The purpose of this study was to examine how middle managers within the social services in Sweden perceived their working conditions. The study group included 475 middle managers who were registered in the labour union akademikerförbundet SSR. The study group answered a digital questionnaire based on Karasek’s control and demand model which contained questions concerning their working environment. The result showed that 80 percent of the managers worked more than 40 hours a week and 60 percent of the managers experience high job strain. Four groups with different working conditions were identified through Karasek's control and demand model and the one that showed the most alarming working conditions were analysed further, the high strained group. Within our studygroup we also identified a utterly small group that could be defined as ISO-strained. This working condition is the most harmful working situation for your health since it contains high risk of psychological strain and physical illness.

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The purpose of this research is to analyze the dynamics of innovation and technological diffusion from the channels of international linkage at the microeconomic level. We specify and want to learn about the effects of sectoral innovation and technology transfer with international linkages: Imported technology, Information and Communication Technology, Foreign direct investment and its spillovers and trade. We apply a dynamic factor demand model to analyze the relationship between four channels of international technology transfer and diffusion, allowing for heterogeneous international linkages and their contribution to productive performance on Taiwan¡¦s manufacturing industries. We adopt the econometric method of the Generalized Method of Moment (GMM) to estimate the parameters of related equations. Throughout the empirical analysis, we hope to understand how degree of effects the four channels of technology transfer have on firm¡¦s productivity performance and the adjustment process of quasi-fixed input, capital, because of technology transfers. We found that:(1) It has the highest output level in Electrical and Electronic Manufacturing in Taiwan¡¦s manufacturing industry.(2) The exogenous technical change has a positive effect on output growth. As for the channels of international linkage, imported technology and R&D all have positive contribution to productivity. FDI has a negative impact on output growth except for Petroleum & Coal Products Manufacturing, but the effect of the FDI spillover has a positive contribution in the Taiwan¡¦s manufacturing industry.

Larger size TFT-LCD panels, consists of notebook panel, monitor panel, and TV panel, enjoys great growth momentum for years. To fulfill the growing demand, panel makers keep continuous investment for expansion. Therefore, this creates over-supply, under-supply, or balanced supply-demand. Supply and demand decides the price of an item. So does TFT-LCD panel. Through thorough industry historic and forecasted data, complete supply-demand model is built with 2 years forward forecast. The result shows that in the following 2 years the occurrence of oversupply is very possible. However by controlling utilization rate and carefully talking orders, panel makers create shortage-like situation to raise panel price successfully. By the result of this model, accompanied with current global economics situations, some managerial suggestions are given for TFT-LCD makers.

It has become more important for operators to be able to predict the future number of public transport passengers when consider to place a tender for operating public transport in a city or region, this is due to the new types of operator contracts was introduced quite recently. There are models in use today that can predict this, but they are often time consuming and complex and therefore it can be expensive to perform a forecast. Aside from this, most models in use for Sweden today are adapted for larger cities. Thus, the aim of this thesis is to propose a model that requires minimal input data with a short set up and execution time that can be used to predict a forecast for the public transport system in smaller cities without notably affecting the quality of the result. The developed model is based on a forecast model called LuTrans, which in turn is based on a common method, the four step model. The aim of the model lies within public transportation but it also consider other modes. The input data used by the model mainly consists of socio-economic data, the travel time and distance between all the zones in the network. The model also considers the cost for traveling by car or public transport. The developed model was applied to the Swedish city, Örebro, where a forecast was conducted for a future scenario. It is easily to apply the model to different cities to estimate a forecast for the public transport system. The developed model for the base scenario predicts trips for individual bus lines with an accuracy of 85 % for the city of Örebro. The developed model gave the result that the trips made by public transport in the future scenario of Örebro 2025 will increase annually by 0.94 %. The conclusion is that it is possible to develop a simple model that can be easily applied for a desired city. Although the developed model produced a plausible result for Örebro, further work such as implementation on other cities are required in order to fully evaluate the developed model.

Microsimulation is becoming more popular in transportation research. The purpose of this research is to explore the potential of microsimulation by integrating an existing activity-based travel demand model with an agent-based traffic simulation model. Differences in model precisions from the two models are resolved through a series of data conversions, and the models are able to form an iterative process similar to previous modelling frameworks. The resulting model is then used for emission modelling where the traditional average-speed model is improved by exploiting agent-based traffic simulation results. Results from emission modelling have demonstrated the advantages of the microsimulation approach over conventional methodologies that rely heavily on temporal or spatial aggregation.

Microsimulation is becoming more popular in transportation research. The purpose of this research is to explore the potential of microsimulation by integrating an existing activity-based travel demand model with an agent-based traffic simulation model. Differences in model precisions from the two models are resolved through a series of data conversions, and the models are able to form an iterative process similar to previous modelling frameworks. The resulting model is then used for emission modelling where the traditional average-speed model is improved by exploiting agent-based traffic simulation results. Results from emission modelling have demonstrated the advantages of the microsimulation approach over conventional methodologies that rely heavily on temporal or spatial aggregation.

No presente trabalho, é analisado o comportamento da demanda por transporte coletivo em quatro cidades de porte médio do interior do Estado de São Paulo (Araraquara, São Carlos, Jaú e São José do Rio Preto), visando a identificar os principais fatores que afetam o volume de passageiros, como: população, valor da tarifa, índice de motorização total e desagregada (automóveis e motocicletas), quantidade de empregos formais, produto interno bruto (PIB) per capita, etc. As análises efetuadas mostram que a demanda total por transporte coletivo urbano é influenciada principalmente pelas seguintes variáveis sócio-econômicas: população, índice de motorização e PIB per capita. Outros fatores que também influenciam são: tamanho da cidade, qualidade do transporte coletivo, cultura de utilização da bicicleta, etc.. São desenvolvidos dois modelos matemáticos simples, utilizando a técnica de regressão linear múltipla, que estabelecem relação entre a demanda por transporte coletivo e as principais variáveis sócio-econômicas que a afetam, como ferramenta para a previsão da demanda em diferentes cenários conformados pelas variáveis sócio-econômicas. Os resultados apresentados pelo modelo matemático que utiliza como índice de motorização, a relação entre a frota de veículos de duas rodas e a população refletem de maneira mais próxima a realidade que o modelo que utiliza a frota total. Este modelo é adequado para ser utilizado na previsão da demanda por transporte coletivo no universo das quatro cidades analisadas com erro máximo menor que 10%. / In this paper we analyzed the behavior of demand for public transportation in four mid-sized cities in the state of São Paulo (Araraquara, São Carlos, Jau and Sao Jose do Rio Preto), to identify key factors affecting the volume of passengers, such as population, amount of fare, motorization rate and total breakdown (automobiles and motorcycles), amount of formal employment, gross domestic product (GDP) per capita, etc. In general, the following conclusions can be inferred from the analysis performed: the total demand for transportation in a city depends mainly on the following parameters: population, motorization rate and GDP per capita. Other indirect factors such as quality public transport, culture, use of transport, etc. They also developed two simple mathematical models using multiple linear regression technique with the objective of establishing relations between the demand for public transportation and the following key social-economic variables that were identified as those that most influence the demand: population, motorization rate and GDP per capita, which is useful for predicting the demand for public transport in different scenarios conformed by social-economic variables. The results presented by the mathematical model show that uses such as motorization rate, the relation between the fleet of two-wheeled vehicles and the population, more closely reflect the reality that the model uses the total fleet. The model uses the rate of motorization in considering two vehicles suitable for use in forecasting demand for public transportation in the universe of the four cities analyzed maximum error <10%.

Miami-Dade County implemented a series of water conservation programs, which included rebate/exchange incentives to encourage the use of high efficiency aerators (AR), showerheads (SH), toilets (HET) and clothes washers (HEW), to respond to the environmental sustainability issue in urban areas. This study first used panel data analysis of water consumption to evaluate the performance and actual water savings of individual programs. Integrated water demand model has also been developed for incorporating property’s physical characteristics into the water consumption profiles. Life cycle assessment (with emphasis on end-use stage in water system) of water intense appliances was conducted to determine the environmental impacts brought by each practice. Approximately 6 to 10 % of water has been saved in the first and second year of implementation of high efficiency appliances, and with continuing savings in the third and fourth years. Water savings (gallons per household per day) for water efficiency appliances were observed at 28 (11.1%) for SH, 34.7 (13.3%) for HET, and 39.7 (14.5%) for HEW. Furthermore, the estimated contributions of high efficiency appliances for reducing water demand in the integrated water demand model were between 5 and 19% (highest in the AR program). Results indicated that adoption of more than one type of water efficiency appliance could significantly reduce residential water demand. For the sustainable water management strategies, the appropriate water conservation rate was projected to be 1 to 2 million gallons per day (MGD) through 2030. With 2 MGD of water savings, the estimated per capita water use (GPCD) could be reduced from approximately 140 to 122 GPCD. Additional efforts are needed to reduce the water demand to US EPA’s “Water Sense” conservation levels of 70 GPCD by 2030. Life cycle assessment results showed that environmental impacts (water and energy demands and greenhouse gas emissions) from end-use and demand phases are most significant within the water system, particularly due to water heating (73% for clothes washer and 93% for showerhead). Estimations of optimal lifespan for appliances (8 to 21 years) implied that earlier replacement with efficiency models is encouraged in order to minimize the environmental impacts brought by current practice.

The cosmetic industry is characterized by having the ability to offer a wide range of differentiatedproducts. This leads in turn retailers to make strategic decisions regarding assortment planning. Itmeans choosing the right breadth and depth of products that should be allocated to a distributioncenter. This is essential to the ability to answer the needs of their customers. Besides the range ofproducts retailers also face the choice of the optimal location of the distribution center. Both the rangeof carefully chosen products and agglomeration economies affect efficiency, customer satisfaction aswell as transportation delays and costs. Therefore, in this research, we have developed a framework tooptimize both the ranges of products and agglomeration economies. To do this study, we havecollaborated with LYKO AB, a firm within the cosmetics industry offering highly differentiatedproducts with e-commerce solutions. We frame their problem by creating a three-step optimizationsolution. It is combined with a demand module, optimization module, and localization module. Theresult showed that 36 products within the selected subset had a high demand,10 out of these productsfurther maximized the profit of the firm. The localization module showed that among the fourconsidered countries in Europe (Germany, Netherlands, Poland, and Austria) the optimal geographicallocation to locate the warehouse was Germany. This result was based on logistic decisions such ascustomer population, best distance, and level of competition. In conclusion, to be able to optimize theassortment planning of highly differentiated products to maximize the profit based on localization andcustomer demand complexity one can use a three-step optimization solution.