38 resultados para Hierarchical Linear Modelling

em Aston University Research Archive


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This study extends research on creativity by exploring the boundary conditions of the creativity-job effectiveness relationship. Building on social exchange theory, we argue that the extent to which employee creativity is related to sales - an objective work effectiveness measure - depends on the quality of leader-member exchange (LMX). We hypothesize that the relationship between creativity and sales is significant and positive when LMX is high, but not when LMX is low. Hierarchical linear modelling analysis provided support for the interaction hypothesis in a sample of 151 sales agents and 26 supervisors drawn from both pharmaceutical and insurance companies. Results showed that sales agents who were more creative generated higher sales only when they had high quality LMX. An ad-hoc qualitative study provided a more detailed understanding of the moderator role played by LMX. Copyright © 2012 John Wiley & Sons, Ltd.

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The major contribution of the study is the identification of a positive link between perceived effective managerial coaching (PEMC) and team task performance and also, the examination of PEMC adopting a multilevel research design and incorporating dual-source data. Specifically, drawing on social psychology, the thesis aims at developing and testing a comprehensive conceptual framework of the antecedents and consequences of PEMC for knowledge workers. The model takes into consideration intrapersonal, interpersonal and team-level characteristics, which relate to PEMC and, subsequently associate with important work outcomes. In this regard, the thesis identifies PEMC as a practice of dual nature in that it may be experienced not only as a one-on-one workplace developmental interaction, but also as a managerial practice that is experienced by each member of a team for co-ordination purposes. Adopting a cross-sectional survey research design, the hypotheses are tested in three organisations in Greece and the UK. In particular, hierarchical linear modelling of 191 employees nested in 60 teams yields that employees’ learning goal orientation (LGO) and high-quality exchanges between an employee and a manager (LMX) are positively related to effective MC, while a manager’s LGO moderates the relationship between employees’ LGO and PEMC. In turn, PEMC, as a one-on-one practice, is related to cognitive outcomes, such as information sharing, while as a shared team practice is related also to behavioural outcomes, including individual and team performance. Overall, the study contributes to a growing body of coaching and management literature that acknowledges PEMC as a core managerial practice.

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Underpinned by the resource-based view (RBV), social exchange theory (SET), and a theory of intrinsic motivation (empowerment), I proposed and tested a multi-level model that simultaneously examines the intermediate linkages or mechanisms through which HPWS impact individual and organizational performance. First and underpinned by RBV, I examined at the unit level, collective human capital and competitive advantage as path-ways through which the use of HPWS influences – branch market performance. Second and-, underpinned by social exchange (perceived organizational support) and intrinsic motivation (psychological empowerment) theories, I examined cross and individual level mechanisms through which experienced HPWS may influence employee performance. I tested the propositions of this study with multisource data obtained from junior and senior customer contact employees, and managers of 37 branches of two banks in Ghana. Results of the Structural Equation Modeling (SEM) analysis revealed that (i) collective human capital partially mediated the relationship between management-rated HPWS and competitive advantage, while competitive advantage completely mediated the influence of human capital on branch market performance. Consequently, management-rated HPWS influenced branch market performance indirectly through collective human capital and competitive advantage. Additionally, results of hierarchical linear modeling (HLM) tests of the cross-level influences on the motivational implications of HPWS revealed that (i) management-rated HPWS influenced experienced HPWS; (ii) perceived organizational support (POS) and psychological empowerment fully mediated the influence of experienced HPWS on service-oriented organizational citizenship behaviour (OCB), and; (iii) service-oriented OCB mediated the influence of psychological empowerment and POS on service quality and task performance. I discuss the theoretical and practical implications of these findings.

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Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

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Sponsorship fit is frequently mentioned and empirically examined as a success factor of sponsorship. While sponsorship fit has been considered as a determinant of sponsorship success, little knowledge exists about the antecedents of sponsorship fit. In the present paper, individual and firm-level antecedents of sponsorship fit are examined in a single hierarchical linear model. Results show that sponsorship fit is influenced by the perception of benefits, the firm’s regional identification, sincerity, relatedness to the sponsored activity, and its dominance. On a partnership level, results show that contract length contributes to sponsorship fit while contract value is found to be unrelated.

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Drawing on the perceived organizational membership theoretical framework and the social identity view of dissonance theory, I examined in this study the dynamics of the relationship between psychological contract breach and organizational identification. I included group-level transformational and transactional leadership as well as procedural justice in the hypothesized model as key antecedents for organizational membership processes. I further explored the mediating role of psychological contract breach in the relationship between leadership, procedural justice climate, and organizational identification and proposed separateness–connectedness self-schema as an important moderator of the above mediated relationship. Hierarchical linear modeling results from a sample of 864 employees from 162 work units in 10 Greek organizations indicated that employees' perception of psychological contract breach negatively affected their organizational identification. I also found psychological contract breach to mediate the impact of transformational and transactional leadership on organizational identification. Results further provided support for moderated mediation and showed that the indirect effects of transformational and transactional leadership on identification through psychological contract breach were stronger for employees with a low connectedness self-schema.

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Grounded in Vroom’s motivational framework of performance, we examine the interactive influence of collective human capital (ability) and aggregated service orientation (motivation) on the cross-level relationship between high-performance work systems (HPWS) and individual-level service quality. Results of hierarchical linear modeling (HLM) revealed that HPWS related to collective human capital and aggregated service orientation, which in turn related to individual-level service quality. Furthermore, both HLM and ordinary least squares regression analyses revealed a cross-level interaction effect of collective human capital and aggregated service orientation such that high levels of collective human capital and aggregated service orientation influence individual-level service quality.

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We proposed and tested a multilevel model, underpinned by empowerment theory, that examines the processes linking high-performance work systems (HPWS) and performance outcomes at the individual and organizational levels of analyses. Data were obtained from 37 branches of 2 banking institutions in Ghana. Results of hierarchical regression analysis revealed that branch-level HPWS relates to empowerment climate. Additionally, results of hierarchical linear modeling that examined the hypothesized cross-level relationships revealed 3 salient findings. First, experienced HPWS and empowerment climate partially mediate the influence of branch-level HPWS on psychological empowerment. Second, psychological empowerment partially mediates the influence of empowerment climate and experienced HPWS on service performance. Third, service orientation moderates the psychological empowerment-service performance relationship such that the relationship is stronger for those high rather than low in service orientation. Last, ordinary least squares regression results revealed that branch-level HPWS influences branch-level market performance through cross-level and individual-level influences on service performance that emerges at the branch level as aggregated service performance. © 2011 American Psychological Association.

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This research investigates the interrelationship between service characteristics and switching costs and makes two contributions to the service retailing literature: (1) As a means of better understanding the effectiveness of switching costs, the study suggests a two-dimensional typology of switching costs, including internal and external switching costs and (2) it reveals that the effect of these switching costs on customer loyalty is contingent upon four service characteristics (the IHIP characteristics of service). We carried out a meta-analytic review of the literature on the switching costs-customer loyalty link and created a hierarchical linear model using a sample of 1,694 customers from 51 service industries. Results reveal that external switching costs have a stronger average effect on customer loyalty than do internal switching costs. Moreover, we find that IHIP characteristics moderate the links between switching costs and customer loyalty. Thus, the link between external switching costs and customer loyalty is weaker in industries higher in the four service characteristics (as compared to industries lower in these characteristics), while the opposite moderating effect of service characteristics for the internal switching costs-loyalty link is noted. © 2014 New York University.

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Research has looked at single rather than a configuration of human resource management (HRM) practices to influence creativity so it is not yet clear how these practices synergistically facilitate creativity and organisational performance. I address this significant but unanswered question in a three-part study. In Study 1, I develop a high performance work system (HPWS) for creativity scale. I use Study 2 sample to test the validity of the new scale. In Study 3, I test a multilevel model of the intervening processes through which branch HPWS for creativity influences creativity and branch performance. Specifically, at the branch level, I draw on social context theory and hypothesise that branch HPWS for creativity relates to climate for creativity which, in turn, leads to creativity, and ultimately, to profit. Furthermore, I hypothesise environmental dynamism as a boundary condition of the creativity-profit relationship. At the individual level, I hypothesise a cross-level effect of branch HPWS for creativity on employee-perceived HPWS. I draw on self-determination theory and argue that perceived HPWS for creativity relate to need satisfaction and the psychological pathways of intrinsic motivation and creative process engagement to predict creativity. I also hypothesise climate for creativity as a cross-level moderator of the intrinsic motivation-creativity and creative process engagement-creativity relationships. Results of hierarchical linear modeling (HLM) indicate that ten out of the fifteen hypotheses were supported. The findings of this study respond to calls for HPWS to be designed around a strategic focus by developing and providing initial validity evidence of an HPWS for creativity scale. The results reveal the underlying mechanisms through which HPWS for creativity simultaneously influences individual and branch creativity leading to profit. Lastly, results indicate environmental dynamism to be an important boundary condition of the creativity-profit relationship and climate for creativity as a cross-level moderator of the creative process engagement-creativity.

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Based on a review of the servant leadership, well-being, and performance literatures, the first study develops a research model that examines how and under which conditions servant leadership is related to follower performance and well-being alike. Data was collected from 33 leaders and 86 of their followers working in six organizations. Multilevel moderated mediation analyses revealed that servant leadership was indeed related to eudaimonic well-being and lead-er-rated performance via followers’ positive psychological capital, but that the strength and di-rection of the examined relationships depended on organizational policies and practices promot-ing employee health, and in the case of follower performance on a developmental team climate, shedding light on the importance of the context in which servant leadership takes place. In addi-tion, two more research questions resulted from a review of the training literature, namely how and under which conditions servant leadership can be trained, and whether follower performance and well-being follow from servant leadership enhanced by training. We subsequently designed a servant leadership training and conducted a longitudinal field experiment to examine our sec-ond research question. Analyses were based on data from 38 leaders randomly assigned to a training or control condition, and 91 of their followers in 36 teams. Hierarchical linear modeling results showed that the training, which addressed the knowledge of, attitudes towards, and ability to apply servant leadership, positively affected leader and follower perceptions of servant leader-ship, but in the latter case only when leaders strongly identified with their team. These findings provide causal evidence as to how and when servant leadership can be effectively developed. Fi-nally, the research model of Study 1 was replicated in a third study based on 58 followers in 32 teams drawn from the same population used for Study 2, confirming that follower eudaimonic well-being and leader-rated performance follow from developing servant leadership via increases in psychological capital, and thus establishing the directionality of the examined relationships.

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The main aim of this paper is to provide a tutorial on regression with Gaussian processes. We start from Bayesian linear regression, and show how by a change of viewpoint one can see this method as a Gaussian process predictor based on priors over functions, rather than on priors over parameters. This leads in to a more general discussion of Gaussian processes in section 4. Section 5 deals with further issues, including hierarchical modelling and the setting of the parameters that control the Gaussian process, the covariance functions for neural network models and the use of Gaussian processes in classification problems.

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It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets, and therefore a hierarchical visualization system is desirable. In this paper we extend an existing locally linear hierarchical visualization system PhiVis ¸iteBishop98a in several directions: bf(1) We allow for em non-linear projection manifolds. The basic building block is the Generative Topographic Mapping. bf(2) We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. bf(3) Using tools from differential geometry we derive expressions for local directional curvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the parent visualization plot which are captured by a child model. We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set and apply our system to two more complex 12- and 19-dimensional data sets.

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It has been argued that a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex data sets, and therefore a hierarchical visualization system is desirable. In this paper we extend an existing locally linear hierarchical visualization system PhiVis ¸iteBishop98a in several directions: bf(1) We allow for em non-linear projection manifolds. The basic building block is the Generative Topographic Mapping (GTM). bf(2) We introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree. General training equations are derived, regardless of the position of the model in the tree. bf(3) Using tools from differential geometry we derive expressions for local directional curvatures of the projection manifold. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. It enables the user to interactively highlight those data in the ancestor visualization plots which are captured by a child model. We also incorporate into our system a hierarchical, locally selective representation of magnification factors and directional curvatures of the projection manifolds. Such information is important for further refinement of the hierarchical visualization plot, as well as for controlling the amount of regularization imposed on the local models. We demonstrate the principle of the approach on a toy data set and apply our system to two more complex 12- and 18-dimensional data sets.

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Hierarchical visualization systems are desirable because a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex high-dimensional data sets. We extend an existing locally linear hierarchical visualization system PhiVis [1] in several directions: bf(1) we allow for em non-linear projection manifolds (the basic building block is the Generative Topographic Mapping -- GTM), bf(2) we introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree, bf(3) we describe folding patterns of low-dimensional projection manifold in high-dimensional data space by computing and visualizing the manifold's local directional curvatures. Quantities such as magnification factors [3] and directional curvatures are helpful for understanding the layout of the nonlinear projection manifold in the data space and for further refinement of the hierarchical visualization plot. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. We demonstrate the visualization system principle of the approach on a complex 12-dimensional data set and mention possible applications in the pharmaceutical industry.