Ensuring dynamic strategic fit of firms that compete globally in alliances and networks: proposing the Global SNA - Strategic Network Analysis - framework

In order to sustain their competitive advantage in the current increasingly globalized and turbulent context, more and more firms are competing globally in alliances and networks that oblige them to adopt new managerial paradigms and tools. However, their strategic analyses rarely take into account the strategic implications of these alliances and networks, considering their global relational characteristics, admittedly because of a lack of adequate tools to do so. This paper contributes to research that seeks to fill this gap by proposing the Global Strategic Network Analysis - SNA - framework. Its purpose is to help firms that compete globally in alliances and networks to carry out their strategic assessments and decision-making with a view to ensuring dynamic strategic fit from both a global and relational perspective.

A blockmodel study of managerial hierarchies, verbal networks, and organizational culture in four hospitals

This study demonstrates and applies a social network methodology for studying the dynamics of hierarchies in organizations. Social network (blockmodel) analysis of verbal networks in four hospitals contrasted hierarchical and structurally equivalent partitions of the sociomatrices of frequent ties and perceptions of organizational culture. It was found that the verbal networks in these organizations follow a center periphery pattern rather than a hierarchical logic and that perceptions of culture vary more by verbal network than by formal hierarchy. The perceptions of culture of central groups in one organization are much like those of peripheral groups in another. In all four hospitals, structurally equivalent social networks are more important in predicting subcultures than are hierarchical groupings and hierarchy has a limited impact on the development of verbal networks. These findings suggest the value of an amoeba rather than a pyramid metaphor in interpreting the cultures and relational structures of organizations.

HUMAN T-LYMPHOTROPIC VIRUS 1 (HTLV-1) AND HUMAN T-LYMPHOTROPIC VIRUS 2 (HTLV-2): GEOGRAPHICAL RESEARCH TRENDS AND COLLABORATION NETWORKS (1989-2012)

Publications are often used as a measure of research work success. Human T-lymphotropic virus (HTLV) type 1 and 2 are human retroviruses, which were discovered in the early 1980s, and it is estimated that 15-20 million people are infected worldwide. This article describes a bibliometric review and a coauthorship network analysis of literature on HTLV indexed in PubMed in a 24-year period. A total of 7,564 documents were retrieved, showing a decrease in the number of documents from 1996 to 2007. HTLV manuscripts were published in 1,074 journals. Japan and USA were the countries with the highest contribution in this field (61%) followed by France (8%). Production ranking changed when the number of publications was normalized by population (Dominican Republic and Japan), by gross domestic product (Guinea-Bissau and Gambia), and by gross national income per capita (Brazil and Japan). The present study has shed light on some of the defining features of scientific collaboration performed by HTLV research community, such as the existence of core researchers responsible for articulating the development of research in the area, facilitating wider collaborative relationships and the integration of new authors in the research groups.

Evolution of coauthorship networks: worldwide scientific production on leishmaniasis

Introduction Collaboration is one of the defining features of contemporary scientific research, and it is particularly important with regard to neglected diseases that primarily affect developing countries. Methods The present study has identified publications on leishmaniasis in the Medline database from 1945 to 2010, analyzing them according to bibliometric indicators and statistics from social network analysis. Examining aspects such as scientific production, diachronic evolution, and collaboration and configuration of the research groups in the field, we have considered the different types of Leishmania studied and the institutional affiliation and nationality of the authors. Results Seven-hundred and thirty-five authors participate in 154 prominent research clusters or groups. Although the most predominant and consolidated collaborations are characterized by members from the same country studying the same type of Leishmania, there are also notable links between authors from different countries or who study different clinical strains of the disease. Brazil took the lead in this research, with numerous Brazilian researchers heading different clusters in the center of the collaboration network. Investigators from the USA, India, and European countries, such as France, Spain, the United Kingdom, and Italy, also stand out within the network. Conclusions Research should be fostered in countries such as Bangladesh, Nepal, Sudan, and Ethiopia, where there is a high prevalence of different forms of the disease but limited research development with reference authors integrated into the collaboration networks.

Future trypanosomatid phylogenies: refined homologies, supertrees and networks

There has been good progress in inferring the evolutionary relationships within trypanosomes from DNA data as until relatively recently, many relationships have remained rather speculative. Ongoing molecular studies have provided data that have adequately shown Trypanosoma to be monophyletic and, rather surprisingly, that there are sharply contrasting levels of genetic variation within and between the major trypanosomatid groups. There are still, however, areas of research that could benefit from further development and resolution that broadly fall upon three questions. Are the current statements of evolutionary homology within ribosomal small sub-unit genes in need of refinement? Can the published phylograms be expanded upon to form `supertrees' depicting further relationships? Does a bifurcating tree structure impose an untenable dogma upon trypanosomatid phylogeny where hybridisation or reticulate evolutionary steps have played a part? This article briefly addresses these three questions and, in so doing, hopes to stimulate further interest in the molecular evolution of the group.

Coevolutionary networks: a novel approach to understanding the relationships of humans with the infectious agents

Human organism is interpenetrated by the world of microorganisms, from the conception until the death. This interpenetration involves different levels of interactions between the partners including trophic exchanges, bi-directional cell signaling and gene activation, besides genetic and epigenetic phenomena, and tends towards mutual adaptation and coevolution. Since these processes are critical for the survival of individuals and species, they rely on the existence of a complex organization of adaptive systems aiming at two apparently conflicting purposes: the maintenance of the internal coherence of each partner, and a mutually advantageous coexistence and progressive adaptation between them. Humans possess three adaptive systems: the nervous, the endocrine and the immune system, each internally organized into subsystems functionally connected by intraconnections, to maintain the internal coherence of the system. The three adaptive systems aim at the maintenance of the internal coherence of the organism and are functionally linked by interconnections, in such way that what happens to one is immediately sensed by the others. The different communities of infectious agents that live within the organism are also organized into functional networks. The members of each community are linked by intraconnections, represented by the mutual trophic, metabolic and other influences, while the different infectious communities affect each other through interconnections. Furthermore, by means of its adaptive systems, the organism influences and is influenced by the microbial communities through the existence of transconnections. It is proposed that these highly complex and dynamic networks, involving gene exchange and epigenetic phenomena, represent major coevolutionary forces for humans and microorganisms.

Multimedia materials for education, training, and advocacy in international health: experiences with the Schistosomiasis Control Initiative CD-ROM

We describe an innovative use of multimedia materials to support training and advocacy within a schistosomiasis control programme. The Schistosomiasis Control Initiative (SCI) at Imperial College London works with selected sub-Saharan African countries to develop schistosomiasis control programmes. Two elements of the SCI programme were supported by multimedia materials developed at the Wellcome Trust in collaboration with the SCI: (1) training of programme managers, district health officers, and those delivering practical elements of the programme; and (2) advocacy targeted at decision-makers and donors. Evaluation of the materials revealed high reported ratings for both user satisfaction and impact from use of the product. From this experience we draw out several general messages about development of multimedia materials and how these will play a growing future role in promoting training within international health.

Networks in Argentine agriculture: a multiple-case study approach

Argentina is among the four largest producers of soybeans, sunflower, corn, and wheat, among other agricultural products. Institutional and policy changes during the 1990s fostered the development of Argentine agriculture and the introduction of innovative process and product technologies (no-till, agrochemicals, GMO, GPS) and new investments in modern, large-scale sunflower and soybean processing plants. In addition to technological changes, a "quiet revolution" occurred in the way agricultural production was carried out and organized: from self-production or ownership agriculture to a contract-based agriculture. The objective of this paper is to explore and describe the emergence of networks in the Argentine crop production sector. The paper presents and describes four cases that currently represent about 50% of total grain and oilseed production in Argentina: "informal hybrid form", "agricultural trust fund", "investor-oriented corporate structure", and "network of networks". In all cases, hybrid forms involve a group of actors linked by common objectives, mainly to gain scale, share resources, and improve the profitability of the business. Informal contracts seem to be the most common way of organizing the agriculture process, but using short-term contracts and sequential interfirm collaboration. Networks of networks involve long-term relationships and social development, and reciprocal interfirm collaboration. Agricultural trust fund and investor-oriented corporate structures have combined interfirm collaboration and medium-term relationships. These organizational forms are highly flexible and show a great capacity to adapt to challenges; they are competitive because they enjoy aligned incentives, flexibility, and adaptability.

Nursing Actions in practicing inpatient advocacy in a Burn Unit

OBJECTIVEUnderstanding nursing actions in the practice of inpatient advocacy in a burn unit.METHODA single and descriptive case study, carried out with nurses working in a referral burn center in southern Brazil. Data were collected through focus group technique, between February and March 2014, in three meetings. Data was analysed through discursive textual analysis.RESULTSThree emerging categories were identified, namely: (1) instructing the patient; (2) protecting the patient; and (3) ensuring the quality of care.CONCLUSIONSThis study identified that the nurses investigated exercised patient advocacy and that the recognition of their actions is an advance for the profession, contributing to the autonomy of nurses and the effectiveness of patients' rights and social justice.

Adolescent support networks in a health care context: the interface between health, family and education

AbstractOBJECTIVEAnalyze adolescents' perceptions about support networks and their health needs.METHODAnalytical and interpretive study using focus groups conducted in municipal state schools in Fortaleza, in the State of Ceará during the first semester of 2012. The sample comprised 36 male and female adolescents aged between 13 and 16 years attending the ninth grade of the second phase of elementary school.RESULTSThematic analysis revealed that the health care support network and interaction between health professionals, education professionals and family members was insufficient, constituting a lack of an integrated network to enable and provide support for health promotion.CONCLUSIONCoordination between education, health and family services has the potential to act as a support network to help meet adolescents' healthcare needs and demands.

Nursing beliefs and actions in exercising patient advocacy in a hospital context

AbstractOBJECTIVEAnalyzing beliefs and actions of nurses in exercising patient advocacy in a hospital context.METHODA quantitative cross-sectional exploratory and descriptive study, conducted with 153 nurses from two hospitals in southern Brazil, one public and one philanthropic, by applying Protective Nursing Advocacy Scale - Brazilian version. Data were analyzed using descriptive statistics and analysis of variance.RESULTSNurses believe they are advocating for patients in their workplaces, and agree that they should advocate, especially when vulnerable patients need their protection. Personal values and professional skills have been identified as major sources of support for the practice of advocacy.CONCLUSIONNurses do not disagree nor agree that advocating for patients in their working environments can bring them negative consequences. It is necessary to recognize how the characteristics of public and private institutions have helped or not helped in exercising patient advocacy by nurses.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks

This study evaluates the application of an intelligent hybrid system for time-series forecasting of atmospheric pollutant concentration levels. The proposed method consists of an artificial neural network combined with a particle swarm optimization algorithm. The method not only searches relevant time lags for the correct characterization of the time series, but also determines the best neural network architecture. An experimental analysis is performed using four real time series and the results are shown in terms of six performance measures. The experimental results demonstrate that the proposed methodology achieves a fair prediction of the presented pollutant time series by using compact networks.