Narrow Results

We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

We show that a nontrivial example of universal algebra appears in quantum field theory. For a unital C*-algebra , a sector is a unitary equivalence class of unital *-endomorphisms of . We show that the set of all sectors of is a universal algebra with an N-ary sum which is not reduced to any binary sum when includes the Cuntz algebra as a C*-subalgebra with common unit for N ≥ 3. Next we explain that the set of all unitary equivalence classes of unital *-representations of is a right module of . An essential algebraic formulation of branching laws of representations is given by using submodules of . As an application, we show that the action of on distinguishes elements of .

In this study, we address an issue of stability of global production network by constructing a scheme combining classical Leontieff input–output analysis and modeling of contagion in financial networks. We propose a model of disruptive cascades in global economy with nonlinear effects similar to those in the financial contagion model proposed by Elliott, Golub and Jackson (2014). We apply the model to the analysis of stability of the global input–output sectoral network using the data from the World Input-Output Database (WIOD). We show that this sectoral network appears to be very stable with respect to sectoral shocks. However, by introducing synthetic substructure of economic sectors in the WIOD data we show that this stability is to a significant extent an artifact of working with aggregated data. Namely, we show that the impact of economic shocks may be much more pronounced if an underlying disaggregated network is sufficiently sparse.

A technology evaluation model based on the negotiation between a licensor and a licensee is proposed. This model also considered information asymmetry which decreases the probability of technology transfer between the licensor and the licensee. Factors which affect this decrease and sectors which are more exposed to this decrease using the technology evaluation model are explored using the pooled technology transferred cases of NTB (National Technology Bank), Korea. The only explanatory factor which covers all sectors is the "technology regime-based innovation pattern," and the factor named "patent authorization stage" is the most influencing variable within a specific sector. In three sectors of the four "technology regime-based innovation patterns," namely, scale intensive, specialized supplier, and science based, the variation of licensing probability is likely to increase when the "patent authorization stage" increases. Using SOFM and ANOVA, the negotiated result and the value of technology evaluated are likely to increase.

The aim of this paper is to conduct an empirical study to explore the influence of size category on innovation incorporation in Irish SMEs. Changes in markets and in large organisation strategies have resulted in the need for SMEs to re-examine and modify their competitive strategies to increase innovation. Although there is some literature on innovation incorporation in SMEs, there is a lack of direct studies on this issue, with a reliance on related but indirect studies such as Reengineering and New product development in SMEs. Furthermore, there is a paucity of studies and data on the innovation incorporation in different organisational size categories within SMEs.

This study uses a grounded SME innovation model developed from earlier studies as the basis of a questionnaire survey of 2086 SMEs in Northern Ireland. The results indicate that SME organisational size categories has a significant effect on innovation incorporation in relation to leadership, people and culture, TQM/CI, product and process and Knowledge and information management.

The text and associated Supplemental Materials contribute internally consistent and therefore entirely comparable regional, temporal, and sectoral risk profiles to a growing literature on regional economic vulnerability to climate change. A large collection of maps populated with graphs of Monte-Carlo simulation results support a communication device in this regard — a convenient visual that we hope will make comparative results tractable and credible and resource allocation decisions more transparent. Since responding to climate change is a risk-management problem, it is important to note that these results address both sides of the risk calculation. They characterize likelihood distributions along four alternative emissions futures (thereby reflecting the mitigation side context); and they characterize consequences along these transient trajectories (which can thereby inform planning for the iterative adaptation side). Looking across the abundance of sectors that are potentially vulnerable to some of the manifestations of climate change, the maps therefore hold the potential of providing comparative information about the magnitude, timing, and regional location of relative risks. This is exactly the information that planners who work to protect property and public welfare by allocating scarce resources across competing venues need to have at their disposal — information about relative vulnerabilities across time and space and contingent on future emissions and future mitigation. It is also the type of information that integrated assessment researchers need to calibrate and update their modeling efforts — scholars who are exemplified by Professor Nordhaus who created and exercised the Dynamic Integrated Climate-Economy and Regional Integrated Climate-Economy models.

The aim of this paper is to conduct an empirical study to explore the influence of size category on innovation incorporation in Irish SMEs. Changes in markets and in large organisation strategies have resulted in the need for SMEs to re-examine and modify their competitive strategies to increase innovation. Although there is some literature on innovation incorporation in SMEs, there is a lack of direct studies on this issue, with a reliance on related but indirect studies such as Reengineering and New product development in SMEs. Furthermore, there is a paucity of studies and data on the innovation incorporation in different organisational size categories within SMEs.

This study uses a grounded SME innovation model developed from earlier studies as the basis of a questionnaire survey of 2086 SMEs in Northern Ireland. The results indicate that SME organisational size categories has a significant effect on innovation incorporation in relation to leadership, people and culture, TQM/CI, product and process and Knowledge and information management.

The text and associated Supplemental Materials contribute internally consistent and therefore entirely comparable regional, temporal, and sectoral risk profiles to a growing literature on regional economic vulnerability to climate change. A large collection of maps populated with graphs of Monte-Carlo simulation results support a communication device in this regard — a convenient visual that we hope will make comparative results tractable and credible and resource allocation decisions more transparent. Since responding to climate change is a risk-management problem, it is important to note that these results address both sides of the risk calculation. They characterize likelihood distributions along four alternative emissions futures (thereby reflecting the mitigation side context); and they characterize consequences along these transient trajectories (which can thereby inform planning for the iterative adaptation side). Looking across the abundance of sectors that are potentially vulnerable to some of the manifestations of climate change, the maps therefore hold the potential of providing comparative information about the magnitude, timing, and regional location of relative risks. This is exactly the information that planners who work to protect property and public welfare by allocating scarce resources across competing venues need to have at their disposal — information about relative vulnerabilities across time and space and contingent on future emissions and future mitigation. It is also the type of information that integrated assessment researchers need to calibrate and update their modeling efforts — scholars who are exemplified by Professor Nordhaus who created and exercised the Dynamic Integrated Climate-Economy and Regional Integrated Climate-Economy models.