A Survey on Intangible Capital

This study provides a survey of topics related to intangible capital, including concepts, definitions, measurement issues, and classifications. It shows that despite the growing importance of intangible capital, we do not know enough about it and only have imperfect methods of measuring it. While at the macroeconomic level, measurement of intangibles is now available for many countries, definitional and measurement issues pose a greater problem at the microeconomic level. This study points out that researchers not only have to confront data deficiencies but also need to grapple with conceptual issues. Finally, it also provides brief surveys of studies dealing with particular detailed topics. Many of these studies prove the existence of intangible capital at the microeconomic level as well as at macroeconomic level.

Innovation Systems and Knowledge-Intensive Enterpreneurship: a Country Case Study of Poland

This study surveys the current state of affairs in Poland with regard to the development of knowledge-intensive entrepreneurship (KIE), or new firm creation in industries considered to be science-based or to use research and development (R&D) intensively. We place KIE in Poland in the larger institutional context, outlining the key features of the country’s National Innovation System, and then focus on KIE itself. Our findings are perhaps more optimistic than many previous studies of knowledge-based economy development in Poland. We observe significant progress due to Polish access to the European Union. The frequency with which universities are playing a significant role as partners for firms in the innovation process has increased significantly; moreover, we observe a significant degree of internationalization of innovation-related cooperation. Another optimistic development is that the level of activity of venture capitalists seems to be fairly high in Poland considering the relatively low degree of development of capital markets offering VC investors exit opportunities. Moreover, after almost two decades of decline in the share of R&D spending in GDP, there are signs that this is beginning to rise, and that businesses are beginning to spend more on R&D. While demand-side problems continue to be significant barriers for the development of KIE, due to the relatively low level of education and GDP per capita in the country, the trends here are optimistic, with high rates of economic growth and improvements in the level of education of younger generations. Significant improvement is still needed in the area of intellectual property protection

Innovation Systems and Developing Countries

Connecting the theory of National Systems of Innovation with Development theory offers new insights for a global and interdisciplinary analysis of the current problems of underdevelopment. Some of the main contributions of classical Development thinking are seen to be most relevant. The role of different social actors is highlighted. Attention is driven to concrete processes of interaction., as well as to their economic, political, institutional and cultural contexts.Economic development, Interactive learning

A participatory approach for assessing alternative climate change adaptation responses to cope with flooding risk in the upper Brahmaputra and Danube river basins

This work illustrates the preliminary findings of a participatory research process aimed at identifying responses for sustainable water management in a climate change perspective, in two river basins in Europe and Asia. The paper describes the methodology implemented through local workshops, aimed at eliciting and evaluating possible responses to flooding risk. Participatory workshops allowed for the identification of four categories of possible responses and a set of nine evaluation criteria, three for each of the three pillars of sustainable development. The main result of such activities consists in the ranking of broad response categories, to contribute to the orientation of the Brahmatwinn research project towards the identification of Integrated Water Resource Management Strategies (IWRMS) well grounded upon the issues and preferences elicited from local experts. The mDSS tool was used to facilitate transparent and robust management of the information collected through Multi-Criteria Decision Analysis (MCDA) and the communication of the outputs.Participatory process, Climate Change, Flooding Risk, Decision Support System, MCDA

Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as Statement, Question, Backchannel, Agreement, Disagreement, and Apology. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence. The dialogue model is based on treating the discourse structure of a conversation as a hidden Markov model and the individual dialogue acts as observations emanating from the model states. Constraints on the likely sequence of dialogue acts are modeled via a dialogue act n-gram. The statistical dialogue grammar is combined with word n-grams, decision trees, and neural networks modeling the idiosyncratic lexical and prosodic manifestations of each dialogue act. We develop a probabilistic integration of speech recognition with dialogue modeling, to improve both speech recognition and dialogue act classification accuracy. Models are trained and evaluated using a large hand-labeled database of 1,155 conversations from the Switchboard corpus of spontaneous human-to-human telephone speech. We achieved good dialogue act labeling accuracy (65% based on errorful, automatically recognized words and prosody, and 71% based on word transcripts, compared to a chance baseline accuracy of 35% and human accuracy of 84%) and a small reduction in word recognition error.Comment: 35 pages, 5 figures. Changes in copy editing (note title spelling changed

Cognitive strategic groups and long-run efficiency evaluation : the case of Spanish savings banks

In the framework of Cognitive Approach, this paper proposes a new method to identify strategic groups (SG) using Data Envelopment Analysis (DEA) methods. Two assumptions are maintained in the SG literature: first, firms grouped together value inputs and outputs similarly, and, second, some degree of stability in those valuations should be identified. Virtual weights obtained from DEA are extremely useful in the valuation of the strategic variables, but a problem emerges when longitudinal analysis is performed. This problem is addressed by defining a long run DEA evaluation. SGs are determined by means of Cluster Analysis, using virtual outputs and virtual inputs as variables and Spanish savings banks as observations. The traditional method of determining SGs by clustering on the original variables is also applied and the results are compared. It is shown that the long run DEA weights approach has advantages over the traditional methodology

A framework for the measurement and prediction of an individual scientist's performance

Quantitative bibliometric indicators are widely used to evaluate the performance of scientists. However, traditional indicators do not much rely on the analysis of the processes intended to measure and the practical goals of the measurement. In this study, I propose a simple framework to measure and predict an individual researcher's scientific performance that takes into account the main regularities of publication and citation processes and the requirements of practical tasks. Statistical properties of the new indicator - a scientist's personal impact rate - are illustrated by its application to a sample of Estonian researchers.Comment: 12 pages, 3 figure

Evaluating a Department’s Research: Testing the Leiden Methodology in Business and Management

The Leiden methodology (LM), also sometimes called the “crown indicator”, is a quantitative method for evaluating the research quality of a research group or academic department based on the citations received by the group in comparison to averages for the field. There have been a number of applications but these have mainly been in the hard sciences where the data on citations, provided by the ISI Web of Science (WoS), is more reliable. In the social sciences, including business and management, many journals and books are not included within WoS and so the LM has not been tested here. In this research study the LM has been applied on a dataset of over 3000 research publications from three UK business schools. The results show that the LM does indeed discriminate between the schools, and has a degree of concordance with other forms of evaluation, but that there are significant limitations and problems within this discipline

Do altmetrics correlate with citations? Extensive comparison of altmetric indicators with citations from a multidisciplinary perspective

An extensive analysis of the presence of different altmetric indicators provided by Altmetric.com across scientific fields is presented, particularly focusing on their relationship with citations. Our results confirm that the presence and density of social media altmetric counts are still very low and not very frequent among scientific publications, with 15%-24% of the publications presenting some altmetric activity and concentrating in the most recent publications, although their presence is increasing over time. Publications from the social sciences, humanities and the medical and life sciences show the highest presence of altmetrics, indicating their potential value and interest for these fields. The analysis of the relationships between altmetrics and citations confirms previous claims of positive correlations but relatively weak, thus supporting the idea that altmetrics do not reflect the same concept of impact as citations. Also, altmetric counts do not always present a better filtering of highly cited publications than journal citation scores. Altmetrics scores (particularly mentions in blogs) are able to identify highly cited publications with higher levels of precision than journal citation scores (JCS), but they have a lower level of recall. The value of altmetrics as a complementary tool of citation analysis is highlighted, although more research is suggested to disentangle the potential meaning and value of altmetric indicators for research evaluation