844 resultados para partial least square
Resumo:
Purpose – This paper aims to address the gaps in service recovery strategy assessment. An effective service recovery strategy that prevents customer defection after a service failure is a powerful managerial instrument. The literature to date does not present a comprehensive assessment of service recovery strategy. It also lacks a clear picture of the service recovery actions at managers’ disposal in case of failure and the effectiveness of individual strategies on customer outcomes. Design/methodology/approach – Based on service recovery theory, this paper proposes a formative index of service recovery strategy and empirically validates this measure using partial least-squares path modelling with survey data from 437 complainants in the telecommunications industry in Egypt. Findings – The CURE scale (CUstomer REcovery scale) presents evidence of reliability as well as convergent, discriminant and nomological validity. Findings also reveal that problem-solving, speed of response, effort, facilitation and apology are the actions that have an impact on the customer’s satisfaction with service recovery. Practical implications – This new formative index is of potential value in investigating links between strategy and customer evaluations of service by helping managers identify which actions contribute most to changes in the overall service recovery strategy as well as satisfaction with service recovery. Ultimately, the CURE scale facilitates the long-term planning of effective complaint management. Originality/value – This is the first study in the service marketing literature to propose a comprehensive assessment of service recovery strategy and clearly identify the service recovery actions that contribute most to changes in the overall service recovery strategy.
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The aim of this study was to investigate the effects of numerous milk compositional factors on milk coagulation properties using Partial Least Squares (PLS). Milk from herds of Jersey and Holstein- Friesian cattle was collected across the year and blended (n=55), to maximise variation in composition and coagulation. The milk was analysed for casein, protein, fat, titratable acidity, lactose, Ca2+, urea content, micelles size, fat globule size, somatic cell count and pH. Milk coagulation properties were defined as coagulation time, curd firmness and curd firmness rate measured by a controlled strain rheometer. The models derived from PLS had higher predictive power than previous models demonstrating the value of measuring more milk components. In addition to the well-established relationships with casein and protein levels, CMS and fat globule size were found to have as strong impact on all of the three models. The study also found a positive impact of fat on milk coagulation properties and a strong relationship between lactose and curd firmness, and urea and curd firmness rate, all of which warrant further investigation due to current lack of knowledge of the underlying mechanism. These findings demonstrate the importance of using a wider range of milk compositional variables for the prediction of the milk coagulation properties, and hence as indicators of milk suitability for cheese making.
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This paper describes a novel on-line learning approach for radial basis function (RBF) neural network. Based on an RBF network with individually tunable nodes and a fixed small model size, the weight vector is adjusted using the multi-innovation recursive least square algorithm on-line. When the residual error of the RBF network becomes large despite of the weight adaptation, an insignificant node with little contribution to the overall system is replaced by a new node. Structural parameters of the new node are optimized by proposed fast algorithms in order to significantly improve the modeling performance. The proposed scheme describes a novel, flexible, and fast way for on-line system identification problems. Simulation results show that the proposed approach can significantly outperform existing ones for nonstationary systems in particular.
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This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.
Resumo:
The accurate estimate of the surface longwave fluxes contribution is important for the calculation of the surface radiation budget, which in turn controls all the components of the surface energy budget, such as evaporation and the sensible heat fluxes. This study evaluates the performance of the various downward longwave radiation parameterizations for clear and all-sky days applied to the Sertozinho region in So Paulo, Brazil. Equations have been adjusted to the observations of longwave radiation. The adjusted equations were evaluated for every hour throughout the day and the results showed good fits for most of the day, except near dawn and sunset, followed by nighttime. The seasonal variation was studied by comparing the dry period against the rainy period in the dataset. The least square linear regressions resulted in coefficients equal to the coefficients found for the complete period, both in the dry period and in the rainy period. It is expected that the best fit equation to the observed data for this site be used to produce estimates in other regions of the State of So Paulo, where such information is not available.
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We developed a general method for determination of water production rates from groundbased visual observations and applied it to Comet Hale-Bopp. Our main objective is to extend the method to include total visual magnitude observations obtained with CCD detector and V filter in the analysis of total visual magnitudes. We compare the CCD V-broadband careful observations of Liller [Liller, W. Pre-perihelion CCD photometry of Comet 1995 01 (Hale-Bopp). Planet. Space Sci. 45, 1505-1513, 1997; Liller, W. CCD photometry of Comet C/1995 O1 (Hale-Bopp): 1995-2000. Int. Comet Quart. 23(3), 93-97, 2001] with the total visual magnitude observations from experienced international observers found in the International Comet Quarterly (ICQ) archive. A data set of similar to 400 CCD observations covering about the same 6 years time span of the similar to 12,000 ICQ selected total visual magnitude observations were used in the analysis. A least-square method applied to the water production rates, yields power laws as a function of the heliocentric distances for the pre- and post-perihelion phases. The average dimension of the nucleus as well as its effective active area is determined and compared with values published in the literature. (C) 2009 COSPAR. Published by Elsevier Ltd. All rights reserved.
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Visualization of high-dimensional data requires a mapping to a visual space. Whenever the goal is to preserve similarity relations a frequent strategy is to use 2D projections, which afford intuitive interactive exploration, e. g., by users locating and selecting groups and gradually drilling down to individual objects. In this paper, we propose a framework for projecting high-dimensional data to 3D visual spaces, based on a generalization of the Least-Square Projection (LSP). We compare projections to 2D and 3D visual spaces both quantitatively and through a user study considering certain exploration tasks. The quantitative analysis confirms that 3D projections outperform 2D projections in terms of precision. The user study indicates that certain tasks can be more reliably and confidently answered with 3D projections. Nonetheless, as 3D projections are displayed on 2D screens, interaction is more difficult. Therefore, we incorporate suitable interaction functionalities into a framework that supports 3D transformations, predefined optimal 2D views, coordinated 2D and 3D views, and hierarchical 3D cluster definition and exploration. For visually encoding data clusters in a 3D setup, we employ color coding of projected data points as well as four types of surface renderings. A second user study evaluates the suitability of these visual encodings. Several examples illustrate the framework`s applicability for both visual exploration of multidimensional abstract (non-spatial) data as well as the feature space of multi-variate spatial data.
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Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.
Resumo:
The glycolytic enzyme glyceraldehyde-3 -phosphate dehydrogenase (GAPDH) is as an attractive target for the development of novel antitrypanosomatid agents. In the present work, comparative molecular field analysis and comparative molecular similarity index analysis were conducted on a large series of selective inhibitors of trypanosomatid GAPDH. Four statistically significant models were obtained (r(2) > 0.90 and q(2) > 0.70), indicating their predictive ability for untested compounds. The models were then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results. Molecular modeling studies provided further insight into the structural basis for selective inhibition of trypanosomatid GAPDH.
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A new method is presented for spectrophotometric determination of total polyphenols content in wine. The procedure is a modified CUPRAC method based on the reduction of Cu(II), in hydroethanolic medium (pH 7.0) in the presence of neocuproine (2,9-dimethyl-1,10-phenanthroline), by polyphenols, yielding a Cu(I) complexes with maximum absorption peak at 450 nm. The absorbance values are linear (r = 0.998, n = 6) with tannic acid concentrations from 0.4 to 3.6 mu mol L(-1). The limit of detection obtained was 0.41 mu mol L(-1) and relative standard deviation 1.2% (1 mu mol L(-1); n = 8). Recoveries between 80% and 110% (mean value of 95%) were calculated for total polyphenols determination in 14 commercials and 2 synthetic wine samples (with and without sulphite). The proposed procedure is about 1.5 more sensitive than the official Folin-Ciocalteu method. The sensitivities of both methods were compared by the analytical responses of several polyphenols tested in each method. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
Molecular orbital calculations were carried out on a set of 28 non-imidazole H(3) antihistamine compounds using the Hartree-Fock method in order to investigate the possible relationships between electronic structural properties and binding affinity for H3 receptors (pK(i)). It was observed that the frontier effective-for-reaction molecular orbital (FERMO) energies were better correlated with pK(i) values than highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. Exploratory data analysis through hierarchical cluster (HCA) and principal component analysis (PCA) showed a separation of the compounds in two sets, one grouping the molecules with high pK(i) values, the other gathering low pK(i) value compounds. This separation was obtained with the use of the following descriptors: FERMO energies (epsilon(FERMO)), charges derived from the electrostatic potential on the nitrogen atom (N(1)), electronic density indexes for FERMO on the N(1) atom (Sigma((FERMO))c(i)(2)). and electrophilicity (omega`). These electronic descriptors were used to construct a quantitative structure-activity relationship (QSAR) model through the partial least-squares (PLS) method with three principal components. This model generated Q(2) = 0.88 and R(2) = 0.927 values obtained from a training set and external validation of 23 and 5 molecules, respectively. After the analysis of the PLS regression equation and the values for the selected electronic descriptors, it is suggested that high values of FERMO energies and of Sigma((FERMO))c(i)(2), together with low values of electrophilicity and pronounced negative charges on N(1) appear as desirable properties for the conception of new molecules which might have high binding affinity. 2010 Elsevier Inc. All rights reserved.
Resumo:
O presente trabalho teve como objetivo a identificação de atributos relacionados à atratividade de clientes em clusters comerciais, na percepção de consumidores. Partindo-se da atratividade de clientes para lojas, desenvolveu-se um construto de avaliação de atratividade de clientes para clusters comerciais. Por meio de estudo descritivo-quantitativo junto a 240 consumidores, em dois reconhecidos clusters comerciais, utilizando-se a técnica de PLS-PM (Partial Least Squares Path Modeling), avaliou-se a relação entre a atratividade de clientes (variável reflexiva) e as dimensões do mix varejista de clusters comerciais (variáveis latentes), a partir do tratamento de indicadores de efeitos observáveis. Como principais resultados, observou-se que: (1) atratividade está associada significativamente às variáveis latentes, sugerindo robustez do modelo; (2) condições de compra e preços são dimensões com maior associação à atratividade de clientes, embora lojas, produtos e atendimento apresentem relevância; e (3) localização apresentou-se como dimensão menos correlacionada à atratividade de clientes para ambos os clusters.
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Essa tese foca em diferentes perspectivas sobre CSF (Fatores Críticos de Sucess) em implementações de ERP (Enterprise Resource Planning). A literatura atual foca nos CSF sob o ponto de vista da alta gerência da organização e classifica esses CSF baseado nessa visão. Essa tese irá apresentar a visão do time de implementação de ERP sob os principais CSF e irá utilizar um estudo de caso para avaliar se a alta gerência e o time de implementação compartilham a mesma visão. Além disso ess tese irá propor uma relação entre o sucesso na implementação de ERP e os CSF pesquisados, usando o método PLS (Partial Least Squares) para analisar as respostas do time de implementação a um questionário desenvolvido para medir sucesso na implementação de ERP.
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As fraudes contábeis representam uma grande perda para a economia global tanto na esfera pública quanto privada, destacando, assim, os prejuízos sociais ocasionados por elas. Nesta perspectiva, diversas pesquisas têm demonstrado que as denúncias são um dos principais mecanismos de detecção de fraudes nas organizações. Inspirado em Taylor e Curtis (2010), o presente trabalho tem como objetivo identificar a influência das “camadas” pessoal, organizacional, profissional na intenção individual em denunciar uma situação fraudulenta que o mesmo tenha conhecimento. Ressalta-se, porém, a inclusão de uma “camada social”, bem como a consideração de aspectos peculiares da cultura brasileira na elaboração e análise das hipóteses. Para operacionalização das camadas foram utilizadas variáveis latentes coletadas por meio de um questionário respondido por 124 contabilistas. Para mensuração da influência na intenção em denunciar foi utilizado um Modelo de Equação Estrutural (SEM) estimado pelo método dos Mínimos Quadrados Parciais (PLS). Os resultados obtidos confirmaram a importância das camadas de influência no comportamento do eventual denunciante. Destaca-se, principalmente, a importância da camada social, a qual, além de influenciar diretamente de forma significativa a Intenção de Denunciar, também media o impacto da camada profissional. A camada organizacional não afeta de forma significante a intenção de denunciar. Nota-se, também o grande impacto causado pela camada pessoal. Tais fatos corroboram alguns dos principais traços da cultura brasileira, como a prevalência de relações informais e pessoais em detrimento de relações formais, além de identificar os traços da ambiguidade moral.
Resumo:
No contexto de um mercado tão competitivo, ter equipes bem preparadas e alocadas adequadamente é fundamental para a sobrevivência das empresas. O presente estudo objetiva identificar o reflexo na satisfação dos clientes e nos resultados das empresas, a partir do conhecimento das pessoas que trabalham na linha de frente dessas empresas, aqueles profissionais que exercem um papel importante de negociação, identificando o que eles valorizam subjetivamente em uma negociação. Por meio da ferramenta SVI (Subjective Value Inventory), desenvolvida por Curhan et al (2006), a partir das dimensões de autoimagem independente e interdependente, busca-se identificar os valores subjetivos dos negociadores de um banco de varejo brasileiro, responsáveis por parte significativa das negociações e dos resultados da empresa, relativamente aos sentimentos sobre si mesmos (Self), aos resultados instrumentais, e ao processo e relacionamento (Rapport), utilizando a confiança interpessoal como moderadora nessa relação. Após identificados os valores subjetivos desses negociadores em negociação, relacionar os resultados encontrados com a satisfação dos clientes. Para isso, foi realizada uma pesquisa quantitativa, com a aplicação de um questionário fechado e estruturado a 532 negociadores desse banco que atuam nos estados de Santa Catarina, Rio de Janeiro e Maranhão, responsáveis pelo relacionamento, prospecção e realização de negócios com os clientes da instituição, nos segmentos pessoa física, micro e pequenas empresas e governo. Os dados foram analisados a partir de técnicas estatísticas, utilizando-se o método dos Mínimos Quadrados Parciais. Observou-se que mais de 40% da satisfação de cliente é explicada pelos valores subjetivos dos negociadores. O estudo apontou como resultados, dentre outros, que os gerentes de negócios com autoimagem independente valorizam o Self e os resultados instrumentais em uma negociação, e que a confiança interpessoal cognitiva modera negativamente essa relação. Ainda, que aqueles gerentes de negócios com autoimagem interdependente, valorizam o Rapport em uma negociação e que essa valorização está positivamente relacionada com a satisfação dos clientes.