Structural equation models are systems of simultaneous linear equations that are generalizations of linear regression, and have many applications in the social, behavioural and biological sciences. A serious barrier to applications is that it is easy to specify models for which the parameter vector is not identifiable from the distribution of the observable data, and it is often difficult to tell whether a model is identified or not. In this thesis, we study the most straightforward method to check for identification – solving a system of simultaneous equations. However, the calculations can easily get very complex. Grobner basis is introduced to simplify the process. The main idea of checking identification is to solve a set of finitely many simultaneous equations, called identifying equations, which can be transformed into polynomials. If a unique solution is found, the model is identified. Grobner basis reduces the polynomials into simpler forms making them easier to solve. Also, it allows us to investigate the model-induced constraints on the covariances, even when the model is not identified. With the explicit solution to the identifying equations, including the constraints on the covariances, we can (1) locate points in the parameter space where the model is not identified, (2) find the maximum likelihood estimators, (3) study the effects of mis-specified models, (4) obtain a set of method of moments estimators, and (5) build customized parametric and distribution free tests, including inference for non-identified models.

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In today’s competitive market, a well-integrated business model can play an important role for a competitive advantage. One tool to create business models is the business model canvas. This method is used by many big organizations, and among these users is Communication Ltd. They are currently working on changing their focus from product to service. This change requires some big changes in the company´s business models, revenue streams and in their value proposition. The goal of this thesis is to analyse new possible revenue streams and also investigate if these could be of use for Communication Ltd. To reach this goal this thesis uses a theoretical base along with empirical data such as interviews, secondary data and a study of revenue streams in external markets. The conclusion reached in this thesis is that going from a product focus to a service focus requires structural changes in revenue streams, but also a clear communication of the value an organization is offering their customers. Furthermore for an organization to meet future customer needs, new types of revenue streams must be implemented. One solution to this could be for an organization to offer different types of memberships where different values are bundled together deepening on what the customers’ demands.

In this project, two broad facets in the design of a methodology for performance optimization of indexable carbide inserts were examined. They were physical destructive testing and software simulation.For the physical testing, statistical research techniques were used for the design of the methodology. A five step method which began with Problem definition, through System identification, Statistical model formation, Data collection and Statistical analyses and results was indepthly elaborated upon. Set-up and execution of an experiment with a compression machine together with roadblocks and possible solution to curb road blocks to quality data collection were examined. 2k factorial design was illustrated and recommended for process improvement. Instances of first-order and second-order response surface analyses were encountered. In the case of curvature, test for curvature significance with center point analysis was recommended. Process optimization with method of steepest ascent and central composite design or process robustness studies of response surface analyses were also recommended.For the simulation test, AdvantEdge program was identified as the most used software for tool development. Challenges to the efficient application of this software were identified and possible solutions proposed. In conclusion, software simulation and physical testing were recommended to meet the objective of the project.

The aim of the thesis is to derive a mathematical model of the engine and driveline in a passenger car, capable of describing the wheel speed disturbances related to the engine and driveline. The thesis is conducted in order to improve the disturbance cancelation algorithm in the indirect tire pressure monitoring system, TPI developed by NIRA Dynamics AB. The model consists of two parts, the model of the engine and the model of the driveline. The engine model uses an analytical cylinder pressure model capable of describing petrol and diesel engines. The model is a function of the crank angle, manifold pressure, manifold temperature and spark timing. The output is the pressure in the cylinder. This pressure is then used to calculate the torque generated on the crankshaft when the pressure acts on the piston. This torque is then applied in the driveline model. Both a two wheel and a four wheel driveline model are presented and they consist of a series of masses and dampers connected to each other with stiff springs. The result is a 14 and 19 degrees of freedom system of differential equations respectively. The model is then validated using measurements collected at LiU during two experiments. Measurements where conducted of the cylinder pressure of a four cylinder petrol engine and on the wheel speed of two different cars when driven in a test rig. The validation against this data is satisfactory and the simulations and measurements show good correlation. The model is then finally used to examine wheels speed disturbance phenomenon discovered in the huge database of test drives available at NIRA Dynamics AB. The effects of the drivelines natural frequencies are investigated and so is the difference between the disturbances on the wheel speed for a petrol and diesel engine. The main reasons for the different disturbance levels on the front and rear wheels in a four wheel drive are also discussed.

We collected the data for decomposition of spruce litter to determine the limit values of mass loss and to find both chemical and climate factors that influence limit values. Our data contained 28 sequences of spruce which mainly in Sweden and a small part in other places. We choose mean annual temperature (MAT) and mean annual precipitation (MAP) as climate factors and water solubles, lignin, N, P, K, Ca, Mg and Mn as chemical factors. Then we got the estimated limit values by performing a nonlinear model with mass loss and time spots, and found out the influential factors by using another linear mixed model. At the end we knew that linear mixed model is a proper and efficient approach for determining the factors, P and MAP are the significant factors and Species is a good random effect to explain the variance within groups.

An economic literature concerns instruments to improve the preference elicitation methods for the reform-based governmental programs. We construct an instrument for the budget allocation method using a Cobb-Douglas functional form. We apply the instrument to the survey data which is collected for Swedish Recreational Fishing Industry to elicit the preferences for governmental management actions. We analyze the elasticity or weights in the instrument by the binary logit and censored regression models and by comparing the significant estimates by the gross and net effects we get results which increase credence to the instrument we apply. / I am heartily thankful to my supervisor, Thomas Laitila, whose guidance and support from the initial to the final level enabled me to develop the thesis.More, I offer my regards to Anders Lunander who supported me in any respect during the completion of the thesis.

Business model is a concept that has gained increasing attention in recent years. It is seen as a firm’s ticket to success and has been studied by researchers and managers alike to find the ultimate template for prosperity. Little research has, however, been conducted on the necessary adjustments of a business model in the case of new market entry. Globalization has inspired companies to grow internationally, and firms increasingly look for new markets to capture, and China has become one of the most attractive markets for western firms. Existing theory claims that business model adjustment is necessary when expanding globally. Hence, our aim is to research how a firm’s business model adjusts when entering a new market. We also aim to further develop existing theory on the interrelation between business model elements, and see how change in one element influences other connected elements. We have conducted a qualitative exploratory case study using the business model of a European e-commerce company on the verge of entering China. To reach the purpose of the thesis we have conducted interviews with employees of the studied company to understand their current business model, previous changes when entering new markets and the expectations on China’s influence on the business model. We have also collected information on the Chinese market through interviews and secondary sources. The gathered data has been analyzed in accordance with theories concerning culture, consumer behavior and business model features. The results of the data gave us a foundation for researching the influences of culture on the business model. Through increased knowledge in the area of business models, information on the Chinese culture and market, and theoretical findings regarding e.g. culture and consumer behavior, we have been able to analyze how cultural aspects influence business model elements. We found potential links between cultural traits of the Chinese market and the market’s consumer behavior and preferences. The conclusion of the thesis states that the elements primarily affected by new market entry are target customer, relationships, partnerships and capabilities. The two first are influenced by the changing consumer preferences (culture) whereas the final two are operational and affected by the organizational changes necessary when entering a new market. We also found change in value configuration, distribution channel and cost structure as a result of the adjustments made in the previously mentioned elements. Due to the lack of information on other markets, apart from the European, it has, however, been difficult to draw generally applicable conclusions on cultural influence on the business model.

This dissertation focuses on several issues pertaining to three-state progressive stochastic processes. Casting survival data within a three-state framework is an effective way to incorporate intermediate events into an analysis. These events can yield valuable insights into treatment interventions and the natural history of a process, especially when the right censoring is heavy. Exploiting the uni-directional nature of these processes allows for more effective modelling of the types of incomplete data commonly encountered in practice, as well as time-dependent explanatory variables and different time scales. In Chapter 2, we extend the model developed by Frydman (1995) by incorporating explanatory variables and by permitting interval censoring for the time to the terminal event. The resulting model is quite general and combines features of the models proposed by Frydman (1995) and Kim <i>et al</i>. (1993). The decomposition theorem of Gu (1996) is used to show that all of the estimating equations arising from Frydman's log likelihood function are self-consistent. An AIDS data set analyzed by these authors is used to illustrate our regression approach. Estimating the standard errors of our regression model parameters, by adopting a piecewise constant approach for the baseline intensity parameters, is the focus of Chapter 3. We also develop data-driven algorithms which select changepoints for the intervals of support, based on the Akaike and Schwarz Information Criteria. A sensitivity study is conducted to evaluate these algorithms. The AIDS example is considered here once more; standard errors are estimated for several piecewise constant regression models selected by the model criteria. Our results indicate that for both the example and the sensitivity study, the resulting estimated standard errors of certain model parameters can be quite large. Chapter 4 evaluates the goodness-of-link function for the transition intensity between states 2 and 3 in the regression model we introduced in chapter 2. By embedding this hazard function in a one-parameter family of hazard functions, we can assess its dependence on the specific parametric form adopted. In a simulation study, the goodness-of-link parameter is estimated and its impact on the regression parameters is assessed. The logistic specification of the hazard function from state 2 to state 3 is appropriate for the discrete, parametric-based data sets considered, as well as for the AIDS data. We also investigate the uniqueness and consistency of the maximum likelihood estimates based on our regression model for these AIDS data. In Chapter 5 we consider the possible efficiency gains realized in estimating the survivor function when an intermediate auxiliary variable is incorporated into a time-to-event analysis. Both Markov and hybrid time scale frameworks are adopted in the resulting progressive three-state model. We consider three cases for the amount of information available about the auxiliary variable: the observation is completely unknown, known exactly, or known to be within an interval of time. In the Markov framework, our results suggest that observing subjects at just two time points provides as much information about the survivor function as knowing the exact time of the intermediate event. There was generally a greater loss of efficiency in the hybrid time setting. The final chapter identifies some directions for future research.