Purpose: The aim of this thesis is to elaborate on if organisational culture has an impact on the intention to use a CRM system. Methodology: The data was collected by use of an online questionnaire, the questions used were created based on the literature review andmeasured according to a 5 point Likert-scale Conclusion: Organisational culture has no meaningful impact on intention touse CRM. This since each of the culture types produced results which were outside acceptable perimeters. Out of the three aspects of the technology acceptance model,attitude has the biggest impact on intention to use CRM. PEOU and PU were not within acceptable perimeters. Neither PU nor PEOU had a statistical significant impact on attitude, leaving attitude as a sole positive contributor to intentionto use CRM. K

One situation in survival analysis is that the failure of an individual can happen because of one of multiple distinct causes. Survival data generated in this scenario are commonly referred to as competing risks data. One of the major tasks, when examining survival data, is to assess the dependence of survival time on explanatory variables. In competing risks, as with ordinary univariate survival data, there may be explanatory variables associated with the risks raised from the different causes being studied. The same variable might have different degrees of influence on the risks due to different causes. Given a set of explanatory variables, it is of interest to identify the subset of variables that are significantly associated with the risk corresponding to each failure cause. In this project, we develop a statistical methodology to achieve this purpose, that is, to perform variable selection in the presence of competing risks survival data. Asymptotic properties of the model and empirical simulation results for evaluation of the model performance are provided. One important feature of our method, which is based on the idea of the L1 penalized Cox model, is the ability to perform variable selection in situations where we have high-dimensional explanatory variables, i.e. the number of explanatory variables is larger than the number of observations. The method was applied on a real dataset originated from the National Institutes of Health funded project "Genes related to hepatocellular carcinoma progression in living donor and deceased donor liver transplant'' to identify genes that might be relevant to tumor progression in hepatitis C virus (HCV) infected patients diagnosed with hepatocellular carcinoma (HCC). The gene expression was measured on Affymetrix GeneChip microarrays. Based on the current available 46 samples, 42 genes show very strong association with tumor progression and deserve to be further investigated for their clinical implications in prognosis of progression on patients diagnosed with HCV and HCC.

Thesis advisor: Laura O'Dwyer / In recent decades, the plight of early career teacher turnover has had significant financial ramifications for our nation’s schools and has posed a serious threat to achieving educational equity, with the most disadvantaged schools experiencing the highest rates of turnover. Using data collected from the Beginning Teacher Longitudinal Survey, this study employed discrete-time competing risks survival analysis to explore the first-year experiences of public middle and high school teachers as predictors of their career decisions to stay in their current school, move to a new school, or leave the profession across the first five years of their career. Four facets were conceived as characterizing teachers’ first-year experiences: 1) policies and programs for first-year teachers provided by the administration including mentoring and induction, 2) perceptions of their preparedness to teach, 3) perceptions of school climate and workplace conditions, and 4) satisfaction with teaching. The research questions are: 1. What are the first-year experiences for teachers in the sample and how do they compare between teachers who are retained in their first school placements and teachers who voluntarily or involuntarily turn over in later years? 2. What first-year teacher experiences predict voluntary and involuntary turnover at the end of years 1, 2, 3, and 4? And, how does satisfaction with teaching in the first year interact with the three other facets of the first-year experience to predict voluntary and involuntary turnover across the early career window? Findings suggest there may be differences in the mechanisms that drive the moving and leaving phenomena, suggesting that policymakers treat the two turnover pathways as separate problems requiring separate solutions. Furthermore, findings suggest there may be more policy-amendable variables that can be manipulated in the first year of teaching to prevent leaving than there are to prevent moving, implying that curbing rates of moving to minimize the localized impacts of teacher migration to other schools may be more challenging than reducing rates of leaving the profession. / Thesis (PhD) — Boston College, 2019. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

Made available in DSpace on 2016-04-25T16:44:55Z (GMT). No. of bitstreams: 1 Dissertacao Mestrado PUC.pdf: 629205 bytes, checksum: c6c883b3f57af0cd553e521d11ab32b6 (MD5) Previous issue date: 2005-06-28 / Este trabalho, fruto da experiência profissional voltada para gerenciamento de projetos na área de TI, foi idealizado como instrumento de compreensão e reflexão sobre as práticas de gerenciamento de projetos de TI nas organizações no Brasil, utilizando-se das melhores práticas do PMI e as teorias de Cultura Organizacional. O objetivo, então, dessa pesquisa foi traçar um perfil das organizações que implementaram as práticas de gerenciamento de projetos do PMI no Brasil, baseado na tipologia cultural de Quinn ou CVM, identificando os tipos culturais mais e menos favoráveis à metodologia, levando a um entendimento maior sobre os fatores culturais para as práticas do PMI no Brasil. Palavras-chave: gerenciamento de projetos; cultura organizacional; melhores práticas de gerenciamento de projetos do PMI

This thesis focuses on two fundamental topics, specifically in medical statistics: the modelling of correlated survival datasets and the variable selection of the significant covariates and random effects. In particular, two types of survival data are considered: the classical survival datasets, where subjects are likely to experience only one type of event and the competing risks datasets, where subjects are likely to experience one of several types of event. In Chapter 2, among other topics, we highlight the importance of adding frailty terms on the proposed models in order to account for the association between the survival time and characteristics of subjects/groups. The main novelty of this thesis is to simultaneously select fixed effects and frailty terms through the proposed statistical models for each survival dataset. Chapter 3 covers the analysis of the classical survival dataset through the proposed Cox Proportional Hazard (PH) model. Utilizing a Cox PH frailty model, may increase the dimension of variable components and estimation of the unknown coefficients becomes very challenging. The method proposed for the analysis of classical survival datasets involves simultaneous variable selection on both fixed effects and frailty terms through penalty functions. The benefit of penalty functions is that they identify the non-significant parameters and set them to have a zero effect in the model. Hence, the idea is to 'doubly-penalize' the partial likelihood of the Cox PH frailty model; one penalty for each term. Estimation and selection implemented through Newton-Raphson algorithms, whereas closed iterative forms for the estimation and selection of fixed effects and prediction of frailty terms were obtained. For the selection of frailty terms, penalties imposed on their variances since frailties are random effects. Based on the same idea, we further extend the simultaneous variable selection in the competing risks datasets in Chapter 4, using extended cause-specific frailty models. Two different scenarios are considered for frailty terms; in the first case we consider that frailty terms vary among different types of events (similar to the fixed effects) whereas in the second case we consider shared frailties over all the types of events. Moreover, our 'individual penalization' approach allows for one covariate to be significant for some types of events, in contrast to the frequently used 'group-penalization' where a covariate is entirely removed when it is not significant over all the events. For both proposed methods, simulation studies were conduced and showed that the proposed procedure followed for each analysis works well in simultaneously selecting and estimating significant fixed effects and frailty terms. The proposed methods are also applied to real datasets analysis; Kidney catheter infections, Diabetes Type 2 and Breast Cancer datasets. Association of the survival times and unmeasured characteristics of the subjects was studied as well as a variable selection for fixed effects and frailties implemented successfully.

Li, Li. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 34-36). / Abstracts in English and Chinese. / Chapter Chapter One --- Introduction --- p.1 / Chapter Chapter Two --- Methodology --- p.5 / Chapter Chapter Three --- Data --- p.9 / Chapter 3.1 --- Data Description --- p.9 / Chapter 3.2 --- Selection of Covariate --- p.13 / Chapter Chapter Four --- Empirical Analysis --- p.20 / Chapter 4.1 --- General Survival Analysis by Cox PH Model --- p.20 / Chapter 4.2 --- Competing Risk Analysis of Listed Firms --- p.24 / Chapter 4.3 --- Robustness Check --- p.28 / Chapter Chapter Five --- Conclusion --- p.30 / Appendix 1 --- p.32 / Appendix II --- p.33 / Reference --- p.34 / Tables --- p.37 / Figures --- p.58

There is limited research on the relationship between trauma exposure, depression, and suicidality, particularly in high-risk primary care samples. The present study aims to: 1) characterize the prevalence of suicidality, depression, and trauma exposure in this sample; 2)develop and test models of the relationships between suicidality, depression, and trauma exposure in this sample; 3) augment the selected model with key protective factors, including social support and religiosity; and 4) further elaborate the nature of religiosity as a potential protective factor using the subscales of the Attitudes toward God scale, Anger toward God and Comfort with God. Patients (n=207) in a safety net primary care clinic waiting room completed measures assessing childhood and adult trauma, depression, and suicidal ideation. Approximately half of patients in this sample report having experienced at least four traumatic events, 82.13% of individuals were in the clinical range for depression, and nearly half of the sample endorsed some level of suicidality. In the first model, trauma exposure moderated the relationship between depression and in the second model, suicidality and depression mediated the relationship between trauma exposure and suicidality. Both models were then augmented with social support, religiosity, Anger toward God, and Comfort with God. All moderated moderational and moderated mediational models were nonsignificant, though certain paths were found to be significant. Social support had some protective effects, but all three aspects of religiosity exacerbated the models tested, in contrast to existing literature. These findings may be used to encourage more extensive and nuanced assessment for suicidality.

A state of conflict has existed in the Niger Delta for fifty years. The nature of the conflict, whether it is terrorism or civil insurrection, has not been resolved by the respective legislative entities. This qualitative case study was designed to explore the nature of the Niger Delta conflict from the perspective of several members of the Nigerian National Assembly and determine whether terrorism in Nigeria is related to the general conflict. Social conflict theory provided the basis for the exploration. An ancillary question explored whether antiterrorism legislation in 2006 alleviated the Niger Delta conflict. Interview data were collected from 1 senator and 5 representatives of the Nigerian National Assembly. These data were inductively coded and manually analyzed for major themes, and then triangulated with a review of internal and public documents pertaining to the relevant legislation. The study established that the root causes of the Niger Delta conflict were economic inequities. Three conclusions were drawn from the case study and data regarding legislative attempts to address the conflict: (1) the antiterrorism legislation of 2006 did not criminalize the Niger Delta conflict, (2) the legislation did not have an impact on fiscal resource allocations to the region, and (3) no link between the conflict and current terrorism activities in Nigeria was evident. Recommendations are given for the Nigerian state to engage in fiscal federalism as a means of equitable allocations of resources to the region, thereby contributing to positive social change.

In clustered survival data, unobservable cluster effects may exert powerful influences on the outcomes and thus induce correlation among subjects within the same cluster. The ordinary partial likelihood approach does not account for this dependence. Frailty models, as an extension to Cox regression, incorporate multiplicative random effects, called frailties, into the hazard model and have become a very popular way to account for the dependence within clusters. We particularly study the two-level nested lognormal frailty model and propose an estimation approach based on the complete data likelihood with frailty terms integrated out. We adopt B-splines to model the baseline hazards and adaptive Gauss-Hermite quadrature to approximate the integrals efficiently. Furthermore, in finding the maximum likelihood estimators, instead of the Newton-Raphson iterative algorithm, Gauss-Seidel and BFGS methods are used to improve the stability and efficiency of the estimation procedure. We also study competing risks models with missing cause of failure in the context of Cox proportional hazards models. For competing risks data, there exists more than one cause of failure and each observed failure is exclusively linked to one cause. Conceptually, the causes are interpreted as competing risks before the failure is observed. Competing risks models are constructed based on the proportional hazards model specified for each cause of failure respectively, which can be estimated using partial likelihood approach. However, the ordinary partial likelihood is not applicable when the cause of failure could be missing for some reason. We propose a weighted partial likelihood approach based on complete-case data, where weights are computed as the inverse of selection probability and the selection probability is estimated by a logistic regression model. The asymptotic properties of the regression coefficient estimators are investigated by applying counting process and martingale theory. We further develop a double robust approach based on the full data to improve the efficiency as well as the robustness.

Workplace incidents result in significant human and financial costs. Despite these costs, it is estimated that less than 1% of organisational research focuses on issues concerning occupational health and safety (Barling & Zacharatos, 2000; Reason, 1990). Safety research has begun however to focus increasing attention on understanding the role that the wider organisational context, and in particular the role that safety climate, plays in influencing safety (Barling, Kelloway, & Iverson, 2003; Clarke, 2006a; Cox & Cheyne, 2000; Parker, Axtell, & Turner, 2001; Zohar, 2000). Safety climate refers to safety related policies, procedures and practices that signal the concern for safety (Griffin & Neal, 2000). The aim of the current program of research was to further understanding of the structure, antecedents and cross-level effects of safety climate. Specifically, this research aimed to better understand how organisational factors, and more specifically culture, influence safety climate and safety incidents. This knowledge is important as it assists organisations to purposively engineer stronger climates for safety and in doing so assists them to reduce the number of workplace incidents and accidents. The current program of research consists of three field-based studies. An overview of each study is provided below: Overview Study 1 Study 1 aimed to identify the safety climate schema for a sample of individuals working within the rail industry and explore whether safety climate schemas differ across individuals with and without leadership responsibilities. A proportional number of upper managers (n = 6), supervisors (n = 7) and workers (n = 12) were purposively sampled and interviewed. Interview data was analysed using Leximancer – an advanced computer assisted data mining tool. Results identified 10 emergent themes underlying a safety climate schema – many of these themes aligned closely with common safety climate factors in the academic literature. Results also showed differences between the safety factors that were dominant in the safety climate schemas of upper managers, supervisors and workers: upper managers were more closely associated with themes relating to ‘culture,’ and ‘people’; supervisors were more closely associated with themes relating to ‘corporate values,’ ‘management practices,’ and ‘safety communication’; whereas workers were more closely associated with themes relating to ‘procedures,’ and ‘safety training’. Results are discussed in relation to safety climate theory and in relation to how managers can use this knowledge to better communicate to the specific safety needs of different sub-groups. Overview Study 2 Study 2 aimed to better understand how perceived cultural profiles are related to safety. The Competing Values Framework adopted in this study proposes that four cultural types exist in unison in any organisation. Depending on the demands that are placed on the organisation, each type will be more or less dominant and each organisation will have a specific ‘cultural profile’ reflecting the strengths of each type. A cross-section of individuals (N = 368) working in high risk industries were sampled to identify the relationship between perceived cultural profiles and (1) psychological safety climate and (2) individual safety incidents. Modal Profile Analysis (MPA) identified four commonly perceived cultural profiles across the sample. A one-way MANOVA indicated that individuals who perceived their organisation had a strong human relations profile, or a dual focused human relations-rational goal profile, reported higher safety climate perceptions and fewer safety incidents. Comparably, individuals who perceived their organisation had a strong internal process profile, or a dual focused internal process-rational goal profile, reported lower safety climate perceptions and more safety incidents. These findings are discussed in terms of their theoretical contribution to the safety climate literature, and in relation to the practical importance that culture plays in influencing safety. Overview Study 3 Study 3 aimed to better understand how the culture of an organisation influences safety, and to explore the levels of analysis that are involved in this relationship. Specifically, this study examined the role that an internal process culture played in influencing safety climate; and in turn the mediating role that two sources of safety climate – business-unit safety climate and perceived supervisory safety climate – played in explaining the relationship between culture and individual-level outcomes (incidents, satisfaction and turnover intentions). Results showed that business-unit culture was related to business-unit safety climate; and that business-unit safety climate and perceived supervisory safety climate mediated the relationship between business-unit culture and incidents, satisfaction and turnover intentions. This research adds to the safety climate literature by providing evidence for the multi-level nature of the relationship between culture, safety climate and outcomes.