This programme of research was focused on developing a better understanding of pro-environmental behaviours and pro-environmental behaviour change, with consideration of the powerful effect of habits in thinking, affect and behaviour. Habit networks are discussed with reference to HOT topics (Habits, Opportunities and Thoughts), and explored empirically within the context of the FIT Framework (Fletcher & Stead, 2000). This programme of research started with a literature review on established models of pro-environmental behaviour. It found a large degree of similarity in the approaches used to conceptualise pro-environmental behaviour, and suggested the need to explore pro-environmental activity from different perspectives. The FIT Framework was then presented as an alternative approach. FIT variables measure the strength of an individual's cognitive characteristics and their degree of behavioural flexibility using the FIT Profiler (Fletcher, 1999). The empirical studies presented in this programme of research suggest that levels of personal FITness are related to engagement with pro-environmental activity and the extent to which lifestyles are environmentally sustainable. Study 1 (N = 325) explored the relationships between FITness and measures of pro-environmental activity, and Study 2 (N = 134) sought to confirm these relationships in a different sample. Both studies found positive relationships between levels of personal FITness and pro-environmental activity. Based on these results, it was suggested that FIT offers a useful alternative framework to study pro-environmental activity. Studies 3 (N = 75) and 4 (N = 100) considered the performance of pro-environmental behaviours in different sites of practice, as follow-up to the differences that emerged in Studies 1 and 2. They also explored the perceived influence of intrinsic and extrinsic variables on energy saving in home and work settings. The results suggested that the pro-environmental behaviours that are performed at home are often not transferred to the workplace and this might be because extrinsic factors in an organisational setting constrain action. Higher levels of personal FITness helped to align behaviours with intrinsic beliefs; individuals with higher levels of FITness behaved as they felt they ought to, whereas individuals with lower levels of FITness behaved as they were told to. It was suggested, therefore, that higher levels of FITness might support behavioural consistency across contexts. Study 5 (N = 95) explored the extent to which pro-environmental behaviours are characterised by habit and how the strength of habit changes according to level of personal FITness. The results suggested that people act pro-environmentally within distinct behaviour categories and this has little or no bearing on their propensity to behave in an environmentally friendly way in other areas. Habits can have a positive influence on the performance of pro-environmental behaviour but a negative influence on behaviour change. The empirical results suggest that a higher level of FITness might help people to engage more readily with pro-environmental behaviours that are performed less frequently. It was, therefore, suggested that developing levels of personal FITness might help individuals to extend their behavioural repertoire and be sufficiently flexible to include more pro-environmental behaviours, including those that are, at present, characterised less by habit. A second literature review on interventions for pro-environmental behaviour change found that many techniques have been developed from the perspective of bounded rationality and have assumed that the provision of information will initiate behaviour change. These approaches are often ineffective because of the resistive effects of habit. In light of this and the findings of the empirical studies, a FIT-based behaviour change intervention, named here as Do Something Greener, was developed as an alternative approach to address directly the problem of habit. Overall, this programme of research suggests that the influence of habits, opportunities, and thoughts should be considered in the study of pro-environmental activity. Further research exploring the effectiveness of Do Something Greener for pro-environmental behaviour change is necessary and planned as the next step in this programme of research. By exploring pro-environmental behaviour from a different perspective, it is hoped that this programme of research has also challenged some of the habitual tendencies that researchers are themselves starting to develop in relation to the study of pro-environmental behaviour, and that it has added a degree of eclecticism and pragmatism to psychological approaches to pro-environmental behaviour change. It is hoped that this will help to set a more practically oriented agenda for future research.

In the presented thesis we investigate heteroepitaxial growth of one element (one type of adsorbate A with negative or positive misfit relative to substrate S) and static properties of two-component surface alloy, i.e. ternary system (two types of adsorbate A and B with negative and positive misfit relative to different substrat S). We use Monte Carlo simulations for an off-lattice model in (1+1) dimensions with Lennard-Jones interaction. In case of incoherent heteroepitaxial growth we investigate formation of misfit dislocations, their influence on structure of growing film and impurity-induced formation of dislocations. Two different types of formation of dislocations are found, depending on the sign and magnitude of misfit. Simulations of static properties of two-component surface alloys show that morphology is quite different for phase separation (formation of domains consist of one type of particles in direction along and vertically towards to substrate-adsorbate interface) and intermixing regime. The structures, which emerged, depend on relative misfit, interaction and concentration of individual elements.

This thesis deals with the goodness of fit tests in nonparametric model in the presence of unknown parameters of the probability distribution. The first part is devoted to understanding of the theoretical basis. We compare two methodologies for the construction of test statistics with application of empirical characteristic and empirical distribution functions. We use kernel estimates of regression functions and parametric bootstrap method to approximate the critical values of the tests. In the second part of the thesis, the work is complemented with the simulation study for different choices of weighting functions and parameters. Finally we illustrate the use and the comparison of goodness of fit tests on the example with the real data set. Powered by TCPDF (www.tcpdf.org)

The presented master thesis is an exploratory, multiple case study that analyzes the recruitment practices and their respective processes in five family firms located in the Southern part of Germany. A strong HR function inside a company is necessary to stay competitive in the market and survive in the long-run. Hereby recruitment is an important field of research because firms depend on their employees who are ultimately the vital factor in running a successful business. Recruitment is an ongoing process in a dynamic business world and a very crucial responsibility of HRM inside the organization. Especially due to the strong family involvement, commitment to the localities, overlap between financial and nonfinancial goals, and a deeply ingrained business culture based on the family founders’ values, establishing an effective recruitment process is even more important in family than in nonfamily firms. Thus, this study aims at exploring and researching individual characteristics associated with the recruitment practices and tries to display the main influencing factors in the recruitment process of the studied firms. Through analyzing secondary and primary data collected with the help of semi-structured interviews, the authors were able to gather insightful data from CEOs and HR representatives in order to draw comprehensive conclusions regarding how suitable employees are recruited in family firms. The results show that the person-organization (P-O) fit is a main component which family firms try to assess in their applicants. Personality and the fit to the respective business culture, apart from the actual skill-set, is an additional requirement for being recruited. Through various recruitment channels, strategies, and assessments the family firms try to use the construct of familiness to their advantage and benefit.

Doctor of Philosophy / Department of Statistics / Weixing Song / The regression model has been given a considerable amount of attention and played a significant role in data analysis. The usual assumption in regression analysis is that the variances of the error terms are constant across the data. Occasionally, this assumption of homoscedasticity on the variance is violated; and the data generated from real world applications exhibit heteroscedasticity. The practical importance of detecting heteroscedasticity in regression analysis is widely recognized in many applications because efficient inference for the regression function requires unequal variance to be taken into account. The goal of this thesis is to propose new testing procedures to assess the adequacy of fitting parametric variance function in heteroscedastic regression models. The proposed tests are established in Chapter 2 using certain minimized L[subscript]2 distance between a nonparametric and a parametric variance function estimators. The asymptotic distribution of the test statistics corresponding to the minimum distance estimator under the fixed model and that of the corresponding minimum distance estimators are shown to be normal. These estimators turn out to be [sqrt]n consistent. The asymptotic power of the proposed test against some local nonparametric alternatives is also investigated. Numerical simulation studies are employed to evaluate the nite sample performance of the test in one dimensional and two dimensional cases. The minimum distance method in Chapter 2 requires the calculation of the integrals in the test statistics. These integrals usually do not have a tractable form. Therefore, some numerical integration methods are needed to approximate the integrations. Chapter 3 discusses a nonparametric empirical smoothing lack-of-fit test for the functional form of the variance in regression models that do not involve evaluation of integrals. empirical smoothing lack-of-fit test can be treated as a nontrivial modification of Zheng (1996)'s nonparametric smoothing test and Koul and Ni (2004)'s minimum distance test for the mean function in the classic regression models. The asymptotic normality of the proposed test under the null hypothesis is established. Consistency at some fixed alternatives and asymptotic power under some local alternatives are also discussed. Simulation studies are conducted to assess the nite sample performance of the test. The simulation studies show that the proposed empirical smoothing test is more powerful and computationally more efficient than the minimum distance test and Wang and Zhou (2006)'s test.

By testing a fiber beard, certain cotton fiber length parameters can be obtained rapidly. This is the method used by the High Volume Instrument (HVI). This study is aimed to explore the approaches and obtain the inference of length distributions of HVI beard sam- ples in order to develop new methods that can help us find the distribution of original fiber lengths and further improve HVI length measurements. At first, the mathematical functions were searched for describing three different types of length distributions related to the beard method as used in HVI: cotton fiber lengths of the original fiber population before picked by the HVI Fibrosampler, fiber lengths picked by HVI Fibrosampler, and fiber beard's pro-jecting portion that is actually scanned by HVI. Eight sets of cotton samples with a wide range of fiber lengths are selected and tested on the Advanced Fiber Information System (AFIS). The measured single fiber length data is used for finding the underlying theoreti-cal length distributions, and thus can be considered as the population distributions of the cotton samples. In addition, fiber length distributions by number and by weight are dis- cussed separately. In both cases a mixture of two Weibull distributions shows a good fit to their fiber length data. To confirm the findings, Kolmogorov-Smirnov goodness-of-fit tests were conducted. Furthermore, various length parameters such as Mean Length (ML) and Upper Half Mean Length (UHML) are compared between the original distribution from the experimental data and the fitted distributions. The results of these obtained fiber length distributions are discussed by using Partial Least Squares (PLS) regression, where the dis-tribution of the original fiber length from the distribution of the projected one is estimated.

No description available.

<div>Networks and point processes provide flexible tools for representing and modeling complex dependencies in data arising from various social and physical domains. Graphs, or networks, encode relational dependencies between entities, while point processes characterize temporal or spatial interactions among events.</div><div><br></div><div>In the first part of this dissertation, we consider dynamic network data (such as communication networks) in which links connecting pairs of nodes appear continuously over time. We propose latent space point process models to capture two different aspects of the data: (i) communication occurs at a higher rate between individuals with similar latent attributes (i.e., homophily); and (ii) individuals tend to reciprocate communications from others, but in a varied manner. Our framework marries ideas from point process models, including Poisson and Hawkes processes, with ideas from latent space models of static networks. We evaluate our models on several real-world datasets and show that a dual latent space model, which accounts for heterogeneity in both homophily and reciprocity, significantly improves performance in various link prediction and network embedding tasks.</div><div><br></div><div>In the second part of this dissertation, we develop nonparametric goodness-of-fit tests for discrete distributions and point processes that contain intractable normalization constants, providing the first generally applicable and computationally feasible approaches under those circumstances. Specifically, we propose and characterize Stein operators for discrete distributions, and construct a general Stein operator for point processes using the Papangelou conditional intensity function. Based on the proposed Stein operators, we establish kernelized Stein discrepancy measures for discrete distributions and point processes, which enable us to develop nonparametric goodness-of-fit tests for un-normalized density/intensity functions. We apply the kernelized Stein discrepancy tests to discrete distributions (including network models) as well as temporal and spatial point processes. Our experiments demonstrate that the proposed tests typically outperform two-sample tests based on the maximum mean discrepancy, which, unlike our goodness-of-fit tests, assume the availability of exact samples from the null model.</div><div><br></div>

The study sought to investigate whether the effects of an employee’s fit or misfit with the ethical climate of an organisation is mitigated or exacerbated by the quality of the leader-member exchange experienced. The outcome variables looked at includes organisational commitment, job satisfaction and turnover intentions. Data was gathered from a total sample of 125 employees from three different non profit making organisations. Pearson Product Moment Correlations and moderated regressions were used to address the main research questions of the study. Despite, the implied theoretical link between ethical climate fit and leader member exchange, partly as a function of the constructs being centred on the notion of fit, and the role organisational leaders play in the formation of ethical climates, no significant moderation effects were found. Both variables were found to relate significantly to all job outcomes, but no combined effects of these variables on job outcomes were found. The findings of the study highlight a need for further empirical research on these concepts, and for the inquiring of existing theoretical propositions linking leaders to ethical climates.

Denna rapport behandlar ett arbete sju studenter som läste kursen TDDD96: Kandidatprojekt i programutveckling utförde under vårterminen 2019. Arbetets syfte var att utforska möjligheten att skicka in personlig hälsodata till Region Östergötland via en hemsida. För att åstadkomma detta utvecklades en webbapplikation, samt utfördes en utredning av openEHR:s datastrukturer och API för att kunna koppla applikationen till Region Östergötlands journalsystem. Resultatet blev en fungerande webbapplikation som hämtar data från hälsoplattformen Google Fit och skickar därefter in det till en journal via openEHR:s REST-API. Hälsodata som hämtats från Google Fit är data som samlats in med sensorer från mobiler och smartklockor såsom puls och antal steg. Denna rapport avser att ge en inblick i utvecklingsprocessen, beskriva de bakomliggande besluten, de problem som uppstått under projektets gång och dess lösningar, samt diskutera resultatet. Med i rapporten finns även de individuella kandidatrapporter medlemmarna i gruppen har skrivit, dessa hittas sist i dokumentet.