914 resultados para Three Factor Model
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A Internet está inserida no cotidiano do indivíduo, e torna-se cada vez mais acessível por meio de diferentes tipos de dispositivos. Com isto, diversos estudos foram realizados com o intuito de avaliar os reflexos do seu uso excessivo na vida pessoal, acadêmica e profissional. Esta dissertação buscou identificar se a perda de concentração e o isolamento social são alguns dos reflexos individuais que o uso pessoal e excessivo de aplicativos de comunicação instantânea podem resultar no ambiente de trabalho. Entre as variáveis selecionadas para avaliar os aspectos do uso excessivo de comunicadores instantâneos tem-se a distração digital, o controle reduzido de impulso, o conforto social e a solidão. Através de uma abordagem de investigação quantitativa, utilizaram-se escalas aplicadas a uma amostra de 283 pessoas. Os dados foram analisados por meio de técnicas estatísticas multivariadas como a Análise Fatorial Exploratória e para auferir a relação entre as variáveis, a Regressão Linear Múltipla. Os resultados deste estudo confirmam que o uso excessivo de comunicadores instantâneos está positivamente relacionado com a perda de concentração, e a variável distração digital exerce uma influência maior do que o controle reduzido de impulso. De acordo com os resultados, não se podem afirmar que a solidão e o conforto social exercem relações com aumento do isolamento social, devido à ausência do relacionamento entre os construtos.
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This study examines the concept of engagement in samples of volunteers from different non-profit organisations. Study 1 analyzes the psychometric properties of the abbreviated version of the Utrecht Work Engagement Scale (UWES) (Schaufeli, Bakker, & Salanova, 2006a). Two factorial structures are examined: one-dimensional and three-dimensional structures. Based on the Three-Stage Model of Volunteers’ Duration of Service (Chacón, Vecina, & Dávila, 2007), Study 2 investigates the relationship between engagement, volunteer satisfaction, and intention to remain in a sample of new volunteers and the relationship between engagement, organisational commitment, and intention to remain in a sample of veteran volunteers. Moderated mediation analysis is provided using duration of service as a moderator in order to set a splitting point between new and veteran volunteers. The results of the confirmatory factor analysis suggest that the three-factor model fits better to the data. Regarding the structural models, the first one shows that engagement is crucial to volunteer satisfaction during the first stage, while volunteer satisfaction is the key variable in explaining intention to continue. The second structural model shows that engagement reinforces the participant’s commitment to the organisation, while organizational commitment predicts intention to continue. Both models demonstrate a notable decline when samples are changed.
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Thesis (Ph.D.)--University of Washington, 2016-06
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This empirical study employs a different methodology to examine the change in wealth associated with mergers and acquisitions (M&As) for US firms. Specifically, we employ the standard CAPM, the Fama-French three-factor model and the Carhart four-factor models within the OLS and GJR-GARCH estimation methods to test the behaviour of the cumulative abnormal returns (CARs). Whilst the standard CAPM captures the variability of stock returns with the overall market, the Fama-French factors capture the risk factors that are important to investors. Additionally, augmenting the Fama-French three-factor model with the Carhart momentum factor to generate the four-factor captures additional pricing elements that may affect stock returns. Traditionally, estimates of abnormal returns (ARs) in M&As situations rely on the standard OLS estimation method. However, the standard OLS will provide inefficient estimates of the ARs if the data contain ARCH and asymmetric effects. To minimise this problem of estimation efficiency we re-estimated the ARs using GJR-GARCH estimation method. We find that there is variation in the results both as regards the choice models and estimation methods. Besides these variations in the estimated models and the choice of estimation methods, we also tested whether the ARs are affected by the degree of liquidity of the stocks and the size of the firm. We document significant positive post-announcement cumulative ARs (CARs) for target firm shareholders under both the OLS and GJR-GARCH methods across all three methodologies. However, post-event CARs for acquiring firm shareholders were insignificant for both sets of estimation methods under the three methodologies. The GJR-GARCH method seems to generate larger CARs than those of the OLS method. Using both market capitalization and trading volume as a measure of liquidity and the size of the firm, we observed strong return continuations in the medium firms relative to small and large firms for target shareholders. We consistently observed market efficiency in small and large firm. This implies that target firms for small and large firms overreact to new information resulting in a more efficient market. For acquirer firms, our measure of liquidity captures strong return continuations for small firms under the OLS estimates for both CAPM and Fama-French three-factor models, whilst under the GJR-GARCH estimates only for Carhart model. Post-announcement bootstrapping simulated CARs confirmed our earlier results.
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The number of dividend paying firms has been on the decline since the popularity of stock repurchases in the 1980s, and the recent financial crisis has brought about a wave of dividend reductions and omissions. This dissertation examined the U.S. firms and American Depository Receipts that are listed on the U.S. equity exchanges according to their dividend paying history in the previous twelve quarters. While accounting for the state of the economy, the firm’s size, profitability, earned equity, and growth opportunities, it determines whether or not the firm will pay a dividend in the next quarter. It also examined the likelihood of a dividend change. Further, returns of firms were examined according to their dividend paying history and the state of the economy using the Fama-French three-factor model. Using forward, backward, and step-wise selection logistic regressions, the results show that firms with a history of regular and uninterrupted dividend payments are likely to continue to pay dividends, while firms that do not have a history of regular dividend payments are not likely to begin to pay dividends or continue to do so. The results of a set of generalized polytomous logistic regressions imply that dividend paying firms are more likely to reduce dividend payments during economic expansions, as opposed to recessions. Also the analysis of returns using the Fama-French three factor model reveals that dividend paying firms are earning significant abnormal positive returns. As a special case, a similar analysis of dividend payment and dividend change was applied to American Depository Receipts that trade on the NYSE, NASDAQ, and AMEX exchanges and are issued by the Bank of New York Mellon. Returns of American Depository Receipts were examined using the Fama-French two-factor model for international firms. The results of the generalized polytomous logistic regression analyses indicate that dividend paying status and economic conditions are also important for dividend level change of American Depository Receipts, and Fama-French two-factor regressions alone do not adequately explain returns for these securities.
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For the last three decades, the Capital Asset Pricing Model (CAPM) has been a dominant model to calculate expected return. In early 1990% Fama and French (1992) developed the Fama and French Three Factor model by adding two additional factors to the CAPM. However even with these present models, it has been found that estimates of the expected return are not accurate (Elton, 1999; Fama &French, 1997). Botosan (1997) introduced a new approach to estimate the expected return. This approach employs an equity valuation model to calculate the internal rate of return (IRR) which is often called, 'implied cost of equity capital" as a proxy of the expected return. This approach has been gaining in popularity among researchers. A critical review of the literature will help inform hospitality researchers regarding the issue and encourage them to implement the new approach into their own studies.
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This study explored the relationship between workplace discrimination climate on team effectiveness through three serial mediators: collective value congruence, team cohesion, and collective affective commitment. As more individuals of marginalized groups diversify the workforce and as more organizations move toward team-based work (Cannon-Bowers & Bowers, 2010), it is imperative to understand how employees perceive their organization’s discriminatory climate as well as its effect on teams. An archival dataset consisting of 6,824 respondents was used, resulting in 332 work teams with five or more members in each. The data were collected as part of an employee climate survey administered in 2011 throughout the United States’ Department of Defense. The results revealed that the indirect effect through M1 (collective value congruence) and M2 (team cohesion) best accounted for the relationship between workplace discrimination climate (X) and team effectiveness (Y). Meaning, on average, teams that reported a greater climate for workplace discrimination also reported less collective value congruence with their organization (a1 = -1.07, p < .001). With less shared perceptions of value congruence, there is less team cohesion (d21 = .45, p < .001), and with less team cohesion there is less team effectiveness (b2 = .57, p < .001). In addition, because of theoretical overlap, this study makes the case for studying workplace discrimination under the broader construct of workplace aggression within the I/O psychology literature. Exploratory and confirmatory factor analysis found that workplace discrimination based on five types of marginalized groups: race/ethnicity, gender, religion, age, and disability was best explained by a three-factor model, including: career obstruction based on age and disability bias (CO), verbal aggression based on multiple types of bias (VA), and differential treatment based on racial/ethnic bias (DT). There was initial support to claim that workplace discrimination items covary not only based on type, but also based on form (i.e., nonviolent aggressive behaviors). Therefore, the form of workplace discrimination is just as important as the type when studying climate perceptions and team-level effects. Theoretical and organizational implications are also discussed.
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In order to map the modern distribution of diatoms and to establish a reliable reference data set for paleoenvironmental reconstruction in the northern North Pacific, a new data set including the relative abundance of diatom species preserved in a total of 422 surface sediments was generated, which covers a broad range of environmental variables characteristic of the subarctic North Pacific, the Sea of Okhotsk and the Bering Sea between 30° and 70°N. The biogeographic distribution patterns as well as the preferences in sea surface temperature of 38 diatom species and species groups are documented. A Q-mode factor analysis yields a three-factor model representing assemblages associated with the Arctic, Subarctic and Subtropical water mass, indicating a close relationship between the diatom composition and the sea surface temperatures. The relative abundance pattern of 38 diatom species and species groups was statistically compared with nine environmental variables, i.e. the summer sea surface temperature and salinity, annual surface nutrient concentration (nitrate, phosphate, silicate), summer and winter mixed layer depth and summer and winter sea ice concentrations. Canonical Correspondence Analysis (CCA) indicates 32 species and species groups have strong correspondence with the pattern of summer sea surface temperature. In addition, the total diatom flux data compiled from ten sediment traps reveal that the seasonal signals preserved in the surface sediments are mostly from spring through autumn. This close relationship between diatom composition and the summer sea surface temperature will be useful in deriving a transfer function in the subarctic North Pacific for the quantitative paleoceanographic and paleoenvironmental studies. The relative abundance of the sea-ice indicator diatoms Fragilariopsis cylindrus and F. oceanica of >20% in the diatom composition is used to represent the winter sea ice edge in the Bering Sea. The northern boundary of the distribution of F. doliolus in the open ocean is suggested to be an indicator of the Subarctic Front, while the abundance of Chaetoceros resting spores may indicate iron input from nearby continents and shelves and induced productivity events in the study area.
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Based on the quantitative analysis of diatom assemblages preserved in 274 surface sediment samples recovered in the Pacific, Atlantic and western Indian sectors of the Southern Ocean we have defined a new reference database for quantitative estimation of late-middle Pleistocene Antarctic sea ice fields using the transfer function technique. The Detrended Canonical Analysis (DCA) of the diatom data set points to a unimodal distribution of the diatom assemblages. Canonical Correspondence Analysis (CCA) indicates that winter sea ice (WSI) but also summer sea surface temperature (SSST) represent the most prominent environmental variables that control the spatial species distribution. To test the applicability of transfer functions for sea ice reconstruction in terms of concentration and occurrence probability we applied four different methods, the Imbrie and Kipp Method (IKM), the Modern Analog Technique (MAT), Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WAPLS), using logarithm-transformed diatom data and satellite-derived (1981-2010) sea ice data as a reference. The best performance for IKM results was obtained using a subset of 172 samples with 28 diatom taxa/taxa groups, quadratic regression and a three-factor model (IKM-D172/28/3q) resulting in root mean square errors of prediction (RMSEP) of 7.27% and 11.4% for WSI and summer sea ice (SSI) concentration, respectively. MAT estimates were calculated with different numbers of analogs (4, 6) using a 274-sample/28-taxa reference data set (MAT-D274/28/4an, -6an) resulting in RMSEP's ranging from 5.52% (4an) to 5.91% (6an) for WSI as well as 8.93% (4an) to 9.05% (6an) for SSI. WA and WAPLS performed less well with the D274 data set, compared to MAT, achieving WSI concentration RMSEP's of 9.91% with WA and 11.29% with WAPLS, recommending the use of IKM and MAT. The application of IKM and MAT to surface sediment data revealed strong relations to the satellite-derived winter and summer sea ice field. Sea ice reconstructions performed on an Atlantic- and a Pacific Southern Ocean sediment core, both documenting sea ice variability over the past 150,000 years (MIS 1 - MIS 6), resulted in similar glacial/interglacial trends of IKM and MAT-based sea-ice estimates. On the average, however, IKM estimates display smaller WSI and slightly higher SSI concentration and probability at lower variability in comparison with MAT. This pattern is a result of different estimation techniques with integration of WSI and SSI signals in one single factor assemblage by applying IKM and selecting specific single samples, thus keeping close to the original diatom database and included variability, by MAT. In contrast to the estimation of WSI, reconstructions of past SSI variability remains weaker. Combined with diatom-based estimates, the abundance and flux pattern of biogenic opal represents an additional indication for the WSI and SSI extent.
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Este artigo visa testar um hexa-modelo dimensional do empenhamento organizacional sugerido em pesquisas anteriores de Rego (2002b, 2003). O modelo difere do esquema tri-dimensional mais comum (afectivo, normativo e instrumental) no que concerne a três aspectos: a) a faceta afectiva é desmembrada em duas (empenhamento afectivo; futuro comum); b) a faceta instrumental é dividida nas facetas “escassez de alternativas” e “sacrifícios elevados”; c) é sugerida uma nova dimensão, designada “ausência psicológica” e que representa o “grau zero” do empenhamento. A amostra é constituída por 366 indivíduos, com actividades profissionais bastante distintas. Análises factoriais confirmatórias sugerem que o modelo de seis dimensões se ajusta satisfatoriamente aos dados, embora os modelos de quatro e cinco dimensões denotem igualmente boas qualidades psicométricas.
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Background: Older adults experience varying challenges in old age. This study aims to explore the indicators of adjustment to aging (AtA) and to examine the potential explanatory mechanisms of a correlational model for AtA for the old and oldest-old adults. Methods: This qualitative study comprised demographics and semistructured interviews. Complete information on 152 older adults aged between 75 years and 102 years (mean ¼ 83.76 years; standard deviation ¼ 6.458). Data was subjected to content analysis. The correlational model of indicators of AtA was analyzed using a multiple correspondence analysis. Results: “Occupation and achievement” was the most mentioned indicator of AtA by the old participants (17.7%), whereas “existential meaning and spirituality” was the most verbalized indicator of AtA for the oldest-old participants (16.9%). AtA was explained by a three-factor model for each age group. For the old participants, the largest factor “occupational and social focus” accounted for 33.6% of total variance, whereas for the oldest-old participants, “spirituality and health focus” represented 33.5% of total variance. Conclusion: The outcomes presented in this paper stressed the varied perspectives concerning AtA, contoured in two different models, and the need of considering these when designing and implementing programs in health care for the old and the oldest-old.
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Previous research shows that correlations tend to increase in magnitude when individuals are aggregated across groups. This suggests that uncorrelated constellations of personality variables (such as the primary scales of Extraversion and Neuroticism) may display much higher correlations in aggregate factor analysis. We hypothesize and report that individual level factor analysis can be explained in terms of Giant Three (or Big Five) descriptions of personality, whereas aggregate level factor analysis can be explained in terms of Gray's physiological based model. Although alternative interpretations exist, aggregate level factor analysis may correctly identify the basis of an individual's personality as a result of better reliability of measures due to aggregation. We discuss the implications of this form of analysis in terms of construct validity, personality theory, and its applicability in general. Copyright (C) 2003 John Wiley Sons, Ltd.
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A simple theoretical framework is presented for bioassay studies using three component in vitro systems. An equilibrium model is used to derive equations useful for predicting changes in biological response after addition of hormone-binding-protein or as a consequence of increased hormone affinity. Sets of possible solutions for receptor occupancy and binding protein occupancy are found for typical values of receptor and binding protein affinity constants. Unique equilibrium solutions are dictated by the initial condition of total hormone concentration. According to the occupancy theory of drug action, increasing the affinity of a hormone for its receptor will result in a proportional increase in biological potency. However, the three component model predicts that the magnitude of increase in biological potency will be a small fraction of the proportional increase in affinity. With typical initial conditions a two-fold increase in hormone affinity for its receptor is predicted to result in only a 33% increase in biological response. Under the same conditions an Ii-fold increase in hormone affinity for receptor would be needed to produce a two-fold increase in biological potency. Some currently used bioassay systems may be unrecognized three component systems and gross errors in biopotency estimates will result if the effect of binding protein is not calculated. An algorithm derived from the three component model is used to predict changes in biological response after addition of binding protein to in vitro systems. The algorithm is tested by application to a published data set from an experimental study in an in vitro system (Lim et al., 1990, Endocrinology 127, 1287-1291). Predicted changes show good agreement (within 8%) with experimental observations. (C) 1998 Academic Press Limited.
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Fibroblasts are thought to be partially responsible for the persisting contractile forces that result in burn contractures. Using a monolayer cell culture and fibroblast populated collagen lattice (FPCL) three-dimensional model we subjected hypertrophic scar and non-cicatricial fibroblasts to the antifibrogenic agent pentoxifylline (PTF - 1 mg/mL) in order to reduce proliferation, collagen types I and III synthesis and model contraction. Fibroblasts were isolated from post-burn hypertrophic scars (HSHF) and non-scarred skin (NHF). Cells were grown in monolayers or incorporated into FPCL`s and exposed to PTF. In monolayer, cell number proliferation was reduced (46.35% in HSHF group and 37.73% in NHF group, p < 0.0001). PTF selectively inhibited collagen III synthesis in the HSHF group while inhibition was more evident to type I collagen synthesis in the NHF group. PTF also reduced contraction in both (HSHF and NHF) FPCL. (C) 2009 Elsevier Ltd and ISBI. All rights reserved.
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A PhD Dissertation, presented as part of the requirements for the Degree of Doctor of Philosophy from the NOVA - School of Business and Economics