Building Successful Commercialization Teams

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Acknowledgements

The authors wish to acknowledge: the Social Sciences and Humanities Research Council, Agriculture and Agri-Food Canada, the Canada Centre for Mineral and Energy Technology (of Natural Resources Canada), the National Research Council, and the University of Ottawa's Faculty of Administration for financial assistance; and Agriculture and Agri-Food Canada, Atomic Energy of Canada, Communications Research Centre, Environment Canada, the National Research Council and Natural Resources Canada for submitting projects. The authors wish to especially acknowledge the technical support and financial contribution from the Federal Partners in Technology Transfer during the course of this study.

Summary

Governments around the world are increasingly recognizing that improving technology transfer and commercialization is key to an innovative economy leading to wealth generation and job creation. Recognition, however, must be supplemented by a deep understanding of which factors actually contribute to successful commercializations. Such factors are complex, including appropriate policy changes, project evaluation techniques, portfolio selection techniques, organizational structures, reward structures, team building processes and project management tools, to name but a few.

This report constitutes the completion of an interdepartmental cooperative study into the team-building processes which determine the ultimate success of a technology commercialization project. It contains the results and implications of a pilot empirical investigation of the Theory of Cascading Commitment, which examined 34 case studies from 5 different federal labs. In this study, the dependent variable "success" was defined as the industry manager's perception of how well the project attained the industry partner's profit objective associated with the commercialization of the technology. According to this measure, 19 of the projects were clearly successful, 12 were clearly unsuccessful, and 3 were uncertain. These are our key conclusions pertinent to the Theory of Cascading Commitment:

• "technology-pull" projects have a better chance of success than "technology push" projects;
• a complete team of linchpins from both public and private organizations is necessary;
• there is an optimal sequence for recruiting the organizational partners;
• there is an optimal stage for recruiting each organizational partner; and
• linchpins are motivated by a variety of factors drawn from a diversified set of perceived incentives and rewards, and the credibility of the team's prior organizations and/or linchpins; interestingly, monetary rewards do not seem to be a prime motivator for lab scientists.

In addition, stemming from a supplementary qualitative analysis, there are several related implications and/or suggestions. To achieve success, greater attention must be given to project selection and team formation at the start. Furthermore, there may be a need to identify possible sources of early stage seed/risk money to enable the project manager to conduct initial commercial feasibility studies, identify credible test customers, and fabricate alpha prototypes to help attract test customers. Finally, to enable the effective and efficient functioning of the project teams once they are formed, labs might consider the implementation of the stage-gate and fast cycle project management techniques employed in the private sector.

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Table of Contents

Glossary
1. Introduction

1. The Commercialization Challenge
2. Purpose and Scope of the Report
3. Background of the Research

2. Principal Research Parameters

1. Conceptual Framework
2. Project Sample
3. Survey Methodology
4. The Questionnaire

3. Results: Basic Descriptive Statistics

1. Response Analysis
2. Length of Project Stages
3. Technology Push vs. Technology Pull

4. Results: Test of Conceptual Framework

1. Propositions 1-2: A Complete Team Necessary
2. Proposition 3: Optimal Recruitment Sequence
3. Proposition 4: Optimal Recruitment Stage
4. Proposition 5: The Need for Commitment
5. Proposition 6: The Determinants of a Linchpin's Commitment

5. Results: Qualitative Findings

1. Commercialization Infrastructure
2. Project Team Selection
3. Project Implementation Process

6. Discussion and Best Team-Building Practices

1. Support for the Theory of Cascading Commitment
2. Towards Best Team-Building Practices
3. Limitations and Potential Future Research

Appendices

Appendix A Projects in the Study
Appendix B Respondents' Comments on Commercialization and Team Issues

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Glossary

Technology Transfer
There are many definitions of technology transfer. In this report, we define technology transfer to be the dynamic process of handing-off of a technology from the federal lab to an industry receptor, with varying degrees of involvement by lab personnel.

Technology Commercialization
In contrast to technology transfer, technology commercialization requires a much deeper and longer-lasting relationship between lab personnel and several other parties, including end customers, re-sellers (manufacturers) and funding agents, where involvement lasts until the technology has been successfully launched into the market.

"Linchpins" (i.e., key individuals who control money and/or knowledge)
Government Lab Manager (GM), Government Lab Scientist (GS)
Re-Seller (company which reproduces and re-sells the technology)
Manager (RSM), Re-Seller Technologist (RST)
Test Customer Manager (TCM), Test Customer Technologist (TCT)
Government Funding Agent (GFA)
Technology Transfer Agent (TTA)
Private Funding Agent (PFA)

Key Project Stages
Conceptualization (C) stage, where the technology is conceived and evaluated, and its feasibility verified with a breadboard or benchtest (coded as "1" in this study);

Early Development (ED) stage, where an initial prototype is designed, fabricated and tested in the lab (the "alpha" test) (coded as "2" in this study);

Advanced Development (AD) stage, where an advanced prototype is designed, built and tested by one or more test customers in actual field conditions (the "beta" test) (coded as "3" in this study);

Introduction (I) stage, where the first commercial version is produced and sold by a for-profit corporation (coded as "4" in this study);

Expansion (E) stage, where modifications are made, production levels increased, and/or more production lines built (coded as "5" in this study).

Project Success
In this research, "success" was defined as the achievement of the Re-Seller Manager's commercial profit objective, rated by the RSM in the RSM questionnaire or by a post hoc telephone interview according to the following scale:

Very Unsuccessful (rated as "1", classified as "Unsuccessful" in this study)
Moderately Unsuccessful (rated as "2", classified as "Unsuccessful" in this study)
Mildly Unsuccessful (rated as "3", classified as "Unsuccessful" in this study)
Uncertain/No opinion (rated as "4", not classified)
Mildly Successful (rated as "5", classified as "Successful" in this study)
Moderately Successful (rated as "6", classified as "Successful" in this study)
Very Successful (rated as "7", classified as "Successful" in this study)

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Building Successful Commercialization Teams for Federal Lab Technologies

1. Introduction

1.1 The Commercialization Challenge

Governments around the world are increasingly recognizing that improving technology transfer and commercialization is key to an innovative economy leading to wealth generation and job creation. Canada's federal labs have always been involved in the commercialization of their technologies, and have experienced success with a wide variety of tools ranging from publication of results to licensing and collaborative partnering agreements with industry partners. However, stemming from today's political climate which encourages more visible results, there is ever greater pressure for the labs to become more effective and more efficient with their commercialization efforts.

1.2 Purpose and Scope of the Report

Factors contributing to successful commercializations are complex, including appropriate policy changes, project evaluation techniques, portfolio selection techniques, organizational structures, reward structures, team building processes and project management tools, to name but a few. The purpose of this report is to contribute to our understanding of these complex factors, with a specific focus on the team building processes. In this report we report the key quantitative results and implications from an empirical study of 34 case studies, supplemented with some qualitative findings.

1.3 Background of the Research

The authors received a Social Sciences and Humanities Research Council (SSHRC) strategic grant to fund a proposed study entitled "Successful Strategies for Technology Commercialization by Canada's Federal Labs". The application for the grant had been endorsed by senior lab managers from Agriculture and Agri-Food Canada, the Canada Centre for Mineral and Energy Technology (CANMET), the Communications Research Centre, Environment Canada, the Canadian Forestry Service and the National Research Council. Subsequent to the award and an extensive literature review, the authors developed and published the Theory of Cascading Commitment which prescribed an optimal process for building technology commercialization teams^{1, 2}. A pilot empirical study of the theory was subsequently devised, and data were gathered from a convenience sample of 34 projects from five of the six participating labs. This report summarizes the findings and implications from the pilot empirical study.

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2. Principal Research Parameters

2.1 Conceptual Framework

The conceptual framework for the study was the Theory of Cascading Commitment, as outlined by Belinko and Large (1995), which was derived from an extensive review of the technology transfer literature. At its core, the theory consists of seven overarching propositions:

Proposition 1: A successful technology transfer requires a complete team of key organizations (i.e., public lab, test customer, transfer agency, public funding agency, a manufacturer which reproduces and re-sells the technology, private funding agency)

Proposition 2: A successful technology transfer requires a complete set of individuals, or "linchpins", within each organization (i.e., those who control the flow of the two key resources of money and expert knowledge).

Proposition 3: The sequence of soliciting organizations and individuals can affect the likelihood of success (in other words, there is an optimal sequence of solicitation). In particular, it may be better to recruit the test customer prior to the re-seller, because the presence of a committed and credible test customer suggests a genuine market need, which may in turn enhance the re-seller's sales expectations.

Proposition 4: The stage of commercialization in which organizations and individuals are solicited can affect the likelihood of success, i.e., there are optimal stages for recruitment. Generally, the earlier the better.

Proposition 5: Every linchpin must be totally committed to the success of the transfer.

Proposition 6: A potential linchpin's level of commitment to the transfer team is a function of his/her perceptions of (1) the prior linchpins' credibility and commitment, (2) the prior linchpins' organizations' credibility, and (3) a personal set of expected benefits comprising incentives and rewards.

Proposition 7: The team of linchpins should remain intact until the commercial launch is successfully achieved or the project is suspended.

2.2 Project Sample

The unit of analysis for the research was specified as a distinct "commercialization project". Thus, all participating labs were asked to submit lists of commercialization projects which met the following requirements:

1. the project involved primarily a tangible product or process, not software;
2. the project was quite discrete, not part of a longitudinal series of projects;
3. the lab was deeply involved in the development of the technology, not simply funding;
4. the project outcome was known and relatively recent, i.e., the project was not still in development, and its commercial success or failure had been established within the previous three years.

Sixty-seven projects were originally nominated by representatives from six federal labs. Note that the list of projects did not represent a random sample of all the labs' projects. Indeed, it was more of a convenience sample, where projects were selected based on their ability to meet the list of qualifications, and the lab representative's expectation that the project's key contact would be available and willing to participate in the study. Thus, no conclusions can be drawn regarding the labs' overall statistical success rates.

2.3 Survey Methodology

Assuming that the contact coordinates of at least one linchpin could be supplied by the lab for each project, a "retrospective snowball survey" was specified as an appropriate empirical methodology, comprising these critical steps:

Step 1 Every linchpin's coordinates would be verified by telephone.

Step 2 Introductory letters would be sent to every linchpin.

Step 3 Every linchpin would be called, and their participation requested.

Step 4 A questionnaire, including a request for coordinates of other linchpins and other projects, would be mailed to every participating linchpin.

Step 5 Follow-up phone calls would be made at 2-week intervals.

Step 6 Steps 1-5 would be repeated, i.e., "snowballed", for every new linchpin identified.

The original intent was to identify over 100 qualified projects, and generate at least five or six questionnaires for each project. Having multiple responses would permit a high degree of validation of project-level data, while permitting separate analyses for the various linchpin roles.

2.4 The Questionnaire

The questionnaire was developed in several stages, including reviews by the lab representatives and a pre-test by three government scientists from projects which were not used in the later study. The questionnaire was customized to some extent for each type of linchpin to reflect the linchpins' different sets of perceived motivators. A copy of the questionnaire is available from David Large upon request. Questionnaires were mailed out and returned in several waves over a 14-month period.

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3. Results: Basic Descriptive Statistics

3.1 Response Analysis

Of the 67 projects originally identified and pursued, 34 projects generated at least one useable questionnaire and were retained for the analysis. The names of the 34 projects, their associated labs, their number of respondents and their success ratings are shown in Appendix A. It was interesting to observe the bimodal nature of the frequency distribution of the project success ratings by the re-seller managers:

Figure 1 - Bi-Modal Project Success

As a result of this "two-hump" distribution, it was not feasible to perform multiple regressions using the success rating as the dependent variable. Instead, projects were classified as "Unsuccessful" for ratings 1-3 (n=11), and "Successful" for ratings 5-7 (n=20), and the principal statistical tests for the propositions became the t-test and discriminant analysis.

For the 34 useable projects, 140 linchpins were ultimately contacted, to which 80 consenting individuals were sent questionnaires, and from whom 63 useable completed questionnaires were returned. Thus, on average, just over 4 linchpins were solicited per project, and just under two questionnaires were received.

Of the 63 questionnaires received, 17 were from Government Managers, 18 were from Government Scientists, and 15 were from Re-Seller Managers. This relatively high response rate from those roles probably reflects a high personal incentive to participate in this study, based on a high personal stake in the improvement of technology commercialization processes.

Both the number of projects retained and number of questionnaires received were substantially lower than we had expected. Thirty-three projects were dropped for various reasons, the most common being: the project was primarily software; the project was still considered to be in a development stage, with the commercial outcome unknown; or the key contact associated with the project could not be contacted or refused to participate.

3.2 Length of Project Stages

We felt it would be useful to report our findings on the length of the various commercialization stages, to serve as a benchmark for managers who may wish to focus on shortening the length of their commercialization projects. Remember that the following figures will only be relevant for similar types of products and processes, and in particular will not be relevant for software or medical/pharmaceutical products.

	Unsuccessful Projects	Successful Projects
Average conceptualization stage	22.4 months	19.1 months
Average early development stage	21.9 months	23.3 months
Average advanced development	25.6 months	16.2 months
Average overall to launch	69.9 months	58.6 months

It is interesting that in very general terms the length of the stages is similar for both unsuccessful and successful projects. The one appreciable difference is the length of the advanced development stage, where the successful projects are noticeably quicker. There are at least two possible explanations for this: 1) perhaps unsuccessful projects linger longer than they should before they are killed, as the team members struggle with various alternate avenues to make them work; or 2) perhaps projects which tend to be unsuccessful also tend to be more complex and time-consuming. We did not collect data to ascertain which explanation might apply.

It is also interesting to note that the average time elapsed to launch is about five years. Without any similar data for similar projects in the private sector, it is hard to make comparisons. Nevertheless, this seems longer than it should for the types of products and processes in this study, possibly reflecting the complex nature of a commercialization team comprised of diverse players from different organizations, as opposed to one structured within a single company where there are no cultural barriers to overcome.

3.3 Technology Push vs. Technology Pull

One issue that was not specifically addressed in the original presentation of the Theory of Cascading Commitment was the effect of a project's origin, i.e., was the project being "pushed" by a government lab researcher, or was it being "pulled" into industry by an industry researcher and/or company.

In the original theory, it was assumed that all of the projects originated in the government lab, but in the course of developing the questionnaire and talking with the research community, we realized that many projects either originated in the private sector, or were developed jointly. Thus, in this research we gathered data to investigate the "push" versus "pull" effect. One hypothesis we explored was that "industry or jointly conceived technology is more likely to succeed", i.e., success will depend on the actual physical origin of the technology. We found:

We concluded that this hypothesis had good statistical support. Thus, while government-conceived technologies can succeed, industry or jointly conceived technologies seem to have a better chance of success. However, this does not imply that no government-conceived projects should be pursued; indeed, perhaps the government-conceived technologies can achieve a higher rate and degree of success if commercialization practices are improved.

A second hypothesis we explored was that "industry-initiated projects are more likely to succeed", i.e., that success was dependent on which party actually took the initiative to establish a collaborative project. We found:

We concluded that this hypothesis had good statistical support. Thus, while government initiated projects can succeed, industry initiated projects seem to have a better chance of success. Again, this does not imply that no government-initiated projects should be pursued; and again, perhaps the government-initiated projects can achieve a higher rate and degree of success if commercialization practices are improved.

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4. Results: Test of the Conceptual Framework

In this section we report quantitative results which help to support or refute the first six propositions of the Theory of Cascading Commitment. The relatively small data set, and high non-response rates for some questions, imposed many restrictions on the type of analyses that could be performed, and reduced the confidence associated with the statistical results. Thus, the results reported here should be considered as tentative, subject to further validation with a larger sample size. Not all of the propositions were tested individually. For example, Propositions 1 and 2 concerning the completeness of the team were tested jointly simply by counting the number of linchpins in each team. Also, data for Proposition 7, concerning the necessity of sustained commitment, were not gathered due to the length and time demands of the questionnaire.

4.1 Propositions 1-2: A Complete Team Necessary

Pursuant to the joint proposition that "a complete team of organizations and linchpins is necessary", we found:

While the difference of only a half-person in average team size may seem managerially unimportant, the statistical evidence suggests otherwise. We conclude that there is good statistical support for propositions 1 and 2.

4.2 Proposition 3: Optimal Recruitment Sequence

Pursuant to the joint proposition that "the sequence of recruitment matters", we chose to examine five sub-propositions or hypotheses:

P3a was "the earlier the test customer in the sequence, the better". We found:

While treating ordinal sequencing data as interval data is not strictly appropriate, we concluded that this hypothesis had good statistical support. Thus, in successful commercialization projects the test customer organization will tend to be recruited earlier in sequence than in unsuccessful projects.

P3b was "the earlier the re-seller in the sequence, the better". We found:

We concluded that this second hypothesis had received weak statistical support, though the evidence is directionally correct and managerially significant. Thus, this hypothesis requires supplementary investigation with a larger sample.

P3c was "recruiting the test customer before the re-seller is better". We found:

We concluded that this third hypothesis had received weak statistical support, though the evidence is directionally correct and managerially very significant. Thus, this hypothesis requires supplementary investigation with a larger sample size. If the results were confirmed in a larger study, this might well prove to be the most important finding of the study.

4.3 Proposition 4: Optimal Recruitment Stage

In addition to the sequence of recruitment, stage is also important. For example, linchpins could be recruited in the optimal sequence, but either at too early or too late a stage in the development process. While some technology transfer research has shown that credible test customers may not be recruitable until an alpha prototype exists, the received wisdom in the new product development literature is that the earlier the test customer is recruited the better. Thus, pursuant to the proposition that "the stage of recruitment matters", we examined three sub-propositions or hypotheses:

P4a was "the earlier the stage of government/industry contact, the better". We found:

As with sequencing data, it was not strictly appropriate to use ordinal stage data as interval data. Nevertheless, we concluded that this hypothesis had received weak statistical support, though the evidence was directionally correct and managerially significant. Thus, this hypothesis requires supplementary investigation with a larger sample size.

P4b was "The earlier the stage of test customer recruitment, the better". We found:

We concluded that this second hypothesis had received good statistical support. Thus, the earlier the test customer can be recruited, the better.

P4c was "the earlier the stage of re-seller recruitment, the better". We found:

We concluded that this hypothesis had received only moderate statistical support, though the evidence was directionally correct and managerially significant. Thus, this hypothesis requires supplementary investigation with a larger sample size.

4.4 Proposition 5: The Need for Commitment

Pursuant to the proposition that "every linchpin must be totally committed", we found:

These results showed no statistical difference between unsuccessful and successful teams, so this proposition received virtually no support. We concluded that commitment is necessary but not sufficient for project success.

4.5 Proposition 6: The Determinants of a Linchpin's Commitment

Proposition 6 was that "a linchpin's commitment is a function of his/her perceptions of the prior linchpins' personal credibility, the prior linchpins' organizations' credibility, the prior linchpins' commitment, and a set of incentives and rewards". As mentioned earlier, we had hoped to be able to do a multiple regression of all the hypothesized independent variables on the dependent variable of "Commitment" for all the individuals who had been identified as the second or subsequent recruit on their team. However, the frequency distribution of Commitment was bi-modal, so we were limited to performing a discriminant analysis, using data from 31 individuals who had been identified as the team's second or subsequent recruit, and who had reported a level of commitment of 4 or 5.

We found a single significant (p<0.01) discriminant function which correctly classified 78% of the cases. The five strongest variables in the structure matrix had correlation coefficients as follows:

Perceived financial benefits for the end customer: 0.73

Prior organization's reputation for tech transfer success: 0.37

Prior linchpin's respect in own organization: 0.37

Prior linchpin's cooperativeness: 0.25

Perceived potential for jobs for Canadians: 0.15

These results confirmed that linchpins consider a variety of factors drawn from a diversified set of perceived incentives and/or rewards, and the credibility of the teams prior organizations and/or linchpins. We concluded that there is good statistical support for Proposition 6.

There were also descriptive results which provided much deeper insight into the relative importance of the various incentives and rewards to the different types of linchpins. The following results show the self-reported importance of the various incentives for the three most frequently reported roles in this study.

Government Manager (n=17)	Motivational Importance (Scale of 7)
Expected technical benefits for the end customer	4.41
Expected status for lab	4.13
Personal interest and satisfaction	4.12
Expected advancement for scientist	3.73
Expected financial benefits for re-seller	3.71
Expected financial benefits for end customer	3.65
Expected personal advancement	3.59
Improvement of public good and quality of life	3.53
Industry experience for scientist	3.47
Expected increase in jobs for Canadians	3.24
Expected income for lab from royalties and/or fees	3.18
Expected proprietary intellectual property for lab	2.82
Expected improvement in Canadian trade balance	2.80

Government Scientist (n=18)	Motivational Importance (Scale of 7)
Expected technical benefits for the end customer	4.72
Personal interest and satisfaction	4.44
Expected financial benefits for end customer	4.22
Expected financial benefits for re-seller	3.67
New experience and contacts	3.61
Expected personal advancement	3.44
Expected increase in jobs for Canadians	3.28
Expected proprietary intellectual property for lab	3.00
Expected personal publications	2.94
Expected income for lab from royalties and/or fees	2.53
Personal travel and conferences	2.17
Personal income from royalties	1.44

Re-Seller's Manager (n=15)	Motivational Importance (Scale of 7)
Expected technical benefits for the end customer	4.60
Expected proprietary technology for re-seller	4.53
Expected financial benefits for re-seller	4.47
New experience and contacts	4.33
Personal interest and satisfaction	4.29
Expected financial benefits for end customer	3.80
Expected personal advancement	3.27
Expected increase in jobs for Canadians	3.14
Expected status for lab	3.07
Expected income for lab from royalties and/or fees	2.71
Improvement of public good and quality of life	2.67
Expected proprietary intellectual property for lab	2.00

These results tended to confirm three points:

1. Linchpins are motivated by a wide range of incentives and rewards, which may be very different among the various roles (e.g., expected financial benefits for re-seller);
2. Having said that, the three major types of linchpins are most highly motivated by the perceived technical benefits of the technology for the end customer; this perhaps tends to reinforce the idea of recruiting the end customer early in the project in order to ascertain the true adoption potential of the new technology; if the end customer becomes committed early, it will serve to motivate the balance of the linchpins to join and to be committed;
3. At least according to self-reports, the expectation of personal income from royalties does not seem to motivate scientists; this implies that a focus on monetary rewards may be misplaced.

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5. Results: Qualitative Findings

Respondents were given space in the questionnaires to provide qualitative comments on any issue pertaining to technology commercialization. Also, many individuals who did not complete a questionnaire felt motivated to submit supplementary commentary. An examination of the qualitative commentary showed that the comments could be grouped under several headings. In the following three sections the authors provide a brief summarial assessment of some of the respondents' comments pertaining to commercialization infrastructure, project team selection and the project implementation process. The respondents' associated verbatim quotes are attached in Appendix B, together with an indication of the individual's role and their project's success rating on a scale of 7 (if applicable).

5.1 Re Commercialization Infrastructure

Many individuals felt that the lab should be better prepared in general in terms of education and training. Beyond preparatory education and training, many suggestions were offered as to how the lab can facilitate projects, especially with more technical, financial and person-year support, less bureaucracy, and more decentralized decision-making. The general thrust is clearly that the labs should become more like the private sector. This type of culture would probably be incompatible with the significant majority of scientists, which in turn suggests that the labs may wish to consider stand-alone facilities which are dedicated to commercial projects, operating with their own rules.

Two comments also open the discussion of the necessity of a government pool of seed money to help with commercial projects. Much time can be wasted, and competitive advantage therefore lost, if a champion has to convince third party financiers of the commercial potential of a new technology. Establishing a "risk-money" pool of capital to help prototype development, market research and advertising might be considered as a mechanism to substantially improve the labs' results in high involvement commercial projects.

5.2 Project Team Selection

Collectively, the respondents' comments emphasize the notion that potential partners need to be rigourously pre-qualified. Especially, the potential partners need top credentials and similar objectives. The need for dedicated champions, both managerial and technical, was also highlighted. We believe that these comments reinforce the propositions of the Theory of Cascading Commitment pertaining to the need for many organizations and many champions needed for the team, but only those which have the necessary credentials and commitment. They are also entirely consistent with private sector practice to form complete and dedicated cross-functional teams.

5.3 Project Implementation Process

Beyond assembling the right team, the project manager should strive to optimize the execution of a high involvement project. Several respondents' comments emphasize the ideas of early and intimate contact among all the members of the team, especially early contact with the end customer of the technology. The need for project speed and the need for the team to endure until commercial launch are also highlighted. These observations go beyond the scope of the Theory of Cascading Commitment, but are entirely consistent with current "fast cycle" practices in the private sector.

To accomplish speed, techniques such as concurrent engineering and stage-gate project execution are ubiquitously employed.

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6. Discussion and Best Team-Building Practices

6.1 Support for the Theory of Cascading Commitment

In general, the quantitative results tend to confirm the Theory of Cascading Commitment. However, pains have been taken to point out that this study examined a very small convenience sample, thus these results can only be considered tentative. The essential results are:

Propositions 1-2: A Complete Team Necessary

We found that the average number of linchpins on successful teams was significantly larger than on unsuccessful teams.

Proposition 3: Optimal Recruitment Sequence

We found numerical and managerially significant support for all of these sub-propositions: the earlier the test customer is recruited, the better; the earlier the re-seller is recruited, the better; and recruiting the test customer before the re-seller is better. Note that in some cases the statistical significance was weak.

Proposition 4: Optimal Recruitment Stage

We found numerical and managerially significant support for all of these sub-propositions: the earlier the stage of government/industry contact the better; the earlier the stage of test customer recruitment the better; and the earlier the stage of re-seller recruitment the better. Note that in some cases the statistical significance was weak.

Proposition 5: The Need for Commitment

We found equal and high levels of commitment for the linchpins in unsuccessful and successful projects. We conclude that commitment is necessary but not sufficient for project success.

Proposition 6: The Determinants of a Linchpin's Commitment

We found significant support for the proposition that linchpins are motivated by a variety of factors drawn from a diversified set of perceived incentives and rewards, and the credibility of the team's prior organizations and/or linchpins. The most important motivators appear to be the linchpin's perceived technical and financial benefits for the end customer. Interestingly, monetary rewards do not seem to be a prime motivator for lab scientists.

The additional qualitative commentary provided by the respondents confirmed the importance of very carefully selecting the right individuals from the right companies in order to maximize the probability of success. In view of the evidence, and in spite of the small sample size employed in this study, we feel that the Theory of Cascading Commitment has been substantially supported. Therefore, we feel comfortable in using our findings to provide recommendations which help the labs move towards a set of best team-building practices.

6.2 Towards Best Team-Building Practices for Lab Managers

The results of this study suggest that these would be a good starting list of best team-building practices to consider for lab managers:

1) In selecting the commercial project portfolio, and all other factors being equal, place more emphasis on projects with industry or jointly-conceived technology; clearly, this does not imply that lab-conceived technologies should be eliminated from the portfolio;

2) For each project, recognize that a complete team of linchpins will be necessary, and allocate the necessary time and financial support for the project manager to identify and recruit the linchpins;

3) Advise the project managers to recruit a credible test customer and re-seller as early as possible in the development cycle, recruiting the test customer before recruiting the re-seller; if a test customer cannot be recruited, it may indicate a lack of market interest, and suggest the need to cancel the project;

4) Identify possible sources of early stage seed/risk money to enable the project manager to conduct initial commercial feasibility studies, identify credible test customers, and fabricate alpha prototypes to help attract test customers;

5) Consider the implementation of fast cycle and stage-gate project management techniques currently employed in the private sector; and

6) Do not rely strictly on monetary rewards to motivate the lab scientists.

6.3 Limitations and Potential Future Research

The actual number of useable projects, and the number of respondents per project, were substantially lower than we expected (see response analysis) because the retrospective snowball methodology we employed proved to be extraordinarily difficult and time-consuming to execute. Any future studies designed to substantiate or enhance our findings should probably adopt a real-time longitudinal approach, which would thus necessitate a 6 to 8 year study.

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Appendix A

Projects in the Study

Lab	Project#	Project Name	#Chris	Success1
AAFC2	1. 2. 3. 4.	Predator Mites Fermented Dairy Ingredients DNA Probe Red Clover Cultivar	2 2 1 2	4 2(U) 1(U) 7(S)
CAMNET	5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.	Automated Ultrasonic Flaw Imaging Varistor Technology X-Ray Diffractometer Strip Casting of Lead-Antimony Sheet Superplasticizer for Concrete Blast Furnace Slag for Concrete Ceramic-LT Total Cyanide Analyzer Safe-T Mortars Hydrotreating Catalyst Ceramic Filter System	3 2 2 2 1 1 1 1 2 1 2	6(S) 6(S) 6(S) 7(S) 7(S) 1(U) 5(S) 1(U) 1(U) 2(U) 5(S)
CRC	16. 17. 18.	Skyfax Data Hail Dollar Bill for Visually Impaired	3 3 3	6(S) 6(S) 6(S)
ENV	19. 20.	MAP Extraction Oil/Water Separator	1 1	6(S) 1(U)
NRC	21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34.	Vacuum Fingerprint Chamber Real-Time Photogrammetric Techniques Ultrasonic Measurement System Smartbar Anticounterfeiting Technologies Herbicide Tolerant Canola Chimeric Antibodies Agricultural Atomizing Nozzle Fuel Combustion Atomizing Nozzle Gas Cleaning Atomizer Coin Cell Assembly Hardware Coal/Oil Agglomeration Membrane Technology Thin Film Luminescent Display	4 1 1 4 4 2 1 2 2 2 1 1 1 1	5(S) 3(U) 4 1(U) 5(S) 1(U) 7(S) 7(S) 5(S) 6(S) 5(S) 1(U) 4 7(S)

Notes:

1. Scale rating 1 = very unsuccessful re RSM's profit objective (ratings 1-3 grouped as "U", i.e., Unsuccessful) Scale rating 7 = very successful re RSM's profit objective (ratings 5-7 grouped as "S", i.e., Successful)

2. AAFC = Agriculture and Agri-food Canada
CANMET = The Canada Centre for Mineral and Energy Technology
CRC = Communications Research Centre
ENV = Environment Canada, NRC = National Research Council

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Appendix B

Respondents' Comments on Commercialization and Team Issues

Re: Commercialization Infrastructure

"Government should recognize, acknowledge limitations, especially their knowledge of industry, markets and the commercialization process." (TTA-6)

"Second government managers into companies where such processes are at work to get a reality check and first-hand knowledge." (TTA-6)

"Promote staff secondment with industry." (GM-5)

"(Implement) training." (GM-4)

"Provide better financial management tools and expertise associated with business." (GS-4)

"Provide funds for networking/travel/professional development of their staff, (and don't) regard same as junkets." (GS-4)

"Obtain training/experience in IP management and commercialization. (GM-6)

"Provide technical and PY support to the staff." (GS-7)

"Establish more formal and structured agreements with defined escape clauses." (GM-1)

"I believe government research is somewhat handicapped by bureaucracy. Reduction of these kinds of overheads would make the research labs more competitive. Reducing the numbers of management personnel would also focus the effort more on the research program rather than on the constant re-organization of the department." (GS-2)

"Use, or set up, commercialization support infrastructure." (GM-4)

"Decentralize decision-making." (GS-4)

"Better advertise themselves. I didn't have a clue what the NRC did before this project. The NRC is an extremely valuable asset to Canada! People don't know of the great things they do!" (RSM-5)

"Be more in touch with "real life" business issues and avoid approaching commercialization from a very bureaucratic perspective. Too many roadblocks were set up on the road to the market." (TCT-5)

"Reduce requests for reports, it's too time consuming. Create a fill-in-the-blank template." (GS-5)

"Establish rewards, awards and promotion systems to recognize performance." (GM-7)

"Encourage and promote risk taking and entrepreneurial approaches." (GM-7)

"Assist in identifying and obtaining government funding sources." (RST-4)

"Understand and work like private industry employees where success or failure means either having or not having a job." (RST-7)

"(Provide) access to an Innovation Centre." (GM)

"The government manager did a great deal to maximize commercialization of the project; (e.g.), articles were issued in related publications to promote the project." (RST-5)

"Allow for more government money to be spent on commercialization. All our money, including NRC money, went to development, leaving little for marketing and commercialization." (RST-6)

Re Project Team Selection

"Government managers should pay particular attention to identifying which industrial organizations will be effective partners in applying project results to solve problems or support commercial objectives." (RSM-7)

"Seek a better understanding of potential partners and their agendas." (GM-1)

"Pick partners having the same objectives." (GM-1)

"Perform due diligence. Try to ensure that only appropriate partners and collaborators are chosen." (GM-7)

"Each project requires a dedicated champion on both sides, and in all cases there needs to be a management champion and a technical champion, in those positions for the duration of the project." (GS-6)

"In successful technology transfer there must be a champion, one who seizes the project and makes sure that it gets from the laboratory to the marketplace." (GM-5)

"The transfer agent must show more enthusiasm and be willing to devote more resources. They should also monitor the licensee's performance, and act if performance is poor." (GS-1)

"Bring all parties/leverage to bear and assist in showing value in the technology to potential investors and the financial community." (GM-7)

Re: Project Implementation Process

"(Encourage) direct personal contacts between the research scientists and their industry counterparts." (GM)

"Listen to private industry, and realize their needs." (TCM-7)

"(Establish) better contacts with industry during the initial stages of development." (GS-1)

"Work closely with the users or customers, and spend time at the user's workplace personally." (GS-6)

"Work with customers and potential re-sellers at an early stage." (GM-6)

"Provide early lab prototypes to technology recipients." (GM)

"Develop the product and demonstrate a working prototype, and test it with the users, before commercialization." (GS-6)

"Work with the manufacturer closely; if possible, bring the technical staff of the manufacturer into the government labs for extended periods." (GS-6)

"Have regular meetings with the customer and re-producer." (RSM-6)

"Time is of the essence. Speed up the process." (TCM-7)

"Encourage strong communication through the research team, and particularly between the research team and the re-seller." (GM-7)

"Intimately involve the research scientists in the collaborative cross-license arrangements." (GM)

"File patent applications prior to publication in the open literature." (GM)

"The technology transfer office (has a key role) in the negotiation, finalization and administration of all agreements." (GM)

"Don't give up on a project before it truly hits the market and is accepted by the market." (GM-5)

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Footnotes

1. Belinko, Keith and David W. Large (1995), "Commercialization of publicly funded technologies: successful team building" Optimum, (The Journal of Public Sector Management), Volume 26-1 (Summer), p. 15-21.

2. Large, David W. and Keith Belinko (1995), "Building Successful Technology Transfer Teams: A Theory of Cascading Commitment", The Journal of Technology Transfer, Vol. 20-1 (April), p. 67-83.