J Technol Transf DOI 10.1007/s10961-012-9267-6
University startups as a commercialization alternative: lessons from three contrasting case studies Paul M. Swamidass
Springer Science+Business Media New York 2012
Abstract A recent National Research Council (NRC) report (2011) recommends that universities must craft policies and allocate resources to enable more university startups because some university technologies will never be commercialized unless licensed to a startup. However, the creation of university startups requires personnel skills and programs not typically associated with an university Office of Technology Transfer (OTT). Estimates show that 75 % of university inventions are not licensed at all. The conclusions of this study include university policies to turn some them to fuel university startups. Carefully selected case studies of three contrasting universities reveal patterns of successful startup policies and performance. MIT’s case is an example of long-term success, the University of Colorado’s case is an example of medium-term success, and Auburn University’s case is an example of a new-comer to the scene. Lessons from the case studies include: the need for very early evaluation of all inventions for their startup potential, the need for prelicense seed funds through proof-of-concept programs to advance early-stage inventions to the next stage, and the need for OTT personnel skilled in enabling startups. NSF’s recent I-Corps program invests heavily in the training of potential enablers and entrepreneurs for commercializing university inventions. Based on the findings of this study, I-Corps must also invest in pre-license proof-of-concept programs to advance early-stage university inventions closer to the market. Implementing the conclusions of this study would also accomplish the recommendations of the 2011 NRC report cited above. Keywords University spinoffs and startups Proof of concept (POC) Technology development stages Management of innovation Technology transfer NSF I-Corps program Auburn University MIT The University of Colorado Stanford University JEL Classification M13
P. M. Swamidass (&) College of Business, Thomas Walter Center for Technology Management, Auburn University, Auburn, AL 36849, USA e-mail:
[email protected]
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1 Introduction A startup may be the best or the only option for commercializing nearly 75 % of university inventions that are never licensed to commercial entities. History shows, unless licensed to a new startup, many university inventions will remain on the shelf indefinitely, benefiting no one; all the investments made in the research leading to the inventions may never be recovered fully or partially (Hayter 2010; DeSimone and Mitchell 2010). It is no surprise that Merrill and Mazza (2011), in their National Research Council (NRC) report, recommend that universities must adopt new policies to increase the incidence of new university startups (the terms ‘‘startups’’ and ‘‘spinoffs’’ are used interchangeably in this paper) to commercialize technologies that may never get commercialized otherwise. One of their recommendations asks universities to ensure that new inventions are evaluated routinely and systematically for their suitability for startups, and another asks them to institute expedited procedures and standardized agreements for easier licensing of university inventions to startup enterprises (Recommendation #9 and #10). Most universities may need new university tech transfer policies to comply with the recommendations of the NRC to enable more startups with university inventions. The goal of this study is to investigate appropriate university as well as public policies to enable more startups based on university technologies. 1.1 Is there a university commercialization problem? Since the Bayh-Dole Act of 1980, US universities have ownership to inventions resulting from federally-sponsored research. Given this ownership to inventions, university Technology Transfer Offices (TTO) prefer to license to ongoing firms because it is much easier than enabling a new startup (Chukumba and Jensen 2005). During 1995–2004, based on an analysis of data routinely published by the Association of University Technology Managers (AUTM), new university startups grew at a rate of 0.14 startups per Research University per year (Swamidass and Vulasa 2009); it amounts to a growth rate of one new startup in 7 years per average Research University; clearly, there is much room for improvement. Nelson and Byers (2010), based on AUTM data, report that 10–15 % of university licenses during the years 1999 and 2007 went to startups; 50–55 % to small companies (\500 employees), and 30–35 % to large companies. While their study covered licensed inventions it did not tell us much about unlicensed university inventions. We know that a large proportion of every university’s inventions are not licensed. For example, in 2008, in approximate terms, Stanford University Office of Technology Licensing received 400 disclosures, made 200 patent applications and executed 100 licenses. The numerous unpatented and unlicensed technologies are the focus of this study; at Sanford they make up about 75 % of all disclosures. Stanford data is confirmed by AUTM survey data, which shows that, in 2007, 19,827 invention disclosures were received by US Research Universities and institutions (about 200), and 5,109 licenses and options (25.8 % of disclosures) were signed; that means, 74.2 % of the disclosed inventions were neither licensed nor optioned (Bostrom and Tieckelmann 2007). A premise of this study is that 75 % of university inventions that are unlicensed today have many candidate technologies for new startups. The research question addressed by this study is, ‘‘Given the magnitude of unlicensed university technologies, what are appropriate polices to generate more university startups?’’ Three universities with contrasting past experiences with startups are investigated in this study to find answers to this research question.
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University startups as a commercialization alternative Table 1 Technology commercialization at Stanford University (selected benchmarking data; 2009) All Stanford inventions till end of 2008 (approx.)
=7,400
All licenses including active licenses
=2,814 (1,782 active)
Licenses to all startups to date
=196
Estimate of licenses to non-startups
=(2,814–196) = 2,618
2008—Number of annual disclosures each year
=400?
Number of patents filed each year
=*200
Number of patents licensed each year
=*100
‘‘Big revenue’’ generators* Big revenue generating licenses ($500 K or more)
=92 (2009)**
Big revenue generating startups
=30 (out of 92 total)
Benchmark 1: startups as big revenue generators* Percent of startups bringing big revenue
=30/196
=15.3 %
Percent of non-startups bringing big revenue
=62/2,618
=2.4 %
=(15.3 %)/2.4 %
=6.4*
Benchmark 2: startup vs. non-startup big revenue generators Startups over non-startups in bringing big revenue
It appears, startups are 6.4 times more likely to bring in big revenue to the university * This analysis, to be meaningful, needs a large sample of startups. The large sample of startups at Stanford University permits this analysis. This is not a conventional metric collected by AUTM or Kauffman Foundation, who routinely study startup and innovation data. Therefore, data for this analysis is not readily available. Further, the raw data is simplified and aggregated by courtesy of Kathy Ku, Director, Stanford University Office of Technology Licensing. The computation of revenue over the life-time of a licensed invention and its improvements is subject to interpretations This analysis is offered more as an indicative metric rather than a precise one; the precision of this metric would improve when the value of this metric is widely accepted, and frequently gathered and reported by several universities ** 111 as of July 2011; during 2010–11 total royalty revenue $67.8 million from 600 technologies, six inventions generated $1 million or more, 101 licenses concluded, OTL received 450 invention disclosures, and total budget for sponsored research = $1.2 billion Source Courtesy Office of Technology Licensing, Stanford University, CA, USA
1.1.1 An insight into the economic value of startups Unpublished data1 in Table 1 from Stanford University reveals an aspect of the economic value of university startups over licenses to ongoing businesses. Stanford University data for 2009 in Table 1 includes an internal metric titled, the number of ‘‘big-revenue generators’’ among licenses. This metric refers to licenses that brought in at least $500,000/ invention until 2009 in total revenue to the university during the life of the invention. An analysis of the big-revenue licenses provides previously-unpublished information on the relative effectiveness of licenses to startups over licenses. Based on Table 1, it appears that startups using licensed university inventions are 6.4 times more likely to bring in ‘‘big revenues’’ than licenses to ongoing businesses. Bray and Lee (2000) also found that, in the long run, an university’s equity in startups produces a better return than the average license-for-cash arrangement.
1
Data: unpublished data based on an interview with the Director of Stanford University, Technology Licensing Office (TLO), and some TLO documents.
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1.1.2 Equity in startups is worth more After studying patents resulting from NSF sponsored research, Bray and Lee (2000) reported that patents licensed to ongoing companies brought in an average of $270 per man-year of research, whereas, equity held in a startup using university inventions brought in an average of $1,195 per man-year of research. They also reported that the average annual income for universities in 1996 was $63 K per license to ongoing companies versus $1.38 million per startup; the latter is based on the value of the equity sold. Thus, taking equity in a start-up company can be extremely beneficial to the university, and therefore any additional effort by universities to bring about startups is justified. The explanations for the superior economic value of equity ownership are several. First, universities with a small equity ownership in new startups become entitled to a portion of the earnings of the entire company, not just the earnings contributed by the licensed technology. If the company expands its product line with other unrelated technologies, the royalty earnings for the university from the startup could be much larger compared to straight royalty income from licenses; additionally, the total value of the equity in the company would grow as the company grows and prospers. Second, even if the firm replaces the university technology, or discards it, the university would still receive its share of the total revenue or income as long as the university retains ownership in the company. Third, once a patent runs out, the licensee may not owe any royalty to a university, however, if the university owns equity in the firm, its share of the revenue or profits will survive the life of the patent. Fourth, the university is eligible for dividends on the equity it owns. Finally, if the startup goes public through an IPO or is bought out, the cash to the university in exchange for the ownership, history shows, are sizable; for example, Stanford University sold its two-percent ownership in Google for over $300 million. Further, royalty income from the license may survive an IPO event and continue to bring income to the university past the IPO event, if the equity is not liquidated by the university. 1.1.3 The superior success rate for university startups A study shows that 70 % of university start-ups that were founded between 1980 and 1998 were still in operation in 1998 (Gregario and Shane 2003). This success rate of 70 % for university startups is far better than the success rate for non-university startups in the USA; according to the US Department of Commerce (DOC) Census Bureau, 1/3 of small startups survive 10 years or more, and survive 15 years or more. The Bureau of Labor data shows that 34 % survive 10 years or more and 26 % survive 15 years or more. Additionally, data shows that equity in small startups is not trivial for universities and faculty inventors; on average, the value of university equity per startup is approximately $280,000 (Bray and Lee 2000). 1.2 Achilles heel: OTTs are unprepared for university startups While the above paragraphs establish the economic value of startups, most OTTs are unprepared to make them happen because startups require new investors, entrepreneurs, management teams and new cash investment upfront while none of the above is a requirement to license a technology to an ongoing business. This distinction explains the vastly different kind of effort needed on the part of OTTs to bring about startups. Swamidass and Vulasa (2009) reported that the significant hurdle to new university
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startups is the lack of skills at the university Office of Technology Transfer (OTT) to market technologies to potential licensees and startup entrepreneurs/investors (see also, Markman et al. 2005). Often, investors in new startups are angel investors, or early-stage investors. Such angel investors may not always understand the technology but they do understand target markets and cash flow; they invest in promising cash flow rather than the technology per se. Startup investors need credible evidence of a strong projected cash flow; an overwhelming majority of OTTs are unprepared for this demand on their skills. Further, while most university inventions may have no immediate market, they may be relevant to future markets (Merrill and Mazza 2011). The challenge of attracting an investor to a technology with a potential future market is beyond the skill set of most OTTs today. 1.2.1 Risk-averse conduct of OTTs Markman et al. (2005) recognized an underlying problem in universities that hinders new venture creation; they said that the TTOs’ motivation to seek cash flows, while minimizing financial and legal risks, leads to a strategic choice that does not favor new startups. While individual universities are beginning to tackle this problem, the default mode is to settle for license-for-cash deals. Other researchers too concluded that an important reason why universities avoid start-up companies is because of the perceived risks involved (Powers 2000; Markman et al. 2005). New startups are better-suited for products that need new markets because on-going companies with established markets rarely show interest in university technologies that are meant for new markets. Risk-averse OTT offices are concerned that university start-up companies cannot create new markets (Siegel and Wright 2007). Therefore, an important step in creating more university startups is the need for enlightened OTT offices that are willing to take well-calculated risks to tap into new markets for university inventions that are unlicensed today. In summary, university technologies rarely go to new startups because, (1) the average OTT does not have many of the requisite skills to enable startups; (2) by and large, OTT staff are trained and experienced in license transactions with ongoing businesses with established markets; and (3) OTTs are mostly risk-averse and avoid the risks associated with startups. Thus, the challenge of creating university startups boils down to this: take a technology that is unattractive to established firms and make it attractive to founders of a small startup company on the basis of potential future markets for the technology. This is a formidable challenge to university scientists/inventors as well as the average risk-averse OTT.
2 Factors associated with university startups Researchers have found some factors correlated with university startups; Table 2 identifies nine different factors reported in the literature. According to the table, high-quality faculty members, a culture that promotes academic entrepreneurship among science and engineering faculty members, proof-of-concept programs to accelerate commercialization, and policies that enable the university to readily accept equity from new university startups, are some of the important factors. The various factors in this list are not held together by any common theme. The following paragraphs attempt to provide such a theoretical framework for the study of university startups.
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P. M. Swamidass Table 2 The author’s compilation of factors and governing principles associated with university startups Factor
Principle
References
The quality of faculty
Faculty quality related to startup formation; create a supportive culture for faculty through recruitment and development
Chukumba and Jensen (2005) Di Gregoriao and Shane (2003) O’Shea et al. (2005) Powers and McDougall (2005)
Business opportunity recognition by faculty inventors
Savvy inventors who know the market can play a vital role
Shane (2000, MIT data)
The presence of technological opportunities in the market
The opportunity welcomes investors/ entrepreneurs
Shane (2000)
Proof-of-concept development
It accelerates commercialization
Gulbranson and Audretsch (2008)
Size of university TTO
Likelihood of startups increases with TTO size
O’Shea et al. (2005)
Cost advantages of startups
Cost of finding licensee may be more than the cost of enabling a start-up
Chukumba and Jensen (2005)
Rate of return & interest rates
Both have negative effect on startups
Chukumba and Jensen (2005)
Stock market performance
Positive effect on startups
Chukumba and Jensen (2005)
University’s willingness to accept equity
Positive effect on startups; Between 1992 and 2000 universities with at least 1 equity participation grew from 40 to 70 %; small startups can afford to give equity participation
Bray and Lee (2000); Feldman et al. (2002); Jensen and Thursby (2001); Powers (2000) Gregario and Shane (2003)
3 The theoretical basis for the study In this study, an investment risk perspective is employed to give a theoretical basis for the study of university startups. Since many university inventions are embryonic or far removed from the commercial market, they pose a higher level of risk for the potential investor. Under this theoretical basis, a sound approach for improving university startups may lie in policies and actions by universities to reduce this perceived or real risk to potential investors and entrepreneurs by making the technology more commercializable or ‘‘ripened’’ (a term used by Hsu and Bernstein 1997). But, it takes time and seed investment to ripen a technology for the market. In a study of university licensed inventions (not startups only) from 1991 to 1995, Jensen and Thursby (2001) found that 75 % had proofof-concept and the rest did not. Therefore, inventions with a proof-of-concept have 75 % chance of getting licensed. University inventions that have proof-of-concept are inventions that have been ripened at the expense of time and some seed investment.
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University startups as a commercialization alternative Table 3 Description of technology stages and tech transfer strategy Technology growth stage*
Description of the stage (tech transfer strategy)
Early stage invention
Basic science or principle discovered (more suitable for sponsored research; rare startups)
Proof of concept
Additional research/work beyond early stage Demonstration of the principle and demonstration of feasibility (likely startup with equity shared with the university)
Reduced to practice
Additional research/work beyond proof of concept Shows that the technology can reliably produce results (likely startup with equity shared with the university, or outright license for licensing fee/royalties)
Prototype
Further research/work beyond reduced to practice Demonstrates that the technology could be scaled up for production. Technology might be directed to different applications and markets (attractive to outright licensees in return for licensing fees/royalties)
The stages could overlap and the line between any two stages is not hard and fast * Adapted from Markman et al. (2005). Commonly used technology stages and their description in the literature are used, although, their meanings may differ somewhat from researcher to researcher
3.1 Technology progression or ‘‘ripening’’ for commercialization To become attractive to startups, embryonic university technologies must progress through one or more stages of technology development; Table 3 shows four overlapping stages that are used to describe the progression of a technology from an embryonic stage to a prototype stage. The four stages in the table are: early stage invention (embryonic), proof-ofconcept, reduced-to-practice, and prototype. The lines between the various stages are not hard and fast; overlaps between stages are likely because of the manner in which the stages may be defined by different practitioners and researchers. While still under the ownership of the university, if a technology could be ripened by making it progress from an earlier stage to later stages shown in Table 3, the chances of a startup would increase. To ripen a technology that is too embryonic for the market, many universities may have to adopt new policies and make provisions in the OTT budget to move the technology to a later stage of development in Table 3. Gubeli and Doloreux (2005), after an in-depth investigation of three university startups, explain how the successes of the three were a function of pre-incubation technology ripening through investment in preliminary prototype development, and mentoring. In a later section of this paper, three case studies of universities with contrasting successes with startups are presented to document successful processes for ripening university technologies for the market. 3.2 The proposed theoretical model The foregoing discussion indicates that more readily commercializable university inventions pose lesser risks to the investor/entrepreneur, who is attracted to inventions with lower risks. The inverse relationship between an investor’s perceived risk and potential commercializability of university inventions in captured in Fig. 1. A conclusion based on Fig. 1 is, universities interested in increasing the rate of startups must invest time and funds in an infrastructure that would increase the commercializability of inventions and reduce any perceived risk associated with the investment. In Fig. 1, at the point where lines
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P. M. Swamidass Fig. 1 Improving the potential for a startup (The hypothesized relationship: as the university invests time and funds, perceived investment risk decreases, and commercial potential increases). X-axis University investment in time and funds increases left to right. Y-axis (1) Perceived investment risk index ranges from 0 to 25 (arbitrary scale); and Y-axis (2) Commercial potential index ranges from 0 to 25 (arbitrary scale)
for rising commercial potential and falling perceived risk intersect, the invention becomes attractive to investors and entrepreneurs.
4 Ripening the invention: three case studies of contrasting universities Except for a few universities that have mastered the process to bring about university spinoffs, the average Research University in the US is taking baby steps towards increasing the number of spinoffs, and are fuzzy about what needs to be done. This section of the paper takes the reader through three case studies to enable the reader see more clearly what it takes to increase university spinoffs. The three contrasting case studies are from: 1. MIT, an exemplary and mature case; 2. University of Colorado (CU), a rapidly growing and upcoming case; and 3. Auburn University, a newcomer to university spinoffs taking baby steps. The three universities have had vastly different technology transfer experiences as shown in Table 4. 4.1 Potential opportunities for startups Table 4 is intended for displaying the potential opportunities for research universities pivoting towards more startups; it is not intended to be an OTT performance assessment tool. Table 4 is revealing and the contrast among the three universities is striking. Using the data for 2009, the table shows that MIT had 21 startups, UC had 11 (51 % of MIT) and Auburn University had none. The number of live licenses and options in 2009 for the three were: *650 for MIT, 361 for CU (in 2010) and 66 for Auburn. The data in Table 4 is primarily for the year 2009, which was a year typified by severe stock market pull back, unemployment in double digits, and a broken housing industry; consequently, CU (with rapidly growing spinoffs) experienced a significant setback in the annual revenue from equity sales of ownership in startups; see note in Table 4.
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University startups as a commercialization alternative Table 4 Three contrasting cases: success with university startups University case
Case 1 Mature, exemplary
Case 2 Growing/upcoming (% of MIT)
Case 3 Newcomer (% of MIT)
Data for 2009
MIT, 2009
U of Colorado (CU), 2009
Auburn U, 2009
Disclosures
501
232 (46 % of MIT)
87 (17.4 %)
Patents granted
153
27 (17.6 %)
14 (9.2 %)
Number of startups
21
11 (52 %)#
0 (0 %)
Total active startups
Not available
83
15
Equity in number of startups
110
54 (2010; 49 %)
13 (11.8 %)
Licenses and options executed
85
57 (67 %)
15 (17.6 %)
Licenses and options active
*650**
361 (2010) (55.5 %)
66 (10.1 %)
Total income
$75,700,000
$2,800,000* (3.7 %)
$693,000 (0.09 %)
The table is not to be viewed as performance evaluation of newcomers * CU’s total income is subject to fluctuations due to changes in year-to-year equity sales. According to the 2009–10 Annual Report ‘‘…no equity liquidations over $100 K occurred last year, compared to an average of $1.5 M just a few years back. The resulting low total revenue of 2.8 M has led TTO to balance its operations by tapping reserves in its long-term investment account, leaving a beginning FY 2010–11 account balance of $4.6 M. CU’s TTO is poised for revenue recovery based on ownership in 55 companies, a maturing licensing portfolio and a few therapeutic compounds in Phase II and Phase III clinical trials. With help from an improving innovation economy, TTO will be able to continue its past six years of financial self-sufficiency and rebuild many programs,’’ that are meant to assist startup businesses ** Nelson (2007) #
https://www.cu.edu/techtransfer/downloads/CU_companies_2009.pdf
The thesis of this study is that a comparison of these contrasting universities is likely to be more revealing and richer than a study of three universities with similar startup success. The three case studies throw light on the unique internal policies, the environment for startups, and attributes associated with spinoff activities at these universities. A reader may learn certain lessons from the MIT experience, and totally different lessons from the Auburn University experience.
5 Case 1: MIT (exemplary, mature case) 5.1 Breeding a culture of business startups in a friendly ecosystem Louis et al. (1989), after studying the entrepreneurial behaviors of life-sciences faculty, reported that equity holding among faculty at 44 percent at MIT topped all universities. Startups tend to be more in universities such as MIT, where the local group norms and entrepreneurial ecosystems play a vital role in university technology commercialization. A recent study (Roberts and Eesley 2009) reported that 6900 MIT alumni companies were headquartered in MA with estimated sales of $164 billion; about 26 % of sales of all MA companies. Further, they reported 25,000 active companies founded by MIT alumni with worldwide annual revenues of almost $2 trillion—approximately, the 11th largest economy in the world—accounted for a total employment of about a million jobs in MA, 526 K jobs in CA and 230 K jobs in NY. MIT demonstrates that university research does have a significant impact on the economy. Therefore, the emerging interest among many
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P. M. Swamidass Fig. 2 Total cash income $58.6 million/year, 2001–2010 (Source MIT Technology Licensing Office data, MIT TLO (2010))
MIT Tech Transfer 2001-2010 New starups 21/yr
Series1
Options 29/yr Licenses 86/yr Issued patents 159/yr Patent applications 275/yr Disclosures 495/yr 0
100
200
300
400
500
600
research universities to devote more of their efforts to commercialization and startups is justified. 5.2 MIT technology transfer performance and spinoffs Figure 2, shows the technology commercialization performance of MIT during the period 2001–2010; the record is remarkable with 21 spinoffs per year. The figure also shows 495 average disclosures/year, 86 licenses and 29 options a year (licenses and options total 115); a yield rate of 115/495 or 23.2 % of all disclosures. The yield rate for new startups was 21/495 or 4.2 %. MIT’s 21/year startup is particularly notable because it has no medical school, which account for most of the licenses and startups in other universities; this fact was noted by the Director of MIT Technology Licensing Office during the interview with the author. 5.3 What enables MIT startups? Nelsen (2010), the head of MIT Technology Licensing Office (TLO), provides a good overview of the MIT technology transfer scene before and after the Bayh-Dole Act. She notes that an ‘‘entrepreneurial ecosystem’’ provides the impetus; it includes businesses, investment communities and the university in a synergistic relationship that gradually developed over decades in an unplanned, spontaneous way. The MIT ecosystem consists of (Nelsen 2010): ready access to law firms and accounting firms geared to entrepreneurial firms; an enviable and generous supply of local venture capital—with eager participation from New York and California venture firms (this is evidence that capital chases good technology regardless of geographical distance); real estate companies eagerly offering leases to new small companies; a cadre of entrepreneurs and managers skilled in managing and raising capital for earlystage companies; a wave of second generation entrepreneurs with priceless experience in earlier local startups, who want to start their own companies with MIT technologies; and investors and venture capitalists, who have a liking for second generation entrepreneurs. 5.4 Initiatives internal to MIT MIT took several tangible and some experimental steps to energize and cultivate the entrepreneurial ecosystem (Nelsen 2010). First, it started the Technology Licensing Office (TLO) in 1986 for increased emphasis on licensing and marketing of inventions. It contributed to the dramatic increase in faculty participation in patenting and licensing. The
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University startups as a commercialization alternative
number of licenses increased five-fold within 2 years, and doubled again in the next 5 years resulting in a total of 350 total startups from 1987 to 2010 at a rate of 14.5/year during the 24-year period. Second, a set of new policies allowed exclusive licenses to companies in which faculty members/inventors owned equity. As a result of the new policies, MIT began to accept equity from startup companies and enacted strong Conflict of Interest (COI) policies— prohibited licensing companies from sponsoring research in the labs of company founders; COI policies such this are essential to earn the support of university colleagues, who do not invent new technologies. Further, MIT policies promoted ‘‘pervasive entrepreneurialism’’ by promoting the ambitions of faculty, students and alumni. Furthermore, MIT promoted the interactions of MIT faculty/students with volunteers from the surrounding business and investment communities for advice and consultation concerning commercialization. The lesson is: MIT has been proactive with its policies towards commercialization and there appears to be a correlation between proactive policies and commercialization performance at this university. 5.5 Initiatives to boost the MIT entrepreneurial eco-system The entrepreneurial ecosystem at MIT is a model one. It may be attributed partially to at least five specific initiatives/practices unique to MIT (see Table 5 for details). First, the MIT Enterprise Forum of the MIT Alumni Association that was started in 1978; second, the Venture Monitoring Service that was started by two MIT Alumni in 1997; third, the Deshpande Center funded by a philanthropic endowment to fund high-potential faculty research projects to attract commercial investments; fourth, the popular MIT $100 K Student Entrepreneurship Contest; and finally, curricular and extra-curricular opportunities at the MIT for entrepreneurial learning for students/faculty/alumni. A notable initiative at MIT School of Engineering is the Deshpande Center, which got started with an initial grant of $17.5 million in 2002; it provides about $1.7 million/year for ‘‘Ignition Grants’’ of up to $50 K/project, and ‘‘Innovation Grants’’ of up to $250 K/ project—selected research projects of faculty members are funded if they show strong commercial startup potential. By November 2007, the Center had funded 39 Ignition Grants and 39 Innovation Grants at the rate of approximately 16 grants a year. The Deshpande Center alone was responsible for 10 startups employing 150, and attracted nearly $89 million in private equity by Nov. 2007. Thus, $1.7 million/year in grants from the Center from 2002 till 2007 was leveraged to attract $89 million in investments. Thus, Deshpande-Center-style initiatives for making selected faculty research attractive to startups are worthy of emulation by other aspiring universities. Universities often obtain gifts from donors for enhancing sports and building facilities, but it would be a desirable goal for more universities to seek donors, who might fund a center such as the Deshpande Center that enhances the commercializability of embryonic university inventions. 5.6 TLO practices that specifically contribute to startups at MIT Universities aspiring for more startups must pay close attention to the following practices of MIT TLO. First, following the disclosure of an invention, experienced technology licensing officers at the TLO evaluate the disclosure for technologies potentially suitable for startups—they look for technologies with cutting edge applications in new markets with a broad range of potential applications—this is not a common practice in most OTTs. Second, TLO is supportive of the inventor (faculty member, student) interested in founding
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P. M. Swamidass Table 5 MIT’s entrepreneurial eco-system No.
Intiative
Decription
1
MIT Enterprise Forum of the Alumni Association; 18 chapters in the US; started 1978
1. Education and assistance to entrepreneurs and emerging companies 2. Periodic events, ‘‘concept clinic,’’ ‘‘startup clinic,’’ ‘‘growth company clinic,’’ ‘‘conferences,’’ etc. 3. Networking bonanza for entrepreneurs, angel investors, service providers, and others
2
The Venture Mentoring Service started in 1997 by two Alumni who were successful entrepreneurs
1. A mentoring service by volunteers for MITaffiliated entrepreneurs 2. Advice on offer on technology, marketing, teams, business plans, fund-raising, presentation, etc.
3
The Deshpande Center, started in 2002 at the MIT School of Engineering with a $17.5 million philanthropic endowment. Unique quality being, commercialization thinking is advanced to the research stage
1. Funds faculty research with potential for commercial use 2. Project selection committee consists of entrepreneurs, angel investors, and venture capitalists 3. A mentor ‘‘catalyst’’ volunteer from the Advisory Board assigned to each funded project 4. At the research stage itself, commercial benefits, commercial applications, and experiments to demonstrate proof-of-concept are introduced by the ‘‘catalyst’’ 5. ‘‘‘‘Catalysts’’ articulate commercial benefits, see commercial applications, and demonstrate proof-of-concept for commercial use 6. Each funded project team is matched with a Innovation-Team (I-Team) composed of MBA students from Sloan School of Management, to speed market identification and early applications 7. Arranges networking between project teams and the investment community for an early look at the opportunity 8. Between 2002 till 2009, the Center enabled 14 startups that have collectively raised $100 million
4
100 K Entrepreneurship contest
Since 1989, run primarily by graduate students; ideas could come from MIT research or elsewhere, over 85 companies raised $600 million in venture capital
5
Other
The Entrepreneurship Center and MBA track for Entrepreneurship at the Sloan School of Business, dozen or so student venture and innovation clubs at MIT, and several short courses on IP, entrepreneurship and innovation in January by volunteers from the business and investment community
Source Nelsen (2010)
a company without leaving the university—at MIT, faculty members could serve as advisors, consultants and Board members in university startups but cannot be ‘‘line’’ officers.
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Third, TLO introduces MIT technology to potential investors including venture capitalists, whose investment profiles appear to fit the invention/inventors. During the interview with the author, the head of TLO indicated that venture capitalists often prefer not to invest in MIT startups after angel investors, particularly inexperienced angel investors, whose earlier agreements with startups may set unrealistic expectations upon VCs in future rounds. Thus, venture capitalists working with MIT prefer to be the first to invest in MIT technology startups; this may be unique to MIT because, in most universities, venture capitalists are unlikely to precede angel investors. Fourth, TLO provides the following services: enables the investors and founders to put together a business plan for the startup company; crafts license agreements that define the intellectual property; develops milestones to be met by the company (including minimum amounts of capital to be raised) and other items vital to the health of the startup. This is a routine, established practice for MIT TLO, but may not be so at the average Research University in the USA.
6 Case 2: The University of Colorado–CU (rapid growth in startups) Prominently displayed on the web pages of the CU Technology Transfer Office (TTO) were the words, ‘‘The University of Colorado regents and president have made technology transfer a high priority system wide’’ (Accessed May 2011). At CU, the growth in the number of startups during the last decade is remarkable; during 2009, 11 new startup companies were formed, placing the university among the top 10 in the USA. The yearly number of startups from 2001 to 2011 was: 3, 3, 6, 9, 9, 9, 10, 10, 11, 11, 9, and 11, respectively.2 The steady growth in the number of startups over nine years from 3/year in 2001 to 11/year in 2009 (stable around 11 since 2009) is remarkable by any yardstick. University of Colorado could serve as a model for other universities seeking to increase the number of university startups in a relatively short period of time. What is notable is, in the number of startups per year, CU has leapfrogged over several illustrious universities known for large research budgets and ‘‘star’’ researchers. The credit goes to specific initiatives to institutionalize the effort to increase new startups. 6.1 Strengthened startup feasibility & planning process at CU The jump in CU’s startups since 2000 may be attributed to the TTO taking an active role in the early-stage feasibility assessment and business planning for university related start-ups. In June 2002, CU appointed Dave Drake, and when Mr. Drake left, Tom Smerdon was appointed as TTO’s new business development director. At the time of their appointments, both Drake and Smerdon had more than a decade of entrepreneurial, venture capital and technology management experience—these skills are not commonly found in the average TTO. One aspect of the business director’s role in OTT is to facilitate business-formation feasibility studies, and commercialization plans for start-ups. This is accomplished at CU by bringing together teams made of faculty and students enrolled in the colleges of business, science and engineering, and law. Non-university members of the teams are seasoned entrepreneurs, investors, and strategic partners. The teams are able to conduct robust market assessment, management recruitment, and early-stage business planning; these skills and associated activities are not found in a typical TTO. Additionally, CU’s 2
https://www.cu.edu/techtransfer/downloads/CU_companies_2011.pdf.
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entrepreneurship education programs and local business incubators provide special assistance to the startup feasibility and commercialization planning process. 6.2 An early assessment of startup potential At the outset, University of Colorado formally assesses all new inventions for their potential suitability for startups; this practice coincides with a similar MIT practice. This confirms that, in universities with a healthy number of spinoffs per year, an early assessment of each technology for a potential startup is essential. At CU, the TTO examines patentability, patent claim breadth, technical feasibility, and commercial interest to determine whether licensing to an existing company or creating a start-up makes the most sense. Broadly, the process includes the joint assessment of the commercial and technical value of the invention by the inventor(s) and the licensing officer assigned by TTO. Additionally, an evaluation of the startup potential is performed by a larger team under the leadership of TTO. The team evaluating the startup potential would consider the following: inventor’s interest in product development for commercial use; the interest of a third-party business champion/entrepreneur; the best deployment option for different products/services derived from the technology; the potential for raising investment capital and attracting a management team; and conflict of interest (COI) issues for inventors as well as a viable COI management plan. 6.3 After the startup decision at CU Once the decision favors a start-up, TTO works with faculty inventors to identify the right entrepreneurs and investors. The steps that follow are: CU actively consults with business people in the local community and the venture capital industry; CU secures the title to the intellectual property (IP) once startup company management or a company business representative has been identified; and CU options the university IP to the start-up company team for a predetermined period of time to allow the company management time to write the business plan, hire personnel, and raise capital. Once the prerequisites for creating a viable startup are in place, TTO will negotiate a license agreement with the startup company. 6.4 Programmatic proof-of-concept emphasis At the heart of CU’s thrust for increased startups is the early identification of promising technologies and proof-of-concept (POC) funding for them; the importance of this wellarticulated strategy was confirmed during the author’s interview with CU’s head of technology commercialization. This POC focus is consistent with the recommendations of Gulbranson and Audretsch (2008). Table 6 summarizes different POC initiatives at CU. While a few programs at CU included in the table are identified as quiescent due to the economic slowdown in the mid-2011, the infrastructure is in place for these programs to resurrect once the overall economy picks up. As of mid-2011, the results reported in Table 6 are impressive. Table 6 summarizes the results of the different forms of POC programs at CU and their success in attracting follow-on capital; this is an important metric in evaluating such programs. For example, the table shows $1.1 million POCg grants brought in $11.6 million follow-on capital; $3.6 million in BDE Grants brought in $10.9 million; $2 million in POCi
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University startups as a commercialization alternative Table 6 University of Colarado’s (CU’s) proof-of-concept initiatives and results Program effect since 2004
Form
Scope
1. Proof of concept grant (POCg)* Projects 58 Active projects 49 Aggreg. funding $1.1 M Followon capital $11.6 M
$10,000–$25,000 grant to faculty lab
IP expansion, concept validation, enable NIH and Foundation grants
2. Bioscience Discovery Evaluation Grant (BDEG or POCsb) Projects 34 Active 32 Aggregate funding $3.6 M Follow on capital $10.9 M
Up to $200 K grant to faculty lab
Auguments venture quality projects; broader aims than POCg
3. Proof of concept investment (POCi)* # of companies 22 Active 18 Aggreg. funding $2.0 M Followon capital $93.5
Up to $100 K loan to CU startup company, uncollateralized, covervtible to stock
Clinical and commercial proof of principle
4. BDEG Company Matching Grants Awards 27 Active 24 Aggreg. funding $3.2 M Followon capital $110.5 M
Up to $250 K per company
Business development, scientific research, market research, consulting, and legal
5. Proof of concept— renewable energy
Up to $50 K
Research and commercial validation
6. Market assessment program (MAP)
Up to $12 K
Feasibility planning, commercial roadmap
Source www.cu.edu/techtransfer/proof/ August 29, 2011 Summary: Total funding for the four POC programs above: $9.9 million Total followon capital: $226.6 million Two out of three UC inventions are in the biomedical field, which is emphasized at CU 2012; update: in 10 years of transition until August 2012, CU processed: 2,120 invention disclosures (average 212/year); 1,420 patent applications (average 142/year), and; 325 exclusive licenses and options (average 32.5/year) * These programs quiescent due to fiscal constraint (as of Aug. 29, 2011)
grants brought in $93.4 million; and finally, $3.2 million BDE Company Matching Grants brought in $110 million. In summary, the university was able to leverage a total of $9.9 M seed investments in four forms of POC programs to yield a total of $226.6 M in follow-on capital for startups; thus, in one sense, the investment in POC has a 22.9 (i.e., 226.6/9.9) fold return–the most effective in this regard is the POCi (Proof of Concept Investments with 42 (i.e., 93.4/2) fold return).
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At the start of this case, the steadily growing number of startups at CU from 2001 to 2009 is listed; the startups per year have gone from 3 to 11 per year—266 % increase over 9 years; thus, in terms of the magnitude of follow-on capital and the number of startups per year, the POC-emphasizing policies embraced by CU are paying off. Clearly, given the effectiveness of the POC-stressing strategy, universities looking for new approaches to form successful university startups could emulate the proven policies of CU. Further, CU experience indicates that more than one form of POC-stressing programs may be necessary to address different types of technologies and their unique markets.
7 Case 3: Auburn University (a newcomer to startups) Auburn University (AU), Alabama, is a relative newcomer to the startup scene. Conventional wisdom says that it could be a challenge to form new startups based on university technologies in a small town (population of Auburn/Opelika twin cities about 87,000; 24,000 university students) that is part of a small metropolitan area (a population of about 150,000 in the county). In contrast, the Denver-Aurora-Boulder Combined Statistical Area (CSA) had an estimated population of 3.15 million in 2011; and the Boston-CambridgeQuincy Metropolitan Statistical Area (MSA) had a population of 4.6 million in 2011. Yet, universities such as AU, in small communities, are waking up to the fact that they have inventions that could fuel a number of startups for the benefit of the regional economy and the university community. However, the effort needed to bring about many startups in a small metro area should not be underestimated. Certain developments in Auburn University and the surrounding community since 2004 are notable: First, Auburn University planned and established the Auburn Research Park on the edge of the campus. The park opened its first facility with about 43,000 sq. ft. in 2008, and one of its early tenants was the university Office of Technology Transfer (OTT); the Park has completed its second phase expansion 2 years later to locate a world-class MRI research and commercial center boasting 45,000 sq. ft. This second facility is expected to attract MRI-related research and startup businesses. The construction of the third facility with 68,000 sq. ft. is about half done in 2012; this new facility will be the Center for Advanced Science, Innovation and Commerce. The 156-acre research park has many sites for new businesses to construct their own facilities. Second, the entrepreneurial eco-system began taking shape in 2010–11 with the formation of a local angel investors group called Auburn Angel Network (AAN; the first of its kind here). In a few months, the Network boasted over forty dues-paying members—far beyond expectations. AAN has made four or five investments (not related to AU technology) by April 2012. This reveals deep-seated hunger for entrepreneurial activity in the country, and the availability of private equity in small metro areas even in the prevailing weak economic conditions during 2009–2012. This is a positive sign for all research universities in small communities eager to promote new startups with university inventions. Third, the new Auburn Business Incubator housed in the first building of the Auburn Research Park with offices, cubicles, conference rooms, etc. opened in May 2011. AAN is now one of the tenants at the new Auburn Business Incubator. Fourth, the university has a new commitment to enhancing the commercialization of its inventions through startups; the university reported six startups from 2005 to 2009 for an average of 1.2/year. Fifth, the university participated for the last 5 years in the state-wide Alabama Launchpad competition for business plans based on university inventions. The
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goal of this contest run by an economic-development minded non-profit agency was to award grants to promising university-technology-based startups in the state. Auburn University won the first place award of $100,000, which resulted in a biomedical startup in 2007, and a third-place award of $25,000 in 2011. Sixth, university OTT is leveraging available university resources to increase startups; the Office of Technology Transfer has informal ties with the Thomas Walter Center (TWC) for Technology Management at the university since 2004 for the purpose of using an internal university resource for technology assessment and for developing business plans for startups. The benefits of this relationship are many. First, a startup resulted in 2007 (Modular Carpet Recycling, LLC) as a result of the Center marketing a technology through a business plan developed at the Center. Second, another business plan developed at the Center for an university technology won a third-place award in 2011 in the state-wide Alabama Launchpad contest. Third, in the process of helping the OTT since 2004, the Center has trained over 40 graduate students from engineering and business administration on technology assessment and business plan development thereby preparing trained workforce for the tech transfer ecosystem. Fourth, the Business-Engineering-Technology minor for business and engineering students run by the Center trains students in new products and business plans development; some students from the Program have served as interns at the university OTT for evaluating technologies and for marketing them. Finally, in spring 2011, the university’s Patent and Inventions Disclosure Committee recommended changes to the patent policies to bring it in line with the policies of leading research universities in the country; the intent of the revision was to have policies that are attractive to commercialization-minded strong researchers, who may be attracted to bring their state-of-the-art research to Auburn. The challenges of forming startups in small communities are many, and AU is steadily moving ahead with the goal of putting in place the required infrastructure and processes for increasing the number of startups. One recent lesson learned by AU with regards to startups is that it takes much time and effort to find an entrepreneur/management team for a startup business. For example, finding an entrepreneur-management team for the award-winning third-place 2011 Alabama Launchpad business plan is slow—one wonders if this would take less time in larger, technology-oriented locations such as Boston, Silicon Valley, etc. AU and other universities in small communities embarking on a mission to increase university startups need to work diligently on building a network of investors, potential entrepreneurs, and management team members. Auburn does not have a POC program for university inventions. The University of Colorado experience would suggest that Auburn needs to move decisively in that direction for improving the number of startups. A promising lesson from AU is the successful start of the AAN in the midst of a weak economy during 2010–2011; it revealed the existence of previously-unknown angel investors in this small community.
8 Discussions A significant proportion of patents granted to universities is neither licensed nor optioned (NLO). AUTM data shows that about 75 % of invention disclosures are NLO. In universities that do not have a healthy number of university spin-offs, the inventory of NLO technologies must get a second or third examination and special treatment to turn some of them into university startups; this is a good place to start. For example, a patented invention shelved by the OTT for about 5 years at Auburn University became a startup
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attracting nearly $3 million in private equity, when it was reexamined and marketed by one of the university’s technology management centers outside the OTT. It is now well accepted that some university technologies will never be commercialized unless startup businesses license them. This problem is compounded by the fact that most university OTTs lack the skills needed to bring about startups. Evidence provided in this paper shows that university startups bring better financial rewards compared to licenses to ongoing businesses. Additionally, this study presents evidence of massive long-term benefits from MIT’s technology transfer to the society, the economy, and of course to MIT (BankBoston 1997; Roberts and Eesley 2009). A theoretical model is proposed in the paper (Fig. 1) to explain the policies needed to increase university startups. The theoretical basis for the model is: some university inventions that remain un-commercialized are embryonic in nature with a high degree of risk for the potential licensee/investor; therefore, universities need programs that could move an embryonic university technology closer to the market, and reduce the risk to the investors/licensees by improving the commercializability of such university inventions. 8.1 The success of proof-of-concept programs The theoretical model proposed in Fig. 1 is confirmed by the practices of MIT and the University of Colorado reported here. The evidence is clear that universities desiring more spinoffs/startups must earmark funds and adopt proactive university policies to move risky technologies from the Early Stage (in Table 3) to more advanced stages of commercial development that pose lesser risk to investors. Several POC-stressing initiatives of CU have transformed the university into a powerful actor in the startup scene. For newcomers to the startup sce`ne, CU could be a worthy model to emulate. Another lesson to take away from CU is the fact it uses multiple types of (at least four) POC programs to fund and support proof-of-concept financing projects; given the diversity of technologies in a diverse/integrated university, multiple types of POC programs may be justified.
9 Conclusions Most university inventions are embryonic in nature; that is, they need further development before their commercial value or potential become more imminent or evident. Such technologies may never get licensed by ongoing businesses with established markets; they are better suited for new startups venturing into potentially new markets. These technologies are inherently more risky for potential investors. Therefore, some universities are investing in POC programs that ‘‘ripen’’ these technologies to reduce the risk to potential investors and to increase their commercial value. Lessons from the case studies reported here would favor four selected successful policies and practices for creating more university startups are; they are: assess all university inventions soon after their disclosure for their startup potential with competent OTT staff (see MIT and CU case studies); staff OTT with some employees with entrepreneurial/ investment background and extensive contacts with the investment and business community (through formal and informal networks); encourage academic departments in engineering and sciences to recruit some faculty researchers with interest in startups; and finally, the university must earmark funds to support proof-of-concept (POC) programs to bring inventions closer to the market with reduced risk for potential investors.
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The case of University of Colorado (CU) is evidence that startups can be increased by appropriate university policies. MIT’s case shows that success with startups is partly a function of attributes unique to MIT that cannot be replicated easily, if ever. However, CU’s successful newer policies and programs are in many ways similar to established MIT practices. Therefore, the good news is, after peeling away the attributes unique to MIT, and juxtaposing the CU experience, we can see that there are potent policies and practices that are transferable to any university. 9.1 The validation of NSF’s I-Corp The National Science Foundation (NSF) is diverting a significant amount of research dollars to actively promote startups based on NSF-funded research through its new program called, I-Corps. As of 2011, the NSF started making I-Corps grants available to NSF grant recipients (PIs) to enable the commercialization of their inventions. Grants up to $50,000 are awarded to selected teams composed of a NSF-funded PI, a graduate student likely to work in a startup company using the discovery, and a mentor from the industry. I-Corps began the training of these teams on practical entrepreneurship at two US locations as of 2011–2012. By July 2012, total I-Corps grants reached 100 (for a total of about $5 million since inception, less than a year earlier), and the number of awards is expected to reach a rate of about 300 grants a year. One of the NSF Program Directors for I-Corps, who read an earlier version of this paper, remarked, ‘‘The paper lends strong credence to what we are trying to do with I-Corps.’’ 9.2 Caveats NSF I-Corps program is investing in people and preparing and nudging teams of three members towards startups. However worthy I-Corps initiative is, NSF and similar federal agencies must not underestimate the effort needed to bring about a startup from a successful NSF research project. A typical university researcher, who completes an NSFfunded research project, is not qualified to commercialize a technology; commercialization needs skills that may be alien to almost all NSF-funded inventors. Further, a strong majority of university researchers do not want to become an integral part of startups. Furthermore, the parent university of the PI receiving an I-Corps grant must have a suitable infrastructure tied to the OTT to enable startups based on university inventions. While I-Corps addresses the training aspect of the startup challenge, this paper addresses rest of the challenges faced by universities aspiring to promote new startups with their inventions. A successful new venture using university technology is, at the minimum, a threelegged stool; it needs three determining factors, intellectual capital, angel/venture capital and a strong management team. Weakness in any one of the three will topple the startup or it may never come into being. At Auburn University, in two instances, the intellectual property and an offer for financial investment were on the table, but worthy management teams could not be found within a reasonable time. Thus, the simultaneous occurrence of all three factors is critical to a startup. 9.3 A dual focus for I-Corp? The I-Corps Program that invests in the training of appropriate people is a step in the right direction. This program is evidence that university startups are finally being taken seriously
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at all levels in the country; until recently, university research grants were silent on commercialization. But, for more university startups to occur, internal university POC grants are also necessary to reduce the risks surrounding business investments in embryonic technologies. POC programs can leverage the large investment in the I-Corps Program; perhaps I-Corps program should invest in training as well as POC programs. This could be done by splitting the I-Corps budget into training and POC components; after all, what is really accomplished by training a team if the team’s technology is still embryonic and too risky for potential investors? The recommendations of this study are also relevant to the implementation of NRC Recommendations 9 and 10 cited at the outset of this paper (Merrill and Mazza 2011). Acknowledgments The author gratefully thanks the following for access to data through interviews and unpublished material concerning their university’s technology transfer and for taking the time to check the data presented in the paper: David Allen, Associate Vice President, University of Colorado, Boulder, CO; Katherine Ku, Director, Stanford University Office of Technology Licensing; Lita Nelsen, Director of MIT Technology Licensing Office; and John Weete, Assistant Vice President for Technology Transfer and Commercialization, Auburn University. Without their cooperation, this paper would have been impossible. Errors in the paper, if any, are entirely the responsibility of the author. The author acknowledges two sets of helpful comments of a reviewer that improved the paper.
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