Le turnover au sein des organisations, à un faible niveau, peut être bénéfique pour le renouvellement des ressources. Mais en atteignant des sommets, il perturbe l’organisation et oblige à une gestion de l’immédiat, nuisible pour la performance des hommes et de l’entreprise. Le groupe Veolia Transport souffre de cet aléa organisationnel de manière récurrente, quand le cœur de son activité est basé sur la délégation de service public, où la qualité des hommes est gage de la performance de l’organisation. En appui de cet impératif qualitatif, le groupe promeut une politique générale de formation ambitieuse afin d’intégrer, professionnaliser et fidéliser ses collaborateurs. Le fer de lance de cette politique est l’alternance, la formation diplômante en alternance. Dès lors, l’alternance impacte-t-elle à la baisse le turnover ? À travers une démarche proche d’un design quasi-expérimental, mobilisant une enquête dite longitudinale par questionnaire et l’appui d’un groupe de contrôle je teste, sur les exploitants du groupe en France, un design théorique explicatif de la relation alternance-turnover, par le prisme de l’implication organisationnelle. En proposant une définition gestionnaire de l’alternance, mes résultats démontrent le développement d’une relation dialectique individu-organisation par l’alternance, conditionnée par la mise en exergue d’un contrat psychologique fort et d’un double tutorat organisationnel. En croisant mes résultats avec 18 entretiens dits de validation, il ressort que l’alternance développe une socialisation organisationnelle partielle, en raison de la difficulté à comprendre pleinement son rôle en fin de cursus. Un glissement de la fonction tutorale en un système tutoral apparait, où la communauté de travail aide à l’apprentissage du métier, quand le supérieur-tuteur conserve un rôle de mentor. Enfin, l’alternance possède un effet positif sur l’intention de quitter, en créant les conditions du développement de l’implication organisationnelle, à la condition d’une gestion dédiée. Dans ce dessein, je propose la mise en place d’une gestion spécifique des alternants, en ne considérant plus l’alternance comme un outil de formation mais comme un outil de gestion des ressources humaines, créateur de potentiels. / Within the organizations, the turnover when limited can have a positive influence on the resources’ renewal. But when it grows, it badly affects the organization leading to a management of the immediate, jeopardizing people and company’s effectiveness. Veolia Group is suffering from this regular organizational move, when its core business is made of services and where people are the key quality asset. On top of that, the company encourages an ambitious training policy in order to integrate, professionalize, and retain employees. To be successful, the company relies on the classroom learning (alternation). Therefore, can we claim that alternation has a direct impact on turnover’s decrease?Thanks to a quasi-experimental design approach, using an investigation so called longitudinal per questionnaire strengthened by a group of control, a theoretical design explaining the relationship alternation-turnover in the organizational frame was tested in France over a French population of production units. Alternation shows the emergence of a dialectical relationship human being-organization, monitored by the creation of a strong psychological contract and a double tutorial system. Mixing my results with 18 interviews of so called validation, it appears that alternation develops an organizational socialization only partial, due to the difficulty in the understanding of its own role at the end of the journey. The shift from a tutorial function to a tutorial system is also highlighted in my results, where the learning of the job is supported by the working community and the lead-tutor continues playing a mentor role. Lastly, according my study, when well managed, alternation can prevent the turnover, by supporting the development of a strong involvement within the organization. Therefore, I suggest the set up of a specific management unit for alternates, considering not anymore the alternation as a training tool but also as human resource tool enabling talents’ discovery.

This dissertation focuses on the formation, growth and discontinuance of business populations and firms in Sweden during the 20th century. It addresses some key issues in the domain of economic and social sciences, and in particular entrepreneurship and small business research: if and when firms grow, stagnate and decline, as well as how long firms survive and when they are likely to disband. Previous research has primarily analyzed these questions from a short time frame. Further, an individual or firm-oriented focus is commonly assumed. In that, alternative or complementary explanations to the growth and survival of firms may be disregarded. In contrast to much previous research, this dissertation assumes a micro-to-macro, longitudinal and demographic population approach. The period of investigation is over one hundred years. In addressing the growth and survival of firms, it takes into account the impact of firm-specific structural factors (such as firm age and size), generation (cohort) effects, as well as the influence of macroeconomic, exogenous factors. Further, the relationship between managerial/ownership succession and firm performance is also addressed. Both cross-sectional and longitudinal databases are employed in the dissertation. Its main empirical material consists of unique longitudinal data on new business firms, traced at the firm level from their birth to their termination. More specifically, seven birth cohorts – generations – of approximately 2,200 firms founded in 1899, 1909, 1912, 1921, 1930, 1942 and 1950 are included. The main findings show that ownership/management succession in firms had a quite weak correlation with firm performance and survival. At least at an aggregate level, and with some exceptions, it is debatable if the loss and replacement of owner-managers in small and in larger firms have any observable effects on firm performance. Furthermore, macroeconomic phenomena influence the conditions of individual firms as well as populations/aggregates of businesses. Both the growth and termination of firms and firm populations are found to be related to real economic (environmental) conditions; e.g. favorable macroeconomic conditions implied that firms grew in size. At the same time, under certain circumstances, the influence of structural variables (firm age and size) – as suggested in much previous research – is found to be of importance. As concerns firm growth, as well as firm termination, the economic environment and structural factors interact. These findings challenges individual or firm-level research that mainly focus on personal traits and behaviors in explaining firm success and failure. Other previous assumptions are also challenged when taking a longer time perspective into consideration. For decades, organization and business research have acknowledged a liability of newness and of size for business firms. While this might be true under some conditions, this liability of newness is falsified in the study: the termination behavior of some firm generations did not correspond with these assumptions. Thus, the perspectives and methodology applied in the dissertation complement earlier approaches in entrepreneurship and small business research.

Indiana University-Purdue University Indianapolis (IUPUI) / Symptoms of post-traumatic stress disorder (PTSD) are a common comorbidity in veterans seeking treatment of chronic musculoskeletal pain (CMP). However, little is known regarding the mutual influence of PTSD and CMP in this population. Using cross-sectional and longitudinal data from a randomized clinical trial evaluating a stepped care intervention for CMP in Iraq/Afghanistan veterans (ESCAPE), this dissertation examined the relationships between PTSD and CMP along with other factors including depression, anxiety, catastrophizing and health-related quality of life. The Classification and Regression Tree (CART) analysis was conducted to identify key factors associated with baseline PTSD besides CMP severity. A series of statistical analyses including logistical regression analysis, mixed model repeated measure analysis, confirmatory factor analysis and cross-lagged panel analysis via structural equation modeling were conducted to test five competing models of PTSD symptom clusters, and to examine the mutual influences of PTSD symptom clusters and CMP outcomes. Results showed baseline pain intensity and pain disability predicted PTSD at 9 months. And baseline PTSD predicted improvement of pain disability at 9 months. Moreover, direct relationships were found between PTSD and the disability component of CMP, and indirect relationships were found between PTSD, CMP and CMP components (intensity and disability) mediated by depression, anxiety and pain catastrophizing. Finally, the coexistence of PTSD and more severe pain was associated with worse SF-36 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. Together these findings provided empirical support for the mutual maintenance theory.

Indiana University-Purdue University Indianapolis (IUPUI) / Epidemiologic and clinical studies routinely collect longitudinal measures of multiple outcomes. These longitudinal outcomes can be used to establish the temporal order of relevant biological processes and their association with the onset of clinical symptoms. In the first part of this thesis, we proposed to use bivariate change point models for two longitudinal outcomes with a focus on estimating the correlation between the two change points. We adopted a Bayesian approach for parameter estimation and inference. In the second part, we considered the situation when time-to-event outcome is also collected along with multiple longitudinal biomarkers measured until the occurrence of the event or censoring. Joint models for longitudinal and time-to-event data can be used to estimate the association between the characteristics of the longitudinal measures over time and survival time. We developed a maximum-likelihood method to joint model multiple longitudinal biomarkers and a time-to-event outcome. In addition, we focused on predicting conditional survival probabilities and evaluating the predictive accuracy of multiple longitudinal biomarkers in the joint modeling framework. We assessed the performance of the proposed methods in simulation studies and applied the new methods to data sets from two cohort studies. / National Institutes of Health (NIH) Grants R01 AG019181, R24 MH080827, P30 AG10133, R01 AG09956.

Indiana University-Purdue University Indianapolis (IUPUI) / Magnetic resonance (MR) spectroscopy is a neuroimaging technique. It is widely used to quantify the concentration of important metabolites in a brain tissue. Imbalance in concentration of brain metabolites has been found to be associated with development of neurological impairment. There has been increasing trend of using MR spectroscopy as a diagnosis tool for neurological disorders. We established statistical methodology to analyze data obtained from the MR spectroscopy in the context of the HIV associated neurological disorder. First, we have developed novel methodology to study the association of marker of neurological disorder with MR spectrum from brain and how this association evolves with time. The entire problem fits into the framework of scalar-on-function regression model with individual spectrum being the functional predictor. We have extended one of the existing cross-sectional scalar-on-function regression techniques to longitudinal set-up. Advantage of proposed method includes: 1) ability to model flexible time-varying association between response and functional predictor and (2) ability to incorporate prior information. Second part of research attempts to study the influence of the clinical and demographic factors on the progression of brain metabolites over time. In order to understand the influence of these factors in fully non-parametric way, we proposed LongCART algorithm to construct regression tree with longitudinal data. Such a regression tree helps to identify smaller subpopulations (characterized by baseline factors) with differential longitudinal profile and hence helps us to identify influence of baseline factors. Advantage of LongCART algorithm includes: (1) it maintains of type-I error in determining best split, (2) substantially reduces computation time and (2) applicable even observations are taken at subject-specific time-points. Finally, we carried out an in-depth analysis of longitudinal changes in the brain metabolite concentrations in three brain regions, namely, white matter, gray matter and basal ganglia in chronically infected HIV patients enrolled in HIV Neuroimaging Consortium study. We studied the influence of important baseline factors (clinical and demographic) on these longitudinal profiles of brain metabolites using LongCART algorithm in order to identify subgroup of patients at higher risk of neurological impairment. / Partial research support was provided by the National Institutes of Health grants U01-MH083545, R01-CA126205 and U01-CA086368