984 resultados para method variance


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Operational capabilities são caracterizadas como um recurso interno da firma e fonte de vantagem competitiva. Porém, a literatura de estratégia de operações fornece uma definição constitutiva inadequada para as operational capabilities, desconsiderando a relativização dos diferentes contextos, a limitação da base empírica, e não explorando adequadamente a extensa literatura sobre práticas operacionais. Quando as práticas operacionais são operacionalizadas no ambiente interno da firma, elas podem ser incorporadas as rotinas organizacionais, e através do conhecimento tácito da produção se transformar em operational capabilities, criando assim barreiras à imitação. Apesar disso, poucos são os pesquisadores que exploram as práticas operacionais como antecedentes das operational capabilities. Baseado na revisão da literatura, nós investigamos a natureza das operational capabilities; a relação entre práticas operacionais e operational capabilities; os tipos de operational capabilities que são caracterizadas no ambiente interno da firma; e o impacto das operational capabilities no desempenho operacional. Nós conduzimos uma pesquisa de método misto. Na etapa qualitativa, nós conduzimos estudos de casos múltiplos com quatro firmas, duas multinacionais americanas que operam no Brasil, e duas firmas brasileiras. Nós coletamos os dados através de entrevistas semi-estruturadas com questões semi-abertas. Elas foram baseadas na revisão da literatura sobre práticas operacionais e operational capabilities. As entrevistas foram conduzidas pessoalmente. No total 73 entrevistas foram realizadas (21 no primeiro caso, 18 no segundo caso, 18 no terceiro caso, e 16 no quarto caso). Todas as entrevistas foram gravadas e transcritas literalmente. Nós usamos o sotware NVivo. Na etapa quantitativa, nossa amostra foi composta por 206 firmas. O questionário foi criado a partir de uma extensa revisão da literatura e também a partir dos resultados da fase qualitativa. O método Q-sort foi realizado. Um pré-teste foi conduzido com gerentes de produção. Foram realizadas medidas para reduzir Variância de Método Comum. No total dez escalas foram utilizadas. 1) Melhoria Contínua; 2) Gerenciamento da Informação; 3) Aprendizagem; 4) Suporte ao Cliente; 5) Inovação; 6) Eficiência Operacional; 7) Flexibilidade; 8) Customização; 9) Gerenciamento dos Fornecedores; e 10) Desempenho Operacional. Nós usamos análise fatorial confirmatória para confirmar a validade de confiabilidade, conteúdo, convergente, e discriminante. Os dados foram analisados com o uso de regressões múltiplas. Nossos principais resultados foram: Primeiro, a relação das práticas operacionais como antecedentes das operational capabilities. Segundo, a criação de uma tipologia dividida em dois construtos. O primeiro construto foi chamado de Standalone Capabilities. O grupo consiste de zero order capabilities tais como Suporte ao Cliente, Inovação, Eficiência Operacional, Flexibilidade, e Gerenciamento dos Fornecedores. Estas operational capabilities têm por objetivo melhorar os processos da firma. Elas têm uma relação direta com desempenho operacional. O segundo construto foi chamado de Across-the-Board Capabilities. Ele é composto por first order capabilities tais como Aprendizagem Contínua e Gerenciamento da Informação. Estas operational capabilities são consideradas dinâmicas e possuem o papel de reconfigurar as Standalone Capabilities.

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This study examined the role of information, efficacy, and 3 stressors in predicting adjustment to organizational change. Participants were 589 government employees undergoing an 18-month process of regionalization. To examine if the predictor variables had long-term effects on adjustment, the authors assessed psychological well-being, client engagement, and job satisfaction again at a 2-year follow-up. At Time 1, there was evidence to suggest that information was indirectly related to psychological well-being, client engagement, and job satisfaction, via its positive relationship to efficacy. There also was evidence to suggest that efficacy was related to reduced stress appraisals, thereby heightening client engagement. Last, there was consistent support for the stress-buffering role of Time I self-efficacy in the prediction of Time 2 job satisfaction.

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Uncertainty is a major source of psychological strain during organizational change. This study tested a model of change-related communication, uncertainty, and control and their relationship with psychological strain, job satisfaction, and turnover intentions. Self-report data were obtained from staff at a psychiatric hospital undergoing restructuring. Results indicated that uncertainty had a direct and an indirect (via feelings of lack of control) relationship with psychological strain. Partialling out common method variance led to a complete mediation of this relationship by control. Other predictions about the relationship of these variables with psychological strain, job satisfaction, and turnover intentions were supported. Implications for future research and practice of change communication are discussed.

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Purpose: Previous research has emphasized the pivotal role that salespeople play in customer satisfaction. In this regard, the relationship between salespeople's attitudes, skills, and characteristics, and customer satisfaction remains an area of interest. The paper aims to make three contributions: first, it seeks to examine the impact of salespeople's satisfaction, adaptive selling, and dominance on customer satisfaction. Second, this research aims to use dyadic data, which is a better test of the relationships between constructs since it avoids common method variance. Finally, in contrast to previous research, it aims to test all of the customers of salespeople rather than customers selected by salespeople. Design/methodology/approach: The study employs multilevel analysis to examine the relationship between salespeople's satisfaction with the firm on customer satisfaction, using a dyadic, matched business-to-business sample of a large European financial service provider that comprises 188 customers and 18 employees. Findings: The paper finds that customers' evaluation of service quality, product quality, and value influence customer satisfaction. The analysis at the selling firm's employee level shows that adaptive selling and employee satisfaction positively impact customer satisfaction, while dominance is negatively related to customer satisfaction. Practical implications: Research shows that customer-focus is a key driver in the success of service companies. Customer satisfaction is regarded as a prerequisite for establishing long-term, profitable relations between company and customer, and customer contact employees are key to nurturing this relationship. The role of salespeople's attitudes, skills, and characteristics in the customer satisfaction process are highlighted in this paper. Originality/value: The use of dyadic, multilevel studies to assess the nature of the relationship between employees and customers is, to date, surprisingly limited. The paper examines the link between employee attitudes, skills, and characteristics, and customer satisfaction in a business-to-business setting in the financial service sector, differentiating between customer- and employee-level drivers of business customer satisfaction.

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Robust descriptor matching across varying lighting conditions is important for vision-based robotics. We present a novel strategy for quantifying the lighting variance of descriptors. The strategy works by utilising recovered low dimensional mappings from Isomap and our measure of the lighting variance of each of these mappings. The resultant metric allows different descriptors to be compared given a dataset and a set of keypoints. We demonstrate that the SIFT descriptor typically has lower lighting variance than other descriptors, although the result depends on semantic class and lighting conditions.

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This paper presents a new metric, which we call the lighting variance ratio, for quantifying descriptors in terms of their variance to illumination changes. In many applications it is desirable to have descriptors that are robust to changes in illumination, especially in outdoor environments. The lighting variance ratio is useful for comparing descriptors and determining if a descriptor is lighting invariant enough for a given environment. The metric is analysed across a number of datasets, cameras and descriptors. The results show that the upright SIFT descriptor is typically the most lighting invariant descriptor.

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Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.

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This paper proposes an innovative optimized parametric method for construction of prediction intervals (PIs) for uncertainty quantification. The mean-variance estimation (MVE) method employs two separate neural network (NN) models to estimate the mean and variance of targets. A new training method is developed in this study that adjusts parameters of NN models through minimization of a PI-based cost functions. A simulated annealing method is applied for minimization of the nonlinear non-differentiable cost function. The performance of the proposed method for PI construction is examined using monthly data sets taken from a wind farm in Australia. PIs for the wind farm power generation are constructed with five confidence levels between 50% and 90%. Demonstrated results indicate that valid PIs constructed using the optimized MVE method have a quality much better than the traditional MVE-based PIs.

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A statistical optimized technique for rapid development of reliable prediction intervals (PIs) is presented in this study. The mean-variance estimation (MVE) technique is employed here for quantification of uncertainties related with wind power predictions. In this method, two separate neural network models are used for estimation of wind power generation and its variance. A novel PI-based training algorithm is also presented to enhance the performance of the MVE method and improve the quality of PIs. For an in-depth analysis, comprehensive experiments are conducted with seasonal datasets taken from three geographically dispersed wind farms in Australia. Five confidence levels of PIs are between 50% and 90%. Obtained results show while both traditional and optimized PIs are hypothetically valid, the optimized PIs are much more informative than the traditional MVE PIs. The informativeness of these PIs paves the way for their application in trouble-free operation and smooth integration of wind farms into energy systems. © 2014 Elsevier Ltd. All rights reserved.