A Perspective On Commercialization Commerce Essay Example

involves intricate theorems and subjects that impact the operating environment. Additionally, at the intersection of transportation, commercial contracting practices, laws (such as patent acts), and regulatory bodies also play a role.

, The impact of regulatory bodies like the US Food and Drug Administration on the commercialization of university innovations affects the procedures within the fields of business management, law, and public policy. Thus, a multi-dimensional matrix of theoretical principles and academic subjects is applied in this functional environment. To comprehensively understand this matter, an interdisciplinary or even transdisciplinary investigation is necessary. This article presents the argument for conducting such a study.

Conceptual Model

When examining the conceptual model, it is apparent that there is a clear distinction between the university academic cognition endeavor and the industrial invention procedure. The engineering transportation interface, which is managed by TTOs, lies between these two aspects. One can visually trace the flow of research support entering the academic endeavor, which then generates new knowledge. This knowledge is subsequently disseminated, resulting in societal benefits. This newly created knowledge serves as the basis for further academic inquiry, initiating a continuous cycle of research as long as there is intellectual curiosity and sufficient resources. It is widely acknowledged that this production of academic knowledge may offer the potential for both social benefits and economic returns.

The knowledge that could lead to economic benefit is often discovered by researchers in the engineering transportation departments of universities. This knowledge is often in the form of innovative findings from their research. The technology transfer offices (TTOs) of universities then work to incorporate these innovations into the industrial innovation process through contractual agreements with

private companies. Unfortunately, the majority of these university innovations fail to be commercialized and are left in a metaphorical "Valley of Death" before they even reach the industry. It is also recognized that many potential industrial inventions, regardless of their origin, face the same fate as they progress through the industrial research and development cycle. This additional industry fallout effect is depicted in figure 1 of the conceptual model. The interdisciplinary nature of this model can be illustrated by the various theoretical assumptions and academic disciplines that underpin its constituent elements. Some examples are provided below: At a macro level, the elements relevant to the industrial innovation endeavor are explained by the economic theory of endogenous growth.

Finance theory at a micro level governs investment decisions made under uncertainty, overseeing the evaluation of individual innovations for commercialization. Decisions made by businesses to proceed with an innovation are dependent on achieving an appropriate risk-adjusted, expected rate of return at the company level. The investment decision-making process at the firm level is further impacted by the laws of supply and demand in the overall market for the final products and services resulting from these innovations. Both academia and industry are influenced by the creation, acquisition, and acceptance of knowledge, which forms the basis of human capital development theory.

The universities play a role in the subset of research within education and workforce development theory. The focus of economic development theory is on the factors necessary to support industrial innovation, including the location and application of new technologies to attract, maintain, and develop businesses and entrepreneurship. Entrepreneurship is an increasingly important field. Government policies related to society, finance, and workforce

development are integral components of political, economic, social, and economic development theories. In this context, the relationship and interaction between academia, industry, and government sectors form the framework for effective policy implementation. The execution of government policies is a practical part of agency-stewardship theory in political science.

Systems theory encompasses the mutuality, interconnectedness, and interrelation of a group of constituents that form a coherent whole. The process of engineering transportation can be categorized as a "system." This list, although not exhaustive, gives an indication of the comprehensive nature of the task. By recognizing how various elements from different fields can influence different aspects of the engineering transportation process and its operating environment, the reader can better understand the complexity involved.

Relevance and Estimated Scale of the Problem

Before delving deeper into the historical and academic context surrounding the commercialization of university intellectual property, this section provides some background by estimating the economic scale of the issue. The estimation is based on calculating the opportunity cost resulting from the failure to maximize the commercialization of university technologies.

The interest in the economic effectiveness of university engineering transportation among academics, policymakers, and politicians may be attributed to this estimation. The growth of university engineering transportation in the United States has been heavily influenced by the successful Bayh-Dole Act. According to a recent report to Congress by the Congressional Research Service, this act has successfully promoted the utilization of innovations derived from federally-supported research or development and encouraged collaboration between commercial businesses and non-profit organizations, including universities. In one of the earliest studies on this law, it was found that both university administrators and small business representatives acknowledged a significant impact on

their research and innovation efforts due to the Bayh-Dole Act.

The Association of Technology Managers (``AUTM''), the professional body for universities and other research organizations involved in technology transfer, highlights in its annual report that the Bayh-Dole Act has been successful. It states that by reviewing the data collected over the past 20 years, it is evident that innovative technologies developed in university labs are now benefiting the public. AUTM is proud to mention that new products enter the market daily as a result of university inventions, and each year new companies are formed. This not only creates employment opportunities for Americans but also strengthens local economies (ibid., p.

3). In addition, AUTM states that there are currently 38,473 active engineering licenses among its members and industry, generating approximately $2 billion in licensing revenue annually. What is not mentioned by AUTM or the reports to Congress is that about 600,000 other innovation disclosures received by TTOs since the passage of Bayh-Dole have not been commercialized.

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This represents a potential multiplier effect of 15 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 from their licensed technologies, around 3%, the potential economic opportunity cost of these failures amounts to approximately $1 trillion yearly.

This estimation provides one possible estimate of the order of magnitude and possible deepness of the Valley of Death, although it is simplistic and taken to an extreme. The statement that follows aims to construct an argument for engineering transportation as an interdisciplinary scientific discipline by focusing on the differentiations and inter-relationships among

the cardinal constructs of cognition, innovation, and invention, which underpin the overall procedure. Interestingly, this narrow treatment offers sufficient awareness and argument of the comprehensiveness of the issue. Out of the three constructs to be examined, invention is considered the sole economic player, while cognition and innovation serve as potential inputs into the invention process. The analysis begins with invention and the economy.

The text discusses the process of innovation within industry and its impact on invention. It also examines the relationship between new knowledge and innovation and considers the role of universities in this context.

Invention and the Economy

Most literature and understanding about the connection between innovation and the economy comes from economist Schumpeter's work. Schumpeter's ideas are fundamental to contemporary accounts of capitalism. He distinguished between the creative process and entrepreneurs' acts of invention, emphasizing that entrepreneurs innovate not only by discovering how to use innovations but also by introducing new means of production, products, organizational forms, etc. Schumpeter identified technological change in existing goods production, exploration of new markets or sources of supply, work Taylorization, improved material handling, and establishment of innovative business organizations like department stores as examples of economic activity's innovation.

It is crucial to differentiate between the term 'invention' and the construct [invention].

The level of innovation in an invention is not determined by its scientific freshness. It is possible for an invention to be innovative without being recognized as such, and it may not necessarily have an economic impact. Schumpeter's distinction between innovation and invention is important when considering scientific novelty, especially in relation to innovations originating from universities. Innovations

are the result of knowledge but are not considered inventions until they are applied within an economic framework. Economic studies conducted in the mid-1950s, specifically by Abramovitz and Solow, demonstrated that the growth of the US economy since the Civil War cannot solely be attributed to factors like land, labor, and capital.

The output growth of the economy between 1870 and 1950 was only explained by about 15% of the increase in inputs, such as labor and capital. This leaves an unexplained residual discrepancy of 85%. Solow also found a large residual discrepancy of 87.5% using a different methodology and time period.

Technological innovation is widely acknowledged as a major factor in driving industrial growth in highly industrialized economies. It is now recognized that advanced activity plays a fundamental role in long-term economic expansion. Consistent with previous macro-economic research, investments made by private sector firms in research and development (R&D) have attracted significant attention from business and economic experts. This is because these investments have the potential to stimulate market innovation, improve productivity, and generate economic advantages.

As an example of this type of work, Falk, an industrial economic expert, conducted a study to determine whether the specialization of R & D activities in the high-tech sector had an additional impact on the per capita GDP of the working age population. Falk's estimations showed that both the ratio of business R ; D expenditures to GDP and the proportion of R ; D investment in the high-tech sector positively affected GDP per capita and GDP per hour worked in the long term.

The Industrial Innovative Process

Outcome studies on the impact of private sector R ; D, like Falk's and

those by previous researchers, have led to a need for a deeper understanding of the actual industrial innovation process. Specifically, how do innovations translate into final products and services that eventually reach the marketplace? Maclaurin, a historian and economist, conducted an early study on this subject, which followed this question and expanded upon Schumpeter's initial principles.

In his work, Maclaurin analyzed the progression from innovation to invention to economic growth. He developed a model which incorporated various aspects including the inclination to develop pure scientific discipline, the inclination to contrive, the inclination to introduce, the inclination to finance invention, and the inclination to accept invention. Maclaurin's sequence demonstrated a shift in thinking regarding the overall process of invention, particularly in relation to university innovations. He introduced pure scientific discipline as a precursor to innovation. Today, it is widely recognized that basic scientific discipline serves as a natural starting point for the industrial invention process and constitutes the initial phase of the additive model of invention. This model was conceived early on to illustrate the relationship between science, technology, and the economy. Political scientist Godin argues that according to this model, innovation begins with basic research, progresses through applied research and development, and concludes with production and diffusion.

The precise origins of the additive theoretical account have never been documented (ibid., 2006). Instead, it seems that the model has generally been assumed to have been derived from Bush's work, "Science: The Endless Frontier." However, both Bush and Schumpeter only focused on the connections between science (i.e.

The text discusses the linear model of innovation and its development over time. According to Godin, this model did not originate from one

individual, but rather evolved in three stages. The first stage, from the early 20th century to the end of World War II, focused on basic and applied research. During this period, there was an emphasis on connecting pure science with practical applications. The second stage occurred from 1934 to 1960 and introduced development research as a third component of the model. This created the standard three-stage model of innovation: basic research, applied research, and development research.

Both analytical and statistical evidence were cited as the reasons for this acceptance. The third stage, starting in the 1950s, expanded the model beyond the developmental phase to include the non-R activities of production and diffusion.

As prima facie evidence for technology transfer being an interdisciplinary discipline, these three stages correspond to three separate academic subjects and their successive entries into the field. Each of the subjects brought their own concepts and agenda to the forefront. The first were natural scientists (academic and industrial) who advocated for basic research as the foundation for applied research and technology. The second were researchers from business schools who focused on the industrial management of research and technology development.

Thirdly, there were the economic experts who brought forth the notion of innovation. The three groups had different perspectives and made recommendations on three distinct topics:

1. The need for public support for basic university research,
2. The importance of technological development for businesses, and
3. The impact of research on economic growth and societal benefits.

It is worth mentioning that the model has endured despite ongoing criticism about its simplicity. According to Godin, this is because it relies on statistics. The

federal government collects official data on research, categorizing it into three main components (basic, applied, and developmental), and presents and discusses them consecutively within a linear framework. This solidifies the model's longevity. The lifespan of the linear model demonstrates both how statistics bolster concepts and how the absence of statistics restricts the adoption of alternative analytical models: "Other models lacking statistical foundations cannot easily replace it."

This point also offers a justification for further review using a variety of research disciplinary approaches.

Knowledge and Innovation

In an effort to enhance the understanding of innovation versus invention, Ruttan, an agricultural economist, connected the work of Schumpeter and Usher, a historian at Harvard who was associated with Schumpeter. In his paper titled "Usher and Schumpeter on innovation, invention, and technological change," Ruttan summarized the rationale for this research as follows: Most social scientists would likely agree with the logical sequence in which the three terms - innovation, invention, and technological change - are listed in the title of this paper. That is, innovation in some way precedes invention, and invention is in turn an ancestor to technological change. However, the distinction between what exactly is meant by innovation versus invention, and invention versus technological change, is often unclear. This lack of distinct analytical differentiation between concepts that hold crucial positions in current economic discourse is particularly troubling. According to Ruttan, this deficiency in the knowledge base stems from a lack of insight into the process of innovation. However, Ruttan believed that Usher's work laid the necessary groundwork for such understanding.

Usher examined how and why innovation occurs and defined it as the emergence of new things that require insight beyond technical

or professional skills. He drew on Gestalt psychology, summarizing innovations as the result of combining multiple simpler insights. Ruttan found Usher's theory of cumulative synthesis to be appealing for several reasons. Not only is it grounded in established psychological theory, but it also offers a comprehensive explanation of the social processes involved in the creation of new things.

The text highlights that the field of science, innovation, and invention encompasses a wide range of activities. According to Ruttan's analysis, new technologies are influenced by societal demands, economic opportunities, perceived risk, and changes in factor prices. These advancements also accumulate with the cultural and scientific knowledge and can be accelerated through the exchange of information among colleagues. Overall, the consensus among scholars is that increased awareness and growing knowledge base contribute to freshness and creativity.

The Role of Universities

Based on the preceding information, it seems logical and effective for universities to serve as a source of increased awareness and expanding knowledge necessary for innovation. The conventional academic practice of continually conducting research to enhance the knowledge base aligns well with fostering creativity.

However, "The New Production of Knowledge. The Dynamics of Science and Research in Contemporary Societies" suggests that universities may lose their comparative importance as generators of cognition. The essay introduces the concept of two different forms of cognition generation: Mode 1 and Mode 2. Mode 1 is described as the old paradigm of scientific discovery, characterized by the dominance of theoretical or experimental science, subject taxonomy determined internally, and the freedom of scientists and their institutions, namely universities. On the other hand, Mode 2 is defined as a new paradigm of cognition production that is socially distributed,

application-oriented, trans-disciplinary, and accountable to multiple parties.

The writers predicted that the new paradigm of cognition production would lead to a more distributed theoretical understanding of how cognition is created. They believed that this shift would diminish the importance of universities as the primary producers of knowledge. This belief was later challenged by Godin ; Gingras, who conducted a bibliographic statistical survey in Canada to see if there was any empirical evidence to support Gibbons et al's claims. Godin and Gingras argued that diversification and the decline of universities are separate concepts, and they disagreed with Gibbons et al's implicit assumption that one leads to the other. Despite finding evidence of diversification in the production of knowledge, the Canadian study concluded that universities remained central to the system. The study also noted growth in other sectors that were examined.

, hospitals, factories, and government research labs) were closely connected to and heavily relied on the expertise of universities. This finding is also consistent with the previous results of a similar study in which the authors found that innovation activities (as opposed to Gibbons et al.'s knowledge growth activities) tend to cluster geographically. The authors of that study analyzed patterns of innovation at the level of US metropolitan areas and concluded that there were no significant differences among regions, except for universities. They discovered evidence of positive local spatial externalities between university research and high technology advancement.

The study's findings were based on regional differences in private research and development spending, which served as the measure of advanced activity.

Summary

This paper aimed to advocate for university technology transfer as an interdisciplinary field of study. It reviewed the connections between knowledge

generation, innovation, and economic development to support this argument. It highlighted the role of technology transfer in bridging innovation and invention, and how it helps connect university research to economic innovation. Additionally, the review emphasized that new knowledge is the key driver of this process, and universities are increasingly important in producing a wider range of knowledge.

The text illustrates that various academic subjects encompass different aspects within the field of engineering transportation. Each subject has its own relevant components that contribute to its overall influence. Therefore, considering university engineering transportation as an interdisciplinary scientific discipline is the most suitable approach. Similar to the "Butterfly Effect" which describes the potential ripple effect of events, restricting transportation policies to just one subject, such as economic development, can lead to unintended consequences.

By illustration, politicians and administrative policymakers in the United States are currently focused on increasing the emphasis of academic R as a strategic vehicle for economic development. This shift signifies a significant change in academic intent, which many academics question and fear. The previous approach viewed economic development as a byproduct of university R, while the new approach recognizes its importance as a primary goal. Without a comprehensive understanding of the situation, policy decisions that are too narrowly focused may create negative consequences that extend beyond local economic indicators.