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.

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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.

While information technology has rapidly changed work in the United States in the past 50 years, some businesses and industries have been slow to adopt new technologies. Healthcare is one industry that has lagged behind in information technology investment for a variety of reasons. Recent federal initiatives to encourage IT adoption in the healthcare industry provide an ideal context to study factors that influence technology acceptance. Data from 261 practicing pediatricians were collected to evaluate an extended Technology Acceptance Model. Results indicated that individual (i.e., perceived usefulness, perceived ease of use), organizational (i.e., subjective norm), and device (i.e., compatibility, reliability) characteristics collectively influence pediatricians' intention to adopt tablet computers in their medical practice. Theoretical and practical implications are discussed. Future research should examine additional variables that influence information technology adoption in organizations.

The abilities of life insurers can be divided and measured from various aspects. Through the use of structural equation modeling, we investigate the relations among solvency, operation ability and profitability in year 1994, 1995 and 1996. After within-year analysis and longitudinal data analysis, we found that operation ability has a positive influence on the size and income of life insurers and has a slight negative effect on the return on capital during these years. While the effect of solvency, asset risk and product risk on return on capital is not significant. / text

In order to fully explicate the role of news media in individuals’ political participation, this dissertation aims at establishing an integrative structural model that specifies relationships among news media use, its antecedents and mediators of its influence on political participation. The proposed model is comprised of key factors of political participation that previous research has identified. The relational structure is based on models and theories relevant to prediction of political behaviors. Specifically, the model integrates (a) communication mediation model, which posits that communication behaviors (i.e., news media use and interpersonal discussion) mediate the effects of socio-demographic variables (i.e., income, education, age, gender, and race) and political dispositions (i.e., political interest, partisanship and ideology) on political outcomes; (b) agenda-setting theory, which posits that frequent exposure to news media increases the salience of news objects in audiences’ minds; (c) cognitive mediation model, which posits that elaborative and collective thinking is a prerequisite to produce political outcomes of news exposure; (d) theory of planned behavior, which posits that human behavior can be best predicted by three proximal variables (i.e., attitudes, subjective norms, and perceived behavioral control); (e) O-S-R-O-R (orientations-stimulus-reasoning-orientations-response) model of communication effects, which provides a parsimonious framework of effect process. Using the structural equation modeling (SEM) method, this dissertation analyzes the 2008 American National Election Studies data set to test the validity of the proposed structural model. Results indicate that frequent exposure to news media stimulates attentive news use as well as intra- and interpersonal reasoning, which produce a wide range of political outcomes. Two reasoning behaviors (i.e., self-reflection and interpersonal political discussion) are critical mechanisms that linked news media use to various political outcomes including political participation. Personal-psychological mediators, such as strength in affects, personal traits, opinions about political issues, campaign interest, political knowledge, attitude strength, perceived ability of political parties and political efficacy all significantly mediate the influence of news media use on political participation. News media use mediates significant portion of effects that a set of preexisting variables have on political participation as well as various types of political orientations. / text

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.

Background: The first aim of this thesis was to systematically review the evidence for the impact of interpersonal trauma in childhood on appraisals of auditory hallucinations in adulthood. Informed by this systematic review and cognitive models of psychosis, potential moderators of the relationship between trauma and distress were proposed. Hypotheses: It was hypothesised that the experience of interpersonal trauma in childhood would predict ‘self blaming’ and ‘danger to self’ appraisals made by voice hearers about their auditory hallucinations. It was predicted that these appraisals would interact with the use of avoidant and non avoidant coping strategies and that this would predict wellbeing. Method 1 and results: In order to measure voice appraisals, the Interpretation of Voices Inventory was adapted. It was completed by one hundred and thirteen voice hearing participants and confirmatory factor analysis was used to test the predicted factors. Most items covaried with their respective factors acceptably. A number of items did not load well and it was recommended that they be removed from the measure. The amended factor structure improved the fit of the measure to an acceptable standard. Method 2 and results: Sixty two participants completed additional measures of interpersonal trauma in childhood and wellbeing. Structural equation modeling provided support for a link between severity of childhood trauma and ‘danger to self’ appraisals. ‘Danger to self’ appraisals predicted the use of acceptance based coping and this predicted wellbeing. Independent of this model, interpersonal coping was shown to predict the use of psychological explanations for the experience of auditory hallucinations. Psychological explanations did not predict acceptance or wellbeing. Discussion: It may be clinically helpful to test acceptance based interventions using ‘danger to self’ appraisals as an outcome measure in the future. Possible factors that may have influenced the results were reflected on. The potentially negative impact of insight on wellbeing was discussed. Stigma was highlighted as a potential barrier to non avoidant coping

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.

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.