viable technologies will be found, transferred and implemented. 5. Reward. Measures the existence of a personal reward process, reflected by quicker promotions, for successful technology transfer. Related to informal organizational support, personal financial reward and promotion represents the formal element of support for innovative activity within the technology user organization. It is hypothesized that, ceteris paribus, each of the ten factors described have a positive impact on technology transfer success.
TECHNOLOGY
above will
TYPES
The Navy utilizes a formal technology classification scheme. Due to certain security requirements, however, some specific technologies are grouped together for this study. Seven different technology classes are examined. Hardware technology includes massive parallel processing, connection machines, and high-speed computations engines. Software engineering technology includes large-scale algorithmic processing, protocol communication, natural languages, artificial intelligence and expert systems. Fiberoptics technology includes fiber transmission lines, optical sources and components. Autonomous vehicle technology includes guidance and control, and automatic targeting. Space-bused systems includes surveillance and upper atmospheric weapons delivery. Command and control technology includes application of statistics and logical elements, and computer-aided systems for command decisions. Advanced sensor technology includes transducers and electromagnetic devices, and navigation sensors. DATA AND SAMPLE Questionnaires were mailed to 755 senior managers at the four primary Navy technology user organizations, NAVAIR, NAVSEA, SPAWAR, and Navy related departments at DARPA. The research was authorized by the Director of Navy Laboratories by direction
The Vedcal
Transfer of Technological Know-How
25
of the senior Commander; a letter to this effect was included with the questionnaire. A senior manager is typically responsible for a team of 5 to 20 researchers, engineers, and technicians, and has a particular, specific technology assignment. These research teams then interact with various technology providers to acquire appropriate technology for their specific assignment. Managers were identified by internal directories. Data collected on the questionnaire were: (a) frequency of contact with each of 13 different Navy technology providers: these were the David Taylor Research Center, Naval Air Development Center, Naval Civil Engineering Laboratory, Naval Coastal Systems Center, Naval Ocean Systems Center, Naval Personnel Research and Development Center, Naval Research Laboratory, Naval Surface Warfare Center, Naval Training Systems Center, Naval Underwater Systems Center, Naval Weapons Center, Office of Naval Research, and the Office of Naval Technology; (b) frequency of contact with a variety of non-Navy and private-sector laboratories; (c) technology class of primary involvement; (d) ratings of the technology user’s immediate organization on the five factors: support, interaction, capacity, willingness, and reward; (e) ratings of (i) primary Navy technology provider’s organization and (ii) primary private sector technology provider, on the following characteristics: credibility, R&D selection, documentation, accessibility, channel/linker; and (f) an assessment of (i) user’s success in acquiring “innovative” technology and (ii) the various providers’ success in supplying “innovative” technology. Content validity of the questionnaire was established by a panel of five senior managers at the Naval Ocean Systems Center (NOSC). All panel members had previous formal association with one or more of the technology user organizations. Each question was judged concerning the intended meanings of the responses at the scale extremes for that item, as well as the overall meaning of the question (Bailey, 1978). Questions dealing with items “d” through “f’ were measured in the following manner: for each item under investigation a single statement was provided which required a response on a six point scale (strongly disagree with the statement to strongly agree with the statement). For example, for the Navy R&D laboratory “accessibility” factor respondents were asked to evaluate the statement, “Navy labs allow easy access to needed technical documentation and information.“; items “a” through “c” above required responses based upon a five point scale. The completed questionnaire was then pre-tested with an additional sample of 10 technology user senior managers for clarity and improvements regarding the various items. Although the Navy technology provider and user organizations in this study are all government owned and operated (GOGO), they also all operate under the Navy Industrial Fund (NIF) accounting system. Implemented in the early 198Os, the NIF accounting system attempts to replicate a market system within the naval community by requiring Navy technology providers to identify specific Navy customers and bill for reimbursement of incurred costs. Likewise, the Navy customer is allocated a certain budget, and can therefore, with certain limitations, “shop around” for services. RESULTS Of the 755 original questionnaires, 350 were returned. However 8 stated they did not seek technology from outside sources, thus leaving 342 usable responses, or a 45%
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response. DARPA had the lowest response rate of 29%, while NAVSEA had the highest with 54%. Navy vs. Private Sector R&D Labs One interesting issue is whether technology user organizations perceived significant differences between Navy R&D technology provider laboratories and those of the private sector. Table 1 shows the user perceptions of Navy versus private sector laboratories for the five technology provider factors as well as perception of success in providing innovative technology. Ratings by each of the four technology user organizations are provided. Table 1 suggests several things. First, the three Navy technology user organizations all felt that the Navy laboratories did a much better job in providing access to technical materials and personnel. This is not surprising given the intra-government relationship that exists between the Navy technology users and the Navy laboratories; technology users can readily use internal communications to quickly discuss matters with their “counterparts over in the lab,” sometimes circumventing formal bureaucratic procedures and normal communication channels. Private sector technology providers often have a real, or at least perceived, set of security and other contractual obligations which may inhibit the free flow of information to potential and actual technology users. DARPA, however, perceived the private and public sectors about equal in accessibility which is not surprising given that DARPA has a much higher percentage of employees with previous ties to the private sector. Second, on the average, NAVSEA and NAVAIR rated Navy technology providers the highest on the five provider factors, while DARPA and SPAWAR provided the highest ratings for the private sector. A possible explanation for this phenomenon can be seen in Figure 3. Both DARPA and SPAWAR are typically more involved in the conceptual/ exploratory phase of the research cycle (and rated the private sector significantly higher on the provider factors), while NAVSEA and NAVAIR are more end product/applied development oriented (and tend to rate the public/navy labs higher on the provider factors). This is somewhat contradictory to the previously cited suggestion by Bozeman (1987); our findings might suggest that private sector technology providers are viewed more favorably in supplying non-market oriented early-stage generic technologies, whereas Navy labs are viewed more favorably by those user organizations typically concerned with well-defined and established technologies. Third, on the average, the technology users rated private sector R&D organizations most successful in providing “innovative technology” that meets the user’s needs. One possible explanation is that the different technology users interact with different sets of private sector technology suppliers. However, an examination of the list of private sector technology providers for each of the four technology users revealed, with few exceptions, all four users interacted with essentially the same set of Fortune 500 firms, and many of the smaller firms. As an exception, NAVSEA was the only user to work with one particular shipbuilding firm, and did substantially more work with Westinghouse Corporation than either NAVAIR, SPAWAR, or DARPA.
The Vertical Transfer of Technological Know-How
21
28
Factors Influencing
HIGH TECHNOLOGY
Technology
MANAGEMENT
RESEARCH
Vol. ~/NO. l/1991
Transfer Success
To examine the effect various factors have upon technology transfer success a multiple regression model was estimated. The dependent variable was technology transfer success, measured by the mean of the two success questions identified under item “f” above. The predictor variables were the five technology provider factors and the five technology user factors. Because of limited sample size in some technology classes, the five provider factors were computed as a weighted average (weighted by frequency of interaction) of the ratings for Navy labs and private sector labs. Table 2 presents the intercorrelations for all variables. Regression coefficient estimates were by ordinary least squares (OLS) using the SPSS/ PC+ statistical software; all ten predictor variables were entered into the equation. Multicolinearity did not appear as a major problem (based on tolerance scores), but to minimize possible pooling problems, and to explore whether there were significant differences in the transfer process between different technologies, individual equations for each of the seven technology groups were estimated. As previously mentioned, technologies were classified as computer hardware technology (COMP), software technology (SOFT), communications technology (COMM), fiberoptics technology (OPTICS), advanced sensor technology (SENSOR), space-based systems (SPACE), and autonomous vehicle technology (AUTO). Table 2 shows the estimated unstandardized coefficients for each of the technology area regression models. With the possible exception of space-based systems technology, the various technology groups appear to share somewhat similar results.2 For the technology provider organization, the user’s perception of the provider organization’s credibility (CREDIBILITY) and, with one significant exception (that being space-based systems technology), the degree that the provider incorporates user needs into new R&D project selection (R&D SELECTION) show significant positive impacts on the successful transfer of technology to user groups. The exception found for R&D selection in the space-based systems area can possibly be explained by the fact that this technology is often ill-defined in terms of established standards, and haunted by changing legislative expectations and funding requirements. In addition, there remain nagging questions regarding launch capabilities and schedules in the U.S. space program. Under such conditions a “shotgun” approach to technology development by provider organizations may be more productive than waiting for wellorganized project specifications to flow from the various user groups. Another significant provider organization factor is the channel or linker element (CHANNEL/LINKER) which measures the repeatability of the information conduit. Interestingly, this factor consistently shows a significant negative relationship with transfer success in the regression analysis. Two, albeit somewhat related, explanations for this phenomenon were provided by several of the respondents. First, a well defined set of linker mechanisms that a user organization must work with may actually delay information transfer between organizations if too much information is being funnelled through the conduit-a type of “data bottleneck”; second, a well defined and repeatable information source will inevitably acquire a high degree of public exposure as a “gate-keeper,” and thus organizational power within the system. Any bias, whether by favoring a particular technology, project, or organization, may inhibit the broad flow of technological know-how. The negative sign on the CHANNEL/LINKER factor is consistent across the seven technology areas.
The Vertical Transfer of Technological Know-How
29
COMP
0.450 129
RZ Nb 0.480 95
0.510
0.217** -0.146% 0 209** 0:250** 0.213””
0.026 0.308*** 0.005 - 0.065 -0.170”
SOFT
0.431 84
0.124
0.246** -0.166 0.147 0.312”** 0.260***
0.122 0.044 0.125 0.113 -0.256**
COMM
0.444 39
0.906
0.197* -0.014 -0.151 0.496** 0.257X
- 0,037 - 0.085 0.236 0.006 -0.081
Technology Class oprrcs
0.474 74
0.269
0.365*** 0.035 0.122 0.076 0.173””
0.184* 0.028 - 0.056 0.120 -0.146*
SENSOR
0.528 20
-0.300
0.347* 0.069 0.192 0.207 0.093
0.490* - 0.461* - 0.259 0.285 -0.056
SPACE
0.652 36
- 1.220
0.216* 0.055 0.101 0.170 0.143*
0.420X 0.137 - 0.055 0.489** - 0.476”*
AUTO
~Unstaudardized coefficients are reported; dependent variable is “technology transfer success.” bin several cases respondents indicated they participated extensively in more than one technology class. In such situations the response was counted in each of the technology groups identified. Thus, the total sample for the regression models exceeds the 342 original responses. Two-tailed t-test (* = p < .lO; ** = p < .05; *** = p < .Ol).
0.248
0.255*** -0.165* 0.216”” 0.253”” 0.244***
0.162* 0.156* 0.108 - 0.082 -0.262***
*
Intercept
SUPPORT INTERACTION CAPACITY WILLINGNESS REWARD
~ec~~ient~actors
C~DIBILITY R&D SELECTION D~U~ENT ACCESSIBILITY CHANILINKBR
Provider Factors
Predictor Variables
TABLE 3 Contribution of Factors to Transfer Successa
The Vertical Transfer of Technological Know-How
31
The technology provider organization factors of documentation and accessibility are generally statistically insignificant in the present study; accessibility is very significant for the autonomous vehicle technology area, however. The technology user organization factors of SUPPORT, WILLINGNESS, and REWARD are all statistically significant and positively related to transfer success as hypothesized. INTERACTION, on the other hand, exhibits a slight negative relationship with success-time invested in interacting with other individuals in the same organization may actually distract from the project at hand. The model of technology transfer used in this study explains about half of the observed variance in technology transfer success with R2s ranging from 0.45 to 0.65.
CONCLUSIONS This study explores the mechanism of successful technology transfer within the Navy research and development community, and suggests several important findings. First, technology transfer success does appear to be a function of both technology provider organization factors and technology recipient organization factors. Some of the hypothesized provider organization relationships, such as the technical credibility and sensitivity in R&D project selection by the provider, appear to have a significant and positive effect on technology transfer success. Similarly, organizational support and personal reward for transfer performance by the user organization have a positive impact on the process. The major deviation from received theory in our analysis is the negative effect of the Channel/Linker element. Further investigation in this area may support our contention that the linker may, in fact, create an information bottleneck within the transfer process. Second, with the possible exception of space-based systems, the relationship between these organizational factors does not appear to be technology dependent. Finally, in general, the Navy technology user community views the private sector as being more successful at providing innovative and usable technology than the public sector. In addition, this perception becomes more apparent as the technology moves toward the exploratory end of the research cycle. It is recognized that the target population for this study represents a very specialized category of the nation’s R&D activity. The parameters within which a federal organization is free to act are well established by law or regulation. However, while acknowledging the somewhat restrictive behavior imparted on the government agencies examined in this study, the fundamental managerial and organizational characteristics discussed in this study should be relatively common between all modem technology-driven organizations involved in the “middle ground” of vertical technology transfer.
NOTES 1.
We have omitted 6.5 funding from consideration, as such funding is for management expenses,
2.
not for technology development. A Chow test comparing the pooled results against the individual technology results suggest that there are no significant differences in various model estimates (FG6477 = 0.45).
32
HIGH TECHNOLOGY
MANAGEMENT
RESEARCH
Vol. ~/NO. l/1991
REFERENCES American Association of Engineering Societies. 1987. Management of technology: the key to America’s competitive future, 6. Bailey, K. 1978. Methods of social research. New York: The Free Press. Boyle, K. 1987. Technology transfer between universities and the U.K. offshore industry. IEEE Transactions on Engineering Management, EM-33: 33-42. Bozeman, B. 1987. All organizations arepublic: bridging public andprivate organization theories. San Francisco: Jossey-Bass. Creighton, J., Jolly, J., & Buckles, T. 1985. The manager’s role in technology transfer. Journal of Technology Transfer, 10: 65-81. Creighton, J., Jolly, J., & Denning, S. 1972. Enhancement of research and development output utilization eficiencies: linker concept methodology in the technology transfer process. Monterey, CA: Naval Postgraduate School. Creighton, J., Jolly, J., & Laner (Eds). 1985. Technology transfer: a think tank approach to managing innovation in the public sector. Monterey, CA: Naval Postgraduate School. Defense Science Board. December 1987. Report on the defense science board 1987 summer study on technology base management. Washington DC: U.S. Government Printing Office, 22. Dorf, R. 1988. Modelsfor technology transferfrom universities and research laboratories. Technology Management Publication, TM 1: 302-312. Essoglou, M. 1985. Technology transfer for enhanced research development, test, and evaluation effectiveness. In Creighton, J., J. Jolly, & S. Laner (Eds.), Technology transfer: a think tank approach to managing innovation in the public sector, pp. 77-95. Monterey, CA: Naval Postgraduate School. Federal Council for Science and Technology. 1975. Federal technology transfer: directory of programs, resources, contact points. Washington DC: U.S. Government Printing Office, 5. Godkin, L. 1988. The university’s role of technology transfer. Technology Management Publication, TM 1: 313-324. Kanter, R. 1983. The change masters: innovation for productivity in the american corporation. New York: Simon and Schuster. Karagozoglu, N., & Brown, W. 1986. A multilevel multiphase framework for viewing technological innovation. Journal of Technology Transfer, 10: 15-32. Kay, N. 1984. The emergentfirm: knowledge, ignorance and surprise in economic organization. London: Macmillan. Kimberly, J., & Evanisko, M. 1981. Organizational innovation: The influence of individual, organizational, and contextual factors in hospital adoption of technological and administrative innovations. Academy of Management Journal, 24: 689-7 13. Leonard-Barton, D., & Deschamps, I. 1988. Managerial influence in the implementation of new technology. Management Science, 34: 1252- 1265. Moth, M., & Morse, M. 1977. Size, centralization and organizational adoption of innovations. American Sociological Review, 42: 7 16-725. Mogavero, L., & Shane, R. 1982. What every engineer should know about technology transfer and innovation. New York: Dekker. National Research Council. 1987. Management of technology: the hidden competitive advantage. Washington DC: National Academy Press, 9. Office of Technology Assessment. March 1988. The Defense technology base: a special report. Washington DC: U.S. Government Printing Office, 4. Ring, P., & Perry, J. 1985. Strategic management in public and private organization: implications of distinctive contexts and constraints. Academy of Management Review, 10: 276-286.
The Vertical Transfer of Technological Know-How
33
Schaefer, S. 1987. Technology application program management (TAPM): an Air Force logistics command strategy for technology transition. IEEE 1987 National Aerospace and Electronics Conference, 4: 1182-1187. Sirinaovakul, B., & Czajkiewicz, Z. 1988. A spatial d@ision model for advanced manufacturing technology. Technology Management Publication, TM 1: 291-301. Talaysum, A. 1985. Understanding the diffusion process for technology-intensive products. Research Management, 28: 22-26. Teece, D. 1985. Multinational enterprise, internal governance, and industrial organization. American Economic Review, 75: 233-238. Teece, D. 1977. Technology transfer by multinational firms: the resource costs of transferring technological know-how. Economic Journal, 87: 242-261. Van Gunsteren, L. 1987. Planning for technology as a corporate resource: a strategic classification. Long Range Planning, 20: 51-60. Weijo, R. 1987. Strategies for promoting technology transfer to the private sector. Journal of Technology Transfer, 11: 43-65. Wolf, W. 1984. Up-grading the caliber of linkage agent performance. Journal of Technology Transfer, 9: 25-37.