Uppsatsen ämnar identifiera vilka egenskaper som upplevs vara önskvärda i ett arbete samt om dessa varierar mellan olika grupper i samhället. Vidare studeras i vilken mån önskvärda egenskaper tillgodoses i arbetet och på vilket sätt matchning mellan önskemål och verklighet påverkar arbetstillfredsställelsen. Datamaterialet som ligger till grund för uppsatsen har inom ramen för International Social Survey Programme (ISSP) insamlats 2016 via en enkätundersökning gällande åsikter om jobb och arbetslivet. Resultaten visar att samtliga önskvärda egenskaper som studeras upplevs vara viktiga, samtidigt som vissa skillnader över vad som värderas högt återfinns mellan bland annat kön, ålder och sektor. Vidare visas att önskemål som realiseras i arbetet ökar arbetstillfredsställelsen. Framförallt är ett intressant och självständigt arbete viktigt för att känna sig nöjd.

D. Phil. / There have been two rather distinct approaches to the analysis of time series: the time domain approach and frequency domain approach. The former is exemplified by the work of Quenouille (1957), Durbin (1960), Box and Jenkins (1970) and Ljung and Box (1979). The principal names associated with the development of the latter approach are Slutsky (1929, 1934), Wiener (1930, 1949), Whittle (1953), Grenander (1951), Bartlett (1948, 1966) and Grenander and Rosenblatt (1957). The difference between these two methods is discussed in Wold (1963). In this thesis, we are concerned with a frequency domain approach. Consider a model of the "signal plus noise" form yt = g (2t — 1 2n ) + 77t t= 1,2,—. ,n (1.1) where g is a function on (0, 1) and Ti t is a white noise process. Our interest is primarily in testing the hypothesis that g is constant, that is, that it does not change over time. There is a vast literature related to this problem in the special case where g is a step function. In that case (1.1) specifies an abrupt change model. Such abrupt change models are treated extensively by Csorgo and Horvath (1997), where an exhaustive bibliography can also be found. The methods associated with the traditional abrupt change models are, almost without exception, time domain methods. The abrupt change model is in many respects too restrictive since it confines attention to signals g that are simple step functions. In practical applications the need has arisen for tests of constancy of the mean against a less precisely specified alternative. For instance, in the study of variables stars in astronomy (Lombard (1998a)) the appropriate alternative says something like: "g is non-constant but slowly varying and of unspecified functional form". To accommodate such alternatives within a time domain approach seems to very difficult, if at all possible. They can, however, be accommodated within a frequency domain approach quite easily, as shown by, for example, Lombard (1998a and 1998b). Tests of the constancy of g using the frequency domain characteristics of the observations have been investigated by a number of authors. Lombard (1988) proposed a test based on the maximum of squared Fourier cosine coefficients at the lowest frequency oscillations. Eubank and Hart (1992) proposed a test which is based on the maximum the averages of Fourier cosine coefficients. The essential idea underlying these tests is that regular variation in the time domain manifests itself entirely at low frequencies in the frequency domain. Consequently, when g is "high frequency" , that is consists entirely of oscillations at high frequencies, the tests of Lombard (1988) and of Eubank and Hart (1992) lose most of their power. The fundamental tool used in frequency domain analysis is the periodogram; see Chapter 2 below for the definition and basic properties of the latter. A new class of tests was suggested by Lombard (1998b) based on the weighted averages of periodogram ordinates. When 7i t in model (1.1) are i.i.d. random variables with zero mean and variance cr-2 , one form of the test statistic is T1r, = Etvk fiy (A0/0-2 - (1.2) k=1 where wk is a sequence of constants that decrease as k increases and m = [i]. The rationale for such tests is discussed in detail in Lombard (1998a and 1998b). The greater part of the present Thesis consists of an investigation of the asymptotic null distributions, and power, of such tests. It is also shown that such tests can be applied directly to other, seemingly unrelated problems. Three instances of the latter type of application that are investigated in detail are (i) frequency domain competitors of Bartlett's test for white noise, (ii) frequency domain-based tests of goodness-of-fit and (iii) frequency domain-based tests of heteroscedasticity in linear or non-linear regression. regression. The application of frequency domain methods to these problems are, to the best of our knowledge, new. Until now, most research has been restricted to the case where m in (1.1) are i.i.d. random variables. As far as the correlated data are concerned, the changepoint problem was investigated by, for instance, Picard (1985), Lombard and Hart (1994) and Bai (1994) using time domain methods. Kim and Hart (1998) proposed two test statistics derived from frequency domain considerations and that are modeled along the lines of the statistics considered by Eubank and Hart (1992) in the white noise case. An analogue of the type of test statistic given in (1.2) for use with correlated data was proposed, and used, by Lombard (1998a). The latter author does not, however, provide statements or proofs regarding the asymptotic properties of the proposed test.

Testing uniformity in the univariate case has been studied by many researchers. Many papers have been published on this issue, whereas the multi-dimensional uniformity test seems to have received less attention in the literature. A new test statistic for the multi-dimensional uniformity is proposed in this thesis. The proposed test statistic can be used to test whether an underlying multivariate probability distribution differs from a multi-dimensional uniform distribution. Some important properties of the proposed test statistic are discussed. As a special case, the bivariate test statistic is discussed in detail and the critical values of test statistic are obtained. By performing Monte Carlo simulation, the power of the new test is compared with the Distance to Boundary test, which was a recently proposed statistical test for multi-dimensional uniformity by Berrendero, Cuevas and Vazquez-Grande (2006). It has been shown that the test proposed in this thesis is more powerful than the Distance to Boundary test in some cases.

This thesis investigates Goodness-of-Fit tests for parametric regression models. With the help of sufficient dimension reduction techniques, we develop adaptive-to-model tests using projection in both the fixed dimension settings and the diverging dimension settings. The first part of the thesis develops a globally smoothing test in the fixed dimension settings for a parametric single index model. When the dimension p of covariates is larger than 1, existing empirical process-based tests either have non-tractable limiting null distributions or are not omnibus. To attack this problem, we propose a projected adaptive-to-model approach. If the null hypothesis is a parametric single index model, our method can fully utilize the dimension reduction structure under the null as if the regressors were one-dimensional. Then a martingale transformation proposed by Stute, Thies, and Zhu (1998) leads our test to be asymptotically distribution-free. Moreover, our test can automatically adapt to the underlying alternative models such that it can be omnibus and thus detect all alternative models departing from the null at the fastest possible convergence rate in hypothesis testing. A comparative simulation is conducted to check the performance of our test. We also apply our test to a self-noise mechanisms data set for illustration. The second part of the thesis proposes a globally smoothing test for parametric single-index models in the diverging dimension settings. In high dimensional data analysis, the dimension p of covariates is often large even though it may be still small compared with the sample size n. Thus we should regard p as a diverging number as n goes to infinity. With this in mind, we develop an adaptive-to-model empirical process as the basis of our test statistic, when the dimension p of covariates diverges to infinity as the sample size n tends to infinity. We also show that the martingale transformation proposed by Stute, Thies, and Zhu (1998) still work in the diverging dimension settings. The limiting distributions of the adaptive-to-model empirical process under both the null and the alternative are discussed in this new situation. Simulation examples are conducted to show the performance of this test when p grows with the sample size n. The last Chapter of the thesis considers the same problem as in the second part. Bierens's (1982) first constructed tests based on projection pursuit techniques and obtained an integrated conditional moment (ICM) test. We notice that Bierens's (1982) test performs very badly for large p, although it may be viewed as a globally smoothing test. With the help of sufficient dimension techniques, we propose an adaptive-to-model integrated conditional moment test for regression models in the diverging dimension setting. We also give the asymptotic properties of the new tests under both the null and alternative hypotheses in this new situation. When p grows with the sample size n, simulation studies show that our new tests perform much better than Bierens's (1982) original test.

Riskkapitalister har en särskilt viktig roll i fostrandet av unga innovativa företag. Förutom att bidra med kapital försöker riskkapitalister också tillföra sina portföljbolag värde genom att bistå med värdefulla kontakter, rådgivning och moraliskt stöd. Hur effektivt de lyckas tillföra värde har visats bero på olika egenskaper av deras relation, men exakt på vilket sätt är ännu oklart. För att besvara frågan om hur relationen mellan riskkapitalist och entreprenör påverkar portföljbolagets prestation genomfördes djupintervjuer med fem svenska riskkapitalister. Resultatet visar att (1) en ömsesidig samarbetsvilja och målkongruens, (2) en överensstämmande syn på arbetsprocesser och yrkesroller, (3) en optimal kunskapsöverlappning samt (4) personkemi i relationen mellan riskkapitalist och entreprenör var associerat med en framgångsrik portföljbolagsutveckling, men endast i något större utsträckning jämfört med en misslyckad portföljbolagsutveckling. Slutsatsen är att riskkapitalisten måste beakta relationen till entreprenören innan såväl som efter investering.

Numerous short flapped DNA structures are created during the semi-discontinuous replication. These toxic intermediates are quickly resolved to produce a fully intact duplex of replicated DNA. Structure specific nuclease are key to resolving these structures, and show a high degree of specificity for their cognate substrate structures while being essentially insensitive to nucleotide sequence. Herein I demonstrate through confocal based single molecule experiments that the 5’ structure specific nuclease Flap Endonuclease 1 (FEN1) achieves its substrate specificity by coupling the bending of DNA substrate with structuring of the active site in a way that non-cognate structures binding is significantly destabilized and enzymatic features are incapable of structuring in the absence of particular substrate features, in particular a single nucleotide 3’ flap the FEN1 induces in nearly all DNA substrates. Debate remained over whether DNA was bound via a conformational capture or induced fit mechanism, and so I proceed to investigate the dynamics of the DNA itself in solution. Conclusions about conformational capture or induced fit remain elusive, however I did determine that DNA structures are rigidified by charge repulsion, an effect lessened by the salt concentration, which functions to shield the negative charge of DNA from itself. Additionally unstacking of the DNA in nicked structures incurs a significant free energy penalty, which FEN1 overcomes by its hydrophobic wedge motif, lending credence to an induced fit mechanism.

The purpose of this quantitative study was to determine relationship of the distinct factors to PK-12 teacher retention in one Midwest school district. This study was an examination of multiple factors, including work environment, fit, compensation and benefits, leadership, performance management system, peer support and mentoring, that contributed to the retention of PK-12 teachers with different levels of education, certifications, experience, career plans, and military affiliation. The questions on the Teacher Retention Survey used a Likert-type scale to measure teacher perceptions about retention factors to address 8 research questions. For this study, I surveyed the population of 704 current PK-12 teachers in a public unified school district located in central Kansas using a non-random sample method. The unified school district is comprised of 14 elementary schools (grades PK-5), two middle schools (grades 6-8), and one high school (grades 9-12). The unified school district is located adjacent to a large U.S. Army installation and supports a culturally diverse educational environment with a majority of the district’s students being military-connected in some way. The survey was administered at the beginning of the 2019-2020 academic school year and resulted in 210 usable surveys collected with a 29.8% return rate. The results of the study showed that there were differences in how PK-12 teachers perceived the 6 dimensions of the Teacher Retention Survey depending on demographic groupings. Results indicated that there were differences in how teachers perceived fit, the evaluation process, and mentorship. There were also differences in how teachers perceived leadership and the evaluation process depending on gender. Teachers’ education level appeared to affect perceptions of the work environment and fit, and certification appeared to influence how teachers viewed leadership and the evaluation process. Teachers’ career plans seemed to influence perceptions of the evaluation process and mentorship. Military affiliation and teachers’ experiences of working in multiple schools or districts did not appear to affect perceptions about retention factors. By identifying factors that contribute to teachers’ decision to remain in the field, school leadership can attempt to make improvements to those factors to prevent voluntary attrition.

Brands implement some strategies in choosing the right marketing activities and engaging in CSR activities in order to build up a positive brand image in the consumer's mind and to influence their perceptions. “CSR-brand fit” is the level of matching between a company's objective and  the implemented CSR activities. The purpose of this study is to explore how CSR implemented activities by a brand could positively influence brand image when those activities are in line with the business objectives of a brand. The study is done by the qualitative strategy with the abductive approach reasoning. Nine unstructured interviews were conducted in order to collect the data needed. Three cases were used presenting a “CSR-brand high fit” so the authors could explore how the “CSR-brand high fit” influences the brand image. The authors found that customers consider the high fit as something reasonable and makes common and logical sense.

Behavior Intervention Plans (BIPs) are used in public schools for students with disabilities, replacing target behaviors with socially appropriate behaviors using positive behavior support strategies. However, research suggests that BIPs are often poorly written or fail to be implemented as intended. One reason for the ineffectiveness of BIPs may be that the interventionist (e.g., classroom teacher or other staff member responsible for implementing the plan) and the context of his/her classroom is not considered when plans are written by specialists (e.g., school psychologist, special education teacher, etc.). The purpose of this study was to evaluate BIPs written and used for students in public schools in the intermountain west for their contextual fit, using a researcher-developed measure of contextual fit based on key concepts previously established in research and modeled after the Behavior Support Plan-Quality Evaluation, Second Edition (BSP-QE II). With the coding guide created by our research team, we coded previously collected BIPs for practicality, the skill level and competency required for the interventionist to implement, and the consideration of cultural values for both the interventionist and the student who would receive the intervention. In addition, a previous research study by a graduate student at the same university had previously coded BIPs from the four school districts in Utah for technical adequacy using the BSP-QE II and, using the results from that study, we ran a Pearson correlation to determine whether there was a statistically significant relationship between BIP quality and contextual fit. Ultimately, our study found that BIPs often failed to include all elements for contextual fit to reasonably be considered established, particularly in the cultural values of those who would implement or receive the plan. In addition, we found a moderate, positive relationship between BIP technical adequacy and contextual fit. Implications for practitioners and ideas for future research are also discussed, including: ensuring that BIPs are developed in teams that include the interventionist, creating BIP templates that are culturally and contextually appropriate, and the possibility of research that documents actual interventionist participation in BIP team meetings as a comparison to the results of our scoring guide of BIP contextual fit.

Several authors have determined concepts related to the inclusion of social problems in advertising. One of them is brand-cause fit, which refers to the condition in which a brand and a social problem—with which the target audience feels identified—are conceptually united in a single communication proposal. The purpose of this study was to analyze how university students perceive the brand-cause fit as a communication strategy in Sprite's “You Are Not Alone” campaign. A qualitative methodology was adopted and semi-structured interviews were conducted with 24 university students of which 12 belonged to the LGBT community and 12 were heterosexual. The participants positively perceived the brand-cause fit used as an advertising strategy in Sprite's campaign. Not only do they value the fact that brands include social issues and problems in their communication, but they also claim that it is the brands’ responsibility to do so. / Revisión por pares