Experimentation Matters: Unlocking the Potential of New Technologies for Innovation, Stefan Thomke, 2003.
Some time ago HBS Working Knowledge carried an interview with Stefan Thomke about his book, 'Experimentation Matters: Unlocking the Potential of New Technologies for Innovation.'
Thomke emphasizes that experimentation is vital to innovation and survival in today's business world. Computer modeling and simulation, rapid prototyping, and combinatorial technologies drive down the marginal cost of experimentation and allow companies to create more learning more rapidly.
He also proposes that it may make sense to shift experimentation from producers to customers: some companies have abandoned their efforts to understand exactly what products their customers want and have instead equipped them with tools to design and develop their own new products, ranging from minor modifications to major new innovations. The user-friendly tools, often integrated into a “toolkit” package, deploy new technologies (e.g., computer simulation and rapid prototyping) to make innovation faster, less expensive and, most importantly, better, as customers run “what-if” experiments themselves.
This suggests that since experimentation can be moved up and down the supply chain (relatively) easily, the technology matters more than the location. More on this when I've read the book...
Saturday
Trust, alliances, and innovation in supply chain management
HBS Working Knowledge: Operations: The Missing Link in Supply Chains: People
Research on (global) supply chain management has proven to be a great resource for my work, even though I concentrate on innovation rather than production. There are many similar issues in the two fields: the importance of alliances, the necessity to create trust between different organizations etc.
This panel discussion convened by the Harvard Business Review raises some of these issues. Particularly interesting is David Burt's proposal that trust can be established between organizations, not just individuals. I'm not convinced - and he concedes that he doesn't any evidence yet - but the idea is intriguing...
The panelists also point out that smart contracting is essentially the basis for building trust. Master contracts can avoid repeated drawn-out and possibly nasty negotiations, letting partners focus on cooperation. Another suggestion was to avoid penalties that simply punish the party that violates the agreement. Instead, have the violating party pay the money into an account that is then used for the benefit of the alliance. This way the alliance benefits from enforcement. Simple penalties just provide an incentive to 'catch out' the other person.
Robert Lynch brings up another issue of supply chain management: Buyers are rewarded for cutting costs, not for gaining innovation from the supply chain. He cites a study by Burt in which responding firms on average say that 35% of their innovation comes from the supply chain. He contrasts this number to the 60% that companies like Toyota achieve. Evidently, supply chain management can create strong incentives for suppliers to innovate - or not.
Research on (global) supply chain management has proven to be a great resource for my work, even though I concentrate on innovation rather than production. There are many similar issues in the two fields: the importance of alliances, the necessity to create trust between different organizations etc.
This panel discussion convened by the Harvard Business Review raises some of these issues. Particularly interesting is David Burt's proposal that trust can be established between organizations, not just individuals. I'm not convinced - and he concedes that he doesn't any evidence yet - but the idea is intriguing...
The panelists also point out that smart contracting is essentially the basis for building trust. Master contracts can avoid repeated drawn-out and possibly nasty negotiations, letting partners focus on cooperation. Another suggestion was to avoid penalties that simply punish the party that violates the agreement. Instead, have the violating party pay the money into an account that is then used for the benefit of the alliance. This way the alliance benefits from enforcement. Simple penalties just provide an incentive to 'catch out' the other person.
Robert Lynch brings up another issue of supply chain management: Buyers are rewarded for cutting costs, not for gaining innovation from the supply chain. He cites a study by Burt in which responding firms on average say that 35% of their innovation comes from the supply chain. He contrasts this number to the 60% that companies like Toyota achieve. Evidently, supply chain management can create strong incentives for suppliers to innovate - or not.
Thursday
Production networks vs. innovation networks
Knowledge flows and industrial clusters: An analytical review of literature, Rakesh Basant, 2002
Looking for an overview of the literature on industrial clusters as they relate to knowledge transfer and innovation, I came across this very helpful review by Rakesh Basant. Besides providing a great overview, Rakesh pointed me in the direction of Dieter Ernst's work - an analysis of global production networks (loosely: the network of global supply chains). Looking at production networks also involved analyzing the knowledge flows that accompany transfer of machinery, technology licenses, and finance. Apparently, as global networks increase and ICTs become more readily available, more knowledge is being codified that would earlier remain tacit: a boost for innovation across distance. However, another study by Cassiolato seems to provide evidence that MNCs (dominant sources of knowledge in Ernst's model) may have little incentive to involve local actors in knowledge intensive activities, thereby limiting cooperation across distance to production, rather than innovation.
Looking for an overview of the literature on industrial clusters as they relate to knowledge transfer and innovation, I came across this very helpful review by Rakesh Basant. Besides providing a great overview, Rakesh pointed me in the direction of Dieter Ernst's work - an analysis of global production networks (loosely: the network of global supply chains). Looking at production networks also involved analyzing the knowledge flows that accompany transfer of machinery, technology licenses, and finance. Apparently, as global networks increase and ICTs become more readily available, more knowledge is being codified that would earlier remain tacit: a boost for innovation across distance. However, another study by Cassiolato seems to provide evidence that MNCs (dominant sources of knowledge in Ernst's model) may have little incentive to involve local actors in knowledge intensive activities, thereby limiting cooperation across distance to production, rather than innovation.
Wednesday
Network metaphor
Metaphors we live by, George Lakoff, Mark Johnson, 2003 [1980]
Reading 'Metaphors we live by' reminded me of some of the difficulties of working with network models of the economy. A network is a theoretical structure composed of nodes and links between them. Often individual people, groups or organizations are defined as nodes and the relations between them are the links. But it is possible - and sometimes useful - to define things the other way around. This basically means that looking at networks often presupposes that form or structure is more important than content.
At the same time, talking about networks is a way of understanding any number of things in the world around us, i.e. we apply the network to many different kinds of content and expect to understand that content better. Often the qualitative aspects of nodes and links are just as interesting and relevant as their structure. Incorporating these aspects into a formal model of networks seems like a theoretical/logical contradiction. However, it fits an intuitive understanding model of networks better. This may be because the internet and the World Wide Web - and our own personal experiences with it - shape the meaning of 'network' more strongly than the formal mathematical definition.
Reading 'Metaphors we live by' reminded me of some of the difficulties of working with network models of the economy. A network is a theoretical structure composed of nodes and links between them. Often individual people, groups or organizations are defined as nodes and the relations between them are the links. But it is possible - and sometimes useful - to define things the other way around. This basically means that looking at networks often presupposes that form or structure is more important than content.
At the same time, talking about networks is a way of understanding any number of things in the world around us, i.e. we apply the network to many different kinds of content and expect to understand that content better. Often the qualitative aspects of nodes and links are just as interesting and relevant as their structure. Incorporating these aspects into a formal model of networks seems like a theoretical/logical contradiction. However, it fits an intuitive understanding model of networks better. This may be because the internet and the World Wide Web - and our own personal experiences with it - shape the meaning of 'network' more strongly than the formal mathematical definition.
Sunday
Biotech knowledge and market exchange
Inter-institutional spillover effects in the commercialization of bioscience, Lynne Zucker, Michael Darby and Jeff Armstrong, ISSR Working Paper, vol. 6, no. 3, 1994.
In this study, Zucker, Darby and Armstrong lay out a proposition that partly contradicts a study on knowledge networks by Liebeskind et al. Both studies try to answer the question of how scientific knowledge flows into biotech firms.
Summary
Liebeskind et al. propose that firms source their knowledge through social networks to overcome the problems of market failure and inefficiencies involved in internalizing knowledge. On the other hand, Zucker et al. propose that there is a market exchange at work, especially for knowledge that is successfully commercialized. They work from the observation that much work in rDNA research is characterized by natural excludability, e.g. acquiring it requires working together with someone in a lab and/or a time-consuming effort to learn new skills. This results in intellectual capital for the discovering scientists. This intellectual capital diminishes as the new skills and knowledge diffuse throughout the industry. However, during an initial phase, companies that want to commercialize the intellectual capital must employ the services of the scientist who embody it. Scientists can be formally employed or hired as consultants. Links can also be less evident: full or partial ownership, membership in a scientific advisory board, etc.
Zucker, Darby and Armstrong find that formal affiliation or less formal links (joint publications and various forms of compensation) with 'star' scientists are a significant success factor for biotechnology enterprises. This, together with the presence of scientific and financial links, suggests that there is a market exchange at work.
Market or social network and hierarchy?
Which is true? Do biotech firms source their knowledge primarily through market exchange or primarily through social networks and the internal hierarchy?
Both seem to be relevant to some extent. Many of the market exchange mechanisms described above seem designed to bring a 'star' scientist within the firm boundaries, so that knowledge can then be transferred through the hierarchy. Social networks become relevant when scientific knowledge embodied in leading scientists is scarce and human mobility is limited (e.g. limits on the amount of time professors can spend consulting or formal full-time employment of scientists in a firm ). Where lack of mobility hinders market exchanges, social networks become more important. Also, Liebeskind et al. point out that it is very difficult for firms to evaluate newly available knowledge. Social networks play an important role in assessing knowledge before formal evaluations have ascertained its value or relevance to a specific firm.
Finally, social networks and market exchange are not entirely independent in this case. In both cases a great deal of trust is necessary for successful cooperation between a 'star' scientist and a biotech firm. This trust is probably established to a large degree through the social network: the norms and values of the scientific community provide a basis for cooperation; the reputation of the cooperating partners and initial informal contacts will likely be established through the network. A great deal of knowledge exchange mediated through the social network will probably precede a market exchange, which involves closer cooperation and knowledge, which has greater direct commercial benefits.
Apparently, the market only comes into play where factors such as tacitness and absorptive capacity reduce the market failure generally encountered in trading knowledge (Arrow).
Questions of location
Liebeskind et al. found that most successful partnerships involved a 'star' scientist who lived in the same region as the participating biotech enterprise was located. They mention that a few stars have been affiliated with NBEs (new biotechnology enterprises) outside California or published with NBEs outside of their region. Though they seem to be few cases, it would be interesting to see whether they were as successful as cases of local cooperation. Data may be available at the ISSR site...
New rules of work
A few days ago I wrote about Frances Cairncross's book 'The death of distance'. One of the chapters that I didn't mention dealt with new forms of work in the networked economy. Traditional lifetime employment has been disappearing for a long time now. In a continuation of this development, more and more people are engaging in non-traditional employment: freelancing, entrepreneurship, personnel "leasing" and many others.
Cairncross specifically mentioned that firms will pay a high premium for top talent, especially since the most highly qualified knowledge workers will be scarce and demand for them will be worldwide. 'Star' scientists fall squarely in this category. Zucker, Darby and Armstrong mention a study finding that bioscientists act as individual actors, as opposed to acting as agents of their primary ties, whether to the university or the firm (Zucker, Brewer, Oliver, and Liebeskind, 1993). These bioscientists can exercise their expertise independently primarily because they are recognized as having excellent "scientific taste" in the selection of rescues problems and using exceptional care and expertise in exuding that research. They use their 'scientific taste' to advise firms on the relative merit of different lines of research - certainly an example of intellectual capital that has characteristics of excludability, since this 'scientific taste' is highly tacit, embodied knowledge based to a large extent on personal experience.
In this study, Zucker, Darby and Armstrong lay out a proposition that partly contradicts a study on knowledge networks by Liebeskind et al. Both studies try to answer the question of how scientific knowledge flows into biotech firms.
Summary
Liebeskind et al. propose that firms source their knowledge through social networks to overcome the problems of market failure and inefficiencies involved in internalizing knowledge. On the other hand, Zucker et al. propose that there is a market exchange at work, especially for knowledge that is successfully commercialized. They work from the observation that much work in rDNA research is characterized by natural excludability, e.g. acquiring it requires working together with someone in a lab and/or a time-consuming effort to learn new skills. This results in intellectual capital for the discovering scientists. This intellectual capital diminishes as the new skills and knowledge diffuse throughout the industry. However, during an initial phase, companies that want to commercialize the intellectual capital must employ the services of the scientist who embody it. Scientists can be formally employed or hired as consultants. Links can also be less evident: full or partial ownership, membership in a scientific advisory board, etc.
Zucker, Darby and Armstrong find that formal affiliation or less formal links (joint publications and various forms of compensation) with 'star' scientists are a significant success factor for biotechnology enterprises. This, together with the presence of scientific and financial links, suggests that there is a market exchange at work.
Market or social network and hierarchy?
Which is true? Do biotech firms source their knowledge primarily through market exchange or primarily through social networks and the internal hierarchy?
Both seem to be relevant to some extent. Many of the market exchange mechanisms described above seem designed to bring a 'star' scientist within the firm boundaries, so that knowledge can then be transferred through the hierarchy. Social networks become relevant when scientific knowledge embodied in leading scientists is scarce and human mobility is limited (e.g. limits on the amount of time professors can spend consulting or formal full-time employment of scientists in a firm ). Where lack of mobility hinders market exchanges, social networks become more important. Also, Liebeskind et al. point out that it is very difficult for firms to evaluate newly available knowledge. Social networks play an important role in assessing knowledge before formal evaluations have ascertained its value or relevance to a specific firm.
Finally, social networks and market exchange are not entirely independent in this case. In both cases a great deal of trust is necessary for successful cooperation between a 'star' scientist and a biotech firm. This trust is probably established to a large degree through the social network: the norms and values of the scientific community provide a basis for cooperation; the reputation of the cooperating partners and initial informal contacts will likely be established through the network. A great deal of knowledge exchange mediated through the social network will probably precede a market exchange, which involves closer cooperation and knowledge, which has greater direct commercial benefits.
Apparently, the market only comes into play where factors such as tacitness and absorptive capacity reduce the market failure generally encountered in trading knowledge (Arrow).
Questions of location
Liebeskind et al. found that most successful partnerships involved a 'star' scientist who lived in the same region as the participating biotech enterprise was located. They mention that a few stars have been affiliated with NBEs (new biotechnology enterprises) outside California or published with NBEs outside of their region. Though they seem to be few cases, it would be interesting to see whether they were as successful as cases of local cooperation. Data may be available at the ISSR site...
New rules of work
A few days ago I wrote about Frances Cairncross's book 'The death of distance'. One of the chapters that I didn't mention dealt with new forms of work in the networked economy. Traditional lifetime employment has been disappearing for a long time now. In a continuation of this development, more and more people are engaging in non-traditional employment: freelancing, entrepreneurship, personnel "leasing" and many others.
Cairncross specifically mentioned that firms will pay a high premium for top talent, especially since the most highly qualified knowledge workers will be scarce and demand for them will be worldwide. 'Star' scientists fall squarely in this category. Zucker, Darby and Armstrong mention a study finding that bioscientists act as individual actors, as opposed to acting as agents of their primary ties, whether to the university or the firm (Zucker, Brewer, Oliver, and Liebeskind, 1993). These bioscientists can exercise their expertise independently primarily because they are recognized as having excellent "scientific taste" in the selection of rescues problems and using exceptional care and expertise in exuding that research. They use their 'scientific taste' to advise firms on the relative merit of different lines of research - certainly an example of intellectual capital that has characteristics of excludability, since this 'scientific taste' is highly tacit, embodied knowledge based to a large extent on personal experience.
Saturday
Brain Drain from Europe
Europe and the challenge of the brain drain, IPTS Report, vol. 29, Sami Mahroum, 1998
The brain drain is often treated as a problem of developing countries. This article looks at the migration of highly skilled scientist from Europe to the United States. There is a case that developing countries may gain a net profit from the brain drain thanks to income from remittances. More recently, brain circulation has been discovered as an important source of investment and development.
These patterns don't hold for Europe, however. Remittances aren't a relevant source of income, and - most markedly in the case of the UK - scientists who move to the United States tend to stay there. It has become ever more difficult for Europe to establish and maintain centers of excellence in cutting-edge research. Just a few months ago, the Swiss pharmaceutical Novartis, decided to headquarter all R&D in the Boston area. In terms of retaining star scientists, Europe may actually end up doing worse than, say India, Brazil or China, since few new opportunities are opening up to attract talent back. The article cites Switzerland as an exception to the rule. Yet, as the Novartis example shows, Switzerland may succeed in attracting foreign scientists, but faces similar problems as the rest of Europe in repatriating its own scientists and in retaining research leadership.
Since working with star scientists is crucial to commercial success, especially in the biotech industry (Zucker, Darby, Brewer, 1994), the brain drain of top scientists places Europe at an immediate disadvantage.
The brain drain is often treated as a problem of developing countries. This article looks at the migration of highly skilled scientist from Europe to the United States. There is a case that developing countries may gain a net profit from the brain drain thanks to income from remittances. More recently, brain circulation has been discovered as an important source of investment and development.
These patterns don't hold for Europe, however. Remittances aren't a relevant source of income, and - most markedly in the case of the UK - scientists who move to the United States tend to stay there. It has become ever more difficult for Europe to establish and maintain centers of excellence in cutting-edge research. Just a few months ago, the Swiss pharmaceutical Novartis, decided to headquarter all R&D in the Boston area. In terms of retaining star scientists, Europe may actually end up doing worse than, say India, Brazil or China, since few new opportunities are opening up to attract talent back. The article cites Switzerland as an exception to the rule. Yet, as the Novartis example shows, Switzerland may succeed in attracting foreign scientists, but faces similar problems as the rest of Europe in repatriating its own scientists and in retaining research leadership.
Since working with star scientists is crucial to commercial success, especially in the biotech industry (Zucker, Darby, Brewer, 1994), the brain drain of top scientists places Europe at an immediate disadvantage.
Friday
Biotech knowledge sourcing
Social networks, learning, and flexibility: sourcing scientific knowledge in new biotechnology firms, ISSR Working Paper, vol. 6, no. 4, Julia Liebeskind, Amalya Oliver, Lynne Zucker, Marilynn Brewer, 1994. Published in Organization Science, Jul/Aug 1996, vol. 7, no.4, p. 428-443.
Lynne Zucker was recommended to me as someone who has extensively studied cooperation and innovation in the biotechnology industry. She is probably best known for her work together with Michael Darby on the role of 'star' scientists in the biotechnology industry. It was through their work that I came across this paper. (This requires access to JSTOR. An alternative is to download the working paper.)
Liebeskind et al. treat a different aspect of biotech firms. How do they get their most important input: knowledge. The various forms of contracts and alliances to secure supply chains are relatively well understood by economists where manufacturing industries are concerned. These market-based forms of exchange, however, don't seem to work for firms that need to source science-based knowledge in a hypercompetitive environment.
Summary
Traditional transaction-costs theory analyzes the costs and benefits of internal, hierarchical exchanges vs. external, market-based exchanges. In the first case, exchange depends on rules set by managers and enforced by managerial authority down through the hierarchy of the firm. In the second case, fairness in exchange is assured by price competition or by contract. In situations of high uncertainty, and/or asset specificity internal exchanges tend to be more efficient because the market mechanism and ex ante contracting cannot allocate costs and benefits fairly. (Based on Coase and Williamson.)
However, in fast-changing industries, external knowledge-sourcing may be more efficient than internal sourcing despite the transaction-costs argument above. According to Zucker: While bureaucratic authority is by definition located within the firm's boundaries, expert authority depends on the information resources available to an individual, and not on the authority of office. Thus authority may be located within the organization... but when an external expert authority market can provide information that leads to greater effectiveness, then expert authority tends to migrate into the market. Teece argues that it may not be optimal for a firm (i.e. hierarchy) to seek to internalize numerous exchanges when technology is changing rapidly because the value of internalizing those exchanges may change rapidly under conditions of technological uncertainty, resulting in excess sunk costs. And Camagni adds that, when technology is changing rapidly, firms lose their ability to assess the value of information accurately, because they cannot learn and institutionalize appropriate assessment routines in short periods of time. Hierarchies are just not suited to efficient distribution of fast-changing technological knowledge.
Markets are not well-suited either. As Arrow demonstrated, markets for information are subject to failure, because an efficient price cannot be established for knowledge without revealing its contents. This problem of appropriation can be solved by patenting, secrecy or licensing and first-mover advantages. However, during the innovation process and where exchange of knowledge is necessary to advance innovation, these options are of limited value.
In addition to the traditional forms of exchange (market and hierarchy), a third form has been proposed: social networks. Shared norms and values serve to ensure fairness in exchange, without resort to market pricing, contracts, or managerial authority.
- Unlike hierarchies, but like markets, social networks involve exchanges between legally distinct entities. Network exchanges, like market exchanges, are external to the firm. Therefore, these exchanges are not formally excluded from the rule of law, as are exchanges which take place within hierarchies.
- Unlike markets, but like hierarchies, social networks support exchanges without using competitive pricing or legal contracting. Specifically, exchanges between individuals or organizations which are conducted through social networks have no need for price competition or legal contracting because the shared norms of the exchange partners alone will ensure that outcomes are fair.
This form of exchange is based on trust created through socialization and tradition, repeated exchange, or mechanisms such as posting a bond, testing, or performance monitoring. Biotech firms have access to a particularly useful network. Since the knowledge they use is strongly science-based, they work closely with academic researchers. As Blau and Crane pointed out, there are very strong norms that regulate intellectual property in the academic research network. This significantly reduces the main problem of external exchange.
The authors' own summary:
Where expert information is necessary external sourcing through networks is more promising. Where appropriation becomes too sensitive an issue, internal exchange is better suited. Firms may prefer to use social networks, rather than markets or their won hierarchies (i) for governing exchanges of information or knowledge which (ii) is potentially but uncertainly valuable, (iii) which is appropriable, and (iv) whose production is characterized by human capital immobility.
What might this mean for global innovation networks?
Knowledge sourcing through academic networks would seem to encourage global cooperation in biotech innovation. The academic research network already maintains global links and is probably one of the few global networks that shares such strong norms and values. As the proportion of co-authored papers rises, the network is becoming denser. Other trust-based networks that have fulfilled a similar role to overcome market failures in the past have been families and ethnic groups. Here, as with academic-entrepreneurial cooperation, the boundaries of individual firms are blurred. More recently, another global professional network has received attention: programmers, e.g. the LINUX community. Eric von Hippel has written several papers about such user-communities who share a strong set of common values and also drive innovation in a certain market.
Lynne Zucker was recommended to me as someone who has extensively studied cooperation and innovation in the biotechnology industry. She is probably best known for her work together with Michael Darby on the role of 'star' scientists in the biotechnology industry. It was through their work that I came across this paper. (This requires access to JSTOR. An alternative is to download the working paper.)
Liebeskind et al. treat a different aspect of biotech firms. How do they get their most important input: knowledge. The various forms of contracts and alliances to secure supply chains are relatively well understood by economists where manufacturing industries are concerned. These market-based forms of exchange, however, don't seem to work for firms that need to source science-based knowledge in a hypercompetitive environment.
Summary
Traditional transaction-costs theory analyzes the costs and benefits of internal, hierarchical exchanges vs. external, market-based exchanges. In the first case, exchange depends on rules set by managers and enforced by managerial authority down through the hierarchy of the firm. In the second case, fairness in exchange is assured by price competition or by contract. In situations of high uncertainty, and/or asset specificity internal exchanges tend to be more efficient because the market mechanism and ex ante contracting cannot allocate costs and benefits fairly. (Based on Coase and Williamson.)
However, in fast-changing industries, external knowledge-sourcing may be more efficient than internal sourcing despite the transaction-costs argument above. According to Zucker: While bureaucratic authority is by definition located within the firm's boundaries, expert authority depends on the information resources available to an individual, and not on the authority of office. Thus authority may be located within the organization... but when an external expert authority market can provide information that leads to greater effectiveness, then expert authority tends to migrate into the market. Teece argues that it may not be optimal for a firm (i.e. hierarchy) to seek to internalize numerous exchanges when technology is changing rapidly because the value of internalizing those exchanges may change rapidly under conditions of technological uncertainty, resulting in excess sunk costs. And Camagni adds that, when technology is changing rapidly, firms lose their ability to assess the value of information accurately, because they cannot learn and institutionalize appropriate assessment routines in short periods of time. Hierarchies are just not suited to efficient distribution of fast-changing technological knowledge.
Markets are not well-suited either. As Arrow demonstrated, markets for information are subject to failure, because an efficient price cannot be established for knowledge without revealing its contents. This problem of appropriation can be solved by patenting, secrecy or licensing and first-mover advantages. However, during the innovation process and where exchange of knowledge is necessary to advance innovation, these options are of limited value.
In addition to the traditional forms of exchange (market and hierarchy), a third form has been proposed: social networks. Shared norms and values serve to ensure fairness in exchange, without resort to market pricing, contracts, or managerial authority.
- Unlike hierarchies, but like markets, social networks involve exchanges between legally distinct entities. Network exchanges, like market exchanges, are external to the firm. Therefore, these exchanges are not formally excluded from the rule of law, as are exchanges which take place within hierarchies.
- Unlike markets, but like hierarchies, social networks support exchanges without using competitive pricing or legal contracting. Specifically, exchanges between individuals or organizations which are conducted through social networks have no need for price competition or legal contracting because the shared norms of the exchange partners alone will ensure that outcomes are fair.
This form of exchange is based on trust created through socialization and tradition, repeated exchange, or mechanisms such as posting a bond, testing, or performance monitoring. Biotech firms have access to a particularly useful network. Since the knowledge they use is strongly science-based, they work closely with academic researchers. As Blau and Crane pointed out, there are very strong norms that regulate intellectual property in the academic research network. This significantly reduces the main problem of external exchange.
The authors' own summary:
Where expert information is necessary external sourcing through networks is more promising. Where appropriation becomes too sensitive an issue, internal exchange is better suited. Firms may prefer to use social networks, rather than markets or their won hierarchies (i) for governing exchanges of information or knowledge which (ii) is potentially but uncertainly valuable, (iii) which is appropriable, and (iv) whose production is characterized by human capital immobility.
What might this mean for global innovation networks?
Knowledge sourcing through academic networks would seem to encourage global cooperation in biotech innovation. The academic research network already maintains global links and is probably one of the few global networks that shares such strong norms and values. As the proportion of co-authored papers rises, the network is becoming denser. Other trust-based networks that have fulfilled a similar role to overcome market failures in the past have been families and ethnic groups. Here, as with academic-entrepreneurial cooperation, the boundaries of individual firms are blurred. More recently, another global professional network has received attention: programmers, e.g. the LINUX community. Eric von Hippel has written several papers about such user-communities who share a strong set of common values and also drive innovation in a certain market.
Wednesday
Life and the internet
The death of distance: how the communications revolution is changing our lives, Frances Cairncross, 2001
In 'The death of distance,' Frances Cairncross of The Economist set out to analyze as many facets as possible of the internet in our lives. Her book was initially published in 1999, though she thoroughly revised it for the 2001 edition. Two (or worse, four) years are an eternity in internet time, so it is all the more remarkable that 'The death of distance' remains interesting and relevant. Cairncross covers social and economic topics from the design of homes and new work modes to global trade and network economics.
Firm structure and alliances
In the 1990s there was a marked increase in the number of alliance between firms. This trend was reinforced through the availability of the internet and the world wide web.
The Internet gives companies new incentives to work together: to build a trading hub, say, or to offer links to one another's products on their Web sites. Alliances provide an insurance policy against risk - the risk of new technology and the risk of new business models. They also allow companies to deepen their relationship with customers by offering them bundles of products, some created by alliance partners. On top of all these incentives, the Internet provides the means. It enables the construction of links not just between the folk at the top of two allied companies, but at many levels on the way down.
Openness becomes a corporate strategy as companies allow customers and suppliers unprecedented access to their databases, staff, and inner workings. New opportunities for building alliances and relationships demand greater trust in corporate life. Learning to manage these new relationships in novel ways will clearly be an important - perhaps the most important - competitive advantage for businesses in the new century.
Similarly, a study by Powell et al. found that managing R&D alliances had the beneficial side-effect of building a firm's competence in alliance management in general and thereby improving its competitiveness. In addition, companies increased their reputation as a trustworthy partner the more they engaged in alliance - another gain in competitiveness. As a firm becomes a more valued and more connected alliance partner, it moves closer to the center of the information network in the industry.
Technologically enabled alliances began with companies using proprietary systems to give suppliers or customers access to their databases. However, installing these systems was associated with very high costs and a risk of being locked in with the wrong partners. The internet introduced a cheaper, more flexible and often more user-friendly method of sharing data.
Cairncross (like David and Chakravorti) emphasizes the importance of adapting business models to technology - and points out the radical changes that the internet has facilitated. However, she also says that this process is taking place much faster than for earlier innovations because a) the Internet is being adopted much faster than earlier technologies, and b) there is a greater awareness of the potential of technological change to increase efficiency and a more focused search for ways to make it do so. In a 'reverse product cycle' these efficiency gains can spur further technological improvements or even new product development.
For most companies the road-to-Damascus moment comes when they realize that the Internet offers a way to reorient the entire business so that customers at one end of the chain and suppliers at the other are linked seamlessly together.
Knowledge and innovation
Cairncross's description of the organizational changes in supply chain management suggests that business model innovation is as dramatic as technological innovation. Each builds on the other: On the one hand, firms adapt to exploit new technologies as efficiently as possible. On the other hand, direct customer feedback is a significant driver of further technological innovation.
It seems to me that this may have consequences for the location of innovation. If customer feedback is channeled through electronic systems, this may improve the chances of conducting cutting-edge innovation outside the dominant industry cluster (e.g. Silicon Valley). Although few studies have been done so far on the cooperation of industry clusters, an analysis of the medical instruments industry showed that lack of customer contact and feedback was a significant factor in the failure to keep up technologically in a more distant and technologically less advanced location.
Cairncross points out that collaborative working was the Internet's original function back in the days of the ARPANET.
Goods and services
The distinction between goods and services is no longer clear.
Three distinctions were important in the past. First, manufacturing produced a tangible object; services did not. Second, manufacturing operations could be at a distance from the final consumer; service operations could not. Third, manufactured goods could be mass-produced; services had to be individually created. Now, manufacturing is becoming increasingly intangible, more manufacturing is tailored to the individual's tastes, more services are being produced at a distance, and more services are being mass produced.
Cairncross introduces a new categorization: in the future it will be more important whether a product requires physical delivery or whether it is 'weightless,' ie. digitally deliverable.
The fact that immediacy and the need for personal contact may become less important for some services but more so for some products will probably also be important for innovation in these two domains. While immediacy and personal contact might be seen as drivers of innovation, it appears that the exact opposite is happening. Services have traditionally engaged in very little R&D. Now, they are catching up; especially those services that are mass-produced are benefiting from a large increase in R&D.
Service industries have traditionally been slower to innovate than manufacturing, but some are now more innovative than manufacturers and concentrate on making similar improvements, in quality, market, and range.
The rest
The book covers many more aspects from politics and government to private and social life. Some of Cairncross's conclusion seem a bit rosy, especially when compared to her very balanced analysis of economic and business topics. Well worth a read.
In 'The death of distance,' Frances Cairncross of The Economist set out to analyze as many facets as possible of the internet in our lives. Her book was initially published in 1999, though she thoroughly revised it for the 2001 edition. Two (or worse, four) years are an eternity in internet time, so it is all the more remarkable that 'The death of distance' remains interesting and relevant. Cairncross covers social and economic topics from the design of homes and new work modes to global trade and network economics.
Firm structure and alliances
In the 1990s there was a marked increase in the number of alliance between firms. This trend was reinforced through the availability of the internet and the world wide web.
The Internet gives companies new incentives to work together: to build a trading hub, say, or to offer links to one another's products on their Web sites. Alliances provide an insurance policy against risk - the risk of new technology and the risk of new business models. They also allow companies to deepen their relationship with customers by offering them bundles of products, some created by alliance partners. On top of all these incentives, the Internet provides the means. It enables the construction of links not just between the folk at the top of two allied companies, but at many levels on the way down.
Openness becomes a corporate strategy as companies allow customers and suppliers unprecedented access to their databases, staff, and inner workings. New opportunities for building alliances and relationships demand greater trust in corporate life. Learning to manage these new relationships in novel ways will clearly be an important - perhaps the most important - competitive advantage for businesses in the new century.
Similarly, a study by Powell et al. found that managing R&D alliances had the beneficial side-effect of building a firm's competence in alliance management in general and thereby improving its competitiveness. In addition, companies increased their reputation as a trustworthy partner the more they engaged in alliance - another gain in competitiveness. As a firm becomes a more valued and more connected alliance partner, it moves closer to the center of the information network in the industry.
Technologically enabled alliances began with companies using proprietary systems to give suppliers or customers access to their databases. However, installing these systems was associated with very high costs and a risk of being locked in with the wrong partners. The internet introduced a cheaper, more flexible and often more user-friendly method of sharing data.
Cairncross (like David and Chakravorti) emphasizes the importance of adapting business models to technology - and points out the radical changes that the internet has facilitated. However, she also says that this process is taking place much faster than for earlier innovations because a) the Internet is being adopted much faster than earlier technologies, and b) there is a greater awareness of the potential of technological change to increase efficiency and a more focused search for ways to make it do so. In a 'reverse product cycle' these efficiency gains can spur further technological improvements or even new product development.
For most companies the road-to-Damascus moment comes when they realize that the Internet offers a way to reorient the entire business so that customers at one end of the chain and suppliers at the other are linked seamlessly together.
Knowledge and innovation
Cairncross's description of the organizational changes in supply chain management suggests that business model innovation is as dramatic as technological innovation. Each builds on the other: On the one hand, firms adapt to exploit new technologies as efficiently as possible. On the other hand, direct customer feedback is a significant driver of further technological innovation.
It seems to me that this may have consequences for the location of innovation. If customer feedback is channeled through electronic systems, this may improve the chances of conducting cutting-edge innovation outside the dominant industry cluster (e.g. Silicon Valley). Although few studies have been done so far on the cooperation of industry clusters, an analysis of the medical instruments industry showed that lack of customer contact and feedback was a significant factor in the failure to keep up technologically in a more distant and technologically less advanced location.
Cairncross points out that collaborative working was the Internet's original function back in the days of the ARPANET.
Goods and services
The distinction between goods and services is no longer clear.
Three distinctions were important in the past. First, manufacturing produced a tangible object; services did not. Second, manufacturing operations could be at a distance from the final consumer; service operations could not. Third, manufactured goods could be mass-produced; services had to be individually created. Now, manufacturing is becoming increasingly intangible, more manufacturing is tailored to the individual's tastes, more services are being produced at a distance, and more services are being mass produced.
Cairncross introduces a new categorization: in the future it will be more important whether a product requires physical delivery or whether it is 'weightless,' ie. digitally deliverable.
The fact that immediacy and the need for personal contact may become less important for some services but more so for some products will probably also be important for innovation in these two domains. While immediacy and personal contact might be seen as drivers of innovation, it appears that the exact opposite is happening. Services have traditionally engaged in very little R&D. Now, they are catching up; especially those services that are mass-produced are benefiting from a large increase in R&D.
Service industries have traditionally been slower to innovate than manufacturing, but some are now more innovative than manufacturers and concentrate on making similar improvements, in quality, market, and range.
The rest
The book covers many more aspects from politics and government to private and social life. Some of Cairncross's conclusion seem a bit rosy, especially when compared to her very balanced analysis of economic and business topics. Well worth a read.
Tuesday
Slow pace of fast change
Bhaskar Chakravorti, author of 'The slow pace of fast change: bringing innovations to market in a connected world,' recently gave an interview in Ubiquity that provides a good introduction to his work.
Paul David and others have made the point that it takes a long time for innovations to fulfill their economic potential, especially when the innovation involves a general use technology. For example, the main productivity gains from the introduction of electricity were achieved when firms started moving machines around on the factory floor to create a more efficient workflow. However, before that could happen, firms not only had to invest in electrifying their production plants, they also had to invent an entirely new business model.
Chakravorti takes this argument one step further. In an interconnected world it is often not sufficient that firms adapt to new technology one by one; to benefit from a new technology different organizations (often public and private) need to coordinate their activities.
If you dial 911 from your home phone and you forget to say where you are or you collapse, the emergency system will be able to find you because there's an address tied to your phone. But if you are on a cell phone ... there's no address attached to it and the 911 systems will have no information popping up on their screens.
You need the wireline players to upgrade their networks, because they connect from the cell phone that works into the 911 call centers. The 911 call centers need to upgrade their systems so that the latitude and longitude data shows up on their computer screens. All parties must make investments. Simply putting the pressure on the wireless system is not enough. This is a classic example of the basic dilemma that I talk about in the book. You have the technology to solve the problem, but it will take a long time for that technology to translate into fast change, in terms of plugging this hole in our national security system, because all the different parties must coordinate their choices.
As a game theorist interested in networks, Chakravorti works on the mechanisms that can bring about the necessary coordination, identifying individual players' choices and incentive structures to work out a strategy that will nudge everybody in a common direction.
Paul David and others have made the point that it takes a long time for innovations to fulfill their economic potential, especially when the innovation involves a general use technology. For example, the main productivity gains from the introduction of electricity were achieved when firms started moving machines around on the factory floor to create a more efficient workflow. However, before that could happen, firms not only had to invest in electrifying their production plants, they also had to invent an entirely new business model.
Chakravorti takes this argument one step further. In an interconnected world it is often not sufficient that firms adapt to new technology one by one; to benefit from a new technology different organizations (often public and private) need to coordinate their activities.
If you dial 911 from your home phone and you forget to say where you are or you collapse, the emergency system will be able to find you because there's an address tied to your phone. But if you are on a cell phone ... there's no address attached to it and the 911 systems will have no information popping up on their screens.
You need the wireline players to upgrade their networks, because they connect from the cell phone that works into the 911 call centers. The 911 call centers need to upgrade their systems so that the latitude and longitude data shows up on their computer screens. All parties must make investments. Simply putting the pressure on the wireless system is not enough. This is a classic example of the basic dilemma that I talk about in the book. You have the technology to solve the problem, but it will take a long time for that technology to translate into fast change, in terms of plugging this hole in our national security system, because all the different parties must coordinate their choices.
As a game theorist interested in networks, Chakravorti works on the mechanisms that can bring about the necessary coordination, identifying individual players' choices and incentive structures to work out a strategy that will nudge everybody in a common direction.
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