Interpreting social enterprises

Institutional and organizational variety is increasingly characterizing advanced economic systems. While traditional economic theories have focused almost exclusively on profit-maximizing (i.e., for-profit) enterprises and on publicly-owned organizations, the increasing relevance of non-profit organizations, and especially of social enterprises, requires scientists to reflect on a new comprehensive economic approach for explaining this organizational variety. This paper examines the main limitations of the orthodox and institutional theories and asserts the need for creating and testing a new theoretical framework, which considers the way in which diverse enterprises pursue their goals, the diverse motivations driving actors and organizations, and the different learning patterns and routines within organizations. The new analytical framework proposed in the paper draws upon recent developments in the theories of the firm, mainly of an evolutionary and behavioral kind. The firm is interpreted as a coordination mechanism of economic activity, and one whose objectives need not coincide with profit maximization. On the other hand, economic agents driven by motivational complexity and intrinsic, non-monetary motivation play a crucial role in forming firm activity over and above purely monetary and financial objectives. The new framework is thought to be particularly suitable to correctly interpret the emergence and role of nontraditional organizational and ownership forms that are not driven by the profit motive (non-profit organizations), mainly recognized in the legal forms of cooperative firms, non-profit organizations and social enterprises. A continuum of organizational forms ranging from profit making activities to public benefit activities, and encompassing mutual benefit organizations as its core constituent, is envisaged and discussed.

Information overload, choice deferral, and moderating role of need for cognition: Empirical evidence

ABSTRACT Choice deferral due to information overload is an undesirable result of competitive environments. The neoclassical maximization models predict that choice avoidance will not increase as more information is offered to consumers. The theories developed in the consumer behavior field predict that some properties of the environment may lead to behavioral effects and an increase in choice avoidance due to information overload. Based on stimuli generated experimentally and tested among 1,000 consumers, this empirical research provides evidence for the presence of behavioral effects due to information overload and reveals the different effects of increasing the number of options or the number of attributes. This study also finds that the need for cognition moderates these behavioral effects, and it proposes psychological processes that may trigger the effects observed.

Detection and mapping of a lethal locus in a eucalyptus hybrid population

The objective of this work was to verify the existence of a lethal locus in a eucalyptus hybrid population, and to quantify the segregation distortion in the linkage group 3 of the Eucalyptus genome. A E. grandis x E. urophylla hybrid population, which segregates for rust resistance, was genotyped with 19 microsatellite markers belonging to linkage group 3 of the Eucalyptus genome. To quantify the segregation distortion, maximum likelihood (ML) models, specific to outbreeding populations, were used. These models consider the observed marker genotypes and the lethal locus viability as parameters. The ML solutions were obtained using the expectation‑maximization algorithm. A lethal locus in the linkage group 3 was verified and mapped, with high confidence, between the microssatellites EMBRA 189 e EMBRA 122. This lethal locus causes an intense gametic selection from the male side. Its map position is 25 cM from the locus which controls the rust resistance in this population.

Determinação dos fatores de recuperação do 111In e do 99mTc na quantificação de atividade com imagens SPECT

OBJETIVO: Determinar, experimentalmente, os coeficientes de recuperação do 111In e do 99mTc usando imagens SPECT. MATERIAIS E MÉTODOS: Quatro diferentes concentrações de 111In e de 99mTc foram usadas para quantificar a atividade em esferas de diferentes tamanhos. As imagens foram obtidas com um equipamento híbrido SPECT/CT, com dois detectores. A reconstrução das imagens foi realizada usando o método iterativo ordered subset expectation maximization (OSEM). A correção de atenuação foi realizada com o uso de um mapa de atenuação e a correção de espalhamento foi realizada usando a técnica das janelas de energia. RESULTADOS: Os resultados mostraram que o efeito do volume parcial foi observado de forma mais significativa para as esferas com volume < 6 ml. Para o 111In, os resultados mostram uma dependência com relação às concentrações usadas nas esferas e ao nível de background usado. Para o 99mTc, pôde-se observar uma tendência à subestimação dos resultados quando os níveis mais altos de background foram utilizados. CONCLUSÃO: É necessário usar os fatores de correção para compensar o efeito do volume parcial em objetos com volume < 6 ml para ambos os radionuclídeos. A subtração das contagens espúrias presentes nas imagens SPECT foi o fator que mais influenciou na quantificação da atividade nessas esferas.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Soybean yield maps using regular and optimized sample with different configurations by simulated annealing

ABSTRACT This study aimed to compare thematic maps of soybean yield for different sampling grids, using geostatistical methods (semivariance function and kriging). The analysis was performed with soybean yield data in t ha-1 in a commercial area with regular grids with distances between points of 25x25 m, 50x50 m, 75x75 m, 100x100 m, with 549, 188, 66 and 44 sampling points respectively; and data obtained by yield monitors. Optimized sampling schemes were also generated with the algorithm called Simulated Annealing, using maximization of the overall accuracy measure as a criterion for optimization. The results showed that sample size and sample density influenced the description of the spatial distribution of soybean yield. When the sample size was increased, there was an increased efficiency of thematic maps used to describe the spatial variability of soybean yield (higher values of accuracy indices and lower values for the sum of squared estimation error). In addition, more accurate maps were obtained, especially considering the optimized sample configurations with 188 and 549 sample points.