Over the past decade, the field of organization studies has increasingly focused on knowledge and knowledge processes in organizations. This thesis describes a study of one of those processes, knowledge sharing, in the context of industrial research. Though the attention for knowledge in organizations is rather new, technical communication in industrial research has been subject of research for over the last fifty years (e.g., Herner 1954; Allen 1977; Tushman 1978; Keller 1994). One major lesson that can be learned from past research is that technical communication contributes to research performance. In a study of 1311 researchers from industry and government laboratories, Pelz and Andrews (1966) already found a significant correlation between a researcher's performance and his communication with colleagues within and outside his group. Recently Anderson et al. (2001) established again that colleagues are the most important source of information for researchers (after the use of their own knowledge). Although the importance of technical communication has been confirmed over and over again, we do not know very much about the details of the contribution of technical communication to industrial research practices. With a few exceptions (Johnston and Gibbons 1975; Faulkner and Senker 1995), the content of technical communication has not been systematically studied. Nevertheless, inspired by linear communication models (e.g., Shannon and Weaver 1949), most studies in the field have interpreted technical communication as the transfer of information or knowledge (e.g., Gerstenfeld en Berger 1980; Kogut en Zander 1992; Moenaert en Caeldries 1996). Furthermore, the way in which technical communication is accomplished, is not systematically explored. Most of the things researchers might say will be irrelevant for the work of others. Nevertheless researchers manage to contribute to each others work. Several authors assume that this is because communication is initiated by those in need of information or knowledge (e.g., Leckie et al. 1996; Hansen 1999). Past research has found many factors that enable or constrain knowledge sharing (e.g., Szulanski 1996; van der Bij et al. 2003), but these studies did not yield insight in the ways in which communication is realized. The first objective of the study reported in this dissertation was to gain insight in these issues: in what ways does technical communication contribute to industrial research practices and how is this accomplished. This study had an important theoretical objective as well. Within the field of organization studies two theoretical perspectives have offered an explanation for the value of technical communication. These are the information processing approach (Galbraith 1973; 1977; Tushman and Nadler 1978; Daft and Lengel 1986) and the knowledge-based theory of the firm (Kogut and Zander 1992; 1996; Grant 1996a; 1996b; 2001). According to the information processing approach (IPA), organization members face uncertainty and ambiguity, caused by task characteristics, task interdependencies and the organizational environment. Furthermore, the IPA assumes, in line with others, that technical communication consists of information transfer, making it capable of reducing uncertainty and ambiguity. The central hypothesis of the IPA is that higher performing organizations match their actual information processing to the information processing needs associated with the degrees of uncertainty and ambiguity they face. Thus, the core of the explanation for the value of technical communication is that it is capable of reducing uncertainty or ambiguity by transferring information. Recently, the knowledge-based theory of the firm (KBT) has been developed. This theory starts from the observation that a fundamental asymmetry exists between knowledge development and knowledge application (Demsetz 1991). To develop a thorough knowledge base, individuals have to specialize. However, to produce or develop complex products, a broad range of knowledge is necessary. Therefore, according to the KBT, the performance of an organization depends upon the integration of the specialized knowledge of individuals, that is, upon the coordinated application of this knowledge. The KBT, and the literature on knowledge management, interprets technical communication first and foremost as knowledge transfer. Knowledge transfer is interpreted as one among a number of possible knowledge integration mechanisms. In this way the KBT offers an explanation of the value of communication as well. However, the explanations of the IPA and the KBT are not based on detailed investigations of the content and process of technical communication. Van de Ven and Drazin (1985) note that the IPA uses information as an abstract, latent, unmeasured variable. Grant (1996a; 1996b) calls for detailed empirical research on knowledge sharing and knowledge integration to enhance his theoretical analyses. Therefore, the second objective of this study was to use empirical research results to reflect critically upon the assumptions and explanations of the IPA and the KBT. The objectives of this study called in the first place for exploratory, empirical research. Past studies have emphasized that communication should be studied within the context of the situated practices of group members (Lynch 1985; Orr 1990; Knorr- Cetina 1995). For that reason, a choice was made to study communication among mechanisms, of which 16 were found in the data. Examples of these origination mechanisms are: - 'diffusing': ego selecting existing information without an orientation at a specific problem - 'pushing': ego selecting existing information oriented at a problem of alter - 'pulled origination': existing information is asked by alter - 'thinking along': ego develops new content oriented at a problem of alter - 'self-suggesting': ego develops new content oriented at one of his own problems within an interaction It should be noted that one interaction is often characterized by more than one origination mechanism. This holds especially for interactive communication. Quantitative analyses showed that these origination mechanisms are associated with different moves and effects. For example, 'diffusing' is associated with the description of own activities and own results, and reporting about others. Out of 26 cases (in a total 227) in which this mechanism was found, 23 yielded an indirect contribution and only 5 a direct contribution. Conversely, 'thinking along' is predominantly associated with moves like giving arguments, suggesting experiments and technical solutions, agreeing, rejecting, questioning and concluding. Thinking along yielded a direct contribution in 26 out of 37 cases. The concept of origination mechanisms is a contribution to the existing literature. Only fragments of it have been acknowledged before, such as the distinction between 'pushing' and 'pulling' (e.g., Langrish et al. 1972; Schulz 2001). Furthermore, it enables the identification of biases in the existing literature. For example, most literature on information transfer assumes that this information is always existing before communication, waiting to be transferred. Another bias in the existing literature is that it assumes that information transfer and knowledge transfer are initiated by information searching individuals. A general finding with regard to origination mechanisms is that those origination mechanisms that are oriented at a problem of alter or a shared problem are most likely to yield direct contributions (in 82 out of 112 cases). Nevertheless, direct contributions are also produced via originations that are not oriented at such a problem and by self-suggesting: thinking up new ideas with regard to one's own problem in interaction. The effectiveness of origination mechanisms oriented at a shared problem or a problem of alter depends upon the application and development of knowledge. For example, asking a targeted question is enabled by knowing what knowledge one is lacking and by knowing who has that knowledge. For thinking along that is not necessary. But thinking along requires that ego knows about alter's problem and has relevant background knowledge. Each of the origination mechanisms has its conditions for effective employment. Therefore it is not wise to limit communication to one or a few mechanisms. These empirical results were used to reflect upon the theoretical explanations of the value of technical communication offered by the IPA and the KBT. With regard to the IPA, the following conclusions were drawn. First, a reflection upon the effects of technical communication showed that technical communication does not always reduce uncertainty or ambiguity, as is assumed by the IPA. Communication also leads to new questions and problems, to vanishing certainties and to conflicting interpretations. The increase of uncertainty or ambiguity may be valuable effects of technical communication in research as well. The assumption that technical communication can be interpreted as information transfer is questionable too. Several interpretations of 'information' were discussed (e.g., Shannon and Weaver 1949; Dretske 1981). For example, if information is interpreted as a capacity to reduce uncertainty or to increase knowledge (like Galbraith (1973) and Tushman and Nadler (1978) assume), the assumption that useful technical communication can be interpreted as information transfer is false. Both conclusions undermine the core of the explanation of the value of communication by the IPA. The KBT interprets technical communication as knowledge transfer, and knowledge transfer as a knowledge integration mechanism. According to this perspective, the integration of knowledge determines the performance of firms. However, a reflection upon moves and effects showed that useful technical communication cannot always be interpreted as knowledge transfer. Some instances of technical communication are better described as 'knowledge conducive communication'. Moreover, in contrast with existing views, knowledge application and knowledge generation play a central role in technical communication as well. But, in fact, this strengthens the explanation of the KBT. The analysis of knowledge processes occurring in technical communication shows other ways of integrating knowledge. For example, in thinking along ego applies his knowledge to a problem of alter. In one of the studied episodes, an expert in fracture mechanics applied his knowledge to determine the cause of a broken disc, showed to him by a colleague. The expert communicated his conclusion but did not communicate all knowledge on fracture mechanics that he used. This form of knowledge integration, temporarily applying one's knowledge to somebody else's problem, is more efficient than knowledge transfer, since not all knowledge that gets integrated needs to be transferred. Thus, a number of origination mechanisms that are effective in yielding direct contributions, including thinking along, are efficient as well. Further, the discovery of this knowledge integration mechanism shows the incompleteness of the taxonomy of mechanisms developed by Grant (1996b; 1997). Insight in the effectiveness and efficiency of the origination mechanisms in which ego selects or develops with an eye on a problem of alter or a shared problem was furthered by interpreting research findings in terms of distributed cognition (Hutchins 1995). In these origination mechanisms, including thinking along, a particular distribution of cognitive labor is realized. The temporary distribution of the cognitive labor over more people, for example during an interactive presentation, improves creativity and reliability (probably in an efficient way). Finally this study indicated that the value of this form of integrated cognitive work is not limited to cases in which a need for task integration exists. That suggests that the focus on the integration of knowledge and cognition is a valuable addition to the traditional orientation on the integration of tasks and not just a semantical shift. The research results provide a new explanation for the specific value of personal communication. Existing explanations include that some information cannot be found in published sources or databases (Holland et al. 1976), that personal communication is a richer communication medium (Daft and Lengel 1986) and that personal communication enables the transfer of tacit knowledge (Nonaka 1994). This study suggests that personal communication enables those origination mechanisms in which content is selected or developed by ego with an orientation at a problem of alter or a shared problem. Enabled by the application of knowledge, these origination mechanisms yield effective and efficient contributions to research practices. Finally, it can be concluded that technical communication is a heterogeneous, active and integral part of industrial research practices. These characteristics are insufficiently captured by interpretations of technical communication as information transfer or knowledge transfer.
Marine ecosystems are facing difficult times as climate change and heavy exploitation lead to biodiversity loss, the need of advanced ecosystem services, and deliberate adjustments especially in the food production industry. Cod (Gadus morhua L.), as one of the most important species for human consumption worldwide, is the focus of the presented study along with herring (Clupea harengus L.) and sprat (Sprattus sprattus L.) in the Baltic, as the species' recruitment success oscillate according to environmental changes. The present study consists of three chapters that deal with the question of environmental and intrinsic indicators underlying recruitment success in marine fish species. Apart from Eastern Baltic (EB) (Chapter II) and Atlantic cod (Chapter IV), Baltic herring (Clupea harengus L.) and sprat (Sprattus sprattus L.) (Chapter III) were species examined in this study. The overall idea of the presented approach is to find, besides fishing pressure, key indicators per species, area and period of factors, that fundamentally affect recruitment success. In Chapters II and III, environmental indicators connected with recruitment success were obtained through a simple linear regression approach that can be applied in an easy and timesaving manner in other contexts. From these indicators, individual threshold values are derived by means of a 5-fold crossvalidation approach, that define the barrier between a "good" and "bad" recruitment environment for the analyzed species. As the response variable to recruitment success, the recruitment residuals (RecRes) gained from the recruitment – spawning stock biomass (SSB) relationship were used. By subtracting the threshold value of an environmental indicator, the degree of how "good" and how "bad" recruitment environment was in certain years was assessed. The standard deviation of the crossvalidation method serves as a range of uncertainty, where "good" and "bad" becomes neutral and hence gives more space for natural variability regarding recruitment success. In Chapter II, the main indicators found for EB cod were the depth of the 11 psu isohaline as well as the reproductive volume (RV) (water body [km³], that measures more than 11 psu and oxygen content exceeds 2 ml / l and therefore provides optimal condition for cod egg development) in the central Baltic and in the Gotland Basin. Derived indicators and their correspondent thresholds for EB cod indicate, that abiotic factors seem to be the main drivers affecting Baltic cod recruitment success, as ideal conditions for successful egg development and survival are the most important mechanisms influencing year class strength. The depth of the isohaline was considered to be the most important indicator as it showed the strongest correlation with recruitment. Therefore, it was used for the evaluation of the RecRes as a good measure of response to recruitment and for possible forecast scenarios. Chapter III is an evaluation paper of the method applied in Chapter II. Here, the same approach was conducted within the same area (Subdivisions of Central Baltic) but for different species (sprat and herring). Key indicators for sprat were found to be the depth at 11 psu isohaline in the Bornholm and Gotland Basin, cod recruitment, as well as temperature in the reproductive volume of the Bornholm Basin and prey abundance (Bosmina spp.) in summer. For the evaluation of the RecRes, depth of the 11 psu isohaline (Bornholm Basin) was used. For herring, the main indicators affecting recruitment were found to be Acartia spp. abundance in summer, the depth of the 11 psu isohaline in the Bornholm Basin, as well as cod SSB. Prey abundance (Pseudocalanus spp.) as well as the depth of the 11 psu isohaline in the central Baltic also showed a correlation with herring recruitment but were not used for further analysis as the standard deviation was high. In contrast to Chapter II, biotic factors were also found to affect recruitment success of the clupeid stocks in the Baltic. The method used to derive a suitable set of environmental indicators and their corresponding thresholds per species in both chapters generates the opportunity to use indicators selected for predictive scenarios (i.e. future recruitment success) if underlying mechanisms are well understood and always with the understanding in mind, that systems are continuously changing. Also, revealed recruitment mechanisms could be falsified due to the lack of independence between SSB and recruitment data (i.e. autocorrelation) and therefore must be handled very carefully if implemented in a management context. In Chapter IV the focus was put on physiological, and therefore, intrinsic indicators responsible for recruitment success. Here, the parental contribution to the successful offspring was investigated in an extensive laboratory set up. Intrinsic indicators affecting Atlantic cod recruitment success were found to be egg size (amount of yolk) and fitness of mothers (Fulton's condition factor K) that contributed significantly to decreasing mortality rate in the early life stage of Atlantic cod. The results of Chapter IV indicate that there are more mechanisms driving recruitment success other than field observations and data gained from assessment models, as the indicators found are of intrinsic and genetic nature (i.e. yolk supply, body size, fitness). An obvious conclusion could be stated, that it may be better to estimate recruitment success using length-/weight-at age data of females as female size and fitness contribute significantly to recruitment success. Findings serve as an enhancement to the indicators found in the previous chapters, as well as a cautionary reminder to handle data holistically, if predictions derived from this are to be reliable. ; Marine Ökosysteme sind weltweit schweren Zeiten ausgesetzt, denn durch klimatische Veränderungen und übermäßige Ausbeute kommt es allerorts zur Verringerung der Artenvielfalt, und die Notwenigkeit für sorgfältig durchdachte Ökosystemleistungen und Nahrungsproduktionen wird dringender. Einer der global bedeutendsten Nahrungsfische stellt der Dorsch/Kabeljau (Gadus morhua L.) dar, welcher zusammen mit Hering (Clupea harengus L.) und Sprotte (Sprattus sprattus L.) im Fokus der vorliegenden Arbeit steht, da der Erfolg der Anzahl der Nachkommen als Antwort auf Umweltveränderungen verstanden werden kann. Die vorliegende Arbeit besteht aus drei Kapiteln, welche sich mit der Frage nach den inneren und äußeren Einflüssen beschäftigt, welche im Zusammenhang mit dem Rekrutierungserfolg mariner Fischpopulationen beschäftigt. Äußere Einflüsse sind durch die Umwelt bedingt und können biotischer (z.B. Nahrungsverfügbarkeit, Räuberaufkommen) oder abiotischer (z.B. Salzgehalt, Temperatur) Natur sein. Innere Faktoren beziehen sich auf die Gesundheit und die genetischen Voraussetzungen der Population oder, im kleineren Zusammenhang, der Elterntiere. In den Kapiteln II und III wurden umweltbedingte Indikatoren, welche in unmittelbaren Zusammenhang mit dem Rekrutierungserfolg stehen, anhand von einfachen linearen Modellen erster und zweiter Ordnung berechnet. Diese Methode kann sehr einfach und zeitsparend in anderen Zusammenhängen mit entsprechenden Daten angewandt werden. Als Resonanzgröße auf die Rekrutierung wurden die Residuen aus dem Verhältnis von Rekruten- und Laicherbiomasse genutzt und als RecRes bezeichnet. Durch die Subtraktion der Grenzwerte von den identifizierten Indikatoren, wurde der jährliche Wert der "guten" oder "schlechten" Rekrutierungsvoraussetzung ermittelt. Die Standardabweichung der Vergleichsprüfung definiert einen Raum, in welchem "gut" und "schlecht" neutralisiert werden und so Möglichkeit für natürliche Schwankungen im Rekrutierungserfolg bieten. Die Hauptindikatoren für den Dorsch in Kapitel II waren sowohl die Tiefe der 11 psu Isohaline, als auch die Größe des 'Reproduktiven Volumen' (Wasserkörper [km³], welcher eine höhere Salzkonzentration als 11 psu aufweist und eine Sauerstoffkonzentration von über 2 ml / l misst. Die gefundenen Indikatoren wurde auch für die Evaluation der RecRes genutzt, um zu prüfen, ob sich die RecRes als Resonanzgröße für mögliche Vorhersagen eignen. Die in diesem Kapitel abgeleiteten Indikatoren und ihre entsprechenden Schwellenwerte für EB Dorsch weisen darauf hin, dass abiotische Faktoren die Hauptfaktoren für den Rekrutierungserfolg von Dorsch im Baltikum zu sein scheinen, da ideale Bedingungen für eine erfolgreiche Entwicklung und das Überleben der Eier die wichtigsten Mechanismen sind, die die Stärke der Jahresklasse beeinflussen. Im Kapitel III wurden die gleichen Methoden angewendet, allerdings wurde nun der Rekrutierungserfolg von Hering und Sprotte untersucht. Die Hauptindikatoren für die Sprottenpopulation waren hier ebenfalls die Tiefe der 11 psu Isohalinen im Bornholm und im Gotland Becken, die Größe des Rekrutierungserfolges des Dorsches, die Temperatur im 'Reproductive Volume' und die Nahrungsabundanz von Bosmina sp. im Sommer. Für die Evaluierung der RecRes wurde der stärkste Indikator, die Tiefe der 11 psu Isohalinen (Bornholm Becken) genutzt. Die Hauptindikatoren die das Rekruitment der Heringspopulation in der Zentralen Ostsee beeinflussen waren die Nahrungsabundanz (Acartia sp.) im Sommer, die Tiefe der 11 psu Isohalinen (Bornholm Becken) sowie die die Größe der geschlechtsreifen Dorschpopulation. Im Gegensatz zu Kapitel II zeigten sich hier auch biotische Faktoren, die den Rekrutierungserfolg der Bestände der Clupeiden beeinflussten. Die angewendete Methode zur Identifikation geeigneter Umweltindikatoren und ihrer entsprechenden Grenzwerte pro Art in beiden Kapiteln bietet die Möglichkeit, Indikatoren zu verwenden, die für Vorhersageszenarien (z.B. künftige Rekrutierungserfolge) ausgewählt werden können, wenn zugrundeliegende Dynamiken eines Systems gut verstanden und stets im Auge behalten werden. Außerdem kann die hier verwendete Testvariabel (RecRes) aufgrund der mangelnden Unabhängigkeit zwischen Laicherbestand (SSB) und Rekrutierungsabschätzung durch z.B. Autokorrelation verfälscht sein und muss daher sehr sorgfältig gehandhabt werden, wenn sie in einem Managementkontext implementiert werden soll. In Kapitel IV wurde der Fokus auf die intrinsischen Indikatoren gelegt, die zu einem erfolgreichen Rekruitment führen. In diesem Kapitel wurde der elterliche Beitrag zu einer erfolgreichen Nachkommenschaft in einem umfangreichen laboratorischen Experiment erforscht. Die intrinsischen Indikatoren, die den Rekrutierungserfolg des atlantischen Kabeljaus am meisten beeinflussen waren in dieser Studie Eiergröße und somit der Gehalt an Dotter, sowie die Gesundheit der Mutter. Hier liegt der Rückschluss nahe, dass für die Abschätzung des Rekrutierungserfolges auch die Längen-Gewichtsbeziehungen der Weibchen in Betracht gezogen werden sollten, da diese Merkmale maßgeblich zu dem Rekrutierungserfolg beitragen. Die Ergebnisse dienen als Erweiterung der Indikatoren aus den vorherigen Kapiteln und sollen daran erinnern, dass Daten jeglicher Art mit Vorsicht bearbeitet werden sollen, um nicht voreilige Rückschlüssen (z.B. Vorhersagen) zu ziehen, da nicht jede Dynamik der natürlichen Umstände in jedem Datensatz wiedergegeben ist.
Sustainable development and the protection of the environment are key issues in our society today. The building stock in Europe accounts for over 40% of the final energy consumption, CO2 emissions and generation of waste. A large part of the life cycle performance is determined early. Investigations show that when 1% of the project costs are spent, roughly 70% of the lifecycle cost of the building has been committed indicating that decisions taken early greatly affect the life cycle performance. The building's shape, selected materials, structural system, internal room distribution, and building services systems are some of the most important factors that influence the environmental and energy performance of a building throughout its lifecycle.The objective of the conducted research was to investigate what kind of energy analyses are possible to carry out in the early design phase to give the decision makers a more holistic view of the energy performance of a building over its life cycle. Three research questions have guided the research work; (1) What types of energy simulations are possible to make in the early design phase? (2) How reliable are early energy estimations compared to results when detailed models are available? (3) How does energy consumption affect the life cycle cost of a building?The research work is based on literature reviews, a theoretical framework for model based design of life cycle aspects in general and energy performance in particular developed in the European Union sixth framework project InPro. The study includes a number of energy performance calculations at different levels of information maturity in the early design phase. Different energy simulation programs were used for this purpose. The study was performed for an existing building where design parameters like window area, building envelope and indoor climate been changed. In total 28 cases were analysed using four different energy analysis tools at three levels of information maturity. The resulting life cycle costs were also estimated for the different cases with varying rates of interest and forecasts of the energy price. The result of this study shows that energy calculations usable for design decision can be made at different levels of information maturity. Depending on the maturity level more or less detailed design information is available which influences the estimated energy consumption. Therefore early estimations when the information maturity is low should only be used to compare different design alternatives at the same design stage. However, the result shows that these early estimations can give a clear tendency guiding the design in a more energy efficient direction. When the information maturity is higher and indoor climate simulations are possible to make at room level, the result gets more accurate. However, the use of more sophisticated energy simulations tools is time consuming and error prone since the amount of input data needed is much higher. This calls for better integration between the design and energy analysis especially when more advanced energy simulations are performed. The resulting life cycle costs of the different cases are strongly affected by the estimated energy consumption, the selected real rate of interest, the forecast of energy prices as well as the discount time.The conclusion of this study is that energy calculations are usable for the decision making of design alternatives in the early design phase. Also, life cycle cost estimates can support the decision makers in the analysis of different financial scenarios. ; Godkänd; 2009; 20090505 (jutsch); LICENTIATSEMINARIUM Ämnesområde: Produktionsledning/Construction Engineering and Management Examinator: Professor Thomas Olofsson, Luleå tekniska universitet Tid: Torsdag den 4 juni 2009 kl 13.00 Plats: F 1031, Luleå tekniska universitet
Loet Leydesdorff on the Triple Helix: How Synergies in University-Industry-Government Relations can Shape Innovation Systems
This is the sixth and last in a series of Talks dedicated to the technopolitics of International Relations, linked to the forthcoming double volume 'The Global Politics of Science and Technology' edited by Maximilian Mayer, Mariana Carpes, and Ruth Knoblich
The relationship between technological innovation processes and the nation state remains a challenge for the discipline of International Relations. Non-linear and multi-directional characteristics of knowledge production, and the diffusive nature of knowledge itself, limit the general ability of governments to influence and steer innovation processes. Loet Leydesdorff advances the framework of the "Triple Helix" that disaggregates national innovation systems into evolving university-industry-government eco-systems. In this Talk, amongst others, he shows that these eco-systems can be expected to generate niches with synergy at all scales, and emphasizes that, though politics are always involved, synergies develop unintentionally.
Print version of this Talk (pdf)
What is the most relevant aspect of the dynamics of innovation for the discipline of International Relations?
The main challenge is to endogenize the notions of technological progress and technological development into theorizing about political economies and nation states. The endogenization of technological innovation and technological development was first placed on the research agenda of economics by evolutionary economists like Nelson and Winter in the late 1970s and early 1980s. In this context, the question was how to endogenize the dynamics of knowledge, organized knowledge, science and technology into economic theorizing. However, one can equally well formulate the problem of how to reflect on the global (sub)dynamics of organized knowledge production in political theory and International Relations.
From a longer-term perspective, one can consider that the nation states – the national or political economies in Europe – were shaped in the 19th century, somewhat later for Germany (after 1871), but for most countries it was during the first half of the 19th century. This was after the French and American Revolutions and in relation to industrialization. These nation states were able to develop an institutional framework for organizing the market as a wealth-generating mechanism, while the institutional framework permitted them to retain wealth, to regulate market forces, and also to steer them to a certain extent. However, the market is not only a local dynamics; it is also a global phenomenon.
Nowadays, another global dynamics is involved: science and technology add a dynamics different from that of the market. The market is an equilibrium-seeking mechanism at each moment of time. The evolutionary dynamics of science and technology nowadays adds a non-equilibrium-seeking dynamics over time on top of that, and this puts the nation state in a very different position. Combining an equilibrium-seeking dynamics at each moment of time with a non-equilibrium seeking one over time results in a complex adaptive dynamics, or an eco-dynamics, or however you want to call it – these are different words for approximately the same thing.
For the nation state, the question arises of how it relates to the global market dynamics on the one side, and the global dynamics of knowledge and innovation on the other. Thus, the nation state has to combine two tasks. I illustrated this model of three subdynamics with a figure in my 2006 book entitled The Knowledge-Based Economy: Modeled, measured, simulated (see image). The figure shows that first-order interactions generate a knowledge-based economy as a next-order or global regime on top of the localized trajectories of nation states and innovative firms. These complex dynamics have first to be specified and then to be analyzed empirically.
For example, the knowledge-based dynamics change the relation between government and the economy; and they consequently change the position of the state in relation to wealth-retaining mechanisms. How can the nation state be organized in such a way as to retain wealth from knowledge locally, while knowledge (like capital) tends to travel beyond boundaries? One can envisage the complex system dynamics as a kind of cloud – a cloud that touches the ground at certain places, as Harald Bathelt, for example, formulated.
How can national governments shape conditions for the cloud to touch and to remain on the ground? The Triple Helix of University-Industry-Government Relations can be considered as an eco-system of bi- and tri-lateral relations. The three institutions and their interrelations can be expected to form a system carrying the three functions of (i) novelty production, (ii) wealth generation, and (iii) normative control. One tends to think of university-industry-government relations first as neo-corporatist arrangements between these institutional partners. However, I am interested in the ecosystem shaped through the tri- and bilateral relationships.
This ecosystem can be shaped at different levels. It can be a regional ecosystem or a national ecosystem, for instance. One can ask whether there is a surplus of synergy between the three (sub-)dynamics of university-industry-government relations and where that synergy can generate wealth, knowledge, and control; in which places, and along trajectories for which periods of time – that is, the same synergy as meant by "a cloud touching the ground".
For example, when studying Piedmont as a region in Northern Italy, it is questionable whether the synergy in university-industry-government relations is optimal at this regional level or should better be examined from a larger perspective that includes Lombardy. On the one hand, the administrative borders of nations and regions result from the construction of political economies in the 19th century; but on the other hand, the niches of synergy that can be expected in a knowledge-based economy are bordered also; for example, in terms of metropolitan regions (e.g., Milan–Turin–Genoa).
Since political dynamics are always involved, this has implications for International Relations as a field of study. But the dynamic analysis is different from comparative statics (that is, measurement at different moments of time). The knowledge dynamics can travel and be "footloose" to use the words of Raymond Vernon, although it leaves footprints behind. Grasping "wealth from knowledge" (locally or regionally) requires taking a systems perspective. However, the system is not "given"; the system remains under reconstruction and can thus be articulated only as a theoretically informed hypothesis.
In the social sciences, one can use the concept of a hypothesized system heuristically. For example, when analyzing the knowledge-based economy in Germany, one can ask whether more synergy can be explained when looking at the level of the whole country (e.g., in terms of the East-West or North-South divide) or at the level of Germany's Federal States? What is the surplus of the nation or at the European level? How can one provide political decision-making with the required variety to operate as a control mechanism on the complex dynamics of these eco-systems?
A complex system can be expected to generate niches with synergy at all scales, but as unintended consequences. To what extent and for which time span can these effects be anticipated and then perhaps be facilitated? At this point, Luhmann's theory comes in because he has this notion of different codifications of communication, which then, at a next-order level, begin to self-organize when symbolically generalized.
Codes are constructed bottom-up, but what is constructed bottom-up may thereafter begin to control top-down. Thus, one should articulate reflexively the selection mechanisms that are constructed from the bottom-up variation by specifying the why as an hypothesis. What are the selection mechanisms? Observable relations (such as university-industry relations) are not neutral, but mean different things for the economy and for the state; and this meaning of the observable relations can be evaluated in terms of the codes of communication.
Against Niklas Luhmann's model, I would argue that codes of communication can be translated into one another since interhuman communications are not operationally closed, as in the biological model of autopoiesis. One also needs a social-scientific perspective on the fluidities ("overflows") and translations among functions, as emphasized, for example, by French scholars such as Michel Callon and Bruno Latour. In evolutionary economics, one distinguishes between market and non-market selection environments, but not among selection environments that are differently codified. Here, Luhmann's theory offers us a heuristic: The complex system of communications tends to differentiate in terms of the symbolic generalizations of codes of communication because this differentiation is functional in allowing the system to process more complexity and thus to be more innovative. The more orthogonal the codes, the more options for translations among them. The synergy indicator measures these options as redundancy. The selection environments, however, have to be specified historically because these redundancies—other possibilities—are not given but rather constructed over long periods of time.
How did you arrive where you currently work on?
I became interested in the relations between science, technology, and society as an undergraduate (in biochemistry) which coincided with the time of the student movement of the late 1960s. We began to study Jürgen Habermas in the framework of the "critical university," and I decided to continue with a second degree in philosophy. After the discussions between Luhmann and Habermas (1971), I recognized the advantages of Luhmann's more empirically oriented systems approach and I pursued my Ph.D. in the sociology of organization and labour.
In the meantime, we got the opportunity to organize an interfaculty department for Science and Technology Dynamics at the University of Amsterdam after a competition for a large government grant. In the context of this department, I became interested in methodology: how can one compare across case studies and make inferences? Actually, my 1995 book The Challenge of Scientometrics had a kind of Triple-Helix model on the cover: How do cognitions, texts, and authors exhibit different dynamics that influence one another?
For example, when an author publishes a paper in a scholarly journal, this may add to his reputation as an author, but the knowledge claimed in the text enters a process of validation which can be much more global and anonymous. These processes are mediated since they are based on communication. Thus, one can add to the context of discovery (of authors) and the context of justification (of knowledge contents) a context of mediation (in texts). The status of a journal, for example, matters for the communication of the knowledge content in the article. The contexts operate as selection environments upon one another.
In evolutionary economics, one is used to distinguishing between market and non-market selection environments, but not among more selection environments that are differently codified. At this point, Luhmann's theory offers a new perspective: The complex system of communications tends to differentiate in terms of the symbolic generalization of codes of communication because this differentiation among the codes of communication allows the system to process more complexity and to be more innovative in terms of possible translations. The different selection environments for communications, however, are not given but constructed historically over long periods of time. The modern (standardized) format of the citation, for example, was constructed at the end of the 19th century, but it took until the 1950s before the idea of a citation index was formulated (by Eugene Garfield). The use of citations in evaluative bibliometrics is even more recent.
In evolutionary economics, one distinguishes furthermore between (technological) trajectories and regimes. Trajectories can result from "mutual shaping" between two selection environments, for example, markets and technologies. Nations and firms follow trajectories in a landscape. Regimes are global and require the specification of three (or more) selection environments. When three (or more) dynamics interact, symmetry can be broken and one can expect feed-forward and feedback loops. Such a system can begin to flourish auto-catalytically when the configuration is optimal.
From such considerations, that is, a confluence of the neo-institutional program of Henry Etzkowitz and my neo-evolutionary view, our Triple Helix model emerged in 1994: how do institutions and functions interrelate and change one another or, in other words, provide options for innovation? Under what conditions can university-industry-government relations lead to wealth generation and organized knowledge production? The starting point was a workshop about Evolutionary Economics and Chaos Theory: New directions for technology studies held in Amsterdam in 1993. Henry suggested thereafter that we could collaborate further on university-industry relations. I answered that I needed at least three (sub)dynamics from the perspective of my research program, and then we agreed about "A Triple Helix of University-Industry-Government Relations". Years later, however, we took our two lines of research apart again, and in 2002 I began developing a Triple-Helix indicator of synergy in a series of studies of national systems of innovation.
What would you give as advice to students who would like to get into the field of innovation and global politics?
In general, I would advise them to be both a specialist and broader than that. Innovation involves crossing established borders. Learn at least two languages. If your background is political science, then take a minor in science & technology studies or in economics. One needs both the specialist profile and the potential to reach out to other audiences by being aware of the need to make translations between different frameworks. Learn to be reflexive about the status of what one can say in one or the other framework.
For example, I learned to avoid the formulation of grandiose statements such as "modern economies are knowledge-based economies," and to say instead: "modern economies can increasingly be considered as knowledge-based economies." The latter formulation provides room for asking "to what extent," and thus one can ask for further information, indicators, and results of the measurement.
In the sociology of science, specialisms and paradigms are sometimes considered as belief systems. It seems to me that by considering scholarly discourses as systems of rationalized expectations one can make the distinction between normative and cognitive learning. Normative learning (that is, in belief systems) is slower than cognitive learning (in terms of theorized expectations) because the cognitive mode provides us with more room for experimentation: One can afford to make mistakes, since one's communication and knowledge claims remain under discussion, and not one's status as a communicator. The cognitive mode has advantages; it can be considered as the surplus that is further developed during higher education. Normative learning is slower; it dominates in the political sphere.
What does the "Triple Helix" reveal about the fragmentation of "national innovation systems"?
In 2003, colleagues from the Department of Economics and Management Studies at the Erasmus University in Rotterdam offered me firm data from the Netherlands containing these three dimensions: the economic, the geographical, and the technological dimensions in data of more than a million Dutch firms. I presented the results at the Schumpeter Society in Turin in 2004, and asked whether someone in the audience had similar data for other countries. I expected Swedish or Israeli colleagues to have this type of statistics, but someone from Germany stepped in, Michael Fritsch, and so we did the analysis for Germany. These studies were first published in Research Policy. Thereafter, we did studies on Hungary, Norway, Sweden, and recently also China and Russia.
Several conclusions arise from these studies. Using entropy statistics, the data can be decomposed along the three different dimensions. One can decompose national systems geographically into regions, but one can also decompose them in terms of the technologies involved (e.g., high-tech versus medium-tech). We were mainly relying on national data. And of course, there are limitations to the data collections. Actually, we now have international data, but this is commercial data and therefore more difficult to use reliably than governmental statistics.
For the Netherlands, we obtained the picture that would more or less be expected: Amsterdam, Rotterdam, and Eindhoven are the most knowledge-intensive and knowledge-based regions. This is not surprising, although there was one surprise: We know that in terms of knowledge bases, Amsterdam is connected to Utrecht and then the geography goes a bit to the east in the direction of Wageningen. What we did not know was that the niche also spreads to the north in the direction of Zwolle. The highways to Amsterdam Airport (Schiphol) are probably the most important.
In the case of Germany, when we first analyzed the data at the level of the "Laender" (Federal States), we could see the East-West divide still prevailing, but when we repeated the analysis at the lower level of the "Regierungsbezirke" we no longer found the East-West divide as dominant (using 2004 data). So, the environment of Dresden for example was more synergetic in Triple-Helix terms than that of Saarbruecken. And this was nice to see considering my idea that the knowledge-based economy increasingly prevails since the fall of the Berlin Wall and the demise of the Soviet Union. The discussion about two different models for organizing the political economy—communism or liberal democracy—had become obsolete after 1990.
After studying Germany, I worked with Balázs Lengyel on Hungarian data. Originally, we could not find any regularity in the Hungarian data, but then the idea arose to analyze the Hungarian data as three different innovation systems: one around Budapest, which is a metropolitan innovation system; one in the west of the country, which has been incorporated into Western Europe; and one in the east of the country, which has remained the old innovation system that is state-led and dependent on subsidies. For the western part, one could say that Hungary has been "europeanized" by Austria and Germany; it has become part of a European system.
When Hungary came into the position to create a national innovation system, free from Russia and the Comecon, it was too late, as Europeanization had already stepped in and national boundaries were no longer as dominant. Accordingly, and this was a very nice result, assessing this synergy indicator on Hungary as a nation, we did not find additional synergy at the national (that is, above-regional) level. While we clearly found synergy at the national level for the Netherlands and also found it in Germany, but at the level of the Federal States, we could not find synergy at a national level for Hungary. Hungary has probably developed too late to develop a nationally controlled system of innovations.
A similar phenomenon appeared when we studied Norway: my Norwegian colleague (Øivind Strand) did most of our analysis there. To our surprise, the knowledge-based economy was not generated where the universities are located (Oslo and Trondheim), but on the West Coast, where the off-shore, marine and maritime industries are most dominant. FDI (foreign direct investment) in the marine and maritime industries leads to knowledge-based synergy in the regions on the West Shore of Norway. Norway is still a national system, but the Norwegian universities like Trondheim or Oslo are not so much involved in entrepreneurial networks. These are traditional universities, which tend to keep their hands off the economy.
Actually, when we had discussions about these two cases, Norway and Hungary, which both show that internationalization had become a major factor, either in the form of Europeanization in the Hungarian case, or in the form of foreign-driven investments (off-shore industry and oil companies) in the Norwegian case, I became uncertain and asked myself whether we did not believe too much in our indicators? Therefore, I proposed to Øivind to study Sweden, given the availability of well-organized data of this national system.
We expected to find synergy concentrated in the three regional systems of Stockholm, Gothenburg, and Malmö/Lund. Indeed, 48.5 percent of the Swedish synergy is created in these three regions. This is more than one would expect on the basis of the literature. Some colleagues were upset, because they had already started trying to work on new developments of the Triple Helix, for example, in Linköping. But the Swedish economy is organized and centralized in this geographical dimension. Perhaps that is why one talks so much about "regionalization" in policy documents. Sweden is very much a national innovation system, with additional synergy between the regions.
Can governments alter historical trajectories of national, regional or local innovation systems?
Let me mention the empirical results for China in order to illustrate the implications of empirical conclusions for policy options. We had no Chinese data set, but we obtained access to the database Orbis of the Bureau van Dijk (an international company, which is Wall Street oriented, assembling data about companies) that contains industry indicators such as names, addresses, NACE-codes, types of technology, the sizes of each enterprise, etc. However, this data can be very incomplete. Using this incomplete data for China, we said that we were just going to show how one could do the analysis if one had full data. We guess that the National Bureau of Statistics of China has complete data. I did the analysis with Ping Zhou, Professor at Zhejiang University.
We analyzed China first at the provincial level, and as expected, the East Coast emerged as much more knowledge intense than the rest of the country. After that, we also looked at the next-lower level of the 339 prefectures of China. From this analysis, four of them popped up as far more synergetic than the others. These four municipalities were: Beijing, Shanghai, Tianjin, and Chongqing.
These four municipalities became clearly visible as an order of magnitude more synergetic than other regions. The special characteristic about them is that –as against the others – these four municipalities are administered by the central government. Actually, it came out of my data and I did not understand it; but my Chinese colleague said that this result was very nice and specified this relationship.
The Chinese case thus illustrates that government control can make a difference. It shows – and that is not surprising, as China runs on a different model – that the government is able to organize the four municipalities in such a way as to increase synergy. Of course, I do not know what is happening on the ground. We know that the Chinese system is more complex than these three dimensions suggest. I guess the government agencies may wish to consider the option of extending the success of this development model, to Guangdong for example or to other parts of China. Isn't it worrisome that all the other and less controlled districts have not been as successful in generating synergy?
Referring more generally to innovation policies, I would advise as a heuristics that political discourse is able to signal a problem, but policy questions do not enable us to analyze the issues. Regional development, for example, is an issue in Sweden because the system is very centralized, more than in Norway, for example. But there is nothing in our data that supports the claim that the Swedish government is successful in decentralizing the knowledge-based economy beyond the three metropolitan regions. We may be able to reach conclusions like these serving as policy advice. One develops policies on the basis of intuitive assumptions which a researcher is sometimes able to test.
As noted, one can expect a complex system continuously to produce unintended consequences, and thus it needs monitoring. The dynamics of the system are different from the sum of the sub-dynamics because of the interaction effects and feedback loops. Metaphors such as a Triple Helix, Mode-2, or the Risk Society can be stimulating for the discourse, but these metaphors tend to develop their own dynamics of proliferating discourses.
The Triple Helix, for example, can first be considered as a call for collaboration in networks of institutions. However, in an ecosystem of bi-lateral and tri-lateral relations, one has a trade-off between local integration (collaboration) and global differentiation (competition). The markets and the sciences develop at the global level, above the level of specific relations. A principal agent such as government may be locked into a suboptimum. Institutional reform that frees the other two dynamics (markets and sciences) requires translation of political legitimation into other codes of communication. Translations among codes of communication provide the innovation engine.
Is there a connection between infrastructures and the success of innovation processes?
One of the conclusions, which pervades throughout all advanced economies, is that knowledge intensive services (KIS) are not synergetic locally because they can be disconnected – uncoupled – from the location. For example, if one offers a knowledge-intensive service in Munich and receives a phone call from Hamburg, the next step is to take a plane to Hamburg, or to catch a train inside Germany perhaps. Thus, it does not matter whether one is located in Munich or Hamburg as knowledge-intensive services uncouple from the local economy. The main point is proximity to an airport or train station.
This is also the case for high-tech knowledge-based manufacturing. But it is different for medium-tech manufacturing, because in this case the dynamics are more embedded in the other parts of the economy. If one looks at Russia, the knowledge-intensive services operate differently from the Western European model, where the phenomenon of uncoupling takes place. In Russia, KIS contribute to coupling, as knowledge-intensive services are related to state apparatuses.
In the Russian case, the knowledge-based economy is heavily concentrated in Moscow and St. Petersburg. So, if one aims –as the Russian government proclaims – to create not "wealth from knowledge" but "knowledge from wealth" – that is, oil revenues –it might be wise to uncouple the knowledge-intensive services from the state apparatuses. Of course, this is not easy to do in the Russian model because traditionally, the center (Moscow) has never done this. Uncoupling knowledge-intensive services, however, might give them a degree of freedom to move around, from Tomsk to Minsk or vice versa, steered by economic forces more than they currently are (via institutions in Moscow).
Final question. What does path-dependency mean in the context of innovation dynamics?
In The Challenge of Scientometrics. The development, measurement, and self-organization of scientific communications (1995), I used Shannon-type information theory to study scientometric problems, as this methodology combines both static and dynamic analyses. Connected to this theory I developed a measurement method for path-dependency and critical transitions.
In the case of a radio transmission, for example, you have a sender and a receiver, and in between you may have an auxiliary station. For instance, the sender is in New York and the receiver is in Bonn and the auxiliary station is in Iceland. The signal emerges in New York and travels to Bonn, but it may be possible to improve the reception by assuming the signal is from Iceland instead of listening to New York. When Iceland provides a better signal, it is possible to forget the history of the signal before it arrived in Island. It no longer matters whether Iceland obtained the signal originally from New York or Boston. One takes the signal from Iceland and the pre-history of the signal does not matter anymore for a receiver.
Such a configuration provides a path-dependency (on Iceland) in information-theoretical terms, measurable in terms of bits of information. In a certain sense you get negative bits of information, since the shortest path in the normal triangle would be from New York to Bonn, and in this case the shortest path is from New York via Iceland to Bonn. I called this at the time a critical transition. In a scientific text for instance, a new terminology can come up and if it overwrites the old terminology to the extent that one does not have to listen to the old terminology anymore, one has a critical transition that frees one from the path-dependencies at a previous moment of time.
Thus, my example is about radical and knowledge-based changes. As long as one has to listen to the past, one does not make a critical transition. The knowledge-based approach is always about creative destruction and about moving ahead, incorporating possible new options in the future. The hypothesized future states become more important than the past. The challenge, in my opinion, is to make the notion of options operational and to bring these ideas into measurement. The Triple-Helix indicator measures the number of possible options as additional redundancy. This measurement has the additional advantage that one becomes sensitive to uncertainty in the prediction.
Loet Leydesdorff is Professor Emeritus at the Amsterdam School of Communications Research (ASCoR) of the University of Amsterdam. He is Honorary Professor of the Science and Technology Policy Research Unit (SPRU) of the University of Sussex, Visiting Professor at the School of Management, Birkbeck, University of London, Visiting Professor of the Institute of Scientific and Technical Information of China (ISTIC) in Beijing, and Guest Professor at Zhejiang University in Hangzhou. He has published extensively in systems theory, social network analysis, scientometrics, and the sociology of innovation (see at http://www.leydesdorff.net/list.htm). With Henry Etzkowitz, he initiated a series of workshops, conferences, and special issues about the Triple Helix of University-Industry-Government Relations. He received the Derek de Solla Price Award for Scientometrics and Informetrics in 2003 and held "The City of Lausanne" Honor Chair at the School of Economics, Université de Lausanne, in 2005. In 2007, he was Vice-President of the 8th International Conference on Computing Anticipatory Systems (CASYS'07, Liège). In 2014, he was listed as a highly-cited author by Thomson Reuters.
Literature and Related links:
Science & Technology Dynamics, University of Amsterdam / Amsterdam School of Communications Research (ASCoR)
Leydesdorff, L. (2006). The Knowledge-Based Economy: Modeled, Measured, Simulated. Universal Publishers, Boca Raton, FL.
Leydesdorff, L. (2001). A Sociological Theory of Communication: The Self-Organization of the Knowledge-Based Society. Universal Publishers, Boca Raton, FL.
Leydesdorff, L. (1995). The Challenge of Scientometrics . The development, measurement, and self-organization of scientific communications. Leiden, DSWO Press, Leiden University.
http://www.leydesdorff.net/
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Kemiskinan di Provinsi Kalimantan Barat setiap tahunnya selalu mengalami peningkatan seiring dengan angka pendapatan asli daerah, dana alokasi umum dan pendidikan yang juga ikut meningkat. Berbagai upaya telah dilakukan pemerintah Kabupaten/Kota guna mengurangi angka kemiskinan di Provinsi Kalimantan Barat. Penelitian ini bertujuan untuk melihat seberapa besar pengaruh pendapatan asli daerah, dana alokasi umum dan pendidikan terhadap kemiskinan di Provinsi Kalimantan Barat 2013-2017. Data yang digunakan dalam penelitian ini adalah data sekunder yang di peroleh dari Badan Pusat Statistik (BPS) Provinsi Kalimantan Barat. Pengolahan data dalam penelitian ini adalah menggunakan regresi linier berganda dengan menggunakan model Fixed Effect Weight(FEW) dengan teknik Pooled Least Square. Jenis data yang digunakan yaitu data panel yang merupakan kombinasi dari data time series 5 Tahun (2013-2017) dan data cross section 14 kabupaten/kota. 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From the moment of their emergence, political parties became one of the main subjects of the formation of nations, the providers of ideas of state-building in the national format. Under the universal suffrage they are the primary mechanism for political participation. Parties articulate the values of the national community at the political level, formulate and implement the national interests. They can perform this function through the work in the state and local governments, as well as through the anti-system activities.In the era of globalization the issue of the formation of nations acquires a qualitatively new relevance. The problem of political stability in Ukraine is not so much in the field of international relations, as in the area of ethnic and national identity of its citizens. Political identity is becoming an increasingly dynamic category. In today's Ukraine the synchronization of the processes of state-building, national development and value-civilizational choice causes the widest range of identities. This creates additional opportunities for Ukraine, but at the same time brings new challenges to which society should be prepared.The purpose of this research is to determine the most important factors of political participation and activities of political parties at different stages of formation of the Ukrainian political nation, to justify the significance of their impact on this process.Since the beginning of the XX century, political parties are the determining factor of formation of the Ukrainian political nation. At different stages of historical development they proposed (and more often imposed) to the Ukrainian society one or another model of political nation. Those nation-building practices depended more on historical circumstances, rather than on ideological backgrounds of the political parties.The attempts to hyperbolize the ethnic factors of formation of the political nation and state-building inevitably lead to the internal split in Ukraine. And the length of this path inversely depends on the openness of society: in a totalitarian one any opposition is brutally suppressed, in an authoritarian one the situation escalates slowly but steadily, in a democratic one the centrifugal tendencies appear quite quickly.In different historical circumstances, the non-systemic and anti-systemic activities of political parties play an important role in the formation of the Ukrainian political nation. Nationalists, liberals, anarchists, communists, greens, autonomists – all of them take an active part in the processes of national creation, challenging, criticizing, destroying the existing state and political system.In the post-Soviet period of Ukraine's development political parties actively encouraged the formation of the Ukrainian political nation. At the same time they stabilized socio-political processes, including in the context of nation-building. The activity of political parties, mainly the leftists and left centrists, prevented possible distortions in the state-building that could exacerbate conflicts on ethnic grounds.An important factor of the formation of political nation and civil society in Ukraine is the anti-party activities. The Communist Party of the Soviet Union, Leonid Kuchma's "Parties of Power", "Orangists", the Party of Regions – all these political forces became powerful irritants of the protest moods. It's significant, that in each case the conflict went beyond the framework of political conflict and acquired existential characteristics, exacerbating the contradictions to the dilemma: "Ukrainian nation: To be or not to be".Today in Ukraine, in fact, the two doctrines of political nation are simultaneously confirmed. Each of them is formulated and implemented by a certain group of political parties. And the future of the Ukrainian political nation largely depends on whether these groups will be able to reach a compromise and develop a unified concept of nation- and state-building, that will get a consensus support in the society. ; Розглянуто участь політичних партій у формуванні української політичної нації на різних етапах цього процесу. Запропоновано авторську періодизацію участі політичних партій у процесі націєтворення. Проаналізовано механізми здійснення партійних впливів на цей процес у кожному з періодів.
The Internet started out – with the inception of ARPANET in the 1960s, followed by NSFNET in 1986 – as a government-funded academic research network interconnecting universities and research facilities. Just a few years later, the World Wide Web was invented, and the first commercial service providers emerged. During the transition phase from a research to a commercial-purpose network, most of the crucial changes to protocols, infrastructure, and governance have occurred and continue to shape the Internet today. In its current state, the Internet is a collection of tens of thousands interconnected networks which exchange traffic among each other. These heterogeneous networks, varying in size and type, are owned and operated by organizations with individual interests and goals. While some networks provide connectivity to consumers and companies, other networks focus on the distribution and delivery of content. Depending on their business model, traffic composition and volumes exchanged among these networks can vary significantly. Network operators need to understand the composition of traffic in order to meet the quality expectations of their customers. However, Internet traffic is more diverse than ever. Many different applications, including video streaming, gaming, or file-sharing, dominate the dynamic composition of traffic, while live events such as the World Cup cause major temporal variations in traffic volume. Moreover, an increasing trend towards traffic encryption makes it increasingly difficult for network operators to obtain a holistic picture of the traffic landscape. Further, the manner in which traffic is exchanged between the networks makes it increasingly hard to reason about trends in the Internet. The exchange of traffic is governed by complex business relations among ISPs, or by traffic steering policies performed by CDNs and cloud providers who take advantage of network and path diversity by peering at IXPs. Inter-domain routing and the associated traffic flow is steadily evolving. In order to keep track of developments in the Internet, it is vital to steadily revisit changes to infrastructure and policies and how they affect traffic flow. In this dissertation, we investigate the traffic flow and the underlying routing mechanisms. Specifically, we seek to gain a better understanding of heterogeneity and traffic asymmetries on inter-domain links and the global routing table growth. We dissect the composition of today's Internet traffic and the interactions of the involved parties and highlight the economic incentives that drive many of the main commercial players to deploy their servers deep within third-party networks. Further, we illuminate how hypergiants and complex business relationships impact the balance and distribution of ingress and egress in inter-domain traffic. Finally, we study the ramifications of these complexities on the global routing table growth by investigating one of the contributors to growth, namely prefix delegations, and how different parties use prefix delegations to influence path selection. Through the analysis of the Internet from multiple points of view, we observe an increasing trend towards network heterogeneity and unconventional routing, which is increasingly diverging from our notion of a hierarchical Internet. Our findings contribute to advancing a new mental model for the Internet's ecosystem that goes beyond traffic agnostic AS-graph models and can support network operators in network planning and provisioning. Last, insights in the complexities of prefix delegations shed light on current protocol limitations and can inform protocol designers in the future. ; Das Internet begann – mit der Gründung von ARPANET in den 1960er Jahren, gefolgt von NSFNET im Jahr 1986 – als staatlich finanziertes akademisches Forschungsnetz, das Universitäten und Forschungseinrichtungen miteinander verband. Wenige Jahre später wurde das World Wide Web erfunden und die ersten kommerziellen Provider entstanden. Während der Übergangsphase von einem Forschungs- zu einem kommerziellen Netzwerk fanden die meisten wesentlichen Änderungen an Protokollen, Infrastruktur und Governance statt und prägen das Internet bis heute. Das heutige Internet ist eine Ansammlung Zehntausender, miteinander verbundener Netzwerke, die untereinander Verkehr austauschen. Diese heterogenen Netzwerke unterscheiden sich in Größe und Typ, und werden von Organisationen mit individuellen Interessen und Zielen betrieben. Während einige Netzwerke Konnektivität für Verbraucher und Unternehmen bereitstellen, konzentrieren sich andere auf die Verteilung und Bereitstellung von Inhalten. Abhängig vom Geschäftsmodell, kann die Zusammensetzung und das Volumen des ausgetauschten Verkehrs erheblich variieren. Netzbetreiber müssen die Zusammensetzung des Verkehrs verstehen, um die Qualitätserwartungen ihrer Kunden zu erfüllen. Der Internetverkehr ist jedoch vielfältiger als je zuvor: Verschiedene Anwendungen, z. B. Video-Streaming, Spiele oder Filesharing, dominieren die dynamische Zusammensetzung, während Live-Ereignisse, wie die Fußballweltmeisterschaft, große temporäre Volumenschwankungen verursachen. Der Trend zur Datenverschlüsselung und die Art des Verkehrsaustauschs zwischen den Netzen, machen es zunehmend schwerer für Betreiber ein Bild der Verkehrslandschaft zu erstellen und Trends zu verstehen. Dabei wird der Verkehrsaustausch von komplexen Geschäftsbeziehungen zwischen Providern oder von Verkehrssteuerung durch CDNs und Cloud-Anbietern, die die Netzwerk- und Pfadvielfalt in IXPs ausnutzen, beeinflusst. Inter-Domain Routing, und der damit verbundene Verkehr, entwickeln sich kontinuierlich. Um Entwicklungen im Internet zu verfolgen, ist es wichtig, Änderungen an Infrastruktur und Richtlinien, und deren Auswirkungen auf den Verkehr ständig zu überprüfen. In dieser Arbeit untersuchen wir den Verkehrsfluss und die zugrundeliegenden Routing-Mechanismen. Insbesondere möchten wir ein besseres Verständnis der Heterogenität und der Verkehrsasymmetrien auf Inter-domain-Links, und des Wachstums der globalen Routing-Tabelle erlangen. Wir analysieren die Zusammensetzung des heutigen Verkehrs und die Interaktionen der beteiligten Akteure, und heben wirtschaftliche Anreize vieler kommerziell relevanter Akteure zum Einsatz von Servern in Dritt-Netzwerken hervor. Zudem beleuchten wir Auswirkungen von Hypergiants und komplexer Geschäftsbeziehungen auf die Balance und Verteilung von Ingress und Egress im Inter-Domain-Verkehr. Zum Schluss untersuchen wir die Auswirkungen dieser Komplexitäten auf das Wachstum der globalen Routing-Tabelle, indem wir einen der Wachstumsträger untersuchen, nämlich Präfixdelegationen, und wie sie von verschiedenen Akteuren verwendet werden, um die Pfadauswahl zu beeinflussen. Durch die Analyse des Internets aus mehreren Blickwinkeln beobachten wir einen ansteigenden Trend hin zu Netzheterogenität und unkonventionellem Routing, der zunehmend von unserer Vorstellung eines hierarchischen Internets abweicht. Unsere Resultate tragen zu einem neuen Denkmodell für das Internetökosystem bei, das über verkehrs-unabhängige AS-Graph-Modelle hinausgeht, und Netzbetreiber bei der Netzwerkplanung und -bereitstellung unterstützen kann. Schließlich geben Einblicke in die Komplexität von Präfixdelegationen Aufschluss über aktuelle Protokolleinschränkungen und können Protokolldesigner in der Zukunft informieren.
Background: Dengue is a mosquito-borne viral disease caused by one of four serotypes (DENV1-4). Infection provides long-term homologous immunity against reinfection with the same serotype. Plaque reduction neutralization test (PRNT) is the gold standard to assess serotype-specific antibody levels. We analysed serotype-specific antibody levels obtained by PRNT in two serological surveys conducted in Singapore in 2009 and 2013 using cluster analysis, a machine learning technique that was used to identify the most common histories of DENV exposure. Methods: We explored the use of five distinct clustering methods (i.e. agglomerative hierarchical, divisive hierarchi-cal, K-means, K-medoids and model-based clustering) with varying number (from 4 to 10) of clusters for each method. Weighted rank aggregation, an evaluating technique for a set of internal validity metrics, was adopted to determine the optimal algorithm, comprising the optimal clustering method and the optimal number of clusters. Results: The K-means algorithm with six clusters was selected as the algorithm with the highest weighted rank aggregation. The six clusters were characterised by (i) dominant DENV2 PRNT titres; (ii) co-dominant DENV1 and DENV2 titres with average DENV2 titre > average DENV1 titre; (iii) co-dominant DENV1 and DENV2 titres with average DENV1 titre > average DENV2 titre; (iv) low PRNT titres against DENV1-4; (v) intermediate PRNT titres against DENV1-4; and (vi) dominant DENV1-3 titres. Analyses of the relative size and age-stratification of the clusters by year of sample collection and the application of cluster analysis to the 2009 and 2013 datasets considered separately revealed the epidemic circulation of DENV2 and DENV3 between 2009 and 2013. Conclusion: Cluster analysis is an unsupervised machine learning technique that can be applied to analyse PRNT antibody titres (without pre-established cut-off thresholds to indicate protection) to explore common patterns of DENV infection and infer the likely history of dengue exposure in a population. ; National Environmental Agency (NEA) ; Published version ; This work is jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement and is also part of the EDCTP2 programme supported by the European Union. SS acknowledges funding from the Collaborative Project to Increase Production of Rural Doctor and Royal Thai Government Scholarship. ID also acknowledges research funding from an Imperial College Junior Research Fellowship and a Sir Henry Dale Fellowship funded by Wellcome Trust and the Royal Society [grant 213494/Z/18/Z]. NLC and TLK acknowledge support from the National Environment Agency, Singapore. The funding bodies had no role in the design of the study, analysis of the data, interpretation of the results and in the manuscript preparation.
In this study, we analyzed healthcare provision and health expenditure across six Mediterranean countries that adopt the National Health System (Beveridge model) and that form part of the European Union (EU) with the main aim being that of analyzing and comparing out-of-pocket health spending in countries with a European Mediterranean connection. To this end, we considered various economic indicators and statistics to derive commonalities and differences across these countries and also compared trends in these indicators to those observed across the rest of the EU. We then analyzed these findings in light of other data related to the quality of healthcare delivery and the infrastructure of the health system and discussed recent developments in healthcare within each country and the main challenges faced by the respective health systems. The results show that on average, Mediterranean countries spend less on total healthcare expenditure (THE) than the EU average, both as a proportion of GDP, as well as in per capita terms. This is primarily driven by lower-than-EU-average public funding of healthcare. The 2008/2009 macro-economic and financial crisis had a significant impact on the countries under review, and explains the persistent reductions in public health spending as part of the austerity measures put in force across sectors. On the flipside, Mediterranean countries have a higher presence of private health providers in total funding, thereby explaining the higher Out-of-Pocket (OOPs) health expenditures in these countries relative to the EU-average. With regard to the overall health infrastructure in these countries, we observed that although the supply of physicians is largely in line with the rest of the EU, there is under-supply when it comes to hospital beds. This may be symptomatic of lower government funding. Nonetheless, all countries score highly in the evaluation of the quality of health services, as recorded by international rankings like the WHO's 2000 metric, whereas health system performance indicators, namely mortality rates and life expectancy reveal favorable health outcomes in the Mediterranean EU countries. The findings in this paper may be seen in light of the Mediterranean region's lifestyle in terms of diet, health behavior, health beliefs and shared culture. In particular, the higher out-of-pocket expenditure may reflect the tendency for one-to-one relationships with private clinicians and the pursuit of person-centered care (1). Additionally, the Mediterranean people may not be as disciplined as their European counterparts in accessing and using the public health sector. The lower THE also reflects the fact that the Mediterranean countries are less wealthy than the more economically-advanced European countries. ; peer-reviewed
This note lays out the rationale for including land administration quality index in the standard 'registering property' indicator by doing business and discusses initial evidence from the global sample, showing that many countries, including some that have performed well on Doing Business's traditional ranking, have a long way to go to establish a system of land administration that is reliable and transparent, achieves sufficient coverage, and minimizes disputes. The cases in this brochure document that by smartly deploying new technology, countries can make progress in this direction irrespective of their initial income level. Continued monitoring and learning from experience at all levels had an important role in facilitating such progress. Doing Business will contribute to this agenda by elevating the profile of land governance, tracking countries' performance with respect to land administration quality index, and fostering global exchange and learning from good performers.
RIGHTS TO PROVIDE SOCIAL HOUSING After gaining independence, Ukraine has set out to update the legal framework in all areas of law, streamlining all spheres of society in accordance with international and European standards. At the same time, globalization processes, which have led to rapid changes in the protection of legal rights, freedoms and interests of citizens, have influenced the formation of a mechanism for the realization of the right to social housing in Ukraine. Because, in any period of humanity, housing in the life of every person has always been and remains the most basic need, which provides protection from all dangerous environmental factors and normal living conditions in general. In turn, the system of providing social housing in Ukraine has come a long and dynamic way and continues to take shape. Therefore, in order to properly understand the concept of "social housing" should consider the theoretical and practical aspects of the development of social housing in Ukraine. Despite many in-depth studies on this topic, the question of defining the concept of social housing and the procedure for providing social housing still remains quite controversial, and therefore requires more in-depth analysis, study of certain features and improvement not only theoretical basis but also consolidation of research data. at the legislative level. The purpose of the study is a general analysis of the content of the administrative and legal understanding of social housing, as well as the study of international standards for improving the institution of social housing in Ukraine in order to develop proposals for improving the latter. In accordance with the set goal, the following tasks were identified: to explore the historical aspects of the establishment and development of social housing in Ukraine and European countries; to establish a common legal understanding of social housing in accordance with the legislation of Ukraine; to analyze the legal framework for regulating the provision and use of social housing in Ukraine; to analyze the main ways to protect the right of citizens to social housing, etc. ; Після здобуття незалежності, Україна взяла напрямок на оновлення законодавчого базису в усіх галузях права, впорядковуючи всі сфери життєдіяльності суспільства відповідно до міжнародних та європейських стандартів. Водночас, глобалізаційні процеси, які спричинили стрімкі зміни у захисті законних прав, свобод та інтересів громадянина, вплинули на формування механізму щодо реалізації права на соціальне житло в Україні. Оскільки, в будь-який період людства, житло в житті кожної людини завжди було і залишається найголовнішою базовою потребою, що забезпечує захист від всіх небезпечних факторів навколишнього середовища і нормальні умови існування в цілому. В свою чергу, система надання соціального житла в Україні пройшла доволі довгий та динамічний шлях та й надалі продовжує формуватися. Тому, задля правильного розуміння поняття «соціальне житло» слід розглянути теоретичний та практичний аспекти розвитку сфери надання соціального житла в Україні. Незважаючи на безліч ґрунтовних досліджень з даної тематики, питання щодо визначення поняття соціального житла та питання щодо процедури надання соціального житла й понині залишається доволі дискусійним, а тому потребує більш глибокого аналізу, вивчення певних особливостей та удосконалення не тільки теоретичного базису, а й закріплення даних досліджень на законодавчому рівні. Метою дослідження є загальний аналіз змісту адміністративно-правового розуміння соціального житла, а також вивчення міжнародних стандартів вдосконалення інституту соціального жила в Україні з метою вироблення пропозицій щодо вдосконалення останнього. Відповідно до поставленої мети, були визначені наступні завдання: дослідити історичні аспекти встановлення та розвитку сфери соціального житла в Україні та європейських країнах; встановити загальноправове розуміння соціального житла відповідно до законодавства України; проаналізувати нормативно-правові основи регулювання сфери надання та користування соціальним житлом в Україні; проаналізувати основні способи захисту права громадян на забезпечення соціальним житлом тощо.
Increased environmental concern and favorable government policies in the recent years have resulted in rapid growth of Renewable Energy Sources (RESs), such as Solar Photovoltaics (PVs) and Wind Turbine Generators. Despite creating several benefits, the high integration of the RESs in an electrical network imposes potential problems. In particular, limited dispatchability of the RESs on top of intermittent generation is creating key scientific challenges to the research community. On the other hand, increased trends of electrifying heating, transportation and gas sectors have resulted in new electrical loads, such as Electric Vehicles (EVs), Heat Pumps (HPs), and Electric Water Heaters (EWH), in the distribution network. In addition to the increase in power demand, those loads create high, rapid and random fluctuations in the demand, thereby impacting the power balancing scenario negatively. Conventional solutions to address the aforementioned issues include building excess generation or grid scale storage to compensate the power imbalances resulting from intermittent generations and fluctuating demands. Even though those approaches perform technically well, they are capital intensive to be implemented with the existing technology. One of the potential alternatives is to intelligently control the electrical loads to make them follow the intermittent generation. This not only enables the end consumers to get reliable and cheap electricity but also enables the utility to prevent huge investment in counterpart. Therefore, the theoretical foundation of this research work is based on a paradigm shift in 'generation following demand' to 'demand following generation' scenario. The primary aim of this research work is to develop intelligent control architecture, control strategies, and an adaptive protection methodology to ensure efficient control and operation of the future distribution networks. The major scientific challenge is thus to develop control models and strategies to coordinate responses from widely distributed controllable loads and local generations. Detailed models of key Smart Grid (SG) elements particularly distribution network, controllable loads, namely EV, HP, and EWH, and local generation, namely PV, are developed. The outcome of the projects is demonstrated mostly by simulations and partly by laboratory setups. The research outcome will not only serve as a reference for ongoing research in this direction but also benefit distribution system operators in the planning and development of the distribution network. The major contributions of this work are described in the following four stages: In the first stage, an intelligent Demand Response (DR) control architecture is developed for coordinating the key SG actors, namely consumers, network operators, aggregators, and electricity market entities. A key intent of the architecture is to facilitate market participation of residential consumers and prosumers. A Hierarchical Control Architecture (HCA) having primary, secondary, and tertiary control loops is developed to establish coordinated control of widely distributed loads and generations. Moreover, a heterogeneous communication network is integrated to the HCA for enabling control and communication within each control loop of the HCA. In particular, each control loop of the HCA is designed with specific control latency and time coordinated with the other loops to establish coordination among each other. The outcome of a power and communication co-simulation demonstrated that the proposed architecture effectively integrate responses from widely distributed loads and generations. Detailed models of the controllable loads, local generation, and distribution network are done in the second stage. Transportation loads, namely EV, and heating loads, namely HP and EWH, are modeled as controllable loads, whereas the solar PV is modeled as local generation. Control strategies are developed to realize various DR techniques, namely autonomous, voltage controlled, incentive based, and price based. The performance of the developed models and control strategies are demonstrated in a low voltage distribution network by utilizing the intelligent architecture developed in the first stage. Even though the developed models and control strategies are tested in a particular low voltage network, they are generic to apply to any network. The outcome from this part of the study enables to exploit demand flexibility from the consumers/prosumers for technically supporting the grid as well as for enabling to trade the flexibility in electricity markets. In the third stage, a scaled down SG testbed is developed and implemented for practical demonstration of developed DR models and control strategies. A LV test case network is scaled down to a 1 kVA testbed and is built in a laboratory. An optical fiber and TCP/IP based communication is integrated on the testbed to enable data communication and control. Moreover, a centralized and decentralized control approach is implemented for optimized EV charging coordination in the testbed. As practical demonstration of the SG is significantly lagging, the developed scaled down testbed based approach provides not only a novel approach for practical demonstration of the SG control but also a new research perspective in the SG field. More importantly, the proposed method provides an economic and riskless approach compared to the existing pilot project based SG developments. In the final stage, an adaptive overcurrent protection is developed for the future distribution system having high share of RESs and Active Network Management (ANM) activities. In the future grid, the protection is affected not only by bidirectional power flow due to RESs but also due to the ANM activities such as demand response, network reconfigurations etc. Therefore, unlike the conventional protection methodology where the protective settings are made static, an approach to adapt relay settings based on dynamic network topologies and power infeed is developed. In particular, the developed methodology integrates the protection and ANM such that the protection is ensured for every change in network operation mode and topologies. A two-stage protection strategy, whereby an offline proactive stage combined with online adaptive stage is designed to realize the intended protection approach. The proactive stage determines settings of the relays for every mode of operation using offline short circuit analysis and dispatches the settings to the respective relays. The adaptive stage in turn identifies the operating status of distributed energy resources and operating modes (grid-connected, islanded, network reconfiguration etc.) in real time to adapt/activate proper settings. The performance of the developed method is demonstrated in a medium voltage distribution network using real time digital simulator. The simulation results demonstrated that the proposed adaptive protection approach reliably discriminate the faults and establishes protection coordination in dynamic network topologies. Overall, the research outcomes provide an innovative approach to exploit demand flexibility from controllable loads and establish the integrated ANM and protection to ensure effective control and protection of the future distribution grids. This not only enables the end consumers to get reliable and cheap electricity but also enables the utility to prevent huge investment in counterpart. Moreover, distribution system operators can implement the findings of the projects in their operational stages to avoid grid bottlenecks and in the planning stages to avoid or delay the grid reinforcements.
In today's conditions, the dynamic development of countries is impossible without a comprehensive and continuous production and use of innovations as catalysts of general economic development. The article is a study of innovative positions of TNCs in developed countries of the world in conditions of global competition. As a result of the theoretical foundations' analysis of the world economy's innovative development (the theory of economic development and intellectual technology, the concept of harmonious economy and economic integration, etc.), and the basic components of this process (technological and techno-economic paradigms), it should be noted that the main goal of successful corporations, and also countries are an increase in the innovative component of the national economy. The study of innovation financing processes in leading corporations in Japan, the United States and the EU, which enabled them to analyse their innovation strategies and to identify the need for a separate financial mechanism that depends both on the product stage and on the environment (host country investment climate). The statistical data indicate that the processes of R&D's globalization and internationalization predominantly take place in a closed set of countries – the USA, Western Europe, and Japan, which concentrate the main foreign research units of TNCs. If the trend of creating new research units for TNCs in China and India continues, it is possible that these two countries will in the future become part of the "innovation core" of the world economy. The activity of TNCs in relation to the creation of research units is constrained by various factors, the main of which are: low level of intellectual property protection, imperfection of legislation that regulates the activities of such units. ; В современных условиях динамичное развитие стран невозможно без всестороннего и непрерывного продуцирования и использования инноваций в качестве катализаторов общеэкономического развития. Целью статьи является исследование инновационных позиций ТНК развитых стран мира в условиях глобальной конкуренции. В результате анализа теоретических основ инновационного развития мировой экономики (теорий экономического развития и интеллектуальной технологии, концепций гармоничного экономики и экономической интеграции и др.), а также базисных составляющих данного процесса (технологическая и технико-экономическая парадигмы) следует отметить, что главной целью успешных корпораций, а также стран является наращивание инновационной составляющей национальной экономики. Исследование процессов финансирования инноваций в ведущих корпорациях Японии, США и странах ЕС, что позволило проанализировать их инновационные стратегии и определить необходимость применения отдельного финансового механизма, который зависит как от стадии продукта, так и от окружающей среды (инвестиционного климата принимающей страны). Статистические данные свидетельствуют о том, что процессы глобализации и интернационализации НИОКР происходят в основном в замкнутой совокупности стран – в США, Западной Европе и Японии, в которых сосредоточены основные иностранные научно-исследовательские подразделения ТНК. Если тенденция создания новых исследовательских подразделений ТНК в Китае и Индии сохранится, то возможно, что эти две страны в будущем войдут в «инновационное ядро» мировой экономики. Активность ТНК относительно создания научно-исследовательских подразделений сдерживается различными факторами, основными из которых являются: низкий уровень защиты интеллектуальной собственности, несовершенство законодательства, регулирующего деятельность подобных подразделений. ; В умовах сьогодення динамічний розвиток країн є неможливим без всебічного і безперервного продукування і використання інновацій як каталізаторів загальноекономічного розвитку. Метoю статті є дослідження інноваційних позицій ТНК розвинених країн світу в умовах глобальної конкуренції. У результаті аналізу теоретичних засад інноваційного розвитку світової економіки (теорії економічного розвитку та інтелектуальної технології, концепції гармонійної економіки та економічної інтеграції та ін.) та базисних складових даного процесу (технологічна та техніко-економічна парадигми) варто зазначити, що головною ціллю успішних корпорацій, а також країн є нарощування інноваційної складової національної економіки. Дослідження процесів фінансування інновацій в провідних корпораціях Японії, США та країнах ЄС, що дало змогу проаналізувати їх інноваційні стратегії та визначити необхідність застосування окремого фінансового механізму, який залежить як від стадії продукту, так і від оточуючого середовища (інвестиційного клімату приймаючої країни). Статистичні дані свідчать про те, що процеси глобалізації і інтернаціоналізації НДДКР відбуваються в основному в замкнутій сукупності країн – в США, Західній Європі та Японії, в яких зосереджені основні іноземні науково-дослідні підрозділи ТНК. Якщо тенденція створення нових дослідницьких підрозділів ТНК в Китаї і Індії збережеться, то можливо, що ці дві країни в майбутньому увійдуть до «інноваційного ядра» світової економіки. Активність ТНК відносно створення науково-дослідних підрозділів стримується різними чинниками, основними з яких є: низький рівень захисту інтелектуальної власності, недосконалість законодавства, яке регулює діяльність подібних підрозділів.
