925 resultados para Global innovation index


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Este artigo analisa em detalhes os indicadores e resultado obtidos pelo Brasil na edição 2012 do Global Innovation Index (GII) [1], um dos mais importantes estudos sobre Competitividade de Países. Esta análise, por si só, pode ser útil para os interessados no Brasil e nos estudos sobre Competitividade, mas ele também demonstra que existem fatores de influência, ou influenciadores, que precisam ser considerados juntamente com a análise dos resultados dos países. Estes influenciadores, como as mudanças metodológicas, a latência dos dados, o intervalo de confiança e evolução da economia do país; ajudam a explicar os resultados negativos ou positivos do país, de um ano para outro, demonstrando os cuidados que precisam ser tomados na interpretação dos estudos de competividade. Neste artigo, evitamos traduzir a descrição do nome dos indicadores para facilitar o entendimento.

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Purpose: The studies on links between sustainability, innovation, and competitiveness have been mainly focused at organizational and business level. The purpose of this research is to investigate if there is a correlation between these three variables at country level. Using international well recognized rankings of countries sustainability, innovation, and competitiveness, correlation analysis was performed allowing for the conclusion that there are indeed high correlations (and possible relationships) between the three variables at country level. Design/methodology/approach: Sustainability, innovation, and competitiveness literature were reviewed identifying a lack of studies examining these three variables at country level. Three major well recognized indexes were used to support the quantitative research: The World Economic Forum (2013) Sustainability-adjusted global competitiveness index, the Global Innovation Index (2014) issued by Cornell University, INSEAD, and WIPO and the IMD World Competitiveness Yearbook (2014). After confirming the distributions normality, Pearson correlation analysis was made with results showing high linear correlations between the three indexes. Findings: The results of the correlation analysis using Pearson correlation coefficient (all correlation coefficients are greater than 0.73) give a strong support to the conclusion that there is indeed a high correlation (and a possible relationship) between social sustainability, innovation and competitiveness at country level. Research limitations/implications: Further research is advisable to better understand the factors that contribute to the presented results and to establish a global paradigm linking these three main constructs (social sustainability, innovation, and competitiveness). Some authors consider that these measurements are not fully supported (e.g. due to different countries standards), however, it is assumed these differing underlying methodological approaches, by being used in conjunction, can be considered as a set of reliable and useful performance indicators. Practical implications: The results highlight the simultaneous relationship between social sustainability, innovation and competitiveness superior performance and the need to take that these considerations into business and operating models. Social implications: This research suggests that sustainability and innovation policies, strategies and practices are relevant for countries competitiveness and should be promoted particularly in countries ranked low on sustainability and innovation global scoring indexes. Originality/value: This is one of the few studies addressing the relationships between sustainability, innovation and competitiveness at country level.

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During postharvest, lettuce is usually exposed to adverse conditions (e.g. low relative humidity) that reduce the vegetable quality. In order to evaluate its shelf life, a great number of quality attributes must be analyzed, which requires careful experimental design, and it is time consuming. In this study, the modified Global Stability Index method was applied to estimate the quality of butter lettuce at low relative humidity during storage discriminating three lettuce zones (internal, middle, and external). The results indicated that the most relevant attributes were: the external zone - relative water content, water content , ascorbic acid, and total mesophilic counts; middle zone - relative water content, water content, total chlorophyll, and ascorbic acid; internal zone - relative water content, bound water, water content, and total mesophilic counts. A mathematical model that takes into account the Global Stability Index and overall visual quality for each lettuce zone was proposed. Moreover, the Weibull distribution was applied to estimate the maximum vegetable storage time which was 5, 4, and 3 days for the internal, middle, and external zone, respectively. When analyzing the effect of storage time for each lettuce zone, all the indices evaluated in the external zone of lettuce presented significant differences (p < 0.05). For both, internal and middle zones, the attributes presented significant differences (p < 0.05), except for water content and total chlorophyll.

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The ability to innovate is generally accepted as a critical success factor to growth and future performance of firms. Yet, this acceptance obscures a comprehensive perspective on how firms can influence their innovation capacity and resulting performance. This paper proposes a '3P' construct of innovation measurement that simultaneously considers the Posture, Propensity and Performance related to a firm's innovation capabilities. We propose and provide empirical support showing that robust measurement of the performance implications of innovation requires the consideration of input, throughput and output factors simultaneously. Single or more limited indicators do not offer the degree of fine-tuning to a firm's innovation system that managers require. Thus, we propose the development, and future research into contingent variations, of a Composite Innovation Index (CII). We further demonstrate its use in comparing innovators and allowing managers to design a firm's innovation system.

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In the global economy, innovation is one of the most important competitive assets for companies willing to compete in international markets. As competition moves from standardised products to customised ones, depending on each specific market needs, economies of scale are not anymore the only winning strategy. Innovation requires firms to establish processes to acquire and absorb new knowledge, leading to the recent theory of Open Innovation. Knowledge sharing and acquisition happens when firms are embedded in networks with other firms, university, institutions and many other economic actors. Several typologies of innovation and firm networks have been identified, with various geographical spans. One of the first being modelled was the Industrial Cluster (or in Italian Distretto Industriale) which was for long considered the benchmark for innovation and economic development. Other kind of networks have been modelled since the late 1970s; Regional Innovation Systems represent one of the latest and more diffuse model of innovation networks, specifically introduced to combine local networks and the global economy. This model was qualitatively exploited since its introduction, but, together with National Innovation Systems, is among the most inspiring for policy makers and is often cited by them, not always properly. The aim of this research is to setup an econometric model describing Regional Innovation Systems, becoming one the first attempts to test and enhance this theory with a quantitative approach. A dataset of 104 secondary and primary data from European regions was built in order to run a multiple linear regression, testing if Regional Innovation Systems are really correlated to regional innovation and regional innovation in cooperation with foreign partners. Furthermore, an exploratory multiple linear regression was performed to verify which variables, among those describing a Regional Innovation Systems, are the most significant for innovating, alone or with foreign partners. Furthermore, the effectiveness of present innovation policies has been tested based on the findings of the econometric model. The developed model confirmed the role of Regional Innovation Systems for creating innovation even in cooperation with international partners: this represents one of the firsts quantitative confirmation of a theory previously based on qualitative models only. Furthermore the results of this model confirmed a minor influence of National Innovation Systems: comparing the analysis of existing innovation policies, both at regional and national level, to our findings, emerged the need for potential a pivotal change in the direction currently followed by policy makers. Last, while confirming the role of the presence a learning environment in a region and the catalyst role of regional administration, this research offers a potential new perspective for the whole private sector in creating a Regional Innovation System.

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We present a case for using Global Community Innovation Platforms (GCIPs), an approach to improve innovation and knowledge exchange in international scientific communities through a common and open online infrastructure. We highlight the value of GCIPs by focusing on recent efforts targeting the ecological sciences, where GCIPs are of high relevance given the urgent need for interdisciplinary, geographical, and cross-sector collaboration to cope with growing challenges to the environment as well as the scientific community itself. Amidst the emergence of new international institutions, organizations, and meetings, GCIPs provide a stable international infrastructure for rapid and long-term coordination that can be accessed by any individual. This accessibility can be especially important for researchers early in their careers. Recent examples of early-career GCIPs complement an array of existing options for early-career scientists to improve skill sets, increase academic and social impact, and broaden career opportunities. We provide a number of examples of existing early-career initiatives that incorporate elements from the GCIPs approach, and highlight an in-depth case study from the ecological sciences: the International Network of Next-Generation Ecologists (INNGE), initiated in 2010 with support from the International Association for Ecology and 20 member institutions from six continents.

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Today all kinds of innovations and research work is done by partnerships of competent entities each having some specialized skills. Like the development of the global economy, global innovation partnerships have grown considerably and form the basis of most of the sophisticated innovations today. To further streamline and simplify such cooperation, several innovation networks have been formed, both at local and global levels. This paper discusses the different types of innovations and how cooperation can benefit innovation in terms of pooling of resources and sharing of risks. One example of an open global co-innovation network promoted by Tata Consultancy Services, the TCS COIN is taken as a case. It enables venture capitalists, consultants, research agencies, companies and universities form nodes of the network so that each entity can play a meaningful role in the innovation network. Further, two innovation projects implemented using the COIN are discussed. Innovation Networks like these could form the basis of a unique global innovation network, which is not owned by any company and is used by innovation partners globally to collaborate and conduct research and development.

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Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed.

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In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

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Ireland, as a small, open European economy, relies fundamentally on international engagement. An internationalised education system in Ireland has a crucial role to play in maintaining Ireland’s international profile and attractiveness by educating the next generation of leaders, entrepreneurs and decision-makers in our partner-countries, by giving our own students the intercultural expertise demanded in the global economy, and by enhancing the direct link with Ireland for members of our global diaspora who choose to come home to study. The High-Level Group on International Education takes the view that, from a national perspective, the most compelling rationale for internationalisation is investment in future global relationships: with students educated in Ireland who will become our advocates overseas, with educational institutions that will be the research and teaching partners of the future, and with the countries that will be Ireland’s next trading and business partners. Internationalisation also provides a means of enhancing the quality of learning, teaching and research in Ireland and makes a significant contribution to our broader ambition as a global innovation hub.

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La asignatura de Competitividad Internacional Urbana (ciu) del programa de Gestión y Desarrollo Urbanos (gdu) de la Universidad del Rosario ha sido desde 2009, cuando asumí su dirección y orientación, un reto permanente de aprendizajes tan estimulantes y variados cuantas ciudades y atributos hay por descubrir en el inmenso mundo de lo urbano-rural-regional. Si bien la competitividad es un asunto urbano-regional antes que nacional, la mayor parte de los enfoques y de las consiguientes referencias bibliográficas abordan la competitividad a nivel nacional siendo relativamente escasas las publicaciones sobre la competitividad urbana. Así, los documentos abordan una descripción general de las ciudades, las causas de las crisis y las consecuencias para la ciudad y su estructura económica, analizadas a partir de los impactos sobre el mercado laboral, los precios de la vivienda, el desarrollo del turismo, entre otros, y las diversas estrategias que adoptaron para afrontar la crisis y convertirla en una oportunidad de desarrollo.

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This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

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China is a large country characterized by remarkable growth and distinct regional diversity. Spatial disparity has always been a hot issue since China has been struggling to follow a balanced growth path but still confronting with unprecedented pressures and challenges. To better understand the inequality level benchmarking spatial distributions of Chinese provinces and municipalities and estimate dynamic trajectory of sustainable development in China, I constructed the Composite Index of Regional Development (CIRD) with five sub pillars/dimensions involving Macroeconomic Index (MEI), Science and Innovation Index (SCI), Environmental Sustainability Index (ESI), Human Capital Index (HCI) and Public Facilities Index (PFI), endeavoring to cover various fields of regional socioeconomic development. Ranking reports on the five sub dimensions and aggregated CIRD were provided in order to better measure the developmental degrees of 31 or 30 Chinese provinces and municipalities over 13 years from 1998 to 2010 as the time interval of three “Five-year Plans”. Further empirical applications of this CIRD focused on clustering and convergence estimation, attempting to fill up the gap in quantifying the developmental levels of regional comprehensive socioeconomics and estimating the dynamic convergence trajectory of regional sustainable development in a long run. Four clusters were benchmarked geographically-oriented in the map on the basis of cluster analysis, and club-convergence was observed in the Chinese provinces and municipalities based on stochastic kernel density estimation.

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OBJECTIVE: Define links between psychosocial parameters and metabolic variables in obese females before and after a low-calorie diet. METHOD: Nine female obese patients (age 36.1 +/- 7.1 years, body mass index [BMI] > 30 kg/m2) were investigated before and after a 6-week low-calorie diet accompanied by behavior therapy. Blood lipids, insulin sensitivity (Bergman protocol), fat distribution (by dual-energy X-ray absorptiometry [DEXA]), as well as psychological parameters such as depression, anger, anxiety, symptom load, and well-being, were assessed before and after the dieting period. RESULTS: The females lost 9.6 +/- 2.8 kg (p < .0001) of body weight, their BMI was reduced by 3.5 +/- 0.3 kg/m2 (p < .0001), and insulin sensitivity increased from 3.0 +/- 1.8 to 4.3 +/- 1.5 mg/kg (p = .05). Their abdominal fat content decreased from 22.3 +/- 5.5 to 18.9 +/- 4.5 kg (p < .0001). In parallel, psychological parameters such as irritability (p < .05) and cognitive control (p < .0001) increased, whereas feelings of hunger (p < .05), externality (p < .05), interpersonal sensitivity (p < .01), paranoid ideation (p < .05), psychoticism (p < .01), and global severity index (p < .01) decreased. Prospectively, differences in body fat (percent) were correlated to nervousness (p < .05). Waist-to-hip ratio (WHR) differences were significantly correlated to sociability (p < .05) and inversely to emotional instability (p < .05), whereas emotional instability was inversely correlated to differences in insulin sensitivity (p < .01). DISCUSSION: Weight reduction may lead to better somatic risk factor control. Women with more nervousness and better sociability at the beginning of a diet period may lose more weight than others.