The aim of this thesis is to extend the empirical research which has been undertaken using the GNP function approach to measuring export supply and import demand responsiveness. Exports and imports are divided into several components and detailed sets of elasticities produced. In the second part o£ the thesis imperfect adjustment is allowed for in the GNP function model. The GNP function framework treats imports as an input to the domestic technology while exports are an output. The aggregate technology can then be represented by a restricted profit function facilitating the derivation of net output supply elasticities. In this study the aggregate net outputs are exports, imports, labour and domestic sales supply. Capital is treated as a fixed input. Time-series of input-output data for Canada are used covering the period 1961 to 1980. In the first model estimated, four export and four import components are included by the use of aggregator functions and a two-stage estimation process. The recently developed Symmetric Generalised McFadden functional form which permits imposition of the correct curvature conditions while retaining flexibility is used at both the aggregator and GNP function levels. The aggregate export own-price supply elasticity was found to be 1.67 in 1970 while the aggregate import own-price demand elasticity was -1.62. Increases in the prices of both imports and labour were found to decrease the supply of exports while exports were found to be complementary to the output of domestic sales supply. The demand for labour was found to be more elastic than in earlier studies and a general trend towards increasing price responsiveness in the Canadian economy was observed. The own-price elasticities for the four export and four import components were stable and of reasonable magnitude. All the export and import components were found to be complementary. To remove the assumption of separability, modelling was extended to two larger disaggregated Generalised McFadden GNP function models containing four export (import) components, aggregate imports (exports), labour and domestic sales as net outputs. Using this procedure more substitution between the export and import components was found. A planning price model whereby the producers' notional price adjusts gradually to actual price changes indicated that imperfect adjustment is particularly important in the traded goods sector. Exports fully adjusted to price changes only over an extended period. Finally, an adjustment costs model was estimated which indicated that the main effect of allowing for imperfect adjustment was on input use. Differences between long-run and short-run export supply and import demand responsiveness were relatively small. Considerable substitutability between labour and capital in the long-run was observed and since labour was also variable in the short-run this produced overshooting of labour demand. An increase in export prices thus caused a large short-run increase in labour demand but in the long-run the capital stock was increased and substituted for much of the short-run labour increase. / Arts, Faculty of / Vancouver School of Economics / Graduate

The currently used BOD test attempts to predict oxygen level depletion in a given environment, e.g. a moving stream, and is also a parameter for the design and operation of biological processes. It is run under conditions similar to those occurring in nature, but it has been reported that the oxidation rate in a stream is higher than the corresponding rate obtained from the laboratory BOD test. This study was undertaken to observe the effect of turbulence, light and turbidity, separately and in combinations, on the standard BOD test, using raw sewage samples. Mixing was found to increase the BOD, by an average of 15$. reduce the lag period and increase the ultimate BOD value. Light did not show any appreciable change on the standard BOD test, since only an average 4% increase in BOD^ was found. However, turbidity demonstrated an average reduction of 25% on BOD,, values. When the above physical changes were observed in combinations, the results were not additive. As an example, light and turbidity, in combination, did not reduce the BOD,-decrease to 21% (25%-k%). Instead, the decrease in BOD^ value was 5%. This clearly points out that physical changes to the BOD test should not only be studied separately, but also in combinations. Therefore, this study appears to expose the inade quacy of the present BOD test for actual stream conditions. It has also shown that without further research, extrapolating from the existing standard BOD test,yields questionable results. Inclusion in the BOD test, of the physical characteristics of the stream, is a possible solution to obtaining reliable results. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

With the emergence of cloud computing, many applications are migrated onto clouds. Video-on-demand (VoD) can be implemented on the cloud platform with geo-distributed cloud servers to serve worldwide users. New videos are distributed to these geo-distributed cloud servers. This distribution should be properly scheduled based on the videos' sizes, videos' popularities and the available network bandwidth, so that the mean completion time is minimized. We formulate this problemas a preemptive scheduling problem, prove that it is NP-hard, and design a heuristic scheduling algorithm to solve it. This algorithm iteratively determines: 1) themost preferred file to be received by the most preferred destination server by pairwise analysis and PageRank, and 2) the most preferred source servers which can transmit this file to the most preferred destination server with appropriate data rates. The simulation results demonstrate that the proposed scheduling algorithm gives much smaller mean completion time than four scheduling algorithms.

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Recent developments in the shipping industry have opened some unprecedented trade opportunities on various levels. Be it individual consumption or business needs, the thought of receiving a package on the same day or within 4-hour from some other business or industry in the urban area is worth appreciating. The congestion on ground transportation modes is higher than ever. Since currently the same-day delivery in urban areas is carried mainly by ground modes, the catchment area of this delivery service is limited. The On-Demand Mobility for cargo can elevate the concept of express shipping in revolutionary ways. It will not only increase the catchment area thereby encompassing more business and consumers but will also expedite the delivery as these vehicles will fly over the ground traffic. The objective of this study was to estimate the total demand for ODM Cargo operations and study its effect on ODM passenger operations. The area of interest for this study was Northern California (17 counties). Annual cargo flows in the study area were rigorously analyzed through databases like Transearch, Freight Analysis Framework-4, and T-100 International for freight. The results of this study are presented through a parametric analysis of market share. The end product also includes the flight trajectories (with flight plan) of daily ODM cargo flights in the study region. The On-Demand Mobility cargo operations are expected to complement passenger On-Demand Mobility operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements. Since the movement of cargo is mostly done by private companies, the detailed records of shipments are often not public knowledge. / Master of Science / The recent advancements in shipping industry has made transfer of goods both domestic and international, swifter and more reliable. Nowadays, some business and consumers in urban areas have the options of few-hours or same day delivery. Currently the same-day delivery in urban areas is carried mainly by ground modes (trucks) and hence the catchment area of this delivery service is limited. Adding to it, the traffic congestion on the urban roads is a major hinderance in growth of such services. The On-Demand Mobility for cargo can reform express shipping in revolutionary ways. The concept vehicle can fly over the ground traffic. Therefore, it will increase the catchment area thereby encompassing more business and consumers, along with faster delivery options in currently serviced areas. For the study, we analyzed different databases for annual cargo flows in the region. Seventeen counties in the Northern California were chosen as the study area (or region). The study was focused on estimating the potential market (demand) for the On-Demand Mobility Cargo operations. Multiple set of results were calculated for different market shares that On-Demand Mobility can potentially capture in cargo operations. Flight trajectories (with flight plan) for daily ODM cargo flights were the final product. The On-Demand Mobility cargo operations are expected to complement passenger ODM operations. Therefore, the effect of ODM cargo operations on the passenger ODM operations was also analyzed in this study. The major challenge faced in this study was the unavailability of datasets with the desired level of details and refinements.

For a company to stay profitable and be competitive, the customer satisfaction must be very high. This means that the company must provide the right item at the right place at the right time, or the customer may bring its business to the competitor. But these factors bring uncertainty for the company in the supply chain of when, what and how much of the item to produce and distribute. For reducing this uncertainty and for making better plans for future demand, some sort of forecasting method must be provided. A forecast can however be statistically based and also completed with a judgmental knowledge if the statistics are not sufficient. This thesis has been done in cooperation with the Sales and Operations (S&OP) department at Sandvik Mining Rock Tools in Sandviken, where a statistical forecast is currently used in combination with manual changes from sales. The forecasts are used as base for planning inventory levels and making production plans and are created by looking at the history of sales. This is done in order to meet market expectations and continuously be in sync with market fluctuations. The purpose with this thesis has been to study the item- customer combination demand and the statistical forecasting process that is currently used at the S&OP department. One problem when creating forecast is how to forecast irregular demand accurately. This thesis has therefore been examining the history of sales too see in what extent irregular demand exists and how it can be treated. The result is a basic tool for mapping customers' demand behavior, where the behavior is decomposed into average monthly demand and volatility. Another result is that history of sales can get decomposed into Volatility, Volume, Value, Number of sales and Sales interval for better analysis. These variables can also be considered whenever analyzing and forecasting irregular demand. A third result is a classification of time series working as a guideline if demand should be statistically or judgmentally forecasted or being event based. The study analyzed 36 months history of sales for 56 850 time series of item- customer specific demand. The findings were that customers should have at least one year of continuous sales before the demand can be entirely statistically forecasted. The limits for demand to even be forecasted, the history of sales should at least occur every third month in average and contain at least six sales. Then the demand is defined as irregular and the forecast method is set to judgmental forecasting, which can be forecasted using statistical methods with manual adjustments. The results showed that the class of irregular demand represents approximately 70 percent in the aspect of revenue and therefore requires attention. / För att ett företag ska kunna vara lönsamt och konkurrenskraftigt måste kundnöjdheten vara mycket hög. Detta betyder att ett företag måste kunna förse rätt produkt i rätt tid på rätt plats, annars kommer kunden troligtvis att vända sig till konkurrenten. Men dessa faktorer kommer med osäkerhet för företaget i försörjningskedjan i när, vad och hur mycket av produkten de ska producera och distribuera. För att minska osäkerheten och för att planera bättre för framtida efterfrågan, måste någon typ av prognos upprättas. En prognos kan vara baserad på statistiska metoder men också kompletterad med subjektiv marknadsinformation om statistiken inte är tillräcklig. Studien som denna rapport beskriver är gjord i samarbete med Sales och Operations- avdelning (S&OP) på Sandvik Mining Rock Tools i Sandviken. Där används statistiska prognoser i kombination med manuella förändringar av säljare samt regionala planerare som bas för planering av lagernivåer och produktion. Detta gör man för att möta marknadens efterfråga och för att kontinuerligt vara uppdaterad med marknadens variationer. Syftet med detta arbete har varit att studera kunders efterfrågan av produkt- kund kombination och den metod som används vid statistiska prognoser hos S&OP- avdelningen. Ett problem som finns när man vill skapa prognoser är hur man ska prognostisera oregelbunden försäljning korrekt. Detta arbete har därför analyserat historisk försäljning för att se i vilken utsträckning oregelbunden efterfrågan finns och hur den kan hanteras. Resultatet är ett enkelt verktyg för att kunna kartlägga kunders köpbeteende. Ett till resultat är att historisk försäljning kan bli uppdelat i Volatilitet, Volym, Värde, Antalet köptillfällen och Tidsintervallet mellan köptillfällena. Dessa variabler kan även tas till hänsyn när man analyserar och prognostiserar oregelbunden försäljning. Ett tredje resultat är en klassificering av tidsserier som kan fungera som riktmärken om efterfrågan ska vara statistisk eller manuellt prognostiserade eller inte bör ha en prognos över huvud taget. Denna studie analyserade 36 månaders historik för 56 850 tidsserier av försäljning per produkt- kund kombination. Resultaten var att en kund bör ha åtminstone ett år av kontinuerlig efterfrågan innan man kan ha en prognos med statistiska modeller. Gränsen för att ens ha en prognos är att efterfrågan bör återkomma var tredje månad i genomsnitt och ha en historik av åtminstone sex försäljningstillfällen. Då klassificeras efterfrågan som oregelbunden och prognosen kan vara baserad på statistiska metoder men med manuella ändringar. I resultatet framkom det att oregelbunden efterfrågan representerar cirka 70 procent i avseende på intäkter och kräver således mycket uppmärksamhet.

Based on a previous empirical study of the effect of a residential demand response program in Sala, Sweden, thisproject investigated the economic consequences of consumer behaviour change after a demand-based time ofuse distribution tariff was employed. The economic consequences of consumers were proven to bedisadvantageous in terms of unit electricity price. Consumers could achieve more electricity bill saving throughstabilising their electricity consumption during peak hours, and this way bring least compromising of theircomfort level.In order to estimate the price elasticity of the studies demand response program, a new method of estimationprice elasticity was proposed. With this method, the intensity of demand response of the demand responseprogram was estimated in terms of price elasticity. Regression analysis was also applied to find out the priceincentives of consumer behaviour change. And the results indicated that the rise in electricity supply chargehardly contributes to load reduction, while the demand-based tariff constituted an advantageous solution on loaddemand management. However stronger demand response still

This thesis analyzed Georgia's pre and post embargo consumption of gasoline and residential electricity from 1960 to 1982 to determine: 1) if the structure of gasoline demand was stable; 2) to investigate the arguments for conservation; and 3) to ascertain that the pricing mechanism is indeed able to adjust consumption to levels of supply. Elasticities were computed and they were used to address simple tax issues. The study was significant for several reasons: 1) it is the first ever known study of its kind done on Georgia; 2) Georgia has a ninety five percent dependence rate on other states and foreign countries (indirectly) for her supply of energy resources; 3) the impact of the oil embargo on consumption, prices and the economy at large is necessary both as a post moterm and for future policy decisions. The results overwhelmingly favored stability in the structure of these demands. As such, the restricted model was valid for any projections and conclusions. The short-term price and income elasticities for gasoline were .30 and .06 and the long-term coefficients were 1.5 and .20 respectively. For electricity, the short-term price and income elasticities were .22 and .37 and the long-term estimates were .81 and 1.33 respectively. The weather variables were very inelastic. All coefficients were significant by the usual criteria. With inelastic demands for these energy resources, taxation seemed a welcome proposition for controlling prices and consumption and for generating revenue. However, it is only to the extent that other monetary, fiscal and economic objectives of the government are not jeopardized. Thus, the arguments for conservation holds to a good degree. A hybrid of a comprehensive tax-pricing policy and conservation efforts is necessary for stability in the energy sector.