Elemental Economics

Economics of Biotechnology Home Page



© Harry Hillman Chartrand

Compiler Press, 2007.



0.0 Introduction

0.01 Economics

0.02 Definitions of Biotechnology

0.1 Knowledge & the Knowledge-Based Economy

0.2 Biological Sciences: Wetware vs. Dryware

0.3 Product vs. Process vs. Enabling or Transformative Innovation

0.4 Sub-Sectors

0.5 The IO Model


0.0 Introduction

In this course we will explore 'the economics' of 'biotechnology'.  In this Introduction I first outline, in symbolic logic, the standard model of market economics and then survey alternative definitions of what constitutes 'biotechnology'.  Second, I will define knowledge and the knowledge-based economy which provides the context for the biotechnology industry.   Third, I will distinguish biology and biotechnology from the other natural & engineering sciences and technologies.   Fourth, I will locate biotechnology within the economic theory of innovation.  Fifth, I will survey the various sub-sectors that make up the over all biotechnology industry.  Finally, I will outline the Industrial Organization model that will be used to explore the economics of biotechnology.

0.01 Economics

Please see: Three Page Symbolic Micro


0.02 Definitions of Biotechnology

What is biotechnology?  There are many definitions and facets.  Please see: Multilateral and Other Definitions & Use of Terms.


0.1  Knowledge & the Knowledge-Based Economy

Every organism lives in an active environment consisting of: (i) invariants, e.g., the river, the ocean, the sky, the mountains, the seasons, etc., and, (ii) affordances presented by predator, prey, possible mates and/or symbionts (Grene & Depew 2004).  Environmental invariants become subsidiary or ‘tacit’ to our focal awareness of affordances.  In this view, ‘knowledge’ is orientation in an active environment resulting from the tacit integration of subsidiary and focal awareness into a gestalt whole (Polanyi Oct. 1962).  This is called ‘knowing’.

Such knowledge becomes stored or fixed as neuronal bundles of memories and the reflexes of nerve and muscle.  This constitutes personal knowledge.  Some can be communicated to others; some, such as trained reflexes, cannot.  Thus a brick layer or a brain surgeon has trained reflexes and this cannot be communicated easily to another person.  It is ‘tacit’ and can be leaned only by practice, if at all.  Such ‘tacit’ knowledge plays, as we will see, a critical role in the knowledge-based economy (Cowan, David & Foray 2000).

Humanity, however, lives, as pointed out by Walter Lippman (1922), in a pseudo-environment made out of the complexity of its self-created world.  One’s immediate Space/Time presented by the five physical senses of touch, taste, smell, sight and sound reflects but a small part of the active environment in which one lives, loves and works.  For the rest one relies on what Lippman calls ‘the pictures in our heads’ conveyed through codified knowledge, a.k.a. 'the media'. 

Codified knowledge is fixed in an extra-somatic (Sagan 1977), i.e., out-of-body, media that in Law is sometimes called a matrix.  This conveys knowledge from one human mind to another, usually distant in Space/Time, assuming the Code is mutually understood by sender and receiver (Chartrand July 2006).  Today, codified knowledge takes the form of the written and spoken word, mathematics, the still and moving image, recorded sound & music and, experimentally at least, recorded odour and touch.  In effect, codified knowledge fixes meaning into Matter/Energy.  As noted by Husserl, about writing (but arguably true of all forms of codified knowledge) “makes communications possible without immediate or mediate personal address; it is, so to speak, communication become virtual.  Through this, the communalization of man is lifted to a new level” (quoted in Idhe 1991, 46). 

On the other hand, tooled knowledge, a.k.a., physical technology, is knowledge fixed as function in an extra-somatic matrix.  It enframes and enables Nature to serve human purpose (Heidegger 1955).  Most organisms do not just adapt to their environment they also adjust the environment to serve their purpose, e.g., the ant hill, bird’s nest and beaver dam.  The proof that knowledge can be fixed as function is demonstrated by the practice of ‘reverse engineering’ (Samuelson & Scotchmer 2002).

Tooled knowledge takes three forms: sensors, tools and toys.  The purpose of sensors is measurement of Matter/Energy; the purpose of tools is manipulation of Matter/Energy and, the purpose of toys is pleasure.  Sensors and tools are located on the production-side of the economic equation; toys, on the final consumption-side.  Sensors and tools are utilitarian, i.e., they serve a higher purpose; toys are non-utilitarian, i.e., they have no purpose other than themselves.  Collectively, sensors, tools and toys constitute ‘instruments’.

The critical difference between ancient and modern Science, leaving aside mathematics, is the scientific instrument forcing Nature to reveal her secrets.  Epistemologically Idhe calls this ‘instrumental realism’ (Idhe 1991).  It is the design, development and operation of instruments of ever increasing sensitivity that has allowed humanity to pierce the veil of Nature, of appearances, and establish human dominion.  Such instruments are not verbal constructs; they are tangible works of technological intelligence that measure and manipulate Matter/Energy.

As we will see the economics of biotechnology are fuelled by all three forms of knowledge – personal, codified and tooled.  Ultimately, however, all knowledge is personal.  Without a Natural Person to decode a work or push the right button codified and tooled knowledge remain sterile artifacts without meaning or function.

To understand the meaning of a ‘knowledge-based economy’ (OECD 1996), however, requires us to go a little further and define, in English, what we mean by knowledge rather than simply the forms that it takes.  In English, however, it is difficult to distinguish ways of knowing because the verb ‘to know’ subsumes four different and distinct meanings.  These include: to know by experience or acquaintance; to know by the senses; to know by the mind (derived from the verb ‘to wit’); and, to know by the doing (derived from the verb ‘can’ as in ‘can-do’ or ‘know-how’).  In German there are separate verbs for each (Chartrand July 2006).  Thus when people speak of a knowledge-based economy they generally mean a ‘can-do’ or ‘know-how’ economy, not an economy of the mind.  One final contrast can be drawn between an information-based versus a knowledge-based economy or ‘KBE’.  Knowledge is organized, systematized and retrievable information.

In 1995 the World Trade Organization (WTO) began operations and a new global economy was born (WTO 1994a).  Today, 2007, virtually all member states of the United Nations (UN) belong to the WTO with the notable exception of the Russian Federation.  Put another way, global regulation of political and military competition by the UN beginning in 1945 was extended to global regulation of economic competition by the WTO fifty years later.  This was possible only because of the global triumph of the Market over Marx.

For the first time, virtually all nation-states agreed to abide by common rules of trade recognizing the WTO as final arbitrator of disputes and authorizing it to sanction countervailing measures against offenders of its rules.  Given the historical role of trade disputes fueling international conflict, the WTO compliments the UN as a bulwark of international peace, law and order.  As an international legal instrument, however, the WTO is a ‘single undertaking’, i.e., it is a set of instruments constituting a single package permitting only a single signature without reservation.  One of these instruments is the Trade-Related Intellectual Properties and Services Agreement (TRIPS, WTO 1994b) that constitutes, in effect, a global agreement on trade in knowledge, or more precisely, in intellectual property rights (IPRs) such as copyrights, patents, registered industrial designs and trademarks.  TRIPS is, however, but one part of the complex WTO package that includes the General Agreement on Tariffs and Trade (GATT) and twenty-six other technical agreements. 

TRIPS, in turn, exists in the context of a constellation of international agreements, conventions, covenants and treaties administered by the World Intellectual Property Organization (WIPO 1979) a special subject agency of the United Nations.  TRIPS requires accession to some but not to all WIPO instruments.  In turn, WIPO instruments apply only to Nations-States that accede to them.  Generally, acceding States provide only ‘national treatment’ to citizens of other States, i.e., the same rights are extended as if they were nationals but the rights so extended are defined by each national legislature.  This treatment contrasts with ‘harmonization’, characteristic of other WTO efforts, e.g., definition of subsidies.  Currently ‘in force’ WIPO instruments, as well as TRIPS, ignore and thereby deny protection to ‘non-marketable’ intellectual property rights, e.g., aboriginal heritage rights (Farrer 1994; Chartrand 1995) including rights to traditional ecological knowledge or (TEK) as well as collective or community-based intellectual property rights in general (Shiva 1993).  Such ignored rights, together with commercial rights that have lapsed through time, constitute the public domain of knowledge from which any and all may freely draw.

Creation of the WTO and recognition of the knowledge-based economy by the OECD initiated an avalanche of change.  Almost immediately, rapid institution building began, continuing to this day, in public and private sectors around the world.  A new specialty emerged – ‘knowledge management’, not to be confused with its predecessor - information management; the ‘Chief Knowledge Officer’ (CKO) is becoming an hierarchical feature of multi- and trans-national corporations; governments are creating knowledge ministries, departments and agencies; ‘knowledge audits’ are being conducted by firms and nation-states around the world (Malhorta 2000); and, nation-states themselves are designing ‘national innovation systems’ (NIS) to generate and market new knowledge (OECD 1997).  Even a standardized lexicon or vocabulary is being drafted to guide public and private sector discussion and debate (American National Standards Institute and the Global Knowledge Economics Council 2001). 

One qualification needs to be introduced at this time.  The immeasurability of knowledge is demonstrated by the distinction between information and knowledge management (Bouthillier & Shearer 2002) or between ‘bits’ and ‘wits’ (Boulding 1966).  Information theory involves storage and transmission of human knowledge in electronic rather than hardcopy or analogue format.  These remain the domain of library science and the Dewey Decimal System.  Electronic storage involves audio-video discs, tapes, databases, hard drives, e-books, etc.  Transmission and reception requires hardware such as computers, radios, television sets and the Internet.  ‘Analogue’ content is digitized for storage and transmission then reconverted into human-readable analogue format, e.g., sounds, pictures and words.  The unit of digitization is the binary on/off ‘bit’: (0, 1).  The ‘bit’, however, abstracts from the content of stored or transmitted information.  The same number of bits could emerge from a telephone conversation between two teen-age girls in Saskatoon or between the Presidents of the United States and the Russian Federation.  Bits don’t discriminate.  Developed for the world of telecommunications and computers, the bit lends itself to quantitative analysis.  It does not, however, provide a homogenous unit of knowledge, or what Kenneth Boulding calls ‘the wit’ (Boulding 1966, 2).  The bit also makes no allowance for ignorance, i.e., the absence of knowledge.  Without a wit, we are restricted to qualitative or descriptive analysis. 

Immeasurability has not, however, stopped economists, among others.  The ‘utile’ – Jeremy Bentham’s unit measure of pleasure and pain – is the foundation stone of modern economic analysis.  We cannot, however, measure the pleasure and pain of an individual, nor can we add it up across individuals using felicitous calculus to estimate ‘the greatest good for the greatest number’.  The measurement problem is finessed through reification by proxy.  That is, let us assume the utile can be reified, i.e., made concrete and calculable, specifically as money.  In this philosophy, one works (suffering disutility) to earn income to buy goods and services to consume them, i.e., extract utility.  The money price one pays on the market reflects the utility appropriated by the consumer.  Some day the ‘wit’ too may be reified but at the moment there is no obvious proxy on the horizon


0.2 Biological Sciences: Wetware vs. Dryware

There are three primary natural sciences– biology, chemistry and physics.  Each breaks out into an ever widening range of sub-disciplines and cross-disciplines, e.g., biochemistry.  In each there are distinct engineering specialties, e.g., chemical, genetic, mechanical and, electrical.  It is from these that, today, most physical technology flows.  Price argued that the relationship between Science and Technology is that of the research-front of one relating to the previous generation or archive of the other.  Thus Science operates with the previous generation of Technology while Technology operates with the previous generation of Science (Price 1965, 568).

Knowledge in the Natural & Engineering Sciences (NES) is fact-based and subjected to objective, value-free testing in which replicability of results is the test.  It is concerned with objective truth, understanding and manipulation of the physical world.  It exhibits decreasing tolerance through Time for difference and error as old knowledge is progressively and reductively displaced by the new, i.e., NES knowledge progresses vertically up the ladder of Time.  This assumes, however, ‘normal science’ within an established paradigm not a ‘scientific revolution’ leading to a quantum leap in understanding even with a ‘Kuhnian loss’ (Kuhn 1962, 1970, 1998: Fuller 2000).

When applied for utilitarian purposes, NES knowledge generates physical technology, i.e., the ability to manipulate Matter/Energy to satisfy human want, needs and desires.  Using it in twenty-five generations we have literally enframed our planet with hundreds of artificial satellites enabling ourselves of planetary riches, making them ready at hand to serve our purpose, from the deepest oceans to the outer reaches of the solar system.

Biological science is, however, different from physics and chemistry in a number of ways.  These include: the nature of causality and the classification system used to order understanding of the world around us.

First, causality in biology differs from that associated with physics.  Aristotle identified four causes of things to be the way they are: (i) material cause: that out of which a thing is made, e.g., economic inputs; (ii) formal cause: the form or shape of the final thing, e.g., economic outputs; (iii) efficient cause: the initiating agent, e.g., the entrepreneur or firm; and, (iv) final cause: end purpose or teleos, e.g., satisfaction of consumer wants, needs & desires plus a normal profit.  In effect, traditional 'Newtonian' physics relied upon only material and efficient causes.  It generally ignored formal and explicitly excluded final causes.

Among his many contributions Immanual Kant (1724–1804) established, as a law of nature, that the formal notion of the if-then relationship corresponds to the concept of cause and effect and that there is a single direction to causality, i.e., Time’s Arrow only moves from cause to effect, from the past into the present and then out into the future by means of prediction (Grene & Depew 2004, 93-4).  This law, however, was limited by Kant to matter defined as lifeless stuff (objects) pushed or pulled by measurable forces through Space/Time.  This limitation was required because it was apparent to Kant that material and efficient causes (cause and effect) were insufficient to explain living things, i.e., biology.

Kant addressed the question of biology in his Critique of Judgement (1790) which is divided into two parts.  The first is the “Critique of Aesthetic Judgment”; the second, the “Critique of Teleological Judgment”.  The ordering is important.  While works of technological intelligence, or artifacts, have purpose, works of aesthetic intelligence have purposiveness or meaningfulness but no purpose, i.e., no utilitarian function.

There were three aspects of living things that demonstrated to Kant that teleological or final causes were at play.  I will call these: ecology, metabolism and ontogeny.  First, he could see that the web of mutually supportive relationships between various species of plants and animals constituting an ecological community was so complex that linear ‘when-then’ causality was simply insufficient to explain its existence.  Second, in the metabolism of living things “each part is reciprocally means and end to every other.  This involves a mutual dependence and simultaneity that is difficult to reconcile with ordinary causality” (Grene & Depew 2004, 94).  Third, in ontogeny, or development of the individual, the future mature end-state apparently guides successive stages of development.  This is a clear case of formal and final cause.

Having found teleological processes in living things Kant was concerned to distinguish between Design and designer.  This is, of course, a question that continues to trouble contemporary society.  To do so, Kant distinguished between works of technological intelligence and living things.  Quite simply, parts of a machine are put together by people and parts do not bring other parts into existence, i.e., a machine is not a self-organizing entity.  By contrast: an organism is “a product of nature in which everything is both an end and also a means” and in which the parts are “reciprocally cause and effect of [one another’sl form.” (Grene & Depew 2004, 98-99)

For Kant all works of technological intelligence are finally caused by human purpose.  Living things, however, do not require human or divine purpose but rather reflect a ‘natural purpose’.  Kant called this form of causality purposiveness.  He was so convinced of the inherent complexity of living things that he claimed:

it is absurd for human beings even to attempt it, or to hope that perhaps some day another Newton might arise who would explain to us, in terms of natural laws [cause and effect] unordered by any intention, how even a mere blade of grass is produced. (quoted in Grene & Depew, 2004, 94).

This constraint, as we will see, began to loosen with the discovery by Watson and Cricks of the DNA double helix some fifty years ago.  Their finding that it could split into complementary strands established the physical basis for the encoding and transmission of genetic information within an individual organism and between generations.  In this regard, the New York Times on June 13, 1953 ran an article entitled “Clue to Chemistry of Heredity is Found” calling DNA “a substance as important to biologists as uranium is to nuclear physicists.” (Overbye 2003).  Gathering momentum ever since, genomics achieved critical mass in 1980 with the U.S. Supreme Court decision in Diamond vs. Chakrabarty (447 U.S. 303, [1980]).  The case involved a patent for a genetically engineered microorganism that breaks down crude oil. The Court observed that Congress had the power to limit such patents but by failing to legislate specifically about genetic patents it had, in effect, allowed gene patenting. The Court’s rationale was based on the term ‘manufacture’ in Section 101 of the U.S. Patent Act: “the production of articles for use from raw materials prepared by giving to these materials new forms, qualities, properties, or combinations whether by hand labor or by machinery.” Genes, the Court concluded, were material, i.e., they had tangible material form, even though invisible to the naked eye.

The decision led the U.S. Patent and Trademark Office (USPTO), after initial resistance, to grant genetic patents.  As they say, the rest is history.

Second, biology uses distinct classification systems or taxonomies to order its subject matter.  First, in theoretical biology the world is divided into three spheres: the geosphere of inanimate Matter/Energy; the biosphere of living things; and, the noösphere of human thought.  Second, the biosphere itself is divided into kingdoms based on common forms (morphology) or on evolutionary DNA.  There are five morphological kingdoms according to Whitaker including:

Kingdom Monera which is made up of prokaryotes, i.e., cells without a nucleus including bacteria and archaea, i.e., organisms originally thought to live only in inhospitable conditions such as temperature, pH-extremes, and radiation.  Archaea are considered by Woese to constitute a separate or sixth kingdom;

Kingdom Protoctista which is made up of eukaryotes, i.e., cells with a nucleus, that cannot be classified in any of the other kingdoms as fungi, animals, or plants.  In general they acquire their food by extending their cell wall around the food material to form a food vacuole;

Kingdom Fungi which is made up of eukaryotes such as yeasts, molds and mushrooms which, along with bacteria, are the primary decomposers of organic matter;

Kingdom Plantae which is made up of eukaryotes such as trees, flowers, herbs, bushes, grasses, vines, ferns, and mosses that feed by photosynthesis; and,

Kingdom Animalia which is made up of eukaryotes that feed by consuming other organisms or parts of them.

Kingdoms are, in turn, then progressively sub-divided into Phylum/Division, Class, Order, Family, Tribe, Genus and Species. 

Morphological division has been traditional in biology since the time of Linnaeus in the 18th century.  With the discovery of the DNA helix, however, a new method of classification has emerged based on genomics beginning in the 1980s.  DNA is based on combinations of four nucleotides (or a qubit) made up of adenine (A), thymine (T), guanine (G) and cytosine (C).  These are always paired A-T or C-G.  A sequence of three pairs is called a codon encoding an amino acid.  Amino acids, in turn, combine to form proteins “the molecular machines of life” (Hood 2002).  The study and manipulation of proteins is called proteomics.

Today, biotechnology involves the manipulation of the DNA code or the autobiography of a species (Ridley 1999).  Traditionally and unknowingly, this was done through selective and cross-breeding of plants and animals.  In this sense agriculture was the first biotechnology.  Direct manipulation of genetic material, however, requires:

a) the personal knowledge or ‘know-how’ of molecular biology/chemistry needed to effect a desired change;

b) the codified knowledge documenting the code’s norm state as well as the success or failure of previous manipulations; and,

c) the tooled knowledge or instrumentation required to effect change in the living code.

Different sections of code generate specific proteins.  It is production of specific proteins, their higher order constructs (such as enzymes) and the pathways of production that are the instrumental objectives of genomics realized in its sister science, proteomics, i.e., the science of proteins.

Given the vast array of living things on planet Earth and the different proteins developed and coded by each in its evolutionary struggle for survival, there exists a veritable cornucopia of possible protein codes that may be transferred from one organism to another and/or between types of organisms (transgenetic).  This implies the ability to adapt every evolutionary success of every life form on the planet to the benefit of humanity.

Thus we can now inject (or infect) ‘natural’ with human purpose.  We are arguably beginning the final chapter in human dominion over the Earth extending our grasp out from the geosphere to the living core of the biosphere, its DNA.  One practical implication is that “it has become possible to think that biology can, for the first time, join physics and chemistry as a ‘technoscience’” (Grene & Depew 2004, 345).  And this, of course, brings us to the question of biotechnology.  And with  it we must further distinguish between biotechnology as ‘wetware’ which is carbon-based artifacts such as genetically modified canola versus ‘dryware’ which is silicon-based such as current computer chips, bur perhaps not future ones. 


0.3  Product vs. Process vs. Enabling or Transformative Innovation

In economics we can identify three classes of innovation.  First, however, I must distinguish between invention and innovation.  An invention is a new artifact or process to make an existing artifact.  An innovation, however, is an invention that is successfully brought to market, i.e., it pays its way.  Product innovation thus involves bringing a new product to market, e.g., the iPod.  Process innovation involves a new and generally more cost-effective way of making an existing product, e.g., the Bessemer process in making steel. 

An enabling innovation or technology is a process innovation applicable in the production of a wide range of different goods or services in different industries.  The printing press, telegraph, telephone, radio, television and the WWW Internet are examples of enabling technologies used across all sectors of the economy.  As we will see biotechnology is an enabling technology with respect to existing goods and services but it also promises many product innovations, i.e., new goods and services.

All three – product, process and enabling innovations - involve the impact of new knowledge on the economic process.  The impact of new knowledge on the production function or a firm is called technological change.  Why some things are invented and others are not and why some inventions are successfully innovated and others are not has been called ‘the measure of our economic ignorance’.  As we will see, advances in biotechnology, specifically bioinformatics, may in future aid economists in satisfying their ignorance which literally means ‘want of knowledge’.


0.4  Sub-Sectors

As an enabling innovation biotechnology is like a tidal wave fast approaching the coast line of modern society.  The wake of its bow has already arrived and the contours of the economy are slowly eroding and reshaping.  When the full crest hits sometime in the next decade it will sweep deep inland altering the landscape of human life forever.  It has already reached a number of sectors including agriculture, art, defense, environment, health, informatics, justice and materials technology. 

Some sectors have already been altered dramatically.  This is especially true in agriculture where ‘GM’ food has become a cause célèbre in international trade disputes between the European Union and NAFTA.  Even within agriculture, however, the impact of biotechnology is uneven with plant genomics having a greater immediate impact than animal genomics. The enabling nature of biotechnology, its very ‘newness’, the unevenness of its impact and the varying techniques and technologies used in different sectors presents a problem in the economics of biotechnology (Chartrand 2003). 

In order to maintain an overview we will use the Industrial Organization Model.  This is now a well accepted part of economics with its literature classified by the American Economic Association under category ‘L – Industrial Organization’’ (AEA 2007).  At present this subject descriptor is formally available only with respect to agricultural biotechnology (AgBioForum Subject Index L — Industrial Organization). 


0.5  The IO Model

IO is the brain-child of the late Joe Bain.  His seminal work - Industrial Organization - was published in 1959 (Bain 1968).  Using IO, Bain began what has become an ongoing process within the economics profession of linking macroeconomics (the study of the economy as a whole) to microeconomics (consumer, producer and market theory) to better understand the way the ’real’ world works.  It can be called ‘meso-economics’ in contrast to micro- and macro-economics.

The IO Model takes the industry as the basic unit of analysis.  In effect it is a taxonomy or classification system with limited predictive power.  Its essential prediction is that Basic Condition in an industry determines its Structure that in turn determines the Conduct of its firms that then determines the collective Performance of firms in the industry.

The IO schema (Exhibit 1) thus consists of four parts.  First, basic conditions face an industry on the supply- (production) and demand-side (consumption) of the economic equation.  Second, an industry has a Structure or organizational character, the primary elements of which are barriers to entry, the number and size distribution of firms, product differentiation, and the overall elasticity of demand.  Third, firms in an industry tend to follow typical patterns of Conduct or behavior in adapting and adjusting to a specific but ever changing and evolving marketplace.  Key variables in Conduct include pricing, advertising, capacity, legal tactics and quality of output.  In policy terms, Conduct reflects the strategy of the firm in an industry. Fourth, an industry achieves varying levels of Performance with respect to contemporary socio-economic-political goals defined broadly to include social performance, allocative efficiency (profitability), technical efficiency (cost minimization), and innovativeness.

We will also use four elemental economic terms.  First, buyers and sellers exchange of goods and services in markets - geographic and/or commodity-based.  Second, an enterprise is any entity engaging in productive activity - with or without the hope of making a profit.  This includes profit, nonprofit and public enterprise as well as self-employed individuals.  All enterprises have scarce resources and are accountable to shareholders and/or the public and the courts.  An enterprise is defined in terms of total assets and operations controlled by a single management empowered by a common ownership.  Third, an industry is a group of sellers of close-substitutes to a common group of buyers, e.g. the automobile industry.  Fourth, a sector is a group of related industries, e.g. the automobile, airline and railway industries form part of the transportation sector.  Often, as herein, ‘sector’ and ‘industry’ are used interchangeably, for example - the biotechnology industry or sector.

to 1.0 Basic Conditions



Bain J. S., Industrial Organization, 2nd Edition, John Wiley, NYC, 1968

Chartrand, H.H., Ideological Evolution: The Competitiveness of Nations in a Global Knowledge-Based Economy, Doctoral Dissertation, University of Saskatchewan, July 2006.

Chartrand, H.H., "The Future of Genomic IPRs", March 2003, Saskatchewan Economics Journal, 4, 2003.

Cowan, R., David P.A. & Foray, D.,”The Explicit Economics of Knowledge: Codifcation and Tacitness”, Industrial and Corporate Change, 9 (2), 2000, 211-253.

Fuller, S., Thomas Kuhn: A Philosophical History of Our Times, University of Chicago Press, 2000

Grene M.,& Depew, D., The Philosophy of Biology: An Episodic History, Cambridge University Press, 2004.

Heidegger, M, “The Question Concerning Technology” [1955], in W. Lovitt (trans.), The Question Concerning Technology and Other Essays, Harper Tourchbooks, 1977, 3-35.

Kuhn, T.S., The Structure of Scientific Revolutions, Third Edition, University of Chicago Press, Chicago, [1962, 1970] 1996.

Hood, L., A Personal View of Molecular Technology and How It Has Changed Biology”, Journal of Proteome Research, 1 (5), 2002, 399-409.

Ihde, D., Instrumental Realism: The Interface between Philosophy of Science and Philosophy of Technology, Indiana University Press, Bloomington, 1991.

Lippman, Walter, Public Opinion, [1922] Macmillan, NYC, 1960.

OECD, The Knowledge-Based Economy, Paris, 1996.

Overbye, D., “For the History of Science, the First Draft Is Often Late”, New York Times On-Line, February 25, 2003.

Price, D. de S., “Is Technology Historically Independent of Science? A Study in Statistical Historiography“, Technology & Culture, VI (4), Fall 1965, 553-568

Ridley, M., Genome: The Autobiography of a Species in 23 Chapters: Preface and Chapter 1: Life, HarperCollins, NYC, 1999.

Sagan, C., The Dragons of Eden, Balantine, NYC., 1977.

Samuelson, P. & S. Scotchmer, “The Law and Economics of Reverse Engineering,” Yale Law Journal, 111, 2002.

Scherer, F.M., Industrial Market Structure and Economic Performance, Rand McNally, Chicago, 1971