This thesis is about composite-based structural equation modeling. Structural equation modeling in general can be used to model both theoretical concepts and their relations to one another. In traditional factor-based structural equation modeling, these theoretical concepts are modeled as common factors, i.e., as latent variables which explain the covariance structure of their observed variables. In contrast, in composite-based structural equation modeling, the theoretical concepts can be modeled both as common factors and as composites, i.e., as linear combinations of observed variables that convey all the information between their observed variables and all other variables in the model. This thesis presents some methodological advancements in the field of composite-based structural equation modeling. In all, this thesis is made up of seven chapters. Chapter 1 provides an overview of the underlying model, as well as explicating the meaning of the term composite-based structural equation modeling. Chapter 2 gives guidelines on how to perform Monte Carlo simulations in the statistic software R using the package “cSEM” with various estimators in the context of composite-based structural equation modeling. These guidelines are illustrated by an example simulation study that investigates the finite sample behavior of partial least squares path modeling (PLS-PM) and consistent partial least squares (PLSc) estimates, particularly regarding the consequences of sample correlations between measurement errors on statistical inference. The third Chapter presents estimators of composite-based structural equation modeling that are robust in responding to outlier distortion. For this purpose, estimators of composite-based structural equation modeling, PLS-PM and PLSc, are adapted. Unlike the original estimators, these adjustments can avoid distortion that could arise from random outliers in samples, as is demonstrated through a simulation study. Chapter 4 presents an approach to performing predictions based on models estimated with ordinal partial least squares and ordinal consistent partial least squares. Here, the observed variables lie on an ordinal categorical scale which is explicitly taken into account in both estimation and prediction. The prediction performance is evaluated by means of a simulation study. In addition, the chapter gives guidelines on how to perform such predictions using the R package “cSEM”. This is demonstrated by means of an empirical example. Chapter 5 introduces confirmatory composite analysis (CCA) for research in “Human Development”. Using CCA, composite models can be estimated and assessed. This chapter uses the Henseler-Ogasawara specification for composite models, allowing, for example, the maximum likelihood method to be used for parameter estimation. Since the maximum likelihood estimator based on the Henseler-Ogasawara specification has limitations, Chapter 6 presents another specification of the composite model by means of which composite models can be estimated with the maximum likelihood method. The results of this maximum likelihood estimator are compared with those of PLS-PM, thus showing that this maximum likelihood estimator gives valid results even in finite samples. The last chapter, Chapter 7, gives an overview of the development and different strands of composite-based structural equation modeling. Additionally, here I examine the contribution the previous chapters make to the wider distribution of composite-based structural equation modeling. / Diese Arbeit beschäftigt sich mit kompositen-basierter Strukturgleichungmodellierung. Strukturgleichungsmodellierung kann genutzt werden um sowohl theoretische Konzepte als auch deren Beziehungen untereinander zu modellieren. In der traditionellen faktor-basierten Strukturgleichungsmodellierung werden diese theoretischen Konzepte als “common factor”, d.h. als latente Variablen, die die Kovarianzstruktur ihrer beobachteten Variablen erklären, modelliert. Im Gegensatz dazu, können in kompositen-basierter Strukturgleichungsmodellierung die theoretischen Konzepte sowohl als “common factor” als auch als Komposite, also als Linearkombinationen beobachteter Variablen, die die gesamte Information zwischen ihren beobachteten Variablen und allen anderen Variablen im Modell übertragen, modelliert werden. Diese Arbeit stellt einige methodische Weiterentwicklungen im Bereich der kompositenbasierten Strukturgleichungsmodellierung vor. Sie besteht aus insgesamt 7 Kapiteln. Kapitel 1 gibt zunächst einen Überblick über das zugrundeliegende Modell sowie über die Definition des Begriffs der kompositen-basierten Strukturgleichungsmodellierung. In Kapitel 2 wird anschließend eine Anleitung dafür gegeben, wie Monte Carlo Simulationen in der Statistik Software R mittels des Pakets “cSEM” für verschiedene Schätzer, die der kompositen-basierten Strukturgleichungsmodellierung zugeordnet werden, durchgeführt werden können. Diese Anleitung wird anhand einer beispielhaften Simulationsstudie veranschaulicht, die das Verhalten von Partial Least Squares Path Modeling (PLS-PM) und consistent Partial Least Squares (PLSc) Schätzungen in endlichen Stichproben untersucht, insbesondere im Hinblick auf die Auswirkungen von Stichprobenkorrelationen zwischen Messfehlern auf statistische Inferenz. Im dritten Kapitel werden Schätzer der kompositen-basierten Strukturgleichungsmodellierung vorgestellt, die robust gegenüber Ausreißern sind. Dafür werden Schätzer der kompositen-basierten Strukturgleichungsmodellierung, PLS-PM und PLSc, angepasst. Im Gegensatz zu den ursprünglichen Schätzern, können mit diesen Anpassungen Verzerrungen, die durch zufällig entstandene Ausreißer in Stichproben entstehen können, vermieden werden, was anhand einer Simulationsstudie gezeigt wird. In Kapitel 4 wird eine Methode zur Durchführung von Vorhersagen auf Basis von Modellen vorgestellt, die mit ordinal Partial Least Squares und ordinal consistent Partial Least Squares geschätzt wurden. Die beobachteten Variablen sind dabei ordinal kategorial skaliert, was sowohl bei der Schätzung als auch der Vorhersage explizit berücksichtigt wird. Die Vorhersagegüte wird mittels einer Simulationsstudie untersucht. Zusätzlich wird eine Anleitung, wie solche Vorhersagen mittels des R Pakets “cSEM” durchgeführt werden können, gegeben. Diese wird anhand eines empirischen Beispiels demonstriert. In Kapitel 5 wird die konfirmatorische Kompositenanalyse für Forschung im Bereich von “Human Development” vorgestellt. Mittels konfirmatorischer Kompositenanalyse können Kompositenmodelle geschätzt und auch evaluiert werden. In diesem Kapitel wird die Henseler-Ogasawara Spezifikation für Kompositenmodelle verwendet, wodurch beispielsweise die Maximum Likelihood Methode zur Parameterschätzung verwendet werden kann. Da der auf der Henseler-Ogasawara Spezifikation basierende Maximum Likelihood Schätzer Nachteile aufweist, wird in Kapitel 6 eine andere Spezifikation des Kompositmodells vorgestellt, mit der Kompositenmodelle mit der Maximum Likelihood Methode geschätzt werden können. Die Ergebnisse dieses Maximum Likelihood Schätzers werden mit denen von PLS-PM verglichen und somit gezeigt, dass dieser Maximum Likelihood Schätzer auch in endlichen Stichproben valide Ergebnisse liefert. Das letzte Kapitel, Kapitel 7, gibt einen Überblick über die Entwicklung und die verschiedenen Stränge der kompositen-basierten Strukturgleichungsmodellierung. Darüber hinaus wird hier der Beitrag, den die vorangegangenen Kapitel zur weiteren Verbreitung kompositen-basierter Strukturgleichungsmodellierung leisten, aufgezeigt.

The aim of this thesis is to investigate the appropriateness of B2B technology transfer in developing countries, particularly in Thailand. This study seeks an understanding of how Thai culture affects the appropriateness of B2B technology adoption for inter-firm communication in Thailand. A research model was developed for investigating this issue via a strategic fit lens. The proposed model extended the Task-technology fit (TTF) model by Goodhue and Thompson (1995) by integrating interorganisational theories and theories of national culture. This research takes the view that, to achieve a high utilisation of B2B technology adoption, firms in developing countries need to adopt effective IT strategies that align with their local environment. Hence, this research proposes that cultural fit is a major influence on the perception of appropriateness of B2B technology adoption in Thailand. The study was conducted using both qualitative and quantitative approaches. The first study, the qualitative study, was conducted as a preliminary study by interviewing officials in the Thai government and companies in the tourism industry. The objectives were to explore and identify the cultural dimensions that impact on the appropriateness of B2B technology adoption in Thailand. The resulting dimensionalities of cultural fit are: personal relationships; long-term relationships; interorganisational trust; ability to communicate in the English language and materialism. The second study was conducted via a quantitative approach and scales were developed to validate the proposed research model. Data were collected through a survey questionnaire, and analysed by using Structural Equation Modeling with Partial Least Squares (PLS) method. This study found that cultural fit does influence the appropriateness of B2B technology adoption in Thailand. A better perceived fit between Thai culture and B2B technology results in higher technology utilisation. In addition, the results of moderating effect analysis found that, although task-technology fit had no direct impact on utilisation, task-technology fit did have indirect impact on utilisation by moderating the impact of culture. Nevertheless, the results indicated that task-technology fit still had a greater impact on firms' perceived performance than utilisation.

Executive functions (EFs), specifically a child's ability to shift between two stimuli and a child's ability to inhibit a prepotent response, are a child's self-regulatory cognitive processes used towards achieving a goal (Garon, Bryson, & Smith, 2008) and have been found to predict later school readiness (e.g. Blair & Diamond, 2008; McClelland et al., 2007; Pennington & Ozonoff, 1996). The current study examined possible mechanisms, such as problem behaviors and theory of mind (ToM), through which executive functions predict later cognitive and social school readiness. Problem behaviors occur when children are not effectively functioning in social situations, while ToM is a social-cognitive skill that allows a child to understand another person's mental processes (Wellman, 2002). These variables have been found to relate to one another in predicting preschool children's competence in numerous domains (see Carlson, Mandell, & Williams, 2004; Hughes, 1998b). Little research has been done on how these variables may mediate the relation between EFs and cognitive and social school readiness. This short-term longitudinal study assessed the unique contributions of ToM and problem behaviors to cognitive and social school readiness. Problem behaviors mediated the relation between EF, specifically inhibition, and social school readiness. Both teacher reports and direct assessment of EF revealed that EF, and specifically shifting, were direct predictors of later cognitive school readiness. However, ToM did not mediate any of the relations between EF and either social or cognitive school readiness. These results have several implications for education, including intervening with a child's ability to inhibit in order to improve problem behaviors and later social school readiness, as well as improving children's ability to mentally and behaviorally shift between sets of information in order to improve cognitive school readiness.

Problem: Many individuals with chronic illnesses such as stroke and ongoing activity limitations report self-perceived health related quality of life (HRQL) that is similar to that of healthy individuals. This phenomenon is termed response shift (RS). RS describes how people change: internal standards in assessing HRQL (recalibration), values (reprioritization), or how they define HRQL (reconceptualization), after an event such as stroke. Changes in HRQL post stroke may be inaccurate if RS is not taken into account. Increased knowledge of RS may affect the way in which HRQL measures are used, both clinically and in research. The overall objective was to assess RS in construct specific HRQL models post stroke: physical function, mental health, and participation. Methods: Data were analysed from the longitudinal study “Understanding Quality of Life Post-Stroke: A Study of Individuals and their Caregivers”. Six-hundred and seventy- eight persons with stroke at 1, 3, 6, and 12 months post stroke participated. Generic and stroke specific HRQL measures were collected. Descriptive analysis was completed with SAS, and identification of RS utilized structural equation modeling with LISREL. Results: Mean age of participants was 67 years (SD 14.8), and 45% were female. RS was identified in mental health using a framework which was developed for identifying RS statistically with multiple time points. RS was also identified in physical function where it had not been expected, possibly due to the self perceived nature of the response options. The effect size of change in physical function was affected by the presence of RS. The timing of RS in mental health and physical function was primarily around the 12 month time period, and predominantly recalibration RS. RS was also identified in participation. Conclusions: The framework that was developed was useful in identifying RS and incorporated important issues such as multiple testing and validation of the model. The presence of RS affects measurement of HRQL constructs post stroke; recalibration RS can be measured clinically with specific methods to account for RS. RS should also be measured in research studies to ensure accurate measurement of change. Future research should evaluate additional models in stroke and other populations. / October 2008

Abstract The purpose of this investigation is based on the revision model proposed by Ferris , Adams, Kolodinsky, Hochwarter, Ammeter,(2002).This research is deeply to examine the influence of perceptions of organizational politics on trust - organizational cynicism as mediator variable .The data were analyzed by SPSS 15.0 software and by structural equation modeling (SEM). The major results of this study are as following¡GThe perceptions of organizational politics were found have a significant negative relationship with trust. The perceptions of organizational politics were constructed from three patterns( general political behavior¡Bgo along to get ahead¡Bpay and promotion).Only general political behavior has a significant effect on trust.The other two patterns have no significant effect on trust. The perceptions of organizational politics were found have a significant positive relationship with organizationl cynicism . Organizationl cynicism has a significant negative relationship with trust.Organizationl cynicism has a mediating effect on the relationship between perceptions of organizational politics and trust. Key word¡Gperceptions of organizational politics , trust , organizationl cynicism , structural equation modeling

This research is based on the framework of revision model proposed by Ferris et al. (2002), discussing the influence organization politics consciousness to staff's from Machiavellianism and type A personality. The sample consisted of 1890 employee selected from 40 organizations covering 9 industrial sectors in Taiwan. The data were analyzed by descriptive statistics, reliability analysis, confirmatory factor analysis, correlation analysis and structural equation modeling and the summarized findings are in the following sections. The major results of this study are as fallowing: 1. Machiavellianism has a significant effect on employees¡¦ general political behavior of organizational politics perceptions. 2. Machiavellianism has a significant effect on employees¡¦ benefits of remaining silence of organizational politics perceptions. 3. Machiavellianism has a significant effect on employees¡¦ salary and promotion policies of organizational politics perceptions. 4. Type A personality has a significant effect on employees¡¦ general political behavior of organizational politics perceptions. 5. Type A personality has a significant effect on employees¡¦ benefits of remaining silence of organizational politics perceptions. 6. Type A personality has a significant effect on employees¡¦ salary and promotion policies of organizational politics perceptions.

The perceptions of organizational politics and organizational citizenship behavior are neither regulated nor indentified in any organization. But, they are exactly existed in organization. This study is based on the revise model of Perceptions of Organizational Politics (POP) proposed by Ferris et al. (2002). We investigate the relationship between the perceptions of organizational politics and the organizational citizenship behavior. Furthermore, we investigate the indirect effect between the perceptions of organizational politics and the subordinates of organizational citizenship behavior. This study used the scales of 35 items collected by Dr. Chin-ming Ho and the other members of the last research team of POP in 2008. The research is based on the revision model of POP and questionnaire survey. The sample consisted of 1,890 employee selected from 40 organizations covering 9 industrial sectors in Taiwan. The method, path analysis with latent variables of the structural equation modeling (SEM) is used to measure the relationship among the constructs. The major result of this study is as following: 1. The perceptions of organizational politics have negative effect on the organizational citizenship behavior. 2. The perceptions of organizational politics have negative effect on the altruism toward colleagues 3. The perceptions of organizational politics have negative effect on the conscientiousness 4. The perceptions of organizational politics have negative effect on the identification with company 5. The perceptions of organizational politics have negative effect on the interpersonal harmony 6. The perceptions of organizational politics have negative effect on the protecting company resources

Abstract The escalating fuel price in Taiwan has prompted the transportation industry to explore renewable energy sources for fuels, but what is more urgent at this stage is to improve transportation efficiency to cut transportation costs. The aim of this study is to implement fuel-efficient rewards to modify driving behavior, thereby improving fuel efficiency. The outcome of this strategy is not only about slowing down greenhouse gas production, but also a reduction of fuel costs of transportation companies. Every year highway bus companies consume millions of liters of fuel, and their fuel costs often exceed hundreds of millions of dollars. Therefore, how to conserve on fuel consumption has become an important issue for all of the bus companies. However so far, besides the eventual fuel savings data, there is still a lack of objective methods to evaluate the execution of such conservation programs. the project will use the ¡§Motivation-Opportunity-Ability Method¡¨ ¡]MOA¡^to develop an analysis model; verification of dynamic data analysis will be conducted using Single or Multilevel Structural Equation Modeling (Multilevel SEM). According to the above research results show that Taken together the investigators suggest those public as well as private transportation companies that have not implemented fuel-efficient related policies to start planning fuel-efficient reward programs and implementing the programs as soon as possible. Furthermore, transportation companies should give courses about environmental driving to teach drivers correct environmental-friendly driving as well as award or publicly praise fuel-efficient drivers. These strategies will bring good outcome for drivers, transportation companies, and environmental protection.

none

This research investigated the decision process surrounding the self-regulated learning of new uses of existing technology. With firms investing up to 50% of their capital budgets on information technology (in excess of 1 trillion dollars in aggregate), understanding what factors motivate or inhibit more encompassing use of technology is of practical concern (Bowen 1986; Nambisan et al. 1999; Mahmood et a. 2001). I introduced a dynamic element to the technology adoption/acceptance literature by using a framework based upon deferral option theory. This framework allows for the decision to learn a new use of technology to occur over time. I found that potential users chose to defer learning new uses of technology even when usefulness was evident and ease of learning was not prohibitive. Further, an additional benefit to using the deferral option framework was its inclusion of both rewards and penalties; I found that not only do potential users consider what can be gained by learning, but also what can be lost by trying to learn and failing. In addition to using a framework premised on deferral option theory, I investigated the properties of time pressure and subjective norms on the decision to learn new uses of technology. As time pressure offered a possible alternate explanation for why potential users defer learning, I controlled for it experimentally and determined that time pressure did affect deferral choice. Further, as subjective norms have had limited success as a predictor of intent to use technology in prior literature, I investigated the separate pieces of the theoretical construct, referent group perceptions and the motivation to comply with those perceptions. By manipulating environment between work and play settings, different motivational sources were enacted by the potential users. Specifically, I found that when potential users were externally motivated subjective norms did influence deferral, and when internally motivated, subjective norms did not influence a potential user??s decision to defer learning a new use of technology.