Στόχος της παρούσας διπλωματικής εργασίας είναι να γίνει μια εκτίμηση και ρύθμιση τη λειτουργίας κάποιων συσκευών ενός «έξυπνου» σπιτιού σε ένα ενσωματωμένο σύστημα. Η λογική είναι να μπορεί ο χρήστης να δει ποια είναι η μέση κατανάλωση ισχύος μιας συσκευής και το αντίστοιχο χρηματικό κόστος που αναλογεί σε αυτήν, για κάποιο χρονικό διάστημα λειτουργίας της και υπολογισμού της βέλτιστης συμπεριφορά της συσκευής έτσι ώστε να επιτύχουμε την ελάχιστη δυνατή κατανάλωση. Τα φορτία τα οποία ελέγχθηκαν είναι ένα κλιματιστικό, ένα πλυντήριο και ένας θερμοσίφωνας. Η υλοποίηση έγινε σε ένα ενσωματωμένο σύστημα και δημιουργήθηκε και ένα περιβάλλον γραφικής απεικόνισης για επικοινωνία με τον χρήστη. / Simulation of the behavior of three home electrical devices with the use of demand response algorithms. Calculation of energy consumption of each device and money charge. Setting the behavior of each device to minimize total cost.

Decreasing block pricing refers to the practice of selling a product at successively lower marginal prices as the amount purchased in any one time period increases. In more familiar terms, this practice can be thought of as any quantity discount scheme as long as marginal price does not vary continuously with quantity. Decreasing block pricing results in a faceted, non-convex budget set, and under standard assumptions concerning consumer preferences, yields several nonstandard theoretical implications. The central goal of this paper is to formulate an estimation technique which is consistent with these implications. When the budget set is not convex, the uniqueness of consumer equilibrium is no longer guaranteed. It also follows that discontinuities in demand occur whenever consumer equilibrium shifts from one facet of the budget constraint to another. Prior empirical studies have not made use of demand functions consistent with these results. In Chapter 2, a utility-maximizing algorithm was developed to determine consumer equilibrium given the declining block pricing schedule and income for a Cobb-Douglas utility function. In developing this algorithm, it was made clear that the proper approach for estimating individual demand was through the use of a block-dependent independent variable. The coefficient of this block-department independent variable provided an estimate of a utility function parameter which completely specified the Cobb-Douglas form. Incorporating this utility function estimate into the utility-maximation algorithm made it possible to obtain estimates of consumption given changes in any or all of the rate schedule components. While the use of a block-dependent independent variable is the theoretically correct method for estimating demand, it poses an inescapable problem of errors-in-variables. A Monte Carlo study was performed in Chapter 2 to investigate, among other things, the seriousness of the errors-in-variables bias. The results were quite encouraging. When using data incorporating extremely large error variances, amazingly precise estimates were obtained. Another encouraging Monte Carlo result was when comparing samples not containing a discontinuity with those with one, it was found that the latter produced estimates with statistically significant superiority. Chapter 3 generalized the estimation technique of the previous chapter to allow the estimation of demand using cross-sectional data. The data base recorded monthly electricity consumption for households from a number of cities whose utilities had decreasing block rates. Seven of these cities were selected for analysis. The data also included various demographic characteristics and electric appliance stock information. The generalization was accomplished by assuming that all households had a Stone-Geary utility function. Also, the utility function parameter representing the minimum required quantity of electricity was assumed to depend linearly on the household's appliance stock and demographic characteristics. This allowed demand to vary across households on the basis of this parameter and income. The results of applying this regression technique to the cross-sectional data were then compared with results from a conventional, non-theoretically based demand specification. The data were used in pooled and individual month form with the former yielding much better statistical results. The Stone-Geary form provided a greater number of significant coefficients for price and income variables than the conventional version. The predominant failure of the conventional version was that the coefficient of marginal price was rarely significant and when significant, frequently of the wrong sign. For the same samples, the Stone-Geary results were quite acceptable except for the regressions involving one of the cities. Thus, it was demonstrated that a method consistent with the theoretical implications of decreasing block pricing is easily applied to cross-sectional data and produces better results than conventional techniques.

No description available.

The purpose of this report was to study how the Swedish radio channel Sveriges Radio (SR) website changed over time. What are the differences between various media websites? How many people listen to normal and web-radio and what are the differences between the various services offered on the SR website? Reports from the BBC, Statistics Sweden, Mediavision and the Swedish National Post and Telecom Agency were compared. Several theoreticians have been studied, including Donald A Norman, Jonas Löwgren, Karen Holtzbratt, Jacob Nielsen and Geoffrey Moore. The method used by the author comprised a systematic mapping of statistics from webTrends, KiaIndex, SiteCensus, TNS Gallup/K2analys and reports from RUAB. The data studied have been collected from telephone interviews, postal surveys, internet panels, and from log files. The statistics have then been compared and in some cases tables have been cross-correlated. The results from the various studies showed that SR is following the rising trend displayed by a few of the media websites reviewed. It is of particular interest to note that web-radio listening between the final period 2004 and 2005 almost doubled. The next stage will be to offer the listener/user a more central position. By listening to users, and above all non-users, the function and content can be adapted to the larger group of pragmatists and conservative listeners that are looking for sustainable and convenient solutions. Key words [Streaming, on demand, radio, analogue, web-radio] / Avsikten med den här rapporten var att ta reda på hur Sveriges Radios (SR) sajt förändras över tid. Vilka skillnader finns det mellan olika mediesajter. Hur många lyssnar på vanlig- kontra webbradio samt vad finns det för skillnader mellan olika tjänster på SR:s sajt. Jämförelser har gjorts mellan BBC, SCB, Mediavision samt Post & Telestyrelsens rapporter. Flera teoretiker har studerats som Donald A Norman, Jonas Löwgren, Karen Holtzbratt, Jacob Nielsen och Geoffrey Moore. Författarens metod bestod av att systematiskt kartlägga statistik från webTrends, KiaIndex, SiteCensus, TNS Gallup/K2analys samt RUAB:s rapporter. De data som undersökts kommer från telefonintervjuer, postenkäter, Internetpaneler samt loggfiler. Statistiken har jämförts med varandra samt i vissa fall har tabellerna korskörts. Resultaten från de olika undersökningarna visar att SR följer den uppåtgående trend som några av de undersökta mediesajterna har. Men det mer intressanta är att webbradiolyssningen mellan sista perioden 2004 och 2005 nästan fördubblats. Nästa steg blir att se till att lyssnarna/användarna står mer i centrum. Genom att lyssna på användare, men framför allt icke-användare så skulle funktion och innehåll kunna anpassas till den större gruppen pragmatiker och konservativa som vill ha hållbara och bekväma lösningar.

As many variable pricing projects are still in the implementation stage, long-run driver responses to the variable tolls are largely unknown. This research examined the long-run changes in driver behavior in an existing variable pricing project in Lee County, Florida. Using empirical evidence, it was found that over time the price elasticities of demand on the Lee County toll bridges have decreased from -0.42 to - 0.11 (Midpoint Memorial Bridge) and from -0.31 to -0.06 (Cape Coral Bridge) during the early morning discount period. The elasticities have decreased, but to a lesser extent, during the late morning and early afternoon discount periods. A discount period volume spreading ratio was also developed to analyze these changes. The results from this analysis confirmed the elasticity results. In addition to the empirical analysis of travel patterns discussed above, a telephone survey of drivers was conducted. The survey results indicated that certain driver characteristics such as higher frequency of trips, commute trip purpose, full-time employment status, more people in the household, higher education, and age between 25-34 years, were all indicators that the participant may increase his or her variable pricing usage over time. Other characteristics, including being retired and having a household income less than $16,000, were indicators that the driver may not increase variable pricing participation. Binary logit and semiparametric models were also developed to examine socio-economic and commute characteristics that may influence a driver increasing his or her participation in a variable pricing program. The results from these two variable toll bridges in Lee County indicated a decrease in variable toll price elasticity over time. However, these results may not be typical for variable pricing projects. Factors such as alternative routes, different traveler demographics, traffic congestion levels, and size of the toll discount may influence the results obtained from other variable pricing projects. However, the methodology developed in this research can be applied to other projects in order to determine those toll price elasticities of demand.

In Recent years, global supply chain management has been a popular study area due to the economic globalization. This study mainly focus on the demand planning process of demand management in global supply chain management. The purpose of this thesis is to find the key factors and obstacles in demand planning process both in theory and practice, and solutions for the obstacles. Based on many scholar researches, a brief introduction of demand management and demand planning has been made at the beginning of the theoretical framework. Key factors, key obstacles and solutions are collected and clarified from empirical study and scholar researches in the theoretical framework. Qualitative approach is adopted as basic approach. We use case study to do the research and interviews to collect data. A server manufacturer of IBM named ISTC (International System Technology Corporation) is chosen as a case for this research. The key factors, obstacles and improvements of empirical study are compared with the facts of ISTC. New factors, obstacles and their new descriptions are figured out through the comparison between theory and the fact of the case. A suggestion for improvement and solution for the demand planning process is also put forward based on the empirical study and the facts of ISTC by this method.

Pirmasis darbo skyrius skirtas apgyvendinimo įmonių sampratos ir rūšių, rinkos paklausos terminų analizei. Taip pat analizuojami apgyvendinimo įmonių paklausos vertinimui ir prognozavimui taikomi metodai. Nustatyta, kad pagrindiniai apgyvendinimo įmonių paslaugų paklausos rodikliai – numerių bei vietų užimtumas, svečių nakvynių skaičius. Kaina už paslaugas įvertinama vidutinėmis parduotų numerių pajamomis (ARR) ir pajamomis tenkančioms visiems numeriams (RevPAR). Teorinėje dalyje nustatyta, kad pagrindiniai veiksniai, įtakojantys paklausos pokyčius, yra: nedarbo lygis, vartojimo kainų indekso pokytis, gyventojų skaičius, kuro kaina, valiutų kursas, paslaugų kaina bei pakaitalų kaina. Antrame skyriuje analizuojama Lietuvos apgyvendinimo įmonių pasiūlos ir paklausos struktūra. Vartotojų segmentavimas pagal atvykimo tikslą ir kilmę atskleidė, kad tarp užsienio svečių daugiausia yra apsistojusių poilsio tikslais, o tarp vietinių svečių – verslo tikslais. Šiame tyrime nustatyta, kad viešbučių vietų paklausa per analizuojamą laikotarpį išaugo 2,66 karto, o pasiūla (metinis siūlomų vietų skaičius) padidėjo apie 2 kartus. Pastebima tendencija, kad apgyvendinimo įmonių paslaugų paklausa auga didesniu tempu, nei pasiūla. Atlikus ekonominių rodiklių įtakos analizę, reikšmingiausias ryšys nustatytas tarp nakvynių skaičiaus apgyvendinimo įmonėse ir bendrojo vidaus produkto (BVP) 1 gyventojui. Trečiame skyriuje parengus apgyvendinimo įmonių numerių užimtumo prognozę, patvirtinta hipotezė... [toliau žr. visą tekstą] / The first chapter of this study is devoted to definition of accommodation enterprises, their types and market demand. The ways of estimating the accommodation market demand and forecasting methods are analyzed too. Accommodation demand is generally measured by room and place occupancy rate and visitor bed-nights spent in accommodation enterprises. The measure of the price is average room revenue (ARR) and revenue per available room (RevPAR). In theoretical part of this paper was defined, that accomodation demand is mostly influenced by unemployment rate, consumer price index, exchange rate, residents quantity, price of goods and it’s substitute price. The structure of accommodation enterprises supply and demand in Lithuania is analyzed in the second chapter. Segmentation of consumers, based on purpose of travel, represents arrivals of the foreigners for leisure purpose and the greatest part of domestic guest – for business purpose. It’s estimated that demand of accomodation places grew 2,66 times, meanwile supply - only 2 times. The tendency is that demand grows faster than supply. Analysis revealed that there are significant correlation between nights spent in accomodation enterprises and GDP per capita. The prognosis of rooms occupancy rate was calculated in the third chapter of this study and approved research hypothesis that accommodation demand will exceed supply.

In this paper, we used the Autoregressive Distributed Lag (ARDL) model and the bounds test approach to estimate the elasticity of demand for natural gas in Western and Central Canada. The best model specification selected by Schwarz Information Criterion (SIC) for each province suggests that there exist long-run relationships between the dependent variable and independent variables for all provinces, except Ontario. Consumption per capita in these provinces can be explained by natural gas prices, electricity prices, income, and heating degree days (a measurement for the weather factor) in levels for the selected specification. The results show that natural gas demand is very inelastic with respect to natural gas prices and also with respect to heating degree days.

No description available.

Distance based vehicle insurance (sometimes know as “Pay as you drive,” “Pay by the mile” or “Pay per-km” insurance) has long been advocated by transportation planners as a transportation demand management (TDM) strategy. In addition to reducing congestion and greenhouse gas emissions, it also has the potential to meet a number of planning goals, such as health and equity improvements. Despite the wide interest in and predicted benefits of distance based insurance, there is little consensus on the detailed design of a system that could be implemented. Five main distance based pricing schemes have been proposed: a flat per-km rate, temporal or “time of day” pricing, road-type pricing, demographic pricing and “differential” pricing, which prices low mileages at a higher per-km rate. Each of these systems treats risk differently and thus results in different cross-subsidies between drivers. The proposal’s design thus has implications for an insurance system’s fairness and equity. This report examines the distribution of crash risk across time, across space, and across the different demographic groups. It then compares the current annual insurance system’s treatment of risk with that of various proposals for distance based insurance. It evaluates each proposal, considering its treatment of risk and its potential for increasing fairness and equity of costs and of mobility. It also examines each proposal’s other impacts, such as effectiveness in maintaining privacy and in reducing health impacts, greenhouse gas emissions and congestion. The recommended model is a flat per-km rate. Each driver would pay the same rate for every kilometer driven, regardless of time or place. However, individual drivers’ per-km rates would vary, depending on current insurance rating factors, such as residential location, type of car and driving record.