*) Some parts of this summary were written by Monique Fournier, MSc student during 1996-1997, and by Francine May, MA student in 2001-2002. The course was originally developed in collaboration with Peter van den Besselaar. An analytical introduction to the reader by Peter van den Besselaar can be accessed by clicking here. Note that this introduction is based on an older version of the reader.
Week 2: Questioning Technology
In this chapter we introduce different perspectives on examining technology. The purpose of the chapter is to familiarize you with ways in which one may raise questions about technology.
Devendra Sahal—whom we will meet in another paper as well—distinguishes systematically three alternative conceptions of technology. The author’s purpose is obviously analytical: to organise the results of empirical research. One by one, Sahal introduces the economic conceptualization, the statistical approach (called ‘Pythagorean’ by the author), and his own systems perspective. Try to clarify the differences and/or similarities between the three approaches by taking a concrete innovation, e.g., the robot, as an example. What would each approach imply in terms of, for example, analytical categories and/or empirical research?
In order to see the difference between the three perspectives in terms of policy and policy implications, we suggest that you reflect on the possible effects of the introduction of an environmental legislation that puts an additional charge on pollution. During the meeting we discuss the production function and the related figures presented in the last text in more details.
A collective of authors in Science & Technology Studies (Gibbons et al., 1994) wrote the second paper. It focuses on science policy issues related to technological developments. The authors distinguish between two types of research. “Mode 1” research is concerned with searching for first principles. “Mode 2” research exists in an application based context responding to the demand for solutions to problem. It is said to be transdisciplinary, in transition, and typical for the recent waves of new technologies. Policies developed for “mode 1” research can not be expected to be effective in the case of “mode 2” research.
The third paper by David Noble is from his book America by Design. In this chapter, Noble describes the emergence of modern ‘science based’ technologies in the late 19th and early 20th century, and the intrinsic links with the rise of the modern corporation. This text included also as an introduction to the historical perspective on technology studies. Although the text is rich in historical facts, the line of the argument is analytical. Try to find out, for example, whether you can specify the position of ‘scientific work’ before and after the development that Noble describes. Is Noble’s claim only valid for the U.S.? Do you think that he has a broader claim, and that he could point to analogies elsewhere? Are developments in Europe different, later, earlier?
Week 3: Theoretical Perspectives: Trajectory Approaches
We divided this chapter into two parts that, in our view, represent two major research programs in the area of technology dynamics. Although they do not exclude each other, it seems relevant to first distinguish them analytically before combining them into a concrete research design. The texts in week 2 specifically focus on so-called trajectory approaches in evolutionary economics, while the texts in week 3 focus on the actor/network approach in the sociology of innovation.
Nelson & Winter first formulated the concept of ‘technological trajectory’ in 1977. They built on Schumpeter’s notion that technologies do not occur randomly, but follow instead certain patterns. (Therefore, these authors sometimes call themselves ‘neo-Schumpeterian’ theoreticians. We will read a crucial text by Schumpeter in week 5 when we discuss economic theories of technological innovation.) The concepts of ‘trajectories’ and ‘selection environments’ are central to Nelson & Winter’s approach. While the concept of ‘trajectory’ stands for patterns of technological developments, ‘selection environments’ represent an idea of the environment more sophisticated than markets in which the technological trajectory develops. There are many different forces in the environment; ‘markets’ can no longer be considered the only determinant of technological development.
In the first paper of this chapter, Nathan Rosenberg reveals the existence of different ‘inducement mechanisms and focusing devices’ in technological development. Inducement mechanisms are the forces that stimulate technological change; while focusing devices help to formulate the technical problems and focus attention on them. He shows that there exist different types of economic focusing devices, such as: issues related to the optimisation of a production process, or the scarcity of resources, on the one hand; or issues concerning economic (class) struggle, on the other hand. These issues can be interpreted as concrete examples of ‘selection environments’. Questions to be discussed are, among others:
- The policy of employers to get rid of skilled labour seems a little old fashioned nowadays. Does there exist a ‘technological trajectory’ with regard to labour at the moment?
- The example of mechanical engineering is not generally relevant. What about the more science-based technologies that dominate recent periods?
- What can one learn about technology policy from Rosenberg’s article?
The paper by Giovanni Dosi provides a comprehensive description of the ‘trajectory approach’. Its aim is to elaborate the notion of ‘trajectory’ and to integrate it with the notion of ‘paradigm’ as defined in science studies.
An obvious question is what exactly would count as a trajectory and what not. ‘Miniaturization’ in microelectronics appears to represent one. The aircrafts’ development from the DC 3 to the DC 10 model is also often mentioned as an example of trajectory. But why? How can one explain that the DC 3 had a combustion engine, whereas the DC 10 was equipped with a jet engine? Sometimes it is argued that you can only distinguish trajectories with hindsight, since in the middle of a development process many options are open; would you agree with such an argument?
Note that Dosi defines several terms on p. 152. (On p. 151, he also defines ‘technology’; and ‘progress’ on p. 154.) Can you apply these definitions to the above example of the development of aircraft? Furthermore, while it is very comprehensive, could the approach described in this article lead to policy implications? If yes, to which? If no, why not?
In a final paper of this chapter, Richard Nelson — the founding father of the evolutionary approach in economics — reflects on the issue of the social embedding of technological trajectories. In addition to relations between technological trajectories and selection environments (e.g., markets), he recognizes the tendency of co-evolution between technologies and the institutional framework of society. As a technology develops institutions create new rules and regulations that determine the effect the technology has on its environment. We will return to overview to this issue when discussing the article by Christopher Freeman and Carlota Perez in week 6, but here we wish to note the relation between evolutionary and institutional approaches in economics. In institutional economics, one focuses on transaction costs across institutional barriers. We will not discuss this approach in class extensively, but it is contained in the additional reading (Freeman & Soete, 1997, pp. 227-365).
Week 4: Actor/network approaches
In this second chapter with theoretical perspectives, we draw attention on approaches that are based on networks of social actors. These approaches are more rooted in sociology than the previous ones. Notably in the second article by Pinch and Bijker, the focus will be on the socio-cultural ‘meaning’ of technological artifacts for the actors involved in the networks surrounding such artifacts. Furthermore, the authors refer extensively to correspondences between their approach and the debates in the sociology of scientific knowledge. Through the use of concepts like ‘decision criteria’ and the development of ‘sub-markets’, a rather similar argument can be made in economics.
In the first article of this chapter, Callon analyzes the case of the electric vehicle in a framework that demonstrates how power is built up by a ‘macro-actor’ or ‘translator’ enrolling other actors in a network. Here, the process of technological development depends on whether the actors accept the actor world. Callon emphasizes that non-social elements play a role in the network, elements can be either technical objects or people. Would a technological trajectory or a regime count as a macro-actor? If so, wouldn’t Callon’s perspective be compatible with the previous accounts? Why not? How would one account for the eventual failure of the described network to generate the development of the electric vehicle? (In Callon’s scheme this cannot be an external contingency.)
The article by Pinch and Bijker introduces the so-called SCOT-approach. SCOT stands for the “social construction of technology”. In this approach the process of technological development is one of variation and selection. The result is a multidirectional model unlike the linear models commonly used in other science and technology studies. The study focuses on the construction of the bicycle in the 19th century.
An obvious question, which is also raised in the introduction, is whether the safety bike model survived because of its superiority in terms of economic (market) criteria, or because of its meaning for all relevant groups. What would the latter perspective add to the former? This is an important point for understanding what modern sociology is about: things do not simply exist but have meaning for social groups, and that level has its own dynamics. In what respect would social structural elements (such as class, etc.) differ from elements that are structured by the technology? Take, for example, the DC 3 to DC 10 trajectory; is that just a social construct? Who is socially constructing, the analysand or the participants in the development, or both?
As noted in note 1 of this article, the Pinch & Bijker article is a shortened version of a longer article that appeared under the same title in Social Studies of Science 14 (1984), 399-441. The latter version is particularly clearer on the issue of the relation between EPOR (Empirical Programme of Relativism) and SCOT (Social Construction of Technology). However, we thought this issue not to be of crucial importance for this course.
The authors use two words from Latin: “explanandum” is Latin for the subject of study that has to be explained; “explanans” is Latin for the category/categories that carry the explanation.
Question: has social constructivism come up with concepts (e.g., institutional arrangements) that enable us to improve the monitoring and evaluation of research and development?
In the third paper of this week Van Lente & Rip (1998) radicalized the social-constructivist perspective from an actor-network perspective. The authors argue that expectations are the drivers of technological developments:
• Are these expectations attributes to people and group of agents or attributes to discourses? Or to both? How is this considered and how would it make a difference between the two relevant traditions (that is, the historical-sociological one and the one of the sociology of translation)?
• If the expectations are the independent variables (causes), what then are the dependent variables (consequences)?
In the first article of this week, Devendra Sahal conceptualizes technology as systems that develop along trajectories. In general, a ‘system’ approach means that developments are conceived as being controlled by mechanisms at a higher level than the ones that we observe. Therefore, we have to analyze the phenomena with respect to the mechanisms that control and guide them. Sahal’s claim is that these mechanisms can be described as ‘technological invariants’ that guide technological developments into a trajectory. These invariants are also compared with constants in natural laws. Technological developments are thus conceptualized as an interplay of such invariants with change processes.
Much of Sahal’s argument is based on the graphs that are exhibited in the figures 5 to 10. A critical point which can be raised with respect to these graphs is that they seem systematically composed by two clouds of points: one with relatively low values and one with relatively high values. It may be worthwhile to reflect upon what it would mean if one would consider these two groups separately. However, if Sahal is right, his argument has important implications for policies regarding technological developments. Sahal mentions a few of them in the last paragraph of the article. Could you think of more?
In the second paper, Hughes conceives social development as a systemic one in which technologies are embedded. He broadens Sahal’s narrow definition of ‘technological systems’ by encompassing social systems. And, he adds to Pinch & Bijker’s limited definition of `the social’ political, economic, and managerial processes. His prime example is Thomas Edison as an entrepreneur and the rise of the electricity system. Would you agree that these systems are technological systems, or are they to be conceptualized as social? If so, what would distinguish them from other social systems, such as `housing’ or `health care’?
Hughes claims that a sequence can be found in the analyses of these systems. Could such a sequence also be detected in contemporary systems, or is Hughes’ argument only valid for examples from the period under study? If so, in what respect would things differ today? In his last remarks, the author draws attention on the decline of systems; there is the suggestion of ‘life cycles’. What could be the driving force behind such cycles, e.g., new technologies, changing market structures, or entrepreneurs? Would it be important to make these distinctions for understanding the dynamics of such systems?
Hughes is well-known for introducing the concept of ‘reverse salients’ as a notion relevant to the history of technology. Additionally the article also introduces issues like the role of ‘venture capital,’ and (dis-)economies of scale in organizations. Note also the definition of a ‘presumptive anomaly’ (with a reference to Ed Constant).
Sahal’s text raised issues which relate these neo-evolutionary approaches of technology and economics to complexity studies. Peter Allen’s introduction was written as a counterpart to Nelson’s paper on co-evolution (which we read in week 3). While the models of “demand-pull” and “technology-push” have been considered as linear models of technical change, the evolutionary perspective is recursively building upon previous states, and therefore, is considered non-linear. Technological developments cause adaptive and structural changes, innovations are either incorporated into the system or create new offshoots. Allen provides us with a general introduction to the new field of non-linear dynamics of technical change. An important question remains whether the ‘modeling approach’ has a surplus value, and whether this surplus value can also be specified.
Week 6: Economic Determinants of Technological Development
In this chapter some basic notions of economic determinants of technological development are discussed. The relations can be elaborated both in a long term perspective and in a short term perspective at the level of individual innovations. The articles in this chapter take a long term perspective, like Hughes’ article on Edison.
The paper by Schmookler elaborates on the discussion of ‘waves’ in the economy and their relations with technological developments. This discussion originates from the studies of Kondratieff (on the so-called ‘long waves’) and notably Schumpeter. Schmookler used time series of patents for certain products and tried to correlate these with time series in the production of certain goods, e.g., rail roads, and of capital formation and building activity. He finds that technological development is closely tied to economic phenomena. This paper is an example of the use of patent statistics as an indicator for technological change (cf. Sahal’s ‘Pythagorean conception of technology’). The article raises questions like:
- To what extent do the conclusions depend on the ‘unproven assumptions’ about the data used?
- Does Schmookler use time series of relevant products? (At least for the post W.W. I period we would expect other, more dominant economic sectors to be relevant.)
- Formulate a causal model that would be supported by Schmookler’s data, using relevant variables such as (at least): innovative activities, inventions, sales, economic climate.
- What are the implications of Schmookler’s conclusions for technology policy?
As noted in previous chapters, Nelson & Winter (1977 and 1982) have been seminal to the emergence of “evolutionary economics”. Whereas technology is usually considered by standard (e.g., “neo-classical”) economics as an external factor, these authors have developed models which endogenize the technological developments. In the readings for week 2, we have discussed this approach from the perspective of technology studies. In this chapter, we wish to draw attention on this emerging paradigm from the perspective of economics.
As noted, the evolutionary perspective heavily draws on Schumpeter’s analysis of the capitalist system. Actually, the evolutionary economists are sometimes called neo-Schumpeterians. (Schumpeter, of course, draws on Marx for his analysis of the dynamics of the social system.) It is helpful to read the original passages in which Schumpeter explains the dynamics that upset the movement toward economic equilibrium. For this reason, we reprinted a short part (Chapter 7) of Schumpeter’s famous study Socialism, Capitalism and Democracy. In the reproduced part, Schumpeter briefly explains his notion of innovation as a ‘process of creative destruction’. According to this view, technological (and organizational) innovations disturb the economic equilibrium by creating all kind of new possibilities for economic activities. These innovations are the motor behind economic growth, as well as the cause of pattern that characterizes economic development: the business cycles and the long (Kondratieff-) waves.
In the other paper of this chapter, Freeman & Perez elaborate on this idea of the long waves in economic development and the role of technological revolutions. They discuss the effects of and conditions for the large-scale diffusion of information technology in society and the economy. From this perspective different phases in history are dominated by different technological systems. The social system must be suitable for the technology to diffuse and for society to gain from the new technology. Social factors determine the success of an innovation.
- Does the diffusion of information technology force societies to adapt to a technology, or is there room for ‘designing society’ in different ways, e.g., from a normative point of view?
- Does the ‘information technology revolution’ lead to new possibilities for the underdeveloped countries, or will the gap between the first and third world become even larger?
Week 7: First take-home exam
1. Try to reconstruct the definition of technology in the different articles. How is technology defined (in terms of what)?
How would you wish to define technology? Why?
2. Does each author define a relation between technology and innovation? If so, how?
How would you wish to define innovation? Why?
2. How does the socio-economic environment influence technological developments according to the various authors? Or is technology mainly considered as (semi)autonomous? If so, please explain what you mean with autonomous or semi-autonomous.
3. Try to compare the various definitions of technology and innovation reflexively. Formulate tentative conclusions.
Please, submit your individual answers in hardcopy on March 24!
Selection is a recursive operation. This means that selections can further be selected. Some selections, for example, can be selected for stabilization; stabilizations can be selected for globalization. In the case of a an economy, the market operates as the prevailing (since fastest) selection mechanism, while institutions provide this structure with stability. Institutions were shaped during most of the 19th and 20th century in terms of nation-states. The resulting dynamics can be considered as “political economies.”
The knowledge-based dynamics adds a third axis to this system: the one of creative destruction and subsequent reconstruction. In this series of texts we focus on ongoing developments of globalization of the knowledge-based economy. Each text addresses a current topic in the policy debate.
In the first text of this week, Giovanni Dosi and coauthors provide a critique of the so-called “European Paradox” which states that Europe has the research capacity, but lacks behind in innovation because of the distance between R&D and markets. The institutional barriers between these two domains would have to be softened by privatization so that the “market” can prevail within the systems. Dosi et al. question these assumptions and argue that Europe has been neglecting its knowledge base and therefore structural weaknesses would be more serious than the European paradox suggests. The argument is based on insights in evolutionary economics which we have read during the past few weeks, and it is provocative. (I look forward to a discussion in class.)
In the second text of this week, David Mowery & Sampat Baven discuss the development of intellectual property right (IP) since the introduction of the Bayh-Dole Act in the United States in 1980. This law facilitated patented and licensing by U.S. universities of inventions based on federally funded research causing (?) a spurt in the growth of university-industry collaborations and technology transfer in the U.S.A. Several countries have followed this model in the 1990s. The authors critically discuss these developments and raise a number of questions for government policies.
Since the end of the Cold War, the development of the P.R. of China (and other Asian countries) has become a driving factor in the process of globalization. In the third text Ping Zhou and Loet Leydesdorff provide indicators of the leading role of China in a knowledge-based economy. Would you agree with their methodologies of would other aspects merit further investigation? Which development is leading: the opening of the market or the internationalization of Chinese scientific capacities? Perhaps, we need a model with feedbacks.
Week 8: Algorithmic models of technological developments
In the previous weeks, the discussion concerning the relation between economics and technical change remained at the theoretical and discursive level. The mid-term exam mainly function to familiarize yourself thoroughly with the main concepts and the differences among them. The articles of this chapter show how general mechanisms can be modeled, to gain a deeper understanding of the mechanisms underlying technological development. You will moreover participate in a computer practicum during which one can play with the models.
The article by Paul David about the QWERTY keyboard is the classical place for the discussion of the evolutionary phenomenon of “lock-in”. The QWERTY keyboard was engineered in order to optimise typing speed in the case of mechanical typewriting. It had been designed so that the typebars have a minimum chance of jamming given the character frequency distribution in the English language. Since mechanical typewriting is out of use, the QWERTY keyboard has become sub-optimal. However, one is no longer able to break out of the lock-in given learning curves and network externalities.
In his 1988 paper on ‘Competing Technologies,’ Brian Arthur has used this problem for introducing the linkage between institutional economics and evolutionary theory. In the article by us (Leydesdorff & Van den Besselaar, 1998) we develop this model into a simple routine which we are able to use during the computer practicum. It can be shown that lock-ins against technological developments are robust, but that the occurrence of this event is sensitive to conditions. The conditions for “lock-out” will bring us back to the distinction between trajectories and regimes as introduced by Dosi (1982).
During the computer practicum we shall pragmatically follow the routines specified in the article. Thereafter, you are welcome to experiment with your own variation in the parameters.
Week 9: Computer practicum: simulation models of technological change.
Week 10: Techno-Sciences: Integration and Differentiation
In this chapter, we draw attention to a supply side factor that is of a different nature, namely science as organised knowledge. Science and technology are intrinsically related in modern times. This has, however, not always been the case, as was pointed out, e.g., in the text by Noble (1977) which we read previously.
Bradshaw and Lienert describe the development of the airplane. They show that progress depended on the specific way technological problems can be solved. Where most airplane developers tried to build and test complete planes (that is, were exploring the ‘design space’), the Wright brothers worked by isolating a problem, solving it, and integrating the solution back into an airplane-design (that is, by exploring the function space). This last scientific approach proved to be much more successful. What are the implications of this for the role various actors can play in technological development? Compare the study with the SCOT-approach.
In his paper entitled “Why do firms do basic research (with their own money)?” Rosenberg tries to provide answers to this economic puzzle. After a review of the economic arguments not to invest in knowledge production because of various uncertainties, he argues that some sectors have become knowledge-intensive during the past century or so. These sectors are highly concentrated and the type of corporations is specific, notably, multinational and diversified. In other sectors, “scientification” is an ongoing process. Rosenberg uses “biotechnology” as a case to illustrate the problems, the provisions, and the alliances involved. A third argument for doing basic research can be the structural integration of a firm into a sector that is highly knowledge-intensive, such as the military. The relation with the clients then requires specific competencies.
In the third article of this week, Henk Dits & Guus Berkhout discuss how the knowledge component complicates science and technology policy. An understanding which begins with the practices of science and technology easily becomes confused because there are non-linearities and transformations involved. One needs a model to help in understanding and one often needs to assume that the actors involved also use models for their understanding. Scholars reason from their disciplinary mode of thinking, product developers and entrepreneurs construct a frame of reference that addresses a completely different frame of reference, while policy makers have to solve yet another puzzle. For example, the “productivity growth puzzle”, that is, the problem that sectors grow and innovate at different rates brought the issue of technological developments to the agenda in the 1970s (Nelson & Winter). As knowledge pervades into the “knowledge-based” economy, reflexive turns are increasingly built into the system. In other words, when policies are pursued (or proposed), one has to specify the system of reference. For example, is it technology policy, innovation policy, industrial policy, higher-education policy, etc. The different perspectives may require other planning horizons and among the various perspectives explicit translations are often needed (in order to prevent confusion).
Week 11: National Systems of Innovation
Patterns of technological development differ from one country to another. In this chapter, we discuss three articles that describe and analyse different ‘national systems of innovation’.
Various authors have argued that intensive co-operation between producers and users of innovation is the main key to successful technological innovation. Lundvall elaborates on this idea and discusses its implications for national technology policy and national institutions involved in technological development. How can this user-producer relationship be organised at a national level? What kind of institutions are kinds of institutions are needed? At the same time, he argues that technological developments are based on social innovations and institutional change. are the basis for technological innovations. This theory allows for communication between different elements of the technological system, contrary to the traditional neo-classical approach where market forces exist as an independent force in the economy. If this theory is the case, national systems of innovations may be the vehicle to steer technological innovation in a direction that supports social progress.
Ichizo Yamauchi describes the development of Japanese R&D and the role of long term strategic planning. Here, the role of government is quite different from that of governments in other developed countries. The Japanese strategy has been very effective, as proven by the rise of Japanese economic power. One can wonder whether it is mainly technology policy that is responsible of this phenomenon, or for example, Japanese protectionist trade-policy. An interesting question is: what other countries can learn from the Japanese experience?
The third paper of this week is a typical research paper. It is included because it focuses on the function of regions. Helen Lawton-Smith and Kawai Ho studied the knowledge infrastructure of the Oxford region and its effects on spin-off companies. The argument is that the knowledge infrastructure is “sticky”. This argument places the calls for creating other “Silicon Valleys” in a different light. What would be the main obstacles for such a policy effort?
Week 12: second mid-term exam
Make a short summary of pp. 227-365 of: Chris Freeman & Luc Soete, The Economics of Industrial Innovation (London: Pinter, 1997). Please, keep it below 5 pages at the maximum. Make clear that you have followed the issues, appreciate the lines of thought, and provide us with your conclusions.
2a. As far as you did not finish the first take-home, take the opportunity for a second chance by redoing this exercise with a possible extension to the more recent readings. We will in this case upgrade your grading.
2b. If you have sufficiently finished the previous exercise, I would like you to think about a possible theme paper. Provide us with a short summary or outline of such a paper. Thus, you don’t have to write a full paper now, but only a single page. This should provide us with sufficient understanding and feedback in order to decide (between us) whether a theme paper is feasible in a next round. Alternatively, you may wish to finish the course with the third mid-term exam of essay questions. (This has my preference because a theme paper may be too complex.)
Submit (in hardcopy) on Tuesday, April 21.
In previous chapters, technological developments have been related to general economic processes and the economy as a whole. This chapter focuses more specifically, for example, regarding the economic sectors, the different technologies and different development phases. In the article of Thomas Hughes (week 5), we discussed the energy sector. This sector produced all the innovations by itself and for its own use: the electrotechnical industry. However, this does not follow the general pattern of development after World War II. Many firms do not themselves produce the innovations they use in their production process and in their products. A very different dynamics may have evolved in the service sector as it further develops in relation to the industrial sector. Richard Barras discusses the innovation patterns in the services in more detail, and proposes a ‘reverse innovation cycle’ for understanding innovation processes in services.
- What is considered an innovation in the services? Does this imply technological innovation? Or should it be conceptualized as the use of technology developed elsewhere? And why is such an innovation process thought to be ‘reversed’?
- How would you assess these technological developments in terms of Sahal’s (1985) three types of innovation? (week 5)
More recently, the concept of knowledge-based economies is increasingly used because this enables us also to discuss the issue of globalization. The article of Edward Steinmueller provides us with an overview of the more recent theorizing about the further development of the service sector during the 1990s. The article elaborates on the idea of a reverse innovation cycle and discusses some of the consequences. The issue of “intellectual property rights” is also addressed since new formats (e.g., copyright protection in addition to patenting) have increasingly become important.
On the basis of his life-long work about the sources of innovation, Eric von Hippel and Georg von Krogh suggest that a new model is increasingly emerging that combines elements of innovation prevailing in private companies with elements of innovation in the public sphere. Their prime example is “open source software.” Here, the “consumer” is replaced with the “user:” while a consumer only articulates “demand,” a user may actively (co-)shape the innovation. The model of “open source software” is used because it highlights an element which is analytically to be expected also in other types of innovation. For example, in medical instruments, doctors can be co-shaping the innovations as “leading edge consumers.” Is this option only confined to knowledge-intensive sectors and high-tech or can one also envisage “open” innovation processes to take place in what is traditionally considered as market processes? Can you think of examples?
Week 13: The Dynamics of Codification in Networked Relations
The article by Cowan & Foray specify a theoretical perspective on processes of codification. How are informations codified (transformed into some systematic form that can easily communicated), and then also valued? The authors stress the importance of this process to modern economic activities and suggest that codification is increasingly enabled by information technologies. A model is developed in which Cowan & Foray distinguish between languages, messages and models. For example, codification can reduce transaction costs because one does not have to deconstruct and to learn at the receiving end. The user/producer interaction and the formation of community-based niches can be assessed from this perspective.
Etzkowitz & Leydesdorff (2000) develop the triple helix model (of university-industry-government relations) into a model for innovation. Innovation is based both on recombination and on the reflexive development of all systems and subsystems, but not necessarily in a completely integrated mode. The system is complicated and remains in transition due to the constant internal dialogue and changing relationships. This model provides a more sociological view on the relations between university research and industrial technologies. How are the functional differences (between sciences and markets) integrated with the institutional differences (e.g., between public universities and private industries)? How has this led to an emerging communications regime between universities, industries, and governments? The authors use the term “triple helix” for this integration and they specify a research agenda from this perspective. Some of the papers that we will read hereafter have been chosen from this perspective.
In the paper of Hansen, Nohria, & Tierny differences in codification strategies among large consultants are compared. In this context, the knowledge base is considered as an attribute to an organization. The organization thus has intellectual property rights. The knowledge base of an economy is often also considered as a social coordination mechanism. From the latter perspective, the knowledge base does not have to coincide with existing organizations.
In a study of the brain circulation, AnnaLee Saxenian offers some specific advice to countries that want to incorporate knowledge-based growth into their economies. She urges them to think about their “brain drain” as a possible asset. Find ways to use the people who have studied and worked overseas to help build the domestic economy. She uses the example of Taiwan as a country that has successfully accomplished this. She focuses on the Bangalore Boom—the growth of software companies in India—as an interesting example, and one that is a timely opportunity for India to go the way of Taiwan.
Richard Florida has become famous for his “creativity indices” of U.S. cities. While studying the location choices of high-tech industries and talented people, one of his students had been working on a Gay Index, indicating the location patterns of gay people. The two indices correlated very strongly, and this made him suggest that cultural patterns in cities are a determining factor in the success to attract the knowledge-carriers needed for technological innovations. Pay a visit to http://www.creativeclass.org . What is this: a hype or a scientific theory (or both)?
In the final paper of this week, Ping Zhou & Loet Leydesdorff discuss the spectacular rise of the P.R. of China as a leading nation in science and technology. Access to the global “market” of scientific and technological dissemination has led to an avalanche of contributions from the Chinese side. Some of the other Asian nations (e.g., Singapore and Taiwan) are able to keep pace with the Chinese development. Why might this be?
Week 15: Politics, Institutions, and Innovation
In the first part of this course we focused on economic, social, and technological determinants of innovation processes. However, variation and selection processes have a political dimension too, which will be the subject of this final chapter.
Van de Belt and Rip elaborate on the Nelson/Winter and Dosi model of technological innovation. Although their primary goal is to give a sociological extension to the model by emphasizing the role of heuristics, implications for technology policy can also be specified. One of these is the role of a ‘nexus’ coupling variation and selection, e.g., the patent system in the case of chemical technology. Questions are:
- Governmental policy (patent law) played a crucial role in the commencement of chemical technology, but what would be the relevance of the idea of a ‘nexus’ for contemporary politics and/or for steering chemical technology?
- Van de Belt and Rip argue that the Nelson-Winter and Dosi model should not be interpreted as an evolutionary model. Contrary to the ‘Darwinian’ model, the processes of variation and selection in technological development are related. What are the implications of this for the model? Is not the distinction between the two spheres essential for the evolutionary model?
In the second article of this week, Biggiero argues that the knowledge-creating organizations and enterprises are reaching beyond the institutional structures by generating a synergy at the next-order level of a hyper-network. He relates this to the overlay among partners in the Triple Helix model and to Nonaka’s concept of the ‘ba’ which is crucial for knowledge generation. The ‘ba’ processes organizations instead of organizations processing the ‘ba’? However, this is an evolutionary process. In which stages do you expect the one mechanism to prevail and which the other. Does Biggiero make a convincing case about these dynamics using his empirical materials?
In the third article of this week, Van den Besselaar reports on research projects that concerned technological developments. He discusses various concepts of policy making and so-called technological determinism, in which technology determines social circumstances. Under which conditions can interactions between the various sub-dynamics of technological development be constructed?
At the cultural level and in public debate, technological fixes are often opposed to social fixes. For example, a development policy for less-developed countries can be formulated in terms of social processes (perhaps, revolutions), market forces or technological developments and upgrading of skills in the labour force.
In the first text, Michel Callon discusses the economic concept of negative and positive externalities, which are economic costs or benefits that arise out of economic activity but which are not taken into account within the price mechanism. This is an example of what economists call ‘market failure.’ Can alternative institutional mechanisms be designed to incorporate these costs and benefits in contracts. Importantly, positive externalities associated with spill-over of research results among firms increase social welfare. However, since firms recognize that they cannot fully appropriate the value of research, they might under-invest in R&D.
To design alternative institutional mechanisms—in order to avoid under-investment in R&D—one needs to define and measure externalities so that they can be taken into account in contracts (for example, between universities and industries, or between the nation state and universities). However, in so-called ‘hot situations,’ that is, in situations in which knowledge production is highly uncertain such as in emerging sciences and paradigms, the costs of defining and measuring externalities and of monitoring the actors involved in research as to assign responsibilities and results to them, may well exceed the benefits of taking into account these externalities. The world cannot be framed in such a way that all possible outcomes of R&D and those responsible for this outcome can be fully described. In order to analyze such hot situations, the contractual approach in economics is of little use, and instead, constructivist approaches can be of use. Using such an approach, one can understand the strategies of actors to frame a situation by proposing definitions, measurement instruments, and ways to monitor R&D activities. Within the process, both new ways of social interaction and new constructs of the world are created which may eventually stabilize definitions and measurements which then allow for traditional contractual interaction.
Question: has social constructivism come up with institutional arrangements that improve the monitoring and evaluation of research and development?
Ulrich Beck radicalizes the issue of the relation between technology and society: technological developments are not only socially organized and controlled, they themselves reshape social relations. The division between “mode 1” and “mode 2” research with which we opened this reader is redefined as a contrast between industrial wealth production versus hazard production. Risks with natural origins (such as natural disasters) are replaced by risks originating in decision making and responsibility for those risks is diluted in the bureaucratic network. Technological development from this perspective develops as a predicament. Reflexive modernization may be the only remaining option.
In the first part of the course, the focus was on technological change as an evolutionary process of variation and selection, with the emphasis on the mechanisms of variation (weak spots in a technological artifact; reverse salients in complex technological systems; dominant designs and paradigms; interpretative closure; translation)
In the second part of the course, the emphasis changed to the co-evolution of technological change (‘variation’) and the relevant selection environments (the ‘nexus’, the ‘triple helix’, ‘national systems of innovation’, ‘sectoral differences’, ‘human resources’, ‘regional networks,’ etc.). This process of co-evolution may generate possibilities for social and political influences on technological development other than through the latter’s social construction. These normative influences were central to the reading in the final weeks.
1. Make an overview of the various elements of the selection environment described in several of the articles. How do these elements fit in the more general models, like ‘techno-economic paradigms’ (Freeman & Perez) ‘national systems of innovations’ (Lundvall), and ‘triple helix’ (Leydesdorff). Can you specify differences and similarities among these models in terms of how they conceptualise market and non-market (selection) environments?
2. Which social environments are relevant to political interventions at the various levels of aggregation in the process of technological development? Can you specify policy instruments, with reference to technological trajectories and technology policy instruments, at the level of society? Where could a technology policy become more effective and under which circumstances? Provide an example of what you would consider relevant dimensions for a specific decision about the stimulation of a technology (e.g., at the regional level of the city of Amsterdam)?
3. Can you specify the relations between the knowledge base of an organization, the organization, and its professional practices?
Alternatively, you may wish to write a term paper (approximately 10 pages). However, this latter option is open only for students who have handed in a design for such a paper at the occasion of the second take-home exam (so that I was able to comment on it).