This paper analyses the changes of Eastern European science & technology (S&T) systems caused by the transformation from socialist to capitalist market economies. Our hypothesis is that the largest part of Eastern European S&T capacities has been devalued by this change, leaving behind a highly fragmented system. Domestic enterprises, the ultimate beneficiaries of a national S&T system, have quickly integrated into inter national production and sales networks, leaving domestic S&T capacities largely without a market. Under these specific post-socialist conditions, the S&T-policy approach has to change: instead of continuing to supply capacities, we propose a demand-oriented S&T policy, consisting of i) the identification of newly emerging enterprise networks and the reduction of S&T policy to clearly identified bottlenecks, and ii) the rapid restructuring, buy-outs or closure of those S&T institutes without a market. We apply this approach to three different industries, each with of different technological nature: software, shipbuilding, and computers. We conclude that in the post-socialist transformation process, there is very limited scope for a demand- oriented S&T policy. The radical nature of the break between socialist and post-socialist S&T requirements becomes only evident at enterprise level; policy conclusions based on fragile aggregate S&T statistics may be misleading. The analysis of Eastern Europe may also teach us something on the demand-oriented restructuring of Western S&T systems.
As regards scienceandtechnologypolicy in particular, governments developed and combined a broad range of policy instruments in order to meet the overall goal. Of course, not all policy instruments were new, but even if not they were often given a particular emphasis. For example, governments continued to provide funding for basic research, but they were increasingly looking out for those areas that might be most up-and-coming and likely to have a broad economic impact. Since decisions about which areas should be granted funding were characterized by high degrees of uncertainty, governments would not only rely on the advice of scienceand engineer- ing experts, but often follow the decisions made by the governments of the main competitors. The most significant policy changes took shape since the 1980s with respect to new modes of linking research to commercialization. To this end, institu- tional mechanisms have been created that would allow, encourage, or oblige re- searchers to engage in private commercial ventures or in market-oriented scienceandtechnology transfer. In addition, governments worked on improving the conditions for start-up companies or innovative small and medium-sized businesses. Generally, governments reorganized, and partly extended, their efforts in scienceand techno- logy policy, although to a varying degree. For example, in the USA the Bayh-Dole Act of 1980 (Public Law 69-517), the Stevenson-Wydler Technology Innovation Act of 1980 (Public Law 96-480), the Technology Transfer Commercialization Act of 1980 (Public Law 106-144), the Trademark Clarification Act of 1984 (Public Law 98- 620), the Federal Technology Transfer Act of 1986 (Public Law 99-502), the Omni- bus Trade and Competitiveness Act of 1988 (Public Law 100-418), and the National Competitiveness andTechnology Transfer Act of 1989 (Public Law 101-189) were landmark legislations that were to set standards for systematic commercially oriented scienceandtechnology policies in other countries. As a consequence, traditional in- stitutional boundaries between the private and the public realms were shifted on be- half of the former, i.e. for example, by enabling and promoting private exploitation of publicly funded research. The debate about scienceandtechnologypolicy that has particularly been concerned with competitiveness (thus also touching on the impor- tance of other policy fields) forms the context of innovation regime analysis (Nelson 1993; Lundvall 1992). So we find a partial overlap between the research on innova- tion regimes and that on “varieties of capitalism.”
Science O ne of the most important factors underpinning the effective develop-
ment of the national science, technology, and innovation system is its global integration, based on balanced partnerships with other countries. Strengthening international scienceandtechnology cooperation (ISTC) helps to stabilize the national economy and promote growth in its scientific poten- tial. Up-to-date notions of the nature of S&T development against the back- drop of large-scale changes in the international division of labour and inten- sifying global competition determine the outlined cooperation strategies. The most successful of these strategies are summarized, improved, and circulated on international and national levels. Both traditional, well-established approaches and entirely new, pilot initiatives are introduced. Although the actual forms of partnership and corresponding policy measures are disseminated relatively in- tensively, certain problems that are not always easy to overcome still persist. The continuing emergence of new challenges and trends is forcing a change in the established rules and has prompted a need for a swift response by policy makers, politicians, experts, and economic players [OECD, 1988, 1988, 2015; European Commission, 2011, 2012].
When comparing each field’s results with the average technological implemen- tation time estimates, the field of information, electronics and communica- tion was the fastest (2019), while the field of life and healthcare was the slow- est (2022). Experts surveyed agreed that 519 future technologies (79.6% of the total identified) will be technologically implemented in Korea within the next 10 years (by 2022). Furthermore, they predicted that 294 technologies would be distributed across society within the same period of time. The predicted average time for future technologies to be widely implemented across society is 2.7 years. When examining the current state of countries with the highest level of tech- nology in relation to the 652 future technologies, the fourth TF found that the United States possesses the highest level of technology in 495 technologies. Japan was second with 141 technologies, and the EU was a distant third with 32 technologies. The research revealed that Korea’s average technology levels were 63.4% of the leading countries regarding the 652 future technologies. The level of technology for 18 future technologies was above 80%, which indicates that Korea leads the field in these technological areas, with nine included in the field of information, electronics and communication, which is more than that in any other field. At the same time, the study found that the levels of 22 technologies were below 40% and thus were part of the ‘lagging’ group, among which nine were in the field of machinery, manufacturing, aerospace and astronomy. Of the 652 future technologies, Korea’s highest technology level was in ‘terabit level next-generation memory device technologies’ (90%). When examining the priority policy measures that the government should en-
as industrial inventions or discoveries in basic science. From this root idea there flow a number of subsidiary ideas. One is the reshaping of goods production and the redirection of Research and Development (R and D) that result from the accumulation of knowledge. A second is the distinction between knowledge that is internal to an organization, and outside knowl- edge, or knowledge spillovers. A third theme is the importance of limitations on flows of outside knowledge or knowledge spillovers that are imposed by absorptive capacity, human and institutional constraints, and the intrin- sic relevance of the information. A fourth theme is the comparable impor- tance of basic and often academic sci- ence for production, besides that of industrial R and D. Finally, the research recognizes the role that contract design and public policy play in delib- erate knowledge transfer between firms and outside R and D performers. These in turn influence the limits of the firm in R and D. In pursuing each of these themes, the design, collection, and assembly of new and high quality economic data forms a critical part of the work.
This recruitment policy has resulted in a coherent and synergistic portfolio of research areas, within which a diversity of approaches is brought to bear on a common topic, and between which there are excellent opportunities for interdisciplinary research collaborations. Scientifically the Institute falls into four main research areas: evolutionary biology, neuroscience, computer scienceand cell biology and biophysics. A notable feature of the scientists is their commitment both to developing a quantitative understanding of their own research areas — by integration of events at different levels of organization through experimentation and modeling — and their commitment to interdisciplinary collaboration with the other research areas. This is likely to result in both a true systems approach to organisms and in interdisciplinary cross-fertilization. We found great enthusiasm among the scientists at all levels and many said that part of their motivation for joining IST Austria was the opportunity to work in an interactive, international and interdisciplinary research environment. This attractive research context has undoubtedly helped to ensure the fine hires of faculty at senior and junior levels. The Institute has competed successfully with other internationally leading institutions to appoint the best in the world.
Decision makers in RTI policy therefore need instruments and tools that fulfil the growing demand for information and learning, for example about the methods of operation in the Austrian research and innovation system, the quality of Austrian research and development by international standards, and the effectiveness of research andtechnology funding. These instruments include regular evaluations of public interventions. Good evaluations can successfully reveal “blind spots”, topical and institutional “lock-ins” and places where similar programmes overlap. Through regular assessment, they enable questions to be raised about traditional assumptions of what constitutes “good” science, research, technologyand innovation policy, and about entrenched practices – including in the area of subsidies and institutions themselves. Evaluations help policy-makers to take a broader view, by weighing up various possibilities or highlighting inspiring practices for comparison.
pecially in Africa. At that time, the German government decided that its development aid should be directed to countries far less developed than China.
This change of China’s status had direct effects also for other policy activities and gov- ernmental departments, among them the Federal Ministry of Education and Research (BMBF) as well as the Ministry of Economic Affairs andTechnology (BMWi), recently renamed to Ministry of Economic Affairs and Energy, who are the main actors for sci- ence andtechnology policies in Germany – apart from the technology- or specific task- oriented departments like the Ministry of Environment and Natural Resources or the Ministry of Traffic and Infrastructure, who both have minor budget appropriations for S&T. Since then, China was treated as a partner on eye-level in all aspects, including the expectations on financial contributions to projects and activities of mutual interest. For example, in publicly funded R&D or S&T projects the Chinese side is expected to pay its own researchers and make its own financial contributions, while before that it was possible to apply for travel budget, daily allowance etc. at the BMBF for Chinese researchers visiting Germany.
The government has given such privileges to on-park firms primarily because when the government started the STIPs, it gave the top priority of the STIP policy to the growth of national STIPs. Indeed, the national STIPs have grown at an astonishing speed. For the 14 years from 1992 to 2006, the annual growth rate of real output value per STIP was more than 40%, average labor productivity grew more than sevenfold, and the number of firms in the STIPs also grew more than seven times. Table 1 presents the data on the number of on-park firms in the 53 STIPs in 2001 and 2006. The number of on-park firms per national STIP increased from 458 in 2001 to 865 in 2006. During the same period, the real output per worker also grew from 88,000 yuan to 153,000 yuan. Table 1 also presents the data on the five largest STIPs in terms of the number of on-park firms in 2006, and the five fastest growing parks in terms of labor productivity measured by the value added per worker from 2001 to 2006. The largest STIP is the Beijing Zhongguancun Park, which had 18,096 firms in 2006. The five parks that experienced the fastest growth in labor productivity are located in economically less developed regions. This observation suggests that labor productivity has been converging among the STIPs, consistent with the result of the growth regression by Hu (2007).
The focus of this work is to present an on-going experience of collecting, coding and analyzing Science, Technologyand Innovation (STI) Policy Evaluations in Latin America (LA), with emphasis in the evaluation design and methods. The research is part of a broader initiative named Scienceand Innovation Policy Evaluations Repository (SIPER), coordinated by Manchester Institute of Innovation Research (MIoIR). SIPER is a central source of knowledge on scienceand innovation policy evaluations. Its aim is twofold: (i) to provide on-line access to a unique collection of policy evaluations, located at a single location; and (ii) to allow policy learning by providing an informed analysis of the database contents that is both searchable by policy makers and other stakeholders and which provides the basis for additional academic analysis.
This approach has been taken on board by the public at large, so that Russian society, with rare (but fortunately growing) exceptions, has not yet fully understood the gravity of the cur- rent situation regarding scienceandtechnology. The categories and stereotypes of the past still prevail in the public consciousness with respect to the role and significance of scienceandtechnologyand the place of intellectuals in the socio-economic progress of the nation. This explains, to a great extent, the current failure in the higher echelons of power (parliament and government) to appreciate the importance of the R&D factor) and the delay in adopting adequate measures to maintain and develop Russia's scientific and technological potential. This may be illustrated by the fact that of the nearly twenty anti-crisis programmes that were publicly announced during the period 1992-1995, none included any measures designed to ensure the survival or development of the Russian R&D sphere. At the same time, the Russian Academy of Sciences and the RF Ministry of Scienceand Technological Policy (the minis- try's name at that time) by and large stood by passively and, apart from some piecemeal measures, did not really take any systematic practical steps to maintain national R&D poten- tial or to alert the government's attention to the problems of Russian scienceandtechnology. As a result, the most important strategic resource for overcoming the current socio-economic crisis, for bringing about the success of market reforms and for reinforcing the international position of the Russian Federation still remains untapped either by the state or by commercial structures, thus allowing the perpetuation of negative trends in scienceandtechnology.
t is a great honor to be invited to give the first Rudolph Wildenmann lecture. Prof. Wildenmann was a leader in the development of empirical social science in Germany, particularly in the study of political behavior and of elections. He was also a great sup- porter of innovative methodologies and instrumental in the founding of ZUMA. It is in his spirit and, I hope, a fitting honor to his memory that I have chosen to speak about a topic that lies at the intersection of social science, politics, and concerns for data. In his acceptance speech at the Democratic National Convention in August, President Clinton cited 27 social and economic facts about the nation. These facts ranged over a great variety of topics from better known indicators such as the unemployment and infla- tion rates to lesser known facts about the economy (for example, a 4.4 million increase in home ownership, 15 million persons pay less income tax) to social conditions (for example, 1.8 million fewer persons on welfare, 40 million persons with more pension security) to crime (for example, 100,000 more police on the streets, 60,000 fewer persons could get handguns) to health (for example, the life expectancy of AIDS patients doubled, 12 million families took advantage of new family and medical leave opportunities). Of course, these facts are put forth as an argument for the effectiveness of the policies of the Clinton administration.
The above competency clusters comprise universal metaskills applicable in various areas [Finch et al., 2013] and among those relevant for the technologyand innovation sphere [Collet et al., 2014]. Detailed competency lists drafted by international organiza- tions, various research teams, or individual scien- tists tend to be excessively heterogenous in terms of grouping and the level of detail. Like [Karnouskos, 2017], we identified six major clusters, each compris- ing two main skill groups: research and digital skills in the cognitive competences cluster, intercultural awareness and social intelligence in the interper- sonal one, and emotional intelligence and interdis- ciplinarity in the personal competences cluster. Research skills traditionally play the key role in higher education. Having them, along with the ability to use them, are seen as key characteristics of university graduates, especially those at research universities [Garg et al., 2018]. However, though these skills are frequently learned by taking part in research, the scope for their subsequent application is much wider than that [EuroDoc, 2018], since “re-
This article introduces a new Melitz-type model of heterogeneous producers with de- creasing returns to scale and different productivities. Different to previous models, it describes smallholder producers in rural areas of developing countries in the context of environment and development economics. The model enables a socially sensitive policy analysis considering poverty and distributional effects. In this model, the production input causes a negative environmental externality. External shocks, e.g., caused by climate change, and economic policies affect the producers’ endogenous choice between market entry or exit and between simple or advanced technology. In the first step, var- ious shocks and policies are analyzed theoretically. A novel type of the rebound effect (Jevons paradox) is identified for the production input that occurs when market entry is incentivized by productivity improvements. In the second step, the model is calibrated by applying it to coffee production in rural Vietnam. The simulation results show that secondary effects of the shocks, such as employment effects, can be substantially larger than the original impact. The support of market entry or of the advanced technology creates adverse distributional effects.
If we add indirect and diffusion-oriented measures we come closer to Ergas’ original classification made in 1987. In fig. 5 the respective relative shares of these two broad categories - diffusion-oriented plus indirect and mission-oriented - are depicted. It becomes visible that the dominance of mission-oriented policy ended already in 1986. So, since the mid 80’s an overall diffusion-orientation of German technologypolicy can be claimed. Additionally, there is a growing trend of the dominance of diffusion-oriented policy measures still lasting since the mid of the 90’s. This increasing dominance can be traced back to new promotion areas like ‘new materials’, ‘information and communication technologies’ etc., in which the design of the policy instruments more and more gives up the aim of prescribing technological specificities, leaving it to the creativity of market and non-market actors. Taking this development one may ask for the reasons of this policy change. Of course, political reasons (e.g. nuclear power) are to be taken into account. However, furthering diffusion and thus heterogeneity is always an appropriate measure, when the policy makers do not have a clear idea about the direction of further development. However, the insight that the innovativness of a country depends on collective innovation, too, might also have induced this policy shift. In this sense policy does not have to lead the development but only to manage it - or only to be one actor in the collective process.
discourse might lead to a picture of ITI that varies very much in terms of quality and reliability. Flaws in operating concepts and a small scale spatial competition between single communities may lead to a misallocation of resources. On top there is still another aspect: even when ITI operate on a strictly private finance basis – and therefore any risk of failure is covered by private capital – there is a need for a minimum of coordination with regional or local public bodies. In the Swiss context it is a sure fact, that proactive cooperation between various ITI and public institutions increases the positive impacts of these centers on their economic and social environment.
Despite significant improvements in the last couple of years, women are still under-represented in scienceandtechnology, both in the academic and private sector. This is due to a variety of reasons, mostly related to the role allocated to women in modern society as well as pre-existing prejudices that form glass ceilings while encouraging male presence in the workplace. It is also however, a result of information or lack of, which places young women in difficult position of making a career choice, with little knowledge of available possibilities. What seems to be missing are good role models that could act as inspiration and source of information and guidance, and offer a glimpse into the reality of being a female employed in the field of scienceand/or technology. Parents, teachers, and career guidance counselors all have a significant role in assisting or hindering the way young women chose their career paths and that choice begins early on from school, all the way through to higher education. Choice, essentially, and factors that determine it as well - as ways of encouraging female participation in scienceandtechnology - are the focus of the present article, which is based on results from the European project Information for a choice: empowering young women through learning for scientific and technological career paths, realized under the 6th Framework Program. As this article will show, the promotion through the usage of new technologies, of role models, is crucial in breaking the existing stereotype of women in science, engineering andtechnology. Science is often rejected as a career choice due to limited information available and positive role models to encourage young girls in participating. Career orientation offered at school through the usage of new technologies is an important step in that direction; however, particularly in countries where the family unit is especially influential in career decisions, parents must be brought in and educated on the possibilities available. Mass media also play an important role in introducing and sustaining stereotypical images of women in particular professional roles, thus, any outreach solutions need to include them.
Sensitivity of Optimal Policies to Assumptions
A striking result from these results is that the optimal renewable energy subsidies are relatively low, especially for the non-solar technologies that represent the majority of renewables generation. It would appear that the 2.3 cent/kWh Federal Renewable Electricity Production Tax Credit (PTC) may be overly generous for wind/other energy, at least in combination with the other policies. Feed-in tariffs among many European countries far exceed these levels of support. The comparison with current U.S. policy is more difficult for solar, which is supported at the federal level by a 30 percent investment tax credit, although the per-kWh equivalent value of current U.S. solar incentives appears to be well-above the optimal levels identified here in combination with emissions and R&D policies. How sensitive are these results to our model assumptions?
and clears the market. Hourly prices and quantities are determined in uniform price auctions, i.e., all production units with bids below the clearing price receive the latter.
All units are obligated to place bids for their entire available capacity. Power generators participating in the market are allowed to place both simple and complex bids. Whereas simple bids signal the willingness to sell a certain amount of electricity at or above the price bid, complex bids add constraints on the minimum daily revenue required by a plant. Firms make use of complex bids, for instance, whenever plants face additional costs to start-up. 8 If operating margins throughout a day do not cover a plant’s revenue requirement, all bids by this plant are excluded from the auction. Complex bids thus change the probability of winning and being dispatched for the respective plants ( Reguant , 2014 ). Lastly, there exists a price cap of 180.30 A C /MWh, which was however never binding during our observation period. Indeed, clearing prices ranged between 3 A C /MWh and 127 A C /MWh.
Postharvest technology is predicted to experience a transformation over the next couple of decades. Some of the changes may be wrought by as yet unforeseen developments in science, but others will result from the rapid evolution of computer software and hardware. Commercial software is presently available that integrates many strands of engineering science such as structural mechanics, the flow of particulate solids, the distribution of gases within buildings and thermal analysis. The software also enables interactions between these various processes, and the approach is referred to as multi-physics. Commercially available software can be tailored to account for biological phenomena such as the effects of the microenvironments in grain stores on the viability of seeds, the rate of decay of pesticides, the propensity of insect populations to increase and so on. The time is ripe to integrate these chemico- biological aspects of grain storage with multi-physics to form what might be dubbed an omni-scientific approach to postharvest technology. The development of such an approach will help unify the disparate sciences involved in grain handling, and it will provide an explicit overarching intellectual framework into which individuals' work will fit. Information and communications technology will not only enable technical problems to be addressed, but it will enable a range of specialists to contribute simultaneously to solving particular problems. Such a scenario will have a profound effect on the postharvest profession, and it will require a radically new approach to the education and formation of stored grains technologists. These specialists must continue to have deep knowledge of specialised areas of science such as genetics, analytical chemistry, fluid dynamics and so on, but they must also be familiar with the integrating software tools and a broad range of science. Postharvest professionals will need to be familiar with several scientific disciplines, i.e. they will need to be omni-scientists, whilst recognising that omniscience is unattainable.