A Perspective On Commercialization Commerce Essay

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From an academic standpoint, the accepted general approach to addressing a question or testing a new hypothesis initiates with a review of the theoretical basis underpinning the issue at hand. Typically, this process flows from an understanding of a broad overarching theorem governing the situation and one would drill down through the relevant work within the body of knowledge to select the concepts, arguments and prior findings that are germane to the case. The appropriate research objectives, or experimental design, would then be established and researched. With respect to the subject of commercialization of university inventions, a complexity arises, as there is no accepted or identified overall governing theory, however, recent interest in this field appears to be focusing on the effectiveness of economic development outcomes.

This economic development attention may be part of a systematic progression, expanding on the existing body of work, or alternatively and potentially more probable, a reaction to the political and financial realities of the day. This latter circumstance is no better exemplified than when, in March 2010, the White House issued a request for information . Its purpose was to identify ways in which to increase the economic impact of federal investment in university research and development. Specifically within its objectives, it sought out information on current best practices within the field of university technology transfer and suggestions for methods of improving the university commercialization process to move technologies out of the lab and into the marketplace. Regardless of the underpinning motivation, a comprehensive academic understanding of this matter is still being developed and given its relevance and significance, it is worthy of full consideration.

In the United States, the commercialization of university inventions falls under the purview of a university's technology transfer office ("TTO"). The process of technology transfer, in its most fundamental terms, is the transfer of a university's intellectual property to a third party for commercial use under some form of legal agreement. One might consider this matter to be purely an economically driven business transaction but the environment surrounding the inputs to this process (i.e., the university academic enterprise) represents a collage of overlapping micro and macro level theories from a variety of disciplines. A similar set of circumstances occurs at the output end of the process, where the inventions emanating from technology transfer offices are being propelled towards a market-driven industrial innovation process. On this industrial end, a number of entirely different, but a no less complex group of theorems and disciplines are exerting influence over the operating environment. Additionally, at the actual interface point where the transfer occurs, commercial contracting practices, laws (e.g., patent acts) and regulatory bodies (e.g., US Food and Drug Administration) impact the process, and as a result, theories within the applied fields of business management, law and public policy enter the framework. Accordingly, the overall functional environment encompassing the commercialization of university inventions can be readily described as falling under the application of a multi-dimensional matrix of theoretical precepts and academic disciplines. Therefore, it follows that in order to derive a suitably holistic understanding of the matter it will require an interdisciplinary, if not transdisciplinary course of investigation. This article sets the argument for such a case.

Conceptual Framework

The linkage from lab to market through the university technology transfer interface is graphically depicted in figure 1 below.

Figure 1. Technology transfer conceptual framework, representing the interlinking of the academic enterprise and the flow of university inventions into the industrial innovation process through the technology transfer interface and the resulting "Valley of Death" demise for many potential innovations.

When examining the conceptual framework, the university academic knowledge enterprise on one side is immediately distinguishable from the industrial innovation process on the other. Between the two lays the technology transfer interface, which is managed by TTOs. One can visually trace the path of research funding entering the academic enterprise; producing new knowledge in the process; then dissemination of the resulting knowledge generating benefits to society. This new knowledge becomes the foundation for further academic enquiry, triggering the next round of research that will repeat itself in an ongoing cycle for as long as there is intellectual curiosity and supporting resources. As recognized by many, a component of this academic knowledge production may provide the potential for economic returns over and above societal benefits. Knowledge that may contain potential economic benefit flows to the technology transfer offices of universities, typically in the form of invention disclosures from researchers. In turn, the TTOs endeavor to have these inventions incorporated into the industrial innovation process through contractual arrangements with the private sector . As it turns out, the majority of university inventions fail to be commercialized and come to rest in a metaphoric "Valley of Death" before they even reach industry. It is also been acknowledged that many potential industrial innovations, regardless of source, suffer this same fate as they progress through the industrial research and development cycle . This additional industry fallout effect is likewise captured within the diagrammed conceptual framework of figure 1.

The interdisciplinary nature of this conceptual framework can be illustrated through the various theoretical premises and academic disciplines underpinning its component elements, some of which are presented below:

At a macro level, the elements relevant to the industrial innovation enterprise are captured through the economic theory of endogenous growth.

At a micro level, finance theory governing investment decision making under uncertainty oversees the evaluation of individual inventions for commercialization. Business-based decisions to proceed with an invention are dependent on achieving an appropriate risk-adjusted, expected rate of return at the level of the firm.

Firm level investment decision-making is further influenced through the aggregate market by the laws of supply and demand for the final products and services emanating from the inventions.

Both the academic and industrial enterprise sides of the equation are influenced by the creation, learning and adoption of knowledge, which lies at the foundation of human capital development theory. The specific role of universities forms a subset of study within education and workforce development theory.

Economic development theory concerns itself with the elements required to support the industrial innovation enterprise, including the location and application of new technologies toward the attraction, retention and development of business enterprises and entrepreneurship. Entrepreneurship is an emerging discipline in its own right.

Government social and fiscal policies are direct elements of political, economic, social, workforce development and economic development theories. In this context, the triple helix relationship and interaction of academic, industrial and government sectors frames the mechanism for effective policy action.

Government policy implementation is an operational component of political science's agency-stewardship theory.

Systems theory covers the interdependency, interconnectedness and interrelatedness of a set of components encompassing an identifiable whole. The process of technology transfer may be classified as a "system".

This non-exhaustive list hints at the breadth of the problem, as the reader can envision certain elements of these different disciplines reaching out to influence the various aspects of the technology transfer process and its operating environment.

Relevance and Estimated Scale of the Problem

Prior to delving deeper into the historic and academic setting surrounding commercialization of university intellectual property, this section provides the reader with some context through an approximation of the economic scale of the problem. A calculation of the opportunity cost attributable to the failure to maximize the commercialization of university technologies forms the basis of the approximation. This estimate may also provide an underlying explanation for the current extent of interest on the part of academicians, policymakers and politicians on the economic effectiveness of the activity.

In the United States, a key influence on the growth of university technology transfer has been the Bayh-Dole Act and by most accounts, this Act has been a success. In the most recent report to Congress, the Congressional Research Service stated that "The Bayh-Dole Act appears to have met its expressed goals of using the patent system to promote the utilization of inventions arising from federally-supported research or development; ... and to promote collaboration between commercial concerns and nonprofit organizations, including universities" . In one of the earliest studies of the legislation, the United States General Accounting Office found agreement among university administrators and small business representatives that the Bayh-Dole Act had "a significant impact on their research and innovation efforts" .

The Association of Technology Managers ("AUTM"), the professional body for universities and other research related organizations involved in technology transfer, is also quick to cite in its annual report that "One need only review the data we've gathered over the past twenty years to know that the Bayh-Dole Act is working. Innovative technologies no longer sit in university labs benefiting no one" . They are very proud to boast that as a result of university innovations products that benefit the public enter the market every day and new companies are formed each year, " putting Americans to work and bolstering local economies" (ibid., p. 3). In addition, AUTM cites that there are currently 38,473 active technology licenses between its members and industry, producing approximately $2 billion in licensing revenue annually.

What neither AUTM nor the reports to Congress say is that approximately 600,000 other invention disclosures, received by TTOs since the enactment of Bayh-Dole, have failed to be commercialized. [1] This represents a potential multiplier effect of fifteen times the existing licensing revenue received by universities, or $30 billion US. Since universities only receive royalty income as a small percentage of end product sales derived from their licensed technologies, in the order of 3% , the ultimate potential economic opportunity cost of these failures is in the order of $1 trillion annually. While simplistically calculated and taken to an extreme, this estimate provides one possible approximation of the order of magnitude and potential depth of the Valley of Death.

Making an Argument - The Historical and Theoretical Setting

Rather than building the case for technology transfer as an interdisciplinary science through an exhaustive examination of all the influencing academic disciplines, the argument that follows is based on focusing on the distinctions and inter-relationships among the key concepts of knowledge, invention and innovation, which underpin the overall process. Ironically, this narrow treatment provides sufficient awareness and argument of the breadth of the issue.

Out of the three concepts to be examined, innovation is considered the sole economic actor, while knowledge and invention form potential inputs into the innovation process. The analysis starts with innovation and the economy. It builds backward from there by examining how the innovation process occurs within industry, then describes the influence of invention on innovation and how new knowledge relates to invention. The role of the university is then considered in the overall context.

Innovation and the Economy

Most of the literature and growth in understanding of the relationship of innovation to the economy stems from the founding works of the renowned economist, Schumpeter. As summarized by Nelson "Virtually all contemporary general accounts of the capitalist engine are based on Schumpeter" . Schumpeter distinguished the inventive process as being separate from the entrepreneur's actions of innovation and pointed out that entrepreneurs innovate not just by determining how to use inventions, but also by introducing new means of production, new products, new forms of organization, etc. In drawing the distinction between invention and innovation, Schumpeter specifically noted that:

Technological change in the production of commodities already in use, the opening up of new markets or of new sources of supply, Taylorization of work, improved handling of material, the setting up of new business organizations such as department stores, - in short, any 'doing things differently' in the realm of economic life - all these are instances of what we shall refer to as the term Innovation. It should be noticed at once that that concept [innovation] is not synonymous with 'invention'…

. . . It is entirely immaterial whether an innovation implies scientific novelty or not … Innovation is possible without anything we should identify as invention, and invention does not necessarily induce innovation, but produces of itself ... no economically relevant effect at all .

The separation of the concept of invention from the concept of innovation by Schumpeter lays out a clear consequence for scientific novelty (i.e., university inventions): essentially inventions are an output of knowledge but do not constitute innovation until applied in an economic sense.

Economic studies in the mid-1950s', particularly by Abramovitz and Solow, revealed that the growth in the US economy from the time of the Civil War could not be accounted for simply through the growth in factor inputs of land, labor and capital. For example, it turned out that the measured growth of inputs (i.e., labor and capital) between 1870 and 1950 could only account for about 15% of the actual growth in the output of the economy. A residual variance of 85% remained unexplained . Solow similarly discovered a very large residual variance, using a different methodology and different period. He obtained a residual of 87½% from his approach . The size of these residuals persuaded most economists that technological innovation must have been a major force in the growth of output in highly industrialized economies. Today, as a result, "It is taken as axiomatic that innovative activity has been the single, most important component of long-term economic growth" .

Following the early macro-economic work cited above, research and development ("R&D") investments by private sector companies have attracted a substantial amount of attention from both business and economic scholars. This is due to the recognized potential for market innovation, productivity improvement and resulting economic impact. As a prime recent example of this type of work, Falk, an industrial economist, sought to determine whether the specialization of R&D activities in the high-tech sector had an additional effect on the per capita GDP of the working age population. He generated estimates of the impact of investment in R&D on long-term economic growth and found that both the ratio of business R&D expenditures to GDP and the share of R&D investment in the high-tech sector had a strong positive effect on GDP per capita and GDP per hour worked, over the long term .

The Industrial Innovative Process

Outcome studies on the effect of private sector R&D, such as those of Falk and his predecessors, has and continues to lead to a need for a deeper understanding of the actual industrial innovation process. Specifically, how do inventions translate into final products and services that eventually make their way to the marketplace? The historian and economist, Maclaurin, conducted an early study on the subject, which followed this question and built on Schumpeter's initial principles. He analyzed the sequence from invention to innovation to economic growth and within his work he formulated a framework that considered (1) the propensity to develop pure science, (2) the propensity to invent, (3) the propensity to innovate, (4) the propensity to finance innovation, and (5) the propensity to accept innovation . Maclaurin's sequence demonstrated an evolution in the thinking associated with the overall process of innovation and most importantly with respect to university inventions, he added the elements of pure science into the mix as a pre-curser to invention.

Today it has been determined that basic science provides a natural starting point for the industrial innovation process and constitutes the initial stage of the linear model of innovation . The linear model of innovation was one of the early frameworks established in order to depict how science and technology relate to the economy. According to the political scientist, Godin, the model contends that innovation starts with basic research, moves through applied research and development and ends with production and diffusion.

The exact origin of the linear model is has never been documented (ibid., 2006). Instead, the model appears to have been generally taken for granted but according to many it is drawn from Bush's work , "Science: The Endless Frontier" . However, Bush like Schumpeter, only discussed linkages between science (i.e., basic research) and socioeconomic progress. He did not provide details on the mechanism whereby science translates into either social or economic benefit through some linear or sequential process.

In Godin's, "The Linear Model of Innovation", he traces the history of the model and argues that it developed in various stages, overlapping in time. Godin argues that the linear model of innovation was not a spontaneous invention arising from the mind of one individual [Vannevar Bush]; instead, it evolved over time in three notable phases:

1. The first phase was during the period from the beginning of the twentieth century to the end of the Second World War (i.e., during the times of Bush and Schumpeter) and it was predominately concerned with the first two terms in the model, namely, basic and applied research. This period was characterized by the ideals of pure science and their potential to be linked to applications.

2. The second phase lasted from 1934 to 1960 and added a third term to the equation, namely development. This created the standard three-stage model of innovation: Basic research → Applied research → Development research. Analytical as well as statistical reasons were cited as being responsible for this adoption.

3. The third phase, starting in the 1950s, extended the model beyond the developmental stage to include the non-R&D activities of production and diffusion.

As prima facie evidence for technology transfer being an interdisciplinary science, these three phases correspond to three separate academic disciplines and their successive entries into the field. Each of the disciplines brought their own concepts and agenda to the forefront. First were natural scientists (academic and industrial): they espoused on basic research as the source for applied research and technology. Second were researchers from business schools: they studied the industrial management of research and the development of technology. Third were the economists: they advanced the understanding of innovation. The three groups, with their differing perspectives, were advocating on three different fronts: (1) public support for basic university research, (2) the importance of technological development to the firm and (3) the impact of research on economic growth and societal benefit.

Of additional note is the long survival of the model despite regular criticism of its simplicity. According to Godin, this is because of the use of statistics. The federal government by collecting official data on research, as defined by its three key components (basic, applied, developmental) and presenting and discussing them one after the other within a sequential framework crystallized the model. The longevity of the linear model indicates both how the use of statistics supports concepts and how their absence limits adoption of other analytical models: "Rival models, because of their lack of statistical foundations, could not become substitutes easily" . This point also provides an argument for further review utilizing a variety of research disciplinary approaches.

Knowledge and Invention

In other attempts to deepen the understanding of invention versus innovation, Ruttan (an agricultural economist) tied together the works of Schumpeter and a Harvard colleague of Schumpeter's at the time, Usher (an historian). In his paper entitled "Usher and Schumpeter on invention, innovation, and technological change" , he summarized the motivation for this work as follows:

Most social scientists would probably accept the sequence in which the three terms - invention, innovation, and technological change - are ordered in the title of this paper as representing a logical sequence; that is, invention in some manner is antecedent to innovation, and innovation is in turn antecedent to technological change. The distinction between exactly what is meant by invention in contrast with innovation, and innovation in contrast with technological change, is usually less clear. This absence of any clear-cut analytical distinction among concepts which have been assigned such important places in current economic discussion is particularly disturbing (ibid., p. 596).

To Ruttan this shortfall in the knowledge base stemmed from a lack of insight of the process of invention, but Ruttan judged the work of Usher to provide a necessary foundation for such understanding. Usher had considered the problem of how and why invention takes place. His solution to the problem was to define invention in terms of the emergence of new things, which require an act of insight going beyond the normal exercise of technical or professional skill. He drew on Gestalt psychology where he summarized inventions as being born out of the cumulative synthesis of a number of simpler insights.

Ruttan considered Usher's cumulative synthesis theory to be appealing on many fronts. In addition to its sound basis in accepted psychology theory, it provides a unified theory of the social processes by which new things come into existence. It is also broad enough to include the entire range of activities characterized by the terms science, invention, and innovation.

From Ruttan's analysis we find other advances in the literature indicating that novel technologies are shaped by social needs [2] ; that they respond to economic opportunities, perceived risk, and factor price changes [3] ; that they cumulate with the accretion of cultural and scientific knowledge [4] and that they can be catalyzed by the exchange of information within networks of colleagues [5] .

What distills from the foregoing collage of scholars and disciplines is the commonality that novelty and inventiveness derives from increased awareness and a growing knowledge base.

Universities and Their Role

It follows from the preceding sub-section that universities would appear to be a logical and effective source of increased awareness and the growing knowledge required for invention. That is to say, the standard academic modus operandi of constantly researching to add to the knowledge base is the ideal production function for inventiveness. However, in a recent and somewhat controversial work, "The New Production of Knowledge. The Dynamics of Science and Research in Contemporary Societies" [6] it is suggested that universities may lose their relative importance as generators of knowledge. While described as a reflective essay by the authors, it proffered an argument that distinguished between two modes of knowledge generation. As the authors later pointed out, their theses had been collapsed into single phrase descriptorss, 'Mode 1' and 'Mode 2'. Mode 1 was defined to be "the old paradigm of scientific discovery characterized by the hegemony of theoretical or, at any rate, experimental science; by an internally-driven taxonomy of disciplines; and by the autonomy of scientists and their host institutions, the universities" . They stated this mode was being superseded by a new paradigm of knowledge production, Mode 2, which was defined as being "socially distributed, application-oriented, trans-disciplinary, and subject to multiple accountabilities" (ibid., 40).

Given the evolving characteristics of this new knowledge production paradigm, the authors predicted a more distributed model of knowledge creation. As fallout from this new paradigm, they speculated universities would lose their relative importance as a knowledge producer. This position was subsequently challenged when Godin & Gingras (social-political scientists) undertook a bibliographic statistical study to determine if there was any empirical evidence to support the claims of Gibbons et al. Godin and Gingras asserted that "diversification is one thing and the decline of universities is another and we would like to suggest in this paper that one cannot infer the latter from the former as is implicitly done by Gibbons et al" . While the Godin and Gingras study was limited to the Canadian situation, the authors found that although they observed real diversification of the sites of knowledge production, consistent with Gibbons et al, universities remained at the center of the system. Additionally, they found that the growth of the other sectors examined (i.e., hospitals, industries and government laboratories) was strongly linked to, and relied heavily on the expertise of universities.

This finding is also consistent with the prior results of a somewhat parallel study in which the authors determined that innovation activities (versus Gibbons, et al's knowledge growth activities) have a tendency to cluster geographically. These authors were able to review patterns of innovation at the level of US metropolitan areas. The conclusions of their study revealed that there was no significant difference among US regions, except when it comes to universities. They found evidence of positive local spatial externalities between university research and high technology innovative activity. The results of their study were based on regionalized levels of private research and development spending as the metric of innovative activity.

Summary

This paper set out to create a case for university technology transfer as an interdisciplinary science. It provided a review of the inter-relationships of the concepts of knowledge generation to invention, to innovation, to economic development as a basis for this case and it presented the interplay of these elements, with technology transfer positioned between invention and innovation, as the pathway linking university research activity to economic innovation. This review also indicated that new knowledge is the key driver of the process and universities are playing an important and increasing role in a more diversified environment of knowledge production. In following this sequence of activity, it becomes evident that a plethora of academic disciplines touches on various points along this pathway, each with their relevant component interests exerting their influence. Given this background, the study of university technology transfer should best be considered an interdisciplinary science. Just as the "Butterfly Effect" describes a potential ripple effect of events, to consider technology transfer policies within the isolated framework of only one discipline (e.g., economic development) sets the stage for unintended consequences. By example: given the current economic development focus of politicians and administrative policymakers in the United States to increase the emphasis of academic R&D as a strategic vehicle for economic development, rather than economic development being a by-product of university R&D, are two radically different positions. This represents a fundamental shift in academic purpose that many academicians question and fear . Without a holistic appreciation of the situation, narrowly constructed policy decisions may create negative externalities that could go well beyond any desired localized economic metrics.

Keywords: interdisciplinary, commercialization, technology transfer, innovation, invention

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