Application Of Cluster Analysis Research Articles

Adult education as a common good: conceptualisation and measurement

ABSTRACTThe article outlines a theoretical framework for conceptualising adult education – and more broadly, lifelong learning – as a common good. It argues that the extent to which adult education as a common good is accomplished in a given society/country reflects its accessibility, availability, affordability and the social commitment to its functioning and that it depends on a country’s specific institutional arrangements. Building on this conceptualisation and using data from the Adult Education Survey (AES), the Labour Force Survey (LFS) and the Continuing Vocational Training Survey (CVTS) for 24 European countries, the authors develop a composite index, based on these four dimensions, which measures the extent to which adult education as a common good is practiced in a given country. This index can be used to assess the effectiveness of national policies in the sphere of adult education across Europe. The results indicate substantial cross-country differences, with North European states and Luxembourg scoring best and Romania scoring worst. Finally, applying cluster analysis, the article identifies six distinctive clusters of countries with regard to the extent of adult education as a common good; the authors designate these cluster categories as reality, feasible, ambiguous, problematic, possible and invisible.

A cluster analysis approach for differentiating transportation modes using Bluetooth sensor data

ABSTRACTA variety of automatic data collection technologies have been used to gather road and highway system data. The majority of these automatic data collection technologies are designed to collect vehicle-based data and either do not have the capability to collect other travel mode data (e.g., bicycles and pedestrians), or may need to be deployed differently to support this capability.One type of wireless-based data collection system that has been deployed recently is based on Bluetooth technology. A key feature of Bluetooth-based data collection systems that makes travel mode identification feasible is that the Bluetooth-enabled devices within vehicles are also present on bicyclists and pedestrians. This research explores the effectiveness of applying cluster analysis methods when processing data collected via Bluetooth technology from vehicles, bicyclists, and pedestrians to automatically identify the associated travel modes. The results of several experiments utilizing multiple Bluetooth-based data collection units arranged linearly and in relatively close proximity on a simulated intersection demonstrate the potential of cluster analysis to accurately differentiate transportation modes from the collected data.

Seasonal march patterns of the summer rainy season in the Philippines and their long-term variability since the late twentieth century

This study investigates the seasonal march patterns of rainfall in the Philippines from 1951 to 2012 and their long-term variability. In order to clarify the dominant patterns in the seasonal march of rainfall, an empirical orthogonal function (EOF) analysis was applied to pentad rainfall data of 30 stations. For the first EOF mode (EOF1), we obtained a pattern related to the summer rainy season. We then applied cluster analysis to the time coefficients of EOF1 in each year to classify the seasonal patterns of the summer rainy season. As a result, the patterns were classified into six clusters. We found a long-term change in the pattern appearances with three anomalous patterns frequently observed since the 1990s: (1) a pattern that has an indistinct dry season and a prolonged peak rainfall, (2) a pattern that has a distinct dry season and an earlier withdrawal of the summer rainy season, resulting in a shortened rainy season, and (3) a pattern with a distinct dry season as well as delayed onset and withdrawal of the summer rainy season. This study also shows the relations between these three patterns and the lower atmospheric circulation at the 850 hPa level around the Philippines. Consequently, large positive and negative anomalies in geopotential height were observed around the Philippines for the distinct and indistinct dry seasons, respectively. The duration and condition of the dry season were greatly affected by the strength and location of the subtropical high especially for February–March. It is also noteworthy that the timing of the onset (withdrawal) of the summer rainy season is clearly related to that of the onset of the westerly (northerly) wind in the zonal (meridional) component around the Philippines. Further, the duration and amount of peak rainfall were directly influenced by the strength of the westerly winds in the zonal component. These three anomalous patterns tended to appear in the years when the warm or cold event of the El Niño–Southern Oscillation (ENSO) occurred. This study suggests that the long-term variability in the seasonal march of rainfall is considerably influenced by the variability in ENSO.

Analysis of low carbon pilot industrial parks in China: Classification and case study

Abstract Industrial Parks (IPs) have made tremendous contributions to China’s national economic development. However the economic gains often come with increased environmental pollution and Green House Gas (GHG) emissions. These problems are compounded by the rapid growth of IPs in China. To promote the low carbon and sustainable development of IPs, the Ministry of Industry and Information Technology (MIIT) and the National Development and Reform Commission (NDRC) jointly launched the national Low Carbon Industrial Park Pilot Programme (LCIPPP) in 2013. As the largest pilot programme at the IP level in the world, 51 IPs which vary in location, size, and industrial mix were included. Based on the data of 51 pilot IPs, we applied cluster analysis to propose the 3 H (High carbon intensity, High ratio of coal in energy mix, and High proportion of six energy-intensive industries output), 3 L (Low carbon intensity, Low ratio of coal in energy mix, and Low proportion of six energy-intensive industries output) and Mixed IP classifications. Then a representative IP was selected for case study in accordance with the classification. For each case, the achievements and practices, the drivers and success factors, pathways and models in low carbon development were collected and analyzed. Our findings reveal that 3H IPs should focus more on upgrading traditional heavy industry. Meanwhile, technological innovation and enhancing carbon management are determined to be more efficient ways to realize the low carbon development of 3L IPs. As for Mixed IPs, optimizing the energy mix and adopting an “Industry + town” integrated development model will be effective.

Summarizing metocean operating conditions as a climatology of marine hazards

Marine occupations are plagued by some of the highest accident and mortality rates of any occupation, due in part to the variety and severity of environmental hazards presented by the ocean environment. In order to better study and communicate the potential impacts of these hazards on occupational health and safety, a semi-objective, hazard-focused climatology of a particularly dangerous marine environment (Northwestern Atlantic) has been developed. Specifically, climate has been summarized as the frequency with which responsible government agencies are expected to issue relevant warnings or watches, couching results in language relevant to marine stakeholders. Applying cluster analysis to warning/watch frequencies identified seven distinct ‘hazard climatologies’, ranging from near-Arctic conditions to areas dominated by calm seas and warm waters. Spatial and temporal variability in these clusters reflects relevant annual cycles, such as the advance/retreat of sea ice and shifts in the Atlantic storm track; the clusters also highlight regions and seasons with comparable operational risks. Our approach is proposed as an effective means to summarize and communicate marine risk with stakeholders, and a potential framework for describing climate change impacts.

Bias wanted! Examining people’s information exposure, quality expectations and bias perceptions in the context of the refugees debate among different segments of the German population

AbstractThe growing number of refugees entering Europe since 2015 has quickly ignited a heated public debate on refugees in Germany. Against the backdrop of the media’s information and opinion-forming function, this paper examines the importance of mainstream and social media among different segments of the German population. Applying cluster analysis to survey data (n= 1,579), six clusters with specific attitude-behavior combinations concerning the refugee issue were identified: Pro-Refugee Activists, Passive-Affirmative Mainstream, Directly-Involved Ambivalents, Passive-Worried Mainstream, Worried Agitators, and Anti-Refugee Activists. The results show that these clusters differ both in terms of socio-demographic and political characteristics as well as in terms of people’s issue-specific media usage, expectations, and evaluations of media coverage. Moreover, the findings indicate that social media play a problematic role in the debate as they seem to reinforce people’s pre-existing attitudes toward refugees. The implications of these findings for public debate on refugees are also discussed.

On the link between stress field and small-scale hydraulic fracture growth in anisotropic rock derived from microseismicity

Abstract. To characterize the stress field at the Grimsel Test Site (GTS) underground rock laboratory, a series of hydrofracturing and overcoring tests were performed. Hydrofracturing was accompanied by seismic monitoring using a network of highly sensitive piezosensors and accelerometers that were able to record small seismic events associated with metre-sized fractures. Due to potential discrepancies between the hydrofracture orientation and stress field estimates from overcoring, it was essential to obtain high-precision hypocentre locations that reliably illuminate fracture growth. Absolute locations were improved using a transverse isotropic P-wave velocity model and by applying joint hypocentre determination that allowed for the computation of station corrections. We further exploited the high degree of waveform similarity of events by applying cluster analysis and relative relocation. Resulting clouds of absolute and relative located seismicity showed a consistent east–west strike and 70° dip for all hydrofractures. The fracture growth direction from microseismicity is consistent with the principal stress orientations from the overcoring stress tests, provided that an anisotropic elastic model for the rock mass is used in the data inversions. The σ1 stress is significantly larger than the other two principal stresses and has a reasonably well-defined orientation that is subparallel to the fracture plane; σ2 and σ3 are almost equal in magnitude and thus lie on a circle defined by the standard errors of the solutions. The poles of the microseismicity planes also lie on this circle towards the north. Analysis of P-wave polarizations suggested double-couple focal mechanisms with both thrust and normal faulting mechanisms present, whereas strike-slip and thrust mechanisms would be expected from the overcoring-derived stress solution. The reasons for these discrepancies can be explained by pressure leak-off, but possibly may also involve stress field rotation around the propagating hydrofracture. Our study demonstrates that microseismicity monitoring along with high-resolution event locations provides valuable information for interpreting stress characterization measurements.

Atmospheric Dynamics is the Largest Source of Uncertainty in Future Winter European Rainfall

Abstract The IPCC Fifth Assessment Report highlighted large uncertainty in European precipitation changes in the coming century. This paper investigates the sources of intermodel differences using CMIP5 model European precipitation data. The contribution of atmospheric circulation to differences in precipitation trends is investigated by applying cluster analysis to daily mean sea level pressure (MSLP) data. The resulting classification is used to reconstruct monthly precipitation time series, thereby isolating the component of precipitation variability directly related to atmospheric circulation. Reconstructed observed precipitation and reconstructions of simulated historical and projection data are well correlated with the original precipitation series, showing that circulation variability accounts for a substantial fraction of European precipitation variability. Removing the reconstructed precipitation from the original precipitation leaves a residual component related to noncirculation effects (and any small remaining circulation effects). Intermodel spread in residual future European precipitation trends is substantially reduced compared to the spread of the original precipitation trends. Uncertainty in future atmospheric circulation accounts for more than half of the intermodel variance in twenty-first-century precipitation trends for winter months for both northern and southern Europe. Furthermore, a substantial part of this variance is related to different forced dynamical responses in different models and is therefore potentially reducible. These results highlight the importance of understanding future changes in atmospheric dynamics in achieving more robust projections of regional climate change. Finally, the possible dynamical mechanisms that may drive the future differences in regional circulation and precipitation are illustrated by examining simulated teleconnections with tropical precipitation.

Digital marketing communication and car buying: Differentiating users from non-users

This study aims to differentiate the users of digital and traditional channels of communication while buying a car. Data were collected from 800 respondents from Delhi. The findings of the study revealed that 75% of the respondents used at least one digital channel of communication while buying a car. There were 25% of the respondents who relied exclusively on traditional channels of communication. Five customer segments were identified in the study by applying cluster analysis. Two customer segments made use of only traditional channels of communication and were named ‘Accomplished Magnate’ and ‘Stripling Warrior’. Three customer segments used digital channels of communication while buying a car and were named ‘Young Business Turks’, ‘Generation Next’ and ‘Employed Maestro’. The findings have important implications for the car marketers as they must understand that digital channels of communication are mainly used by the young customers who also have preferences for particular digital channels of communication. However, other important customer segments still rely on traditional channels of communication while buying a car. So, targeting these customers with their preferred channel of communication should produce good business results for the marketers. Few studies so far tried to identify and group the individuals into users and non-users of digital marketing communication in limited problem-solving product categories. However, such classification was not seen in an extended problemsolving product category like car where marketers are spending a significant amount of money.

Water needs and equivalence relations for different irrigated crops in the São Francisco basin

The present work was performed by applying the principal component analysis, in order to compare the water needs of banana, mango, grape, sugarcane, maize and beans crops in different regions of the Sao Francisco river basin, aiming to identify the climate elements that most influence the reference evapotranspiration (ET0) in the locations of Pirapora-MG, Jaiba-MG, Barreiras-BA and Petrolina-PE. In addition, the locations with more similarities, according to the evaluated parameters, were verified by applying cluster analysis, and the equivalence relations between the studied crops were determined by integrating the parameters related to the climatic elements and the characteristics of crops and soils. Based on the principal components analysis, it was observed that the most significant climate elements for ET0 estimation were different for each place. The model with two components explained 90%, 88%, 95% and 97% of the total variance, respectively for the locations of Pirapora, Jaiba, Barreiras and Petrolina. Because it is in a semi-arid climate region, Petrolina showed high crop water needs, a behavior proven with the cluster analysis. The equivalence relations allowed comparing the water needs for the studied crops, providing, in general terms, a parameter comparison between the crops, and specifying which one will be more adequate depending on the water availability in the Sao Francisco basin.

Performance Measurement and Benchmarking of Large-Scale Tourist Hotels

Taiwanese tourism policy underwent a major change in 2008 when restrictions were gradually relaxed on Chinese tourists visiting Taiwan. According to the Tourism Bureau of Taiwan’s statistics, the overall number of mainland tourists increased from 329,204 in 2008 to 4,184,102 in 2015; however, there was a 16.1% reduction (670,000) occurring in 2016. This significant event will cause more harm than good to Taiwan’s all-important tourism industry. In response to such contractions, this study applied cluster analysis combined with entropy to derive suitable clusters useful towards identifying the best market performers among hoteliers through a measurement of large-scale tourist hotels’ operational performance. This may signal a benchmark for the improvement of poor performance hotels. Entropy is used as an objective weight method to calculate the relative importance of all salient attributes by comparing the entropy values of each given attribute. Large-scale international tourist hotels have become the market mainstream in Taiwan; therefore, 17 tourist hotels with more than 5000 employees yearly were selected to become part of this study. Operational performance was measured by attributive means of occupancy rate, average room rate, average production-value-per-employee, total number of domestic tourists, and total number of foreign tourists (including overseas Chinese). A significant F value of the ANOVA analysis indicates that there is at least one significant difference found between the two clusters. Further post-hoc analysis uses the Scheffe method to identify any difference found between clusters and to determine the best performance cluster useful as a benchmark. The methods of this study are different from those of previous studies because of the use of a Data Envelopment Analysis (DEA) technique or mix, while there is also applied cluster analysis combined with entropy. Clear indicators are deemed useful for exacting improvement standards among under-performing tourist hotel properties.

Keystone species of fish community structure in the Bohai Sea

PDF HTML阅读 XML下载 导出引用 引用提醒 渤海鱼类群落结构关键种 DOI: 作者: 作者单位: 1. 中国水产科学研究院 黄海水产研究所, 农业部海洋渔业可持续发展重点实验室, 山东 青岛 266071;2. 青岛海洋科学与技术国家实验室, 海洋渔业科学与食物产出过程功能实验室, 山东 青岛 266235;3. 中国水产科学研究院 黄海水产研究所, 山东省渔业资源与生态环境重点实验室, 山东 青岛 266071 作者简介: 李忠义(1974-),副研究员,主要从事海洋生态研究.E-mail:lizy@ysfri.ac.cn 通讯作者: 中图分类号: S931 基金项目: 国家973计划项目（2015CB453303）；青岛海洋科学与技术国家实验室鳌山科技创新计划（2015ASKJ02）；农业部公益性行业科研专项（2013030503）；农业部黄渤海渔业资源环境重点野外科学观测试验站和山东省泰山学者工程专项. Keystone species of fish community structure in the Bohai Sea Author: Affiliation: 1. Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences;Key Laboratory of Sustainable Development of Marine Fisheries, Ministry of Agriculture, Qingdao 266071, China;2. Laboratory for Marine Fisheries and Aquaculture, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266235, China;3. Shangdong Provincinal Key Laboratory for Fishery Resources and Eco-environment, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:基于2012-2016年每年8月渤海鱼类资源量底拖网调查数据，对鱼类群落进行了CLUSTER聚类分析和MDS标序，根据组间差异种和组内相似种年际贡献率，筛选鱼类群落结构关键种，结果显示：（1）在29.93%~35.69%的相似性水平上，2012-2016年各年度渤海鱼类群落分组情况良好，相应MDS系数都小于0.2。（2）2012-2016年渤海鱼类组间种类组成差异都极显著（）、3个年度共有的种有黄鲫（）；组间差异性贡献率大于10%，且出现率超过50%的鱼类，3个年度共有种仅有鳀，2个年度共有种仅有黄鲫。（3）贡献2012-2016年渤海鱼类群落组内相似性80%累积贡献率，且出现率超过50%的鱼类，2个年度共有的种有鳀、矛尾虾虎鱼（）；组内相似性贡献率大于10%，且出现率超过50%的鱼类，3个年度共有种有鳀，2个年度共有种有矛尾虾虎鱼和矛尾复虾虎鱼。（4）依据2012-2016年渤海鱼类群落结构相似性与差异性中各鱼种累积贡献率和单贡献率的大小和出现频率，推断鳀是渤海鱼类群落结构的首要关键种，其次为黄鲫，然后是矛尾虾虎鱼和矛尾复虾虎鱼。这4种鱼的站位平均资源量对中上层鱼类及底层鱼类站位平均资源量的比例及相关性和回归性，以及年度的优势度指数也证实上述关键种观点。综上所述，渤海鱼类群落结构首要关键种为鳀，其次为黄鲫，渤海鱼类关键种的研究可为渤海捕捞产业的调整和渔业资源的养护提供科学依据。 Abstract:This study applied cluster analysis and MDS sequence analysis to catch-rate data of fish species from bottom-trawl surveys in the Bohai Sea in August of 2012 to 2016. We selected keystone species of the fish community in the Bohai Sea, based on the annual contributions of similar species within clusters and different species between various clusters. (1) When the similarity contribution rate ranged from 29.93% to 35.69%, the fish communities in the Bohai Sea were clustered into 7, 9, 6, 5 and 6 groups for 2012-2016 consecutively, with corresponding MDS coefficients equaling 0.16, 0.14, 0.18, 0.15, and 0.17 respectively. (2) There were significant differences (=0.001) in the species composition of the fish community groups among the five years. The fish species were identified for each year that had cumulatively contributed to about 80% of the difference between community groups and occurred in more than half of the groups. Unfortunately, no common species was identified for all five years. was identified in three years. For species which contributed to more than 10% of the between-groups difference and displayed a more than 50% of occurrence in a year, none occurred in four or five years, only occurred in three years. (3) Similarly, the fish species were identified for each year that had cumulatively contributed to about 80% of the difference within groups and occurred in more than half of the groups. No species were common to three or more years. Three species (i.e. Synechogobius hasta) occurred in two of the five years. For species which had contributed to more than 10% of the within-groups difference and displayed greater than 50% occurrence in a year, no species occurred in more than four years, only Chaeturichthys stigmatias and occurred in two years. (4) Based on the annual cumulative or single similarity or difference contribution rates of every fish species to community groups, we conclude that is the primary keystone species in the fish community structure of the Bohai Sea, the Chaeturichthys stigmatias and . This conclusion is supported by the ratio, correlation, and regression of the average catches per station of these four species to that of all the pelagic or demersal species, and the annual dominance indices of these species. Results of this study provide a scientific basis for the adjustment of the fishing industry and the maintenance of fishery resources in the Bohai Sea. 参考文献 相似文献 引证文献

Application of cluster analysis to geochemical compositional data for identifying ore-related geochemical anomalies

Cluster analysis is a well-known technique that is used to analyze various types of data. In this study, cluster analysis is applied to geochemical data that describe 1444 stream sediment samples collected in northwestern Xinjiang with a sample spacing of approximately 2 km. Three algorithms (the hierarchical, k-means, and fuzzy c-means algorithms) and six data transformation methods (the z-score standardization, ZST; the logarithmic transformation, LT; the additive log-ratio transformation, ALT; the centered log-ratio transformation, CLT; the isometric log-ratio transformation, ILT; and no transformation, NT) are compared in terms of their effects on the cluster analysis of the geochemical compositional data. The study shows that, on the one hand, the ZST does not affect the results of column- or variable-based (R-type) cluster analysis, whereas the other methods, including the LT, the ALT, and the CLT, have substantial effects on the results. On the other hand, the results of the row- or observation-based (Q-type) cluster analysis obtained from the geochemical data after applying NT and the ZST are relatively poor. However, we derive some improved results from the geochemical data after applying the CLT, the ILT, the LT, and the ALT. Moreover, the k-means and fuzzy c-means clustering algorithms are more reliable than the hierarchical algorithm when they are used to cluster the geochemical data. We apply cluster analysis to the geochemical data to explore for Au deposits within the study area, and we obtain a good correlation between the results retrieved by combining the CLT or the ILT with the k-means or fuzzy c-means algorithms and the potential zones of Au mineralization. Therefore, we suggest that the combination of the CLT or the ILT with the k-means or fuzzy c-means algorithms is an effective tool to identify potential zones of mineralization from geochemical data.

Cloninger's Temperament and Character Dimensions of Personality and Binge Drinking Among College Students.

Temperament and character dimensions of personality remain largely unexplored in young adults exhibiting binge drinking (BD) patterns. Moreover, the available studies do not consider gender differences and dismiss possible personality heterogeneity among binge drinkers. In this study, we aimed to compare temperament and character dimensions between young binge drinkers and age- and sex-matched social drinkers. We further applied cluster analysis to investigate the potential heterogeneity of personality patterns among BD college students. This study included 200 university students of 18 to 24years of age, who were recruited via an invitation to take an alcohol use survey. These participants included 100 individuals (50 females and 50 males) with a BD pattern, and 100 participants (50 females and 50 males) with a social drinking (SD) pattern. These subjects were evaluated with regard to their use of alcohol and other substances, impulsiveness, sensation seeking, mood, and Cloninger's Temperament and Character Inventory. Between-group comparisons revealed that both male and female binge drinkers were characterized by high levels of novelty seeking, and low levels of persistence and self-directedness. However, cluster analyses within the binge drinker group revealed 2 distinct groups that differed between males and females. These groups shared similarities with Cloninger's type I (high harm-avoidance) and II (high novelty-seeking) alcoholism typology. The present findings support the subdivision of binge drinkers according to gender and personality dimensions. Male and female binge drinkers should not be considered a unitary group, but rather a population of individuals that encompasses at least 2 distinct personality patterns. These findings have major implications for prevention and treatment approaches.

Employment status and temporal patterns of energy intake: Nutrition and Health Survey in Taiwan, 2005-2008.

To (i) identify the major temporal patterns of energy intake among adults; (ii) examine the association between employment status and the patterns; and (iii) examine the association between dietary quality and the patterns. Secondary analysis based on the cross-sectional population-based nutrition survey in Taiwan, 2005-2008. Based on energy intake levels at six time intervals of a day derived from 24 h recall data, we applied cluster analysis to identify major temporal patterns of energy intake. Self-reported employment status was categorized into six groups: full-time, part-time, no job, student, homemaker and retired. Multinomial logistic regression models were fitted to test the association between temporal patterns of energy intake and employment groups. Non-institutionalized community dwellers. Non-pregnant adults (≥19 years old) with total energy intake between 2092 and 20920 kJ/d (500 and 5000 kcal/d; n 4508). Five major patterns were identified, which can be seen as the traditional meal pattern and its variants. About 20 % of adults had the traditional pattern. The most prevalent pattern was the delayed morning meal pattern (33 %), which had lower Ca and P intakes than the traditional pattern. About 14 % of adults had the delayed lunchtime pattern, which had lower protein, PUFA, fibre, Ca, P, vitamin D and vitamin E intakes than the traditional. Adjusted prevalence of the delayed lunchtime pattern was highest among full-time students (34 %), followed by part-time workers (24 %), and was lower in retired (8 %), homemakers (11 %) and full-time employed adults (12 %). Adults' temporal patterns of energy intake, which varied with their employment status, affected their dietary quality.

Prospective associations between dietary patterns and body composition changes in European children: the IDEFICS study.

To describe dietary patterns by applying cluster analysis and to describe the cluster memberships of European children over time and their association with body composition changes. The analyses included k-means clustering based on the similarities between the relative frequencies of consumption of forty-three food items and regression models were fitted to assess the association between dietary patterns and body composition changes. Primary schools and pre-schools of selected regions in Italy, Estonia, Cyprus, Belgium, Sweden, Hungary, Germany and Spain. Participants (n 8341) in the baseline (2-9 years old) and follow-up (4-11 years old) surveys of the IDEFICS (Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS) study. Three persistent clusters were obtained at baseline and follow-up. Children consistently allocated to the 'processed' cluster presented increased BMI (β=0·050; 95 % CI 0·006, 0·093), increased waist circumference (β=0·071; 95 % CI 0·001, 0·141) and increased fat mass gain (β=0·052; 95 % CI 0·014, 0·090) over time v. children allocated to the 'healthy' cluster. Being in the 'processed'-'sweet' cluster combination was also linked to increased BMI (β=0·079; 95 % CI 0·015, 0·143), increased waist circumference (β=0·172; 95 % CI 0·069, 0·275) and increased fat mass gain (β=0·076; 95 % CI 0·019, 0·133) over time v. the 'healthy' cluster. Children consistently showing a processed dietary pattern or changing from a processed pattern to a sweet pattern presented the most unfavourable changes in fat mass and abdominal fat. These findings support the need to promote overall healthy dietary habits in obesity prevention and health promotion programmes targeting children.

¿Cambió la primera crisis financiera global los valores empresariales en las sociedades digitalizadas basadas en el marketing? El caso de GEM países latinoamericanos

Rev.esc.adm.neg
 Como el mercado mundial está globalizado, las crisis se expanden rápidamente debido al uso masivo de las Tecnologías de la Información y la Comunicación (TICs), afectando también a los valores empresariales insertos en los procesos de creación de empresas. En este sentido, el marketing digital tiene un papel fundamental que jugar, al poder servir como una herramienta basada en la tecnología aplicada para fortalecer el emprendimiento naciente. Usando datos de los países latinoamericanos pertenecientes al proyecto GEM, y aplicando análisis clúster usando el método K-medias, el objetivo de este trabajo es comprobar si la actual Primera Crisis Global ha alterado los valores del emprendimiento en las empresas latinoamericanas. El principal resultado de este trabajo es que los rasgos de la actividad empresarial en los países GEM de América Latina se han desplazado progresivamente de la cantidad a la calidad, por lo que el marketing digital está teniendo una creciente importancia

Identifying peers in international tax competition

ABSTRACTMultinational companies (MNCs) have historically used corporate subsidiaries to isolate income earned in lower-taxed jurisdictions from tax in a higher-rate home country. This planning technique has been long accepted as a strategy to lower the MNC’s effective tax rate and maintain shareholder value. A recently study, however, demonstrates that this is an inefficient, and possibly inappropriate, strategy. This article conducts a comprehensive empirical benchmarking analysis by applying cluster analysis to empirically identify peer groups of MNCs operating in the pharmaceutical industry. We find that most firms consistently fall into the same cluster, providing evidence that income shifting can be benchmarked by industry sector. We also find special cases where firms should be excluded from the benchmark.

Evaluation of peer effects on eating behaviors: a cluster analysis approach

ABSTRACTObjectives: In this study, we aimed to determine the effects of socio-demographic characteristics and the peer groups on the eating attitude and body mass index (BMI) of students at a medical school in Turkey.Methods: This cross-sectional study was conducted with the participation of the students of Gulhane Military Medical Academy (GMMA). Ethical permissions of the study were obtained from the GMMA Ethics Committee. The target population of the study consisted of 703 students, 533 of whom (75.8%) agreed to participate in the study. The Eating Attitudes Test (EAT) was administered to the participants and their BMI was noted. The EAT consists of 10 questions that measure the socio-demographic characteristics of the participants and 40 questions that evaluate eating habits. In order to determine the peer groups of the students, each student was asked to provide the numbers of their three closest friends. Three peer groups were generated for each grade by applying cluster analysis and as a result 18 ...

Identification of relevant subtypes via preweighted sparse clustering

Cluster analysis methods are used to identify homogeneous subgroups in a data set. In biomedical applications, one frequently applies cluster analysis in order to identify biologically interesting subgroups. In particular, one may wish to identify subgroups that are associated with a particular outcome of interest. Conventional clustering methods generally do not identify such subgroups, particularly when there are a large number of high-variance features in the data set. Conventional methods may identify clusters associated with these high-variance features when one wishes to obtain secondary clusters that are more interesting biologically or more strongly associated with a particular outcome of interest. A modification of sparse clustering can be used to identify such secondary clusters or clusters associated with an outcome of interest. This method correctly identifies such clusters of interest in several simulation scenarios. The method is also applied to a large prospective cohort study of temporomandibular disorders and a leukemia microarray data set.