Dissertations / Theses on the topic 'Supply and demand curves'

The ongoing climate change, the depletion of resources and the visible environmental changes led in the last decades to a revolution in our thinking about resources. Several technologies have been and continue to be developed in order to avoid depletion of fossil fuels by shifting the use from non-renewable to renewable resources. One of the most important related fields of study is the energy sector: the need to pass from a fossil-fuels based energy production to the so called Green Energy has brought many opportunities of development and growth but also raised many issues to solve. On a local scale, the main issues of this ongoing process are to meet the needs of the consumer by an optimized use of the local available resources and the economical sustainability of green energy production. In the RegiOpt software the principles of Process Network Synthesis (PNS) are used to advice the stakeholders in the planning of a profitable and sustainable regional energy supply system. The software compares the possible energy supply technologies and gives as output one or more optimal sets of technologies that optimize the use of resources with regard to the economical potential and the sustainability of the single processes. While the economical and the environmental aspects are considered in the RegiOpt, the further development of the software requires the consideration of time-dependency of energy supply and energy demand on annual basis. The capacity of covering energy demand over time is a central issue of energy production industry, under this point of view the current study focused on the time-dependency of supply and demand. Yearly response curves of strong time-dependent supply technologies have been found and have been combined with the yearly demand response curves, in order to evaluate the gap between the proposed energy system and the regional demand. The resulting curve has then been divided into a reasonable number of intervals representing periods of higher and lower difference between production and consumption. To fit the results in the RegiOpt software, we proceeded to an approximation of every period by its mean: the mean value of the curve in every period fairly represents the curve itself. Under this conditions the RegiOpt can be run multi periodically optimizing the technologies network for all periods.

Electricity is the most preferred source of energy, because of its quality and convenience of usage. It is probably one of the most vital infrastructural inputs for economic development of a country. Indeed it is the fulcrum which can leverage the future pace of growth and development. These reasons have made the electric power industry one of the fastest growing sectors in most developing countries and particularly in India. Therefore it is not surprising to observe the economic growth of a country being related to the increase in electricity consumption. In India, the growth rate of demand for power is generally higher than that of Gross Domestic Product (GDP). However, to achieve this kind of growth in electricity supply, the capital investments required are very huge. Even though the electricity sector generally gels a major share in the budgetary allocations in India, this is inadequate to add the required quantum of new generation capacity to keep pace with the increase in demand for electricity. Additional constraints like capital scarcity in the public sector, lack of enthusiasm among the private and foreign investors, and strong opposition from the environmentalists have further contributed to this slow pace of new generating capacity addition. This has resulted in severely constrained systems in India. The main focus of the present research work is on the development of an integrated approach for electricity planning using a mathematical modeling framework in (he context of resource constrained systems. There are very few attempts in the literature to integrate short, medium and long term issues in electricity planning. This is understandable from the point of view of unconstrained electricity systems where this type of integration is unnecessary since such systems have a luxury of surplus capacity to meet the current demand and capacity additions are required only for meeting predicted future increase in demand. However, in the case of constrained electricity systems, which are characterized by shortages, this kind of integration is very essential. These systems have to manage with inadequate capacity in the present, plan capacity additions to bridge the existing gap and to meet future increase in demand, and always explore the possibility of adding capacity with short gestation period. The integrated approach is expected to achieve effective supply-demand matching on a continuous basis encompassing both the short term and long term horizons. To achieve this, we have considered three alternatives- existing supply, new supply and non-supply (rationing) of electricity. The electricity system of the state of Karnataka, which is severely constrained by both limited capital and energy resources, has been selected for this purpose. As a first step, the supply and demand situation has been studied in the context of resource constraints. In terms of supply, both existing and future additions are studied in detail with respect to the potential created, generation types, import potential, technical constraints, energy and power shortages, planned and proposed capacity additions by both public and private sectors, etc. The demand patterns have been studied by introducing a new concept of "Representative Load Curves (RLCs)". These RLCs are used to model the temporal and structural variations in demand for electricity. Also, appropriate non-supply options (rationing measures) for effective management of shortages are identified. Incorporating this information, an integrated mathematical model, which is expected to generate a target plan for a detailed generation scheduling exercises and a requirement plan for a regular generation expansion planning, has been developed. The other important alternative "Demand-Side-Management (DSM)", which could be considered as an effective option to achieve efficient supply-demand matching has not been included in the present research work. The major reason for not including the DSM alternatives is due to the difficulty in integrating these in the modelling approach adopted here. In the present approach we have used typical daily load curves (RLCs) to represent the demand for electricity. These are aggregate load curves and do not contain any sector-wise or end-use-wisc details. On the other hand, DSM alternatives are end-use focused. To incorporate DSM alternatives, we should have information on end-usc-wisc power demand (kW or MW), savings potential, time-of-use, etc. For this purpose it may be required to have end-use-wisc daily load curves. This information is not available and a separate detailed survey may be required to generate these load curves. This, we felt, is out of the scope of this present research work and a separate study may be required to do this. Therefore, we restricted our focus to supply planning alone. A detailed literature review is conducted to understand different types of modeling approaches to electricity planning. For the present study, however, the review of literature has been restricted to the methods of generation expansion planning and scheduling. In doing so, we attempted to bring out the differences in various approaches in terms of solution methods adopted, alternatives included and modifications suggested. Also, we briefly reviewed the literature on models for power and energy rationing, because management of shortages is an important aspect of the present study. Subsequently, a separate section is devoted to present an overview of the non-supply of electricity and its economic impacts on the consumers. We found that the low reliability of the electrical system is an indicator of the existence of severe shortages of power and energy, which cause non-supply of electricity to the consumers. The overview also presented a discussion on reasons for non-supply of electricity, and the types of non-supply options the utilities adopt to over come these shortages. We also attempted to explain what we mean by non-supply of electricity, what are its cost implications, and the methods available in the literature to estimate these costs. The first objective of the research pertains to the development of a new approach to model the varying demand for electricity. Using the concept of Representative Load Curves (RLCs) we model the hourly demand for a period of four years, 1993-94, 1994-95, 1995-96 and 1996-97, to understand the demand patterns of both unconstrained and constrained years. Multiple discriminant analysis has been used to cluster the 365 load curves into nine RLCs for each of the four years. The results show that these RLCs adequately model the variations in demand and bring out the distinctions in the demand patterns existed during the unconstrained and constrained years. The demand analysis using RLCs helped to study the differences in demand patterns with and without constraints, impacts of constraints on preferred pattern of electricity consumption, success of non-supply options in both reducing the demand levels and greatly disturbing the electricity usage patterns. Multifactor ANOVA analyses are performed to quantify the statistical significance of the ability of the logically obtained factors in explaining the overall variations in demand. The results of the ANOVA analysis clearly showed that the considered factors accounted for maximum variations in demand at very high significance levels. It also brought out the significant influence of rationing measures in explaining the variations in demand during the constrained years. Concerning the second objective, we explained in detail, the development of an integrated mixed integer-programming model, which we felt is appropriate for planning in the case of resource constrained electricity systems. Two types of integrations are attempted (i) existing supply, non-supply and new supply options for dynamically matching supply and demand, (ii) operational and strategic planning in terms of providing target plans for the former and requirement plans for the latter. Broadly, the approach addresses the effective management of existing capacity, optimal rationing plan to effectively manage shortages and rationally decide on the new capacity additions both to bridge the existing gap between supply and demand, and to meet the future increases in demand. There is also an attempt to arrive at an optimal mix of public and private capacity additions for a given situation. Finally, it has been attempted to verify the possibility of integration of captive generation capacity with the grid. Further, we discussed in detail about the data required for the model implementation. The model is validated through the development of a number of scenarios for the state of Karnataka. The base case scenario analyses are carried out for both the unconstrained and constrained years to compare the optimal allocations with actual allocations that were observed, and to find out how sensitive are the results for any change in the values of various parameters. For the constrained years, a few more scenarios are used to compare the optimal practice of managing shortages with to what has been actually followed by the utility. The optimal allocations of the predicted demand to various existing supply and non-supply options clearly showed that the actual practice, reflected by the actual RLCs, are highly ad hoc and sub-optimal. The unit cost comparisons among different scenarios show that the least cost choice of options by the utility does not necessarily lead to good choices from the consumers’ perspective. Further, a number of future scenarios are developed to verify the ability of the model to achieve the overall objective of supply-demand matching both in the short and long term. For this purpose both the short horizon annual scenarios (1997-98 to 2000-01) and long horizon terminal year scenarios (2005-06 and 2010-11) are developed assuming capacity additions from only public sector. Overall, the results indicated that with marginal contributions from non-supply options and if the public sector generates enough resources to add the required capacity, optimal matching of supply and demand could be achieved. The scenario analyses also showed that it is more economical to have some level of planned rationing compared to having a more reliable system. The quantum of new capacity additions required and the level of investments associated with it clearly indicated the urgent need of private sector participation in capacity additions. Finally, we made an attempt to verify the applicability of the integrated model to analyse the implications of private sector participation in capacity additions. First, a number of scenarios are developed to study the optimal allocations of predicted hourly demand to private capacity under different situations. Secondly, the impacts of privatisation on the public utility and consumers are analysed. Both short term and long term scenarios are developed for this purpose. The results showed the advantage of marginal non-supply of electricity both in terms of achieving overall effective supply-demand matching and economic benefits that could be generated through cost savings. The results also showed the negative impacts of high guarantees offered to the private sector in terms of the opportunity costs of reduced utilization of both the existing and new public capacity. The estimates of unit cost of supply and effective cost of supply facilitated the relative comparison among various scenarios as well as finding out the merits and demerits of guarantees to private sector and non-supply of electricity. The unit cost estimates are also found to be useful in studying the relative increase in electricity prices for consumers on account of privatization, guarantees and reliable supply of electricity. Using the results of scenario analyses, likely generation expansion plans till the year 2010-11 are generated. The analyses have been useful in providing insights into fixing the availability and plant load factors for the private sector capacity. Based on the analysis, the recommended range for plant utilization factor is 72.88 - 80.57%. The estimated generation losses and the associated economic impacts of backing down of existing and new public capacity on account of guarantees offered to private sector are found to be significantly high. The analyses also showed that the backing down might take place mainly during nights and low demand periods of monsoon and winter seasons. Other impacts of privatization that studied are in terms of increased number of alternatives for the utility to buy electricity for distribution and the associated increase in its cost of purchase. Regarding the consumers, the major impact could be in terms of significant increase in expected tariffs. The major contributions of this thesis are summarized as follows: i. An integrated approach to electricity planning that is reported here, is unique in the sense that it considers options available under various alternatives, namely, existing supply, non-supply and new supply. This approach is most suited for severely constrained systems having to manage with both energy and capital resource shortages. ii. The integration of operational and strategic planning with coherent target plans for the former and requirement plans for the latter bridges the prevailing gap in electricity planning approaches. iii. The concept of Representative Load Curves (RLCs), which is introduced here, captures the hourly, daily and seasonal variations in demand. Together, all the RLCs developed for a given year are expected to model the hourly demand patterns of that year. These RLCs are useful for planning in resource constrained electricity systems and in situations where it is required to know the time variations in demand (e.g. supply-demand matching, seasonal scheduling of hydro plants and maintenance scheduling). RLCs are also useful in identifying the factors influencing variations in demand. This approach will overcome the limitations of current method of representation in the form of static and aggregate annual load duration curves. iv. A new term, "non-supply of electricity" has been introduced in this thesis. A brief overview of non-supply presented here includes reasons for non-supply, type of non-supply, methods to estimate cost of non-supply and factors influencing these estimates. v. The integrated mixed integer programming model developed in the study has been demonstrated as a planning tool for- • Optimal hourly and seasonal scheduling of various existing supply, non-supply and new supply options • Estimation of supply shortages on a representative hourly basis using the information on resource constraints • Effectively planning non-supply of electricity through appropriate power/energy rationing methods • Estimation of the need for the new capacity additions both to bridge the existing gap and to take care of increase in future demand levels • Optimal filling of gaps between demand and supply on a representative hourly basis through new supply of electricity • Optimally arriving at the judicious mix of public and private capacity additions • Studying the impacts of private capacity on the existing and new public sector capacity, and on the consumers • Optimally verifying the feasibility of integrating the captive generation with the total system vi. The demand analysis using RLCs helped to bring out the differences in demand patterns with and without constraints, impacts of constraints on preferred pattern of electricity consumption, success of non-supply options in both reducing the demand levels and greatly disturbing the electricity usage patterns. Multifactor ANOVA analyses results showed that the logically obtained factors accounted for maximum variations in demand at very high significance levels. vii. A comparison of optimal (represented by optimal predicted RLCs) and actual (reflected by actual RLCs) practices facilitated by the model showed that the actual practice during constrained years is highly ad hoc and sub-optimal. viii. The results of the scenario analyses showed that it is more economical to have some amount of planned rationing compared to having a more reliable system, which does not allow non-supply of electricity. ix. The scenarios, which analysed the impacts of high guarantees offered to the private sector, showed the negative impacts of these in terms of reduced utilization of both the existing and new public capacity. x. Generation expansion plans till the year 2010-11 are developed using the results of various kinds of scenario analyses. Two groups of year-wise generation expansion plans are generated, one with only public sector capacity additions and the other with private sector participation. xi. The impacts of privatization of capacity additions are studied from the point of view of the utility and consumers in terms of expected increase in cost of purchase of electricity and tariffs. xii. The analyses are also made for developing some insights into fixing the availability and plant load factors for the private capacity. Based on the analysis, the recommended range for plant utilization factor is 72.88 - 80.57%. We believe that the integrated approach presented and the results obtained in this thesis would help utilities (both suppliers and distributors of electricity) and governments in making rational choices in the context of resource constrained systems. The results reported here may also be used towards rationalization of Government policies vis-a-vis tariff structures in the supply of electricity, planning new generation capacity additions and effective rationing of electricity. It is also hoped that the fresh approach adopted in this thesis would attract further investigations in future research on resource constrained systems.

For the appropriate operation and correct short term planning, daily demand curve (DDC) of municipal water distribution networks should be forecasted beforehand. For that purpose, artificial neural networks (ANN) is used as a new method. The proposed approach employs already recorded DDCs extracted from the database of ASKI (Ankara Water Authority) SCADA center and related independent parameters such as temperature and relative humidity obtained from DMI (State Meteorological Institute). In this study, a computer model was developed in order to forecast hourly DDCs using Matlab and related modules. Parameters that affect the consumption of the water were determined as temperature, relative humidity, human behavior (weekend or workday) and season. Randomly selected days were taken into account for performance of the ANN model. Forecasted DDC values were compared with recorded data and consequently the model gives relatively satisfactory results, an average of 75% match according to R2 values for Ankara N8-3 network. Same architecture was applied for Antalya network give better results, average of 85%. For planning purposes
total volume and peak water consumption values for the selected recorded days, the day before recorded days, ANN forecasted days and seasonal average was compared and seasonal average gave relatively better results. Using the forecasted DDC, (i) performance analysis of the pressure zone and (ii) optimum valve setting evaluation for pressure management were realized. The results of the study may help water utilities for short term planning of a water distribution network, rehabilitation of elements, taking counter measures and setting the valve openings for minimizing leakage and optimizing customer conformity of the distribution network.

In deregulated electricity markets, accurate modeling and forecasting of different variables, e.g. demand, prices, production etc. have obtained increasing importance in recent years. As in most electricity markets, the daily demand and prices are determined the day before the physical delivery by means of (semi-) hourly concurrent auctions, accurate forecasts are necessary for the efficient management of power systems. However, it is well known that electricity (demand/price) data exhibit some specific features, among which, daily, weekly and annual periodic patterns as well as non-constant mean and variance, jumps and dependency on calendar effects. Modeling and forecasting, thus, is a challenging task. This thesis tackles these two issues, and to do this, two approaches are followed. In the first case, we address the issue of modeling and out-of-sample forecasting electricity demand and price time series. For this purpose, an additive component model was considered that includes some deterministic and a stochastic residual components. The deterministic components include a long-term dynamics, annual and weekly periodicities and calendar effects. The first three components were estimated using splines while the calendar effects were modeled using dummy variables. The residual component is instead treated as stochastic and different univariate and multivariate models have been considered with increasing level of complexity. In both cases, linear parametric and nonlinear nonparametric models, as well as functional based models, have been estimated and compared in a one day-ahead out-of-sample forecast framework. The class of univariate models includes parametric autoregressive models (AR), nonparametric and nonlinear regression models based on splines (NPAR) and scalar-response functional models, that in turns can be formulated parametrically (FAR) or non parametrically (NPFAR). The multivariate models are vector autoregressive models (VAR) and functionalresponse, parametric (FFAR) and nonparametric (NPFFAR), models. For this issue, five different electricity markets, namely, British electricity market (APX Power UK), Nord Pool electricity market (NP), Italian electricity market (IPEX), Pennsylvania-New Jersey-Maryland electricity market (PJM) and Portuguese electricity market (OMIE(Po)) were considered for the period 2009 to 2014. The first five years were used for model estimation while the year 2014 was left for one-day-ahead forecasts. Predictive performances are first evaluated by means of descriptive indicators and then through a test to assess the significance of the differences. The analyses suggest that the multivariate approach leads to better results than the univariate one and that, within the multivariate framework, functional models are the most accurate, with VAR being a competitive model in some cases. The results also lead to another important finding concerning to the performance of parametric and nonparametric approach that showed strong linkage with underlying process. Finally the obtained results were compared with other works in the literature that suggest our forecasting errors are smaller compared with the state-of-art prediction techniques used in the literature. In the second part of this thesis the issue of electricity price forecasting is revisited following a completely different approach. The main idea of this approach is that of modeling the daily supply and demand curves, predicting them and finding the intersection of the predicted curves in order to find the predicted market clearing price and volume. In this approach, the raw bids/offers data for demand and supply, corresponding to each (half-) hour is first aggregated in a specific order. The functional approach converts the resulted piece wise curves into smooth functions. For this issue, parametric functional model (FFAR) and the nonlinear nonparametric counterpart (NPFFAR) were considered. As benchmark, an ARIMA model was fitted to the scalar time series corresponding to the market clearing prices obtained from the crossing points of supply and demand curves. Data from Italian electricity market were used for this issue and the results are summarized by different descriptive indicators. As in the first case, results show superior forecasting performance of our functional approach compare to ARIMA. Among different models, the nonparametric functional model produces better results compared to parametric models. Apart from the improvement in forecasting accuracy, it is important to stress that this approach can be used for optimizing bidding strategies. As forecasting the whole curves gives deep insight into the market, our analysis showed that this strategy can significantly improve bidding strategies and maximize traders profit.
Nell’ambito dei mercati elettrici liberalizzati, negli ultimi anni l’interesse verso una buona modellazione e un’accurata previsione di variabili da essi provenienti, ad es. domanda, prezzi, produzione etc., è andato via via crescendo. Ciànche perché in molti mercati elettrici, i prezzi e i volumi giornalieri vengono determinati mediante un sistema di aste (semi-)orarie che ha luogo il giorno precedente a quello della consegna fisica; una previsione accurata permette quindi un’efficiente gestione del sistema elettrico. La modellazione e la previsione di queste variabili, tuttavia, è resa difficile dal fatto che le serie storiche di domanda e prezzi, sono caratterizzate dalla presenza di vari tipi di periodicità, annuale, settimanale e giornaliera, da una media e una varianza che non sono costanti nel tempo, da picchi improvvisi e dalla dipendenza da diversi effetti di calendario. Questa tesi si occupa proprio di questo difficile compito e lo fa seguendo dua approcci principali. Nel primo approccio vengono modellate e previste, in un contesto out-of-sample, le serie storiche della domanda e dei prezzi ufficialmente riportati dal Gestore dei Mercati Energetici. A tal fine, viene considerato un modello a componenti additive che include una parte deterministica ed una componente residua stocastica. La parte deterministica, in particolare, contiene varie componenti che descrivono la dinamica di lungo periodo, quella periodica annuale e settimanale e gli effetti di calendario. Le prime tre componenti vengono stimate utilizzando delle splines del tempo mentre gli effetti di calendario vengono modellati mediante variabili dummy. La componente residuale, invece, viene trattata in maniera stocastica mediante vari modelli, univariati e multivariati, con diversi livelli di complessità. Sia nel caso univariato che in quello multivariato sono stati considerati modelli parametrici e non parametrici, nonché modelli basati sull’approccio funzionale. La classe dei modelli univariati comprende modelli lineari autoregressivi (AR), modelli (auto)regressivi non parametrici e non lineari basati su spline (NPAR) e modelli funzionali a risposta scalare. Questi ultimi, a loro volta, possono essere formulati secondo una specificazione parametrica (FAR) o non parametrica (NPFAR). Relativamente alla classe dei modelli multivariati, invece, sono stati considerati modelli vettoriali autoregressivi (VAR) e modelli funzionali a risposta funzionale, sia nella versione parametrica (FFAR) che in quella non parametrica (NPFFAR). Tutti questi modelli sono stati stimati e confrontati in termini di capacità previsiva nell’ambito della previsione a 1 giorno e out-of-sample. Per verificare le performance dei modelli sono stati considerati i dati provenienti da 5 tra i principali mercati elettrici: il mercato inglese (APX Power UK), il mercato del Nord Pool (NP), quello italiano (IPEX), quello di Pennsylvania-New Jersey-Maryland electricity market (PJM) ed, infine, quello portoghese (OMIE(Po)). Il periodo analizzato va dal 2009 al 2014. I primi cinque anni sono stati utilizzati per la stima dei modelli mentre l’intero 2014 è stato lasciato per le previsioni out-of-sample. La performance predittiva è stata valutata prima mediante indici descrittivi e poi mediante un test statistico per attestare la significatività delle differenze. I risultati suggeriscono che, in generale, l’approccio multivariato produce previsioni più accurate dell’approccio univariato e che, nell’ambito dei modelli multivariati, i modelli basati sull’approccio funzionale risultano i migliori, anche se il VAR è comunque competitivo in diverse situazioni. Questi risultati possono essere letti anche come un segnale della presenza o meno di non linearità nei vari processi generatori dei dati. Anche se il confronto con altri lavori non è mai del tutto omogeneo, gli errori di previsione ottenuti sono tendenzialmente più piccoli di quelli riportati in letteratura. Nella seconda parte della tesi il tema della previsione dei prezzi dell’elettrcità è stato riconsiderato seguendo un percorso completamente diverso. L’idea di fondo di questo nuovo approccio è quella di modellare non le serie dei prezzi di mercato, ma le curve di domanda e di offerta giornaliere mediante modelli funzionali, di prevederle un giorno in avanti, e di trovare l’intersezione tra le due curve previste. Questa intersezione fornisce la previsione della quantità e del prezzo di equilibrio (market clearing price and volume). Questa metodologia richiede di agregare, secondo uno specifico ordine, tutte le offerte di vendita e le richieste di acquisto presentate ogni (mezz’)ora. Ciò produce delle spezzate lineari a tratti che vengono trasformate dall’approccio funzionale in curve liscie (smooth functions). Per questo fine, sono state considerati modelli funzionali parametrici (FFAR) e nonparametrici (NPFFAR). Come benchmark è stato stimato un modello ARIMA scalare alle serie storiche dei prezzi di equilibrio (clearing prices) ottenuti dall’incrocio tra le curve di domanda e di offerta. L’applicazione di questo metodo è stata fatta limitatamente al caso del mercato italiano . Come precedentemente, i risultati suggeriscono una migliore abilità previsiva dell’approccio funzionale rispetto al modello ARIMA. Tra i vari modelli considerati, quello funzionale non parametrico ho fornito i risultati migliori. Va sottolineato poi che un aspetto rilevante, che va oltre il miglioramento nell’accuratezza previsiva, è che l’approccio basato sulla previsione delle curve di offerta e di domanda può essere utilizzato per ottimizzare le strategie di offerta/acquisto da parte degli operatori e, di conseguenza, per massimizzare il profitto dei traders.

På uppdrag av Sundsvall Energi AB har FVB Sverige AB påbörjat en förstudie kring etableringen av fjärrkyla i Sundsvall. Produktionsmedlen i det planerade nätet kommer att innefatta frikyla från akviferen och en kompressordriven kylmaskin. Det övergripande syftet med projektet har dels varit att ta fram en optimal framledningskurva, samt att ta reda på i vilken utsträckning frikylan kan nyttjas innan kylmaskinen måste användas som spetsproduktionsmedel. Projektet har inledningsvis fokuserat på att undersöka hur klimatet och kylbehovet ser uti Sundsvall. Kylbehovet granskades utifrån sex befintliga byggnader som nyttjar dricksvattenkyld fjärrkyla i Sundsvall. Därefter undersöktes olika typer av klimatsystem för att utröna vad de har för krav på framledningstemperaturen. Det konstaterades att kylbatterier var den komponent som kräver lägst framledningstemperatur, varför kyleffektberäkningar utfördes på dem. Resultatet ur kylbatteriberäkningarna fick motsvara den av fjärrkylenätet avgivna kyleffekten vid varierande utomhustemperatur. Genom att väga den avgivna kyleffekten vid varierande framledningstemperatur mot det erforderliga kyleffektbehovet vid varierande utomhustemperatur kunde framledningskurvan ta form. Akviferen antas hålla en temperatur på omkring 7°C till 9°C året runt, men utgångspunkten i detta projekt har varit att den konstant är 9°C. Under de förutsättningarna har framledningstemperaturen kunnat bestämmas till att vara 11°C under större delen av året, men att den sänks vid en utomhustemperatur på omkring 21°C i varierande grad ned till 6°C vid utomhustemperaturen 25°C. Med hjälp av framledningskurvan kunde därefter frikylans täckningsgrad bedömas. Resultatet visar att om framledningens temperatur höjs med 0,5–1,0°C i distributionsnätet kommer kylmaskinen att behöva vara i drift under 159 timmar per år. Om istället uppvärmningen blir 1,5° eller 2,0°C kommer kylmaskinen behöva vara i drift under 233 timmar respektive 325 timmar. Sammantaget har samtliga av projektets konkreta och verifierbara mål besvarats.
On behalf of Sundsvall Energi AB, FVB Sverige AB has initiated a preliminary study on the establishment of a district cooling system in Sundsvall. The main source for the cooling will be cool water drawn from the aquifer and a compressor chiller. The main purpose of this project has both been to provide the optimal supply temperature of the cooling network at different outdoor temperatures, and to find out to what extent the cool water from the aquifer can be used by itself as the cooling source. The project was initially focused on examining the climate and cooling demand in Sundsvall. The cooling demand was examined on the basis of six existing buildings that uses freshwater district cooling, and different types of climatesystems were then examined to ascertain what their requirements for the supply temperature are. Cooling coil batteries were found to be the component that requires the lowest supply temperature; therefore, the cooling power calculations were relied on them. The outcome of the cooling coil battery calculations was presumed to correspond to the cooling power of the network itself. By comparing the cooling power of the coil batteries at different supply temperatures and the cooling demand at different outdoor temperatures the main supply temperature for the district cooling network took shape. The aquifer is expected to maintain a temperature of approximately 7°C to 9°C, but in this project the temperature is set to exactly 9°C. On those premises the supply temperature of the cooling network could be set to 11°C for most of the year, but with a reduction of the supply temperature at outdoor temperatures around 21°C. Subsequently the supply temperature is reduced to 6°C at the outdoor temperature 25°C. Via the supply temperature curve, the aquifer cooling coverage ratio could be assessed. The result shows that if the supply temperature is raised between 0,5°C and 1,0°C in the distribution network the compressor chiller will have to be in operation for 159 hours per year. If instead the supply temperature is raised 1,5°C or 2,0°C, the compressor chiller must be in operation for 233 hours and 325 hours, respectively. In summary, all the goals and targets of the project have been completed.

Purpose: This research aims to enhance the current understanding and knowledge of the demand-supply chain management (DSCM) concept by determining its elements, benefits, and requirements, as well as by analyzing key elements of the concept. Methodology: This research has utilized the case study strategy and the survey strategy, however, the case study strategy dominates. The case study research has involved five companies originating from Sweden and the collection of empirical data mainly from in-depth interviews with key persons representing senior and middle management. The survey research targeted the largest firms in Sweden and Finland and empirical data was collected through an online questionnaire. Findings: This research has established that the main elements of DSCM include market orientation, coordination of the demand and supply processes, viewing the demand and supply processes as being equally important, as well as value creation, differentiation, innovativeness, responsiveness, and cost-efficiency in the demand and supply processes. It has also been revealed that the main benefits of DSCM include enhanced competiveness, enhanced demand chain performance, as well as enhanced supply chain performance, while the main requirements of DSCM include organizational competences, company established principles, demand-supply chain collaboration, and information technology support. A key element of DSCM further investigated is differentiation focused supply chain design. It has been shown that these efforts can be organized into a process of five stages. In addition, it is important that this process is addressed in parallel with the new product development (NPD) process, that information is exchanged between them, and that they are directed on the basis of the same segmentation model. Another key element of DSCM further investigated is coordination between NPD and SCM. This research has identified several significant linkages between these management directions, which motivate the use of an integrative NPD process where the NPD functions are aligned with the main supply functions in the company and other sales-related functions supporting the commercialization. A final key element of DSCM further investigated is the significance of regarding the demand processes and the supply processes as being equally important. This research has revealed that logistics outsourcing can be risky, if it results in the supply processes being considered less important. Nevertheless, if senior management regards the outsourced processes as equally important as the in-house processes, the effect of logistics outsourcing on company strategies and direction in SCM could be reduced and logistics outsourcing could instead provide an opportunity to improve the design and differentiation of the supply chain. Research limitations/implications: This research has proposed, described, and further analyzed a demand-supply oriented management approach. Such a management approach stresses that the demand processes and the supply processes have to be coordinated and directed at an overlying level, in order to gain and sustain a competitive advantage in competitive and fragmented markets. This research is mainly explorative in nature, and more empirical data, from similar and other research settings, is needed to further validate the findings. Another limitation of the research is that it is essentially limited to Swedish companies (even if some Finnish companies are involved in the survey), however, many of the case companies have a large international presence and are among the top three in their industries, facts which provide some grounds for generalization. Practical implications: This research provides researchers and practitioners with insights into how to develop a demand-supply oriented business. It shows that companies should organize themselves around understanding how customer value is created and delivered, as well as how these processes and management directions can be coordinated. In order for this to occur, the demand and supply processes must be considered as being equally important and the firm needs to be managed jointly and in a coordinated manner by the demand- and supply-side of the company. It is also important that value creation is considered in both the demand and supply processes. Originality/value: Despite strong arguments from both researchers and practitioners for a demand-supply oriented management approach only a minority of companies appear to have effectively coordinated the demand and supply processes. This might be influenced by the lack of research examining how the demand and supply processes can be coordinated, what benefits can be gained by coordinating them, and what requirements are necessary to succeed. This research contributes by investigating these types of aspects further.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2003.
Includes bibliographical references (p. 140-141).
This thesis consists of three chapters that investigate the index premium and its underlying economics both theoretically and empirically. The first chapter presents our empirical findings about the index premium and its properties. First, we find that the index premia for both the S&P 500 and Russell 2000 have been growing over time, reaching levels of about 15% and 10%, respectively, in 2000. The premia arise somewhat gradually between the announcement and effective days and do not reverse at least in the next few weeks. Second, we find that the index premium is related to the idiosyncratic risk and market equity of a firm with economic and statistical significance. Third, we introduce a new concept that we label the index turnover cost, which represents a cost borne by index funds due to the index premium. We illustrate this cost and estimate it as 70-85 bp annually for the S&P 500 and 110-211 bp annually for the Russell 2000. The second chapter develops the first theoretical explanation in the literature for downward-sloping demand curves. In traditional multi-asset models such as the CAPM, demand curves for stocks are almost perfectly horizontal, because a representative investor who is sufficiently risk-tolerant to hold the entire market portfolio has to be almost indifferent to idiosyncratic risk. We start with the basic CAPM setting, but we further assume that there is a fixed cost to actively managing a stock portfolio and that individuals pay the cost through an institution as a proportional fee. In equilibrium, the proportional fee can entirely determine the cross-sectional pricing of stocks, while the risk aversion of individual investors still determines the aggregate market risk premium.
(cont.) In contrast to any representative agent models, this allows demand curves for stocks to be sufficiently steep to have economic significance, also implying that stocks will be priced only approximately around their fundamental values. Our explanation can account for several empirically observed puzzles such as the magnitude of the S&P 500 index premium. The third chapter focuses on index investors for whom the index premium creates a recurring cost: as the index is updated, they need to buy stocks with the premium and sell stocks without the premium. Different index rules can produce different index premia due to the different frequency and criteria of updating. We build a model to investigate the behavior of the index turnover cost and the portfolio performance of a mechanical index fund under a market-cap rule, an exogenous random rule, and a deterministic rule. We find that the rational anticipation of future index composition reflected in prices today eliminates any first-order differences in index fund performance across the three index rules. As the index investors become a large part of the market, the non-index investors become less diversified, and this induces hedging motives which hurt the index investors especially under a market-cap rule.
by Antti Petäjistö.
Ph.D.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2006.
Includes bibliographical references (leaves 73-75).
Globalization increases product variety and shortens product life cycles. These lead to an increase in demand uncertainty and variability. Outsourcing to low-cost countries increases supply lead-time and supply uncertainty and variability. Coupled with the increase of mergers and acquisitions, which increase supply chain complexity, and the unforgiving nature of having too little or too much inventory, these factors have accelerated the importance and adoption of the Sales and Operations Planning (S&OP) process. S&OP is driven by a cross functional team, with the purpose of balancing supply and demand with the objective of maximizing a company's goals. It manages the supply and demand uncertainties, balances the different internal and external stakeholders' interests, and aligns the operations towards its strategy and vision. In support of the Supply Chain 2020 Project at MIT, this thesis focuses on analyzing the S&OP function across industries. Using the Phase I SC 2020 theses, literature, white papers, and interviews with industry experts, this thesis compares and contrasts the S&OP practices across nine industries.
(cont.) It examines their best practices and underlying principles, as well as the macro factors that have shaped the practices for the last ten to fifteen years, as well as what is expected in the future. Companies with the "best" S&OP processes collaborate internally to balance sales and operations, and align all internal stakeholders' interests. Furthermore, they collaborate externally with suppliers and customers to reduce supply and demand uncertainties. They also understand and manage demand and supply uncertainties, and align their effort towards their goals. These companies synchronize operations and are agile to changing environments.
by Peng Kuan Tan.
M.Eng.in Logistics

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

Thesis: S.M. in Real Estate Development, Massachusetts Institute of Technology, Program in Real Estate Development in conjunction with the Center for Real Estate, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 66-69).
This thesis documents new methods for gauging supply and demand of data center capacity and addresses issues surrounding potential threats to data center demand. This document is divided between a primer on the composition and engineering of a current data center, discussion of issues surrounding data center demand, Moore's Law and cloud computing, and then transitions to presentation of research on data center demand and supply.
by Laird Bennion.
S.M. in Real Estate Development

Thesis (MSc)--Stellenbosch University, 2013.
ENGLISH ABSTRACT: Supply-demand analysis (SDA) is a tool that allows for the control, regulation and behaviour of metabolic pathways to be understood. In this framework, reactions are grouped into reaction blocks that represent the supply and demand of a metabolic product. The elasticities of these supply and demand blocks can be used to determine the degree of control either block has over the flux in the pathway and the degree of homoeostasis of the metabolic product that links the blocks. Rate characteristic plots, on which the rates of supply and demand blocks are plotted as functions of the concentration of the linking metabolite, represent a powerful visual tool in this framework. Generalised supply-demand analysis (GSDA) allows for the analysis of metabolic models of arbitrary size and complexity without prior knowledge of the regulatory structure of the pathway. This is achieved by performing SDA on each variable metabolite in a pathway instead of choosing a single linking metabolite. GSDA also provides other benefits over SDA as it allows for potential sites of regulation and regulatory metabolites to be identified. Additionally it allows for the identification and quantification of the relative contribution of di erent routes of regulation from an intermediate to a reaction block. Moiety-conserved cycles present a challenge in performing in silico SDA or GSDA, as the total concentration of a moiety must remain constant, thereby limiting the range of possible concentrations of the metabolites between which it cycles. The first goal of this thesis was to develop methods to perform GSDA on two-membered and interlinked moiety-conserved cycles. We showed that by expressing the members of a moiety-conserved cycle as a ratio, rather than individual metabolite concentrations, we can freely vary the ratio without breaking moiety conservation in a GSDA. Furthermore, we showed that by linking the concentrations of the members of two interlinked two-membered moiety-conserved cycles to a “linking metabolite”, we could vary the concentration of this metabolite, within constraints, without breaking moiety conservation. The Python Simulator for Cellular Systems (PySCeS) is a software package developed within our group that provides a variety of tools for the analysis of cellular systems. The RateChar module for PySCeS was previously developed as a tool to perform GSDA on kinetic models of metabolic pathways by automatically generating rate characteristic plots for each variable metabolite in a pathway. The plots generated by RateChar, however, were at times unclear when the models analysed were too complex. Additionally, invalid results where steady-states could not be reached were not filtered out, and therefore appeared together with valid results on the rate characteristic plots generated by RateChar. We therefore set out to improve upon RateChar by building plotting interface that produces clear and error-free rate characteristics. The resulting RCFigure class allows users to interactively change the composition of a rate characteristic plot and it includes automatic error checking. It also provides clearer rate characteristics with e ective use of colour. Using these tools two case studies were undertaken. In the first, GSDA was used to investigate the regulation of aspartate-derived amino acid synthesis in Arabidopsis thaliana. A central result was that the direct interaction of aspartate-semialdehyde (ASA), a metabolite at a branch point in the pathway, with the enzyme that produces it only accounts for 7% of the total response in the flux of supply. Instead, 89% of the observed flux response was due to ASA interacting with of the downstream enzymes for which it is a substrate. This result was unexpected as the ASA producing enzyme had a high elasticity towards ASA. In a second case study moiety-conserved cycles in a model of the pyruvate branches in lactic acid bacteria were linearised using the above mentioned method. This served to illustrate how multiple reaction blocks are connected by these conserved moieties. By performing GSDA on this model, we demonstrated that the interactions of these conserved moieties with the various reaction blocks in the pathway, led to non-monotonic behaviour of the rate characteristics of the supply and demand for the moiety ratios. An example of this is that flux would increase in response to an increase in product for certain ranges. This thesis illustrates the power of GSDA as an entry point in studying metabolic pathways, as it can potentially reveal properties of the regulation and behaviour of metabolic pathways that were not previously known, even if these pathways were subjected to previous analysis and a kinetic model is available. In general it also demonstrates how e ective analysis tools and metabolic models are vital for the study of metabolism.
AFRIKAANSE OPSOMMING: Vraag-en-aanbod analise (VAA) is ’n analisemetode wat mens in staat stel om die beheer, regulering en gedrag van metaboliese paaie beter te verstaan. In hierdie raamwerk word reaksies gegroepeer as reaksieblokke wat die aanbod (produksiestappe) en die aanvraag (verbruik-stappe) van ’n metaboliese produk verteenwoordig. Vanaf die elastisiteite van hierdie aanbod- en aanvraag-blokke kan die graad van beheer van elkeen van die blokke oor die fluksie, asook die graad van homeostase van die metaboliese koppelingsintermediaat, bereken word. Snelheidskenmerk-grafieke, waarop die snelhede van die vraag- en aanbod-blokke as funksies van die konsentrasie van die koppelingsmetaboliet uiteengesit word, verteenwoordig ’n kragtige visuele hulpmiddel in hierdie raamwerk. Veralgemeende vraag-aanbod analise (VVAA), die veralgemeende vorm van VAA, maak dit moontlikommetaboliese modelle van arbitrêre grootte en kompleksiteit te analiseer sonder enige vooraf-kennis van die regulatoriese struktuur van die paaie. Die prosedure is om VAA op elk van die veranderlike metaboliete in die pad uit te voer, eerder as om ’n enkele koppelingsmetaboliet te kies. VVAA het ook ander voordele bo VAA aangesien dit potensiële setels van regulering en regulatoriese metaboliete kan identifiseer. Daarbenewens kan dit die relatiewe bydrae van verskillende regulerings-roetes van vanaf ’n intermediaat na ’n reaksieblok identifiseer en hulle kwantifiseer. Groep-gekonserveerde siklusse bied ’n uitdaging vir in silico VAA of VVAA, aangesien die totale konsentrasie van die gekonserveerde groep konstant moet bly. Dit beperk die waardes van moontlike konsentrasies van die metaboliete wat die siklus uitmaak. Die eerste doelstelling van hierdie tesis was dus om metodes te ontwikkel waarmee VVAA op tweeledige en saamgebonde groep-gekonserveerde siklusse uitgevoer kan word. Deur die lede van groep-gekonserveerde siklusse eerder as verhoudings uit te druk in plaas van as individuele metabolietkonsentrasies, het ons gewys dat ons hierdie verhouding vrylik kan varieer sonder om die groep-konservering te breek in ’n VVAA. Ons het ook gewys dat die konsentrasies van die lede van ’n saamgebonde groep-gekonserveerde siklus gekoppel kan word aan ’n “koppelingsmetaboliet”, waarvan die konsentrasie dan binne perke gevarieer kan word sonder om die groep-konservering te breek. Die “Python Simulator for Cellular Systems” (PySCeS) is ’n programmatuur-pakket wat binne ons navorsingsgroep ontwikkel is met die doel om sellulêre sisteme numeries te analiseer. Die RateChar module vir PySCeS was reeds voor die aanvang van hierdie projek ontwikkel om VVAAop kinetiese modelle van metaboliese paaie uit te voer deur outomaties snelheidskenmerke vir elke veranderlikke metaboliet te genereer. Die grafieke wat deur RateChar gegenereer is, was egter soms onduidelik wanneer die modelle te groot of kompleks geraak het. Daarbenewens is ongeldige resultate, waar ’n bestendige toestand nie bereik kon word nie, nie uitgefiltreer nie, en het dus saam met geldige resultate op die snelheidskenmerke verskyn. Een van die doelstellings was dus om RateChar te verbeter deur ’n koppelvlak vir grafieke te ontwikkel wat duidelike en foutlose snelheidskenmerke kon produseer. Dit het gelei tot die RCFigure klas wat outomatiese foutopsporing uitvoer en gebruikers in staat stel om op ’n interaktiewe wyse die samestelling van ’n snelheidskenmerkgrafiek te verander. Dit bied ook duideliker snelheidskenmerke deur e ektief van kleur gebruik te maak. Met hierdie ontwikkelde gereedskap is twee gevallestudies onderneem. In die eerste is VVAA gebruik om die regulering van aspartaat-afgeleide aminosuursintese in Arabidopsis thaliana te bestudeer. Die belangrikste resultaat was dat die direkte interaksie van aspartaat-semialdehied (ASA), ’n metaboliet by ’n vertakkingspunt in die pad, met die ensiem wat dit produseer, slegs vir 7% van die totale respons in die aanbod-fluksie verantwoordelik was. Daarteen was 89% van die waargenome fluksierespons die gevolg van die interaksie van ASA met drie van die stroomafensieme, waarvoor dit ’n substraat is. Hierdie resultaat was onverwag aangesien die ensiem wat ASA produseer ’n hoë elastisiteit teenoor ASA toon. In ’n tweede gevallestudie is die groep-gekonserveerde siklusse in ’n model van die pirovaat-takke in melksuurbakterie-metabolisme gelineariseer deur gebruik te maak van die bo beskrewe metode. Dit illustreer hoe verskeie reaksieblokke verbind word deur hierdie gekonserveerde groepe. M.b.v. ’n VVAA van hierdie model het ons gedemonstreer dat die interaksies van die gekonserveerde groepe met die verskeie reaksieblokke in die pad kan lei tot nie-monotoniese gedrag van die snelheidskenmerke van die vraag- en aanbod-reaksies vir die verhouding van die gekonserveerde groep-komponente. ’n Voorbeeld hiervan is die onverwagte waarneming dat die fluksie toeneem met toenemende produk-konsentrasie oor sekere gebiede. Hierdie tesis illustreer die krag van VVAA as ’n beginpunt vir die studie van metaboliese paaie, aangesien dit onbekende regulatoriese eienskappe en gedragspatrone kan ontbloot, selfs al is die paaie vantevore m.b.v. kinetiese modelle geanaliseer. Oor die algemeen demonstreer dit die noodsaaklikheid van e ektiewe analisegereedskap en metaboliese modelle vir die bestudering van metabolisme.
National Research Foundation

The implementation of nature conservation as a land use form is characterized by persistent conflicts and low acceptance by landowners and other users of the considered land area. The thesis applies an economic approach that is understood as the consideration of opportunities and problems of social interaction that aims at mutual benefits (Homann 2002: 63; Homann & Suchanek 2005: 4). Nature conservation is treated as a normal economic good that is demanded and supplied. Human action and human choices regarding the good "nature conservation" can be explained and predicted when including the structure of the exchange and transfer of property rights for nature conservation. The property rights perspective on nature conservation demonstrates an unambiguous understanding of the rights individuals are willing to abandon for demanding and supplying nature conservation. The successful implementation of different aims and strategies of nature conservation requires different property rights. The loss of the right to choose other alternatives implies subjective costs (Knight 1924: 592f.; Buchanan 1981: 14) that cannot be reduced to pecuniary units and landowners. This approach broadens the understanding of the term "costs" related to nature conservation. Different organizational and institutional arrangements can be found in practical nature conservation. Both, the demand for and the supply of nature conservation is organized either individually or collectively. Property rights for the good “nature conservation” are either exchanged voluntarily or involuntarily by applying takings and eminent domain. The application of the methodological individualism, the homo economicus and microeconomic theory, allows to elaborate a simple model of individual demand and supply of one property right that is allocated to nature conservation. This model excludes transaction costs, considers only one normal economic good - “nature conservation”. The analysis demonstrates the outcomes, which can be expected when aggregating these individual demand and supply curves within two different organizations. A vertical aggregation represents the process of choice-making within politics in a direct democracy. A horizontal aggregation illustrates the determination of choices within a market. The analysis includes all possible institutional and organizational arrangements. The results reveal the quantity and quality of implemented nature conservation and the expected relation between available and required budgets. It is highlighted, how susceptible collective outcomes are to changing expenditure and revenue sharing systems and voting rules. When making collective choices, only one revenue and expenditure sharing system exists that allows a unanimously chosen quantity of nature conservation. These specific sharing systems are different when considering different collectives. Only voluntary exchanges ensure mutual benefits and a balanced budget. I can show that the institution of takings increases conflicts and reduce the acceptance for implementing nature conservation. A preference order of the considered institutional arrangements is revealed. The majority of the analyzed arrangements allows unambiguous expectations on the quantity and quality of the implemented nature conservation. The discussion justifies the chosen economic approach for examining problems of social interaction within nature conservation. Furthermore, the application of the elaborated model to representative democratic systems is discussed. The thesis closes with examples of the current and expected future development of practical nature conservation. These cases are discussed in the light of the elaborated model and the analysis' results. The present thesis offers an explanation of past and present processes and outcomes in nature conservation and a support for making expectations on the constellation of actors and their acceptance regarding future strategies in practical nature conservation
Die Umsetzung von Naturschutz als Landnutzungsform ist durch beständige Konflikte und niedrige Akzeptanz durch Landeigentümer und andere Landnutzer gekennzeichnet. Die Arbeit verwendet einen ökonomischen Ansatz. Sie betrachtet Möglichkeiten und Probleme sozialer Interaktion, die auf gegenseitigen Nutzen abzielt (Homann 2002: 63; Homann & Suchanek 2005: 4). Naturschutz wird als normales ökonomisches Gut betrachtet. Dieses wird durch interagierende Individuen angeboten und nachgefragt. Das individuelle Handeln und Entscheiden in Bezug auf "Naturschutz" kann durch das Einbeziehen von Verfügungsrechten, welche bei dem Tausch ausgetauscht und übertragen werden, beschrieben und vorhergesagt werden. Die verfügungsrechtliche Betrachtung von Naturschutz ermöglicht ein eindeutiges Verständnis auf jene Rechte, auf die Individuen verzichten würden, um Naturschutz nachzufragen und anzubieten. Die erfolgreiche Umsetzung der unterschiedlichen Naturschutzziele und –strategien erfordert ein Eigentum an unterschiedlichen Verfügungsrechten. Der Verlust des Rechtes, eine Alternative zu wählen, verursacht subjektive Kosten (Knight 1924: 592f.; Buchanan 1981: 14), welche nicht auf Geldeinheiten und nicht auf Landeigentümer begrenzt werden können. Dieser Ansatz erweitert das Verständnis von Kosten in Bezug auf Naturschutz. Unterschiedliche organisatorische und institutionelle Arrangements sind im praktischen Naturschutz zu finden. Nachfrage und Angebot können jeweils individuell oder kollektiv organisiert sein. Verfügungsrechte für das Gut „Naturschutz“ werden entweder freiwillig oder erzwungen - durch Konfiskation und Enteignung getauscht. Die Anwendung des methodologischen Individualismus, des Konzeptes des Homo Economicus und mikroökonomischer Theorie, erlaubt die Entwicklung eines simplen Modells des individuellen Angebots und der individuellen Nachfrage nach Verfügungsrechten für Naturschutz. Dieses Modell schließt Transaktionskosten aus und betrachtet ausschließlich ein normales ökonomisches Gut – Naturschutz. Die Analyse zeigt die zu erwartenden Ergebnisse auf, wenn die individuelle Nachfrage und das individuelle Angebot durch zwei unterschiedliche Organisationen aggregiert werden. Eine vertikale Aggregation verdeutlicht eine politische Wahlhandlung innerhalb einer direkten Demokratie. Eine horizontale Aggregation repräsentiert die Wahl innerhalb eines Marktes. Die Analyse beinhaltet alle Kombinationen der unterschiedlichen institutionellen und organisatorischen Arrangements für die Bereitstellung des Gutes "Naturschutz". Die Ergebnisse dieser Analyse zeigen (1) die zu erwartende Quantität und Qualität des durchgeführten Naturschutzes und (2) das zu erwartende Verhältnis zwischen dem verfügbaren und dem notwendigen Budget auf. Zusätzlich wird die Empfindlichkeit kollektiver Entscheidungsergebnisse gegenüber sich verändernden Abstimmungsregeln und Teilungsregeln von Ausgaben und Einnahmen herausgearbeitet. Bei kollektiven Wahlhandlungen existiert nur jeweils eine Ausgaben- und Einnahmenteilung, die eine einstimmige Wahl einer Menge von Naturschutz ermöglicht. Diese Teilungsregel variiert zwischen unterschiedlichen Kollektiven. Ausschließlich ein freiwilliger Tausch sichert gegenseitige Vorteile und ein ausgeglichenes Budget. Weiterhin zeige ich auf, dass die Institution Konfiskation die Konflikte mit Landnutzern erhöht und deren Akzeptanz für die Umsetzung von Naturschutz reduziert. Eine Präferenzordnung für die verschiedenen Institutionen wird erarbeitet. Der Großteil der analysierten institutionellen und organisatorischen Arrangements erlaubt eindeutige Aussagen über die Quantität und Qualität des praktizierten Naturschutzes. Die Diskussion begründet die gewählte ökonomische Methode zur Untersuchung von Interaktionsproblemen des Naturschutzes. Weiterhin wird die Anwendbarkeit des erarbeiteten Modells für repräsentative Demokratien erörtert. Die Arbeit schließt mit Beispielen der aktuellen und künftig zu erwartenden praktischen Naturschutzarbeit. Diese Beispiele werden anhand des Modells und der Analyseergebnisse diskutiert. Die vorliegende Arbeit bietet ein Erklärungsmodell für vergangene und gegenwärtige Entwicklungen und Ergebnisse im praktischen Naturschutz. Sie stellt eine Unterstützung für die realistische Einschätzung von Akteurskonstellationen und deren Akzeptanz von zukünftigen Implementierungsansätzen von Naturschutz dar

The market mechanism is the mechanism of interrelation and interaction of the basic elements of the market – demand, supply, prices, competition, and the basic economic laws of the market. Supply and demand are interdependent elements of the mechanism. The former is determined by the solvent demand of consumers and offer a set of goods proposed by sellers. The ratio between them is formed in an inverse relationship, determining the corresponding changes in the level of prices for goods.

Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Keskinocak, Pinar; Committee Co-Chair: Vande Vate, John; Committee Member: Ferguson, Mark; Committee Member: Griffin, Paul; Committee Member: Swann, Julie. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.) -- University of Maryland, College Park, 2006.
Thesis research directed by: Business and Management. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

This thesis explores Centralised Demand Information Sharing (CDIS) in supply chains. CDIS is an information sharing approach where supply chain members forecast based on the downstream member’s demand. The Bullwhip Effect is a demand variance amplification phenomenon: as the demand moves upstream in supply chains, its variability increases. Many papers in the literature show that, if supply chain members forecast using the less variable downstream member’s demand, this amplification can be reduced leading to a reduction in inventory cost. These papers, using strict model assumptions, discuss three demand information sharing approaches: No Information Sharing (NIS), Downstream Demand Inference (DDI) and Demand Information Sharing (DIS). The mathematical analysis in this stream of research is restricted to the Minimum Mean Squared Error (MMSE) forecasting method. A major motivation for this PhD research is to improve the above approaches, and assess those using less restrictive supply chain assumptions. In this research, apart from using the MMSE forecasting method, we also utilise two non-optimal forecasting methods, Simple Moving Averages (SMA) and Single Exponential Smoothing (SES). The reason for their inclusion is the empirical evidence of their high usage, familiarity and satisfaction in practice. We first fill some gaps in the literature by extending results on upstream demand translation for ARMA (p, q) processes to SMA and SES. Then, by using less restrictive assumptions, we show that the DDI approach is not feasible, while the NIS and DIS approaches can be improved. The two new improved approaches are No Information Sharing – Estimation (NIS-Est) and Centralised Demand Information Sharing (CDIS). It is argued in this thesis that if the supply chain strategy is not to share demand information, NIS-Est results in less inventory cost than NIS for an Order Up To policy. On the other hand, if the strategy is to share demand information, the CDIS approach may be used, resulting in lower inventory cost than DIS. These new approaches are then compared to the traditional approaches on theoretically generated data. NIS-Est improves on NIS, while CDIS improves on the DIS approach in terms of the bullwhip ratio, forecast error (as measured by Mean Squared Error), inventory holding and inventory cost. The results of simulation show that the performance of CDIS is the best among all four approaches in terms of these performance metrics. Finally, the empirical validity of the new approaches is assessed on weekly sales data of a European superstore. Empirical findings and theoretical results are consistent regarding the performance of CDIS. Thus, this research concludes that the inventory cost of an upstream member is reduced when their forecasts are based on a Centralised Demand Information Sharing (CDIS) approach.

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2008.
"June 2008."
Includes bibliographical references (leaves 68-71).
Sales and operational planning that incorporates unconstrained demand forecasts has been expected to improve long term corporate profitability. Companies are considering such unconstrained demand forecasts in their decisions on investment in supply chain resources. However, demand forecasts are often associated with uncertainty. This research applies Monte Carlo simulation, value at risk and gain curve analysis, and real option analysis to investigate how the uncertainty of demands affects supply chain planning in order to make better supply chain investment decisions. This analytical framework was used to analyze the ocean shipping plans and inland trucking arrangements for Chiquita. Demands for Product A and front haul over a six-year period were simulated based upon forecasted distributions. The net income, revenue and costs as affected by ocean shipping plans were obtained by inputting the simulated demands to ocean shipping models. The major decision for Chiquita is whether to charter one large ship or two ships which provide approximately equivalent capacity. A large ship would save fuel costs. The plans for two smaller ships have the flexibility of using one ship only if future demand or price reactions warrant it. Using the analytical framework, a plan for two smaller ships is superior to that for one large ship because of significant real option value, particularly in the event of increases in fuel costs in the future. Chiquita's current inland trucking model, a mixed arrangement with a dedicated fleet and common carriers, seems to offer a good solution for the future needs. A model provided in this research offers a simple method to optimize the size of the dedicated fleet.
by Yanfeng Anna Huang.
M.Eng.in Logistics

The well-known "law of supply and demand" says that an increase in the price of a commodity leads to a decrease in the aggregate demand for this commodity and an increase in aggregate supply. There is, however, no theoretical foundation for this "law". Empirical evidence, on the other hand, should be interpreted with care. If one estimates the parameters of certain functional forms for demand and supply functions, then the results may simply be consequences of the parametric assumptions made in estimation. The first chapter of the thesis discusses the implications of the assumption of profit and utility maximisation for the properties of demand and supply functions. It explains why economic rationality on the microlevel does not, in general, lead to macroeconomic regularities and suggests replacing the consumption sector of the neoclassical equilibrium model by a large population of individually small consumers. Such a population will be explored in the second chapter. The chapter is a direct outgrowth of a basic contribution by W. Hildenbrand: "On the Law of Demand", Econometrica 1983. In W. Hildenbrand's model the market demand function is defined by integrating an individual demand function with respect to an exogenously given income distribution. We build into the model an individual labour supply function and then compare the matrix of aggregate income effects studied by W. Hildenbrand with that obtained by integrating the individual demand function with respect to a distribution of wage rates. The empirical part of the thesis analyses the labour supply and earnings data in the U.K. Family Expenditure Survey 1970-85. Using non- parametric smoothing methods, the elasticity of labour supply with respect to the wage rate is estimated for several groups of workers. The estimations for full-time workers confirm the famous "downward sloping" labour supply function. The estimated elasticities for the entire population of workers for the years 1970-85 have the mean value 0.2 and the standard deviation 0.02.

Labour market is a system of economic instruments, norms and institutions that establish the link between firms and is influenced by supply and demand price of labor. The most important element of the labor market is the demand for labor, which is determined by the number and structure of employment, volume of means of subsistence, are used to attract the workforce. Labor supply is the need of different groups of the working age population in receipt of employment. Labor demand reflects the need for a certain amount of economy workers on any given time.

Submitted by Guilherme Hideo Assaoka Hossaka (ghossaka@gmail.com) on 2018-09-07T17:43:58Z No. of bitstreams: 1 Stochastic_Supply_Curves_and_Liquidity_Costs.pdf: 6114705 bytes, checksum: 383773b2814d582892c750a566229869 (MD5)
Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2018-09-18T13:52:02Z (GMT) No. of bitstreams: 1 Stochastic_Supply_Curves_and_Liquidity_Costs.pdf: 6114705 bytes, checksum: 383773b2814d582892c750a566229869 (MD5)
Made available in DSpace on 2018-09-26T20:00:18Z (GMT). No. of bitstreams: 1 Stochastic_Supply_Curves_and_Liquidity_Costs.pdf: 6114705 bytes, en checksum: 383773b2814d582892c750a566229869 (MD5) Previous issue date: 2018-06-26
Market Liquidity is characterized by the easiness and freedom to trade assets at desired volumes and for prices perceived as representative of their values. When there is a scarcity of bid and ask offers at those terms, traders face the so called Market Liquidity Risk and they must offer concessions on their original offers, leading to additional costs. Approaches to model this phenomena exist in broad variety but a common component of most Market Liquidity models is an instantaneous cost component, also known as transaction/execution costs or realized/instantaneous impact. This element, here the Liquidity Cost, gives the actual trading prices faced by a trader, frequently a deviation from the unobservable “true price”, normally represented as a GBM with the mid-price as a proxy for modeling purposes. Although it is clear that Liquidity Costs are a relevant aspect of Market Liquidity Risk and it is present in many models, it is relegated to a more simplistic treatment, being though as well-behaved, deterministic, smooth and static. The main point of this work is to follow a different approach by evaluating Liquidity Costs at a microstructural level by estimating the Stochastic Supply Curve from C¸ etin-Jarrow-Protter Model for Brazilian equities. To do so, high-frequency-data from B3’s ftp is used and to build Limit Order Books for several stocks at intraday periods. The empirical findings support the existence of non-trivial Stochastic Supply Curves as a representation for Liquidity Costs in several equities on Brazilian Markets. Additionally, there is evidence that Liquidity Costs may behave in contrast with some of the literature, being stochastic with time-varying functional representations on the LOB and with liquidity parameters that could be represented as mean-reverting stochastic process.

There have been widespread reports of an impending teacher shortage crisis in the U.S. for more than 30 years. In the U.S., there are claims of a widespread national shortage while research indicates teacher shortages are specific to certain subjects and schools. Part of the reason for the conflicting accounts is how shortage is identified and what information is used to assess it. In this study, I test whether a uniform teacher shortage exists across the state of Arkansas. I hypothesize that, rather than a universal shortage, teacher shortages are more likely to occur in certain regions and subjects. I examine the characteristics of districts with the most favorable teaching supply and those with the greatest teaching need using descriptive and multivariate analysis of data collected from district surveys along with administrative data. In this study, “supply” is defined as the ratio of applications to vacancies and “need” is defined as the ratio of vacancies to full-time equivalent (FTE) certified classroom teachers. This is the third study to use applicants to identify teacher supply, and the first to assess teacher need or shortages in this way. Results indicate teacher supply and need are unequally distributed across the state; there is no uniform teacher shortage statewide. Regarding teacher supply, I find district size, region, and urbanicity appear to drive supply. Teacher supply is most favorable for large districts with student enrollments greater than 3,500, districts in the Northwest, and suburban and city districts. Regarding teacher need, I find urbanicity and region contribute most to need and the need appears greatest for districts in cities, and districts in the Central and Southeast regions. Teacher need does not appear to be significantly influenced by district educational success, teacher salary, or district growth. Looking at the relationship between teacher supply and need, I find three clear relationships. In the Central and Southeast regions, there is lower teacher supply and greater teacher need. In urban districts, there is both greater teacher supply and need. In higher poverty districts, there is significantly less teacher supply and more teacher need.

A presente dissertação tem como principal objetivo a conceituação e apresentação das metodologias básicas de previsão de demanda e, a partir de um estudo de caso, a seleção da metodologia mais adequada e sua respectiva implantação. No primeiro capítulo é apresentada, além da importância do referido tema, a empresa selecionada para aplicação dos conceitos levantados, com a descrição de seus principais processos internos. No segundo capítulo foram abordados os conceitos de previsão de demanda e uma revisão dos principais modelos existentes. No capítulo seguinte, o problema que deverá ser tratado com a metodologia proposta é apresentado. Neste momento a metodologia conceituada é aplicada, através da seleção do método de previsão mais adequado ao caso estudado e respectiva modelagem, buscando melhorias em relação aos métodos de previsão existentes na empresa. Neste processo de modelagem utilizou-se o software Forecast Pro, um dos mais conceituados aplicativos de previsão de demanda no mercado. Por fim, na conclusão, avalia-se o impacto das mudanças propostas nos resultados da empresa, principalmente o aumento da precisão da previsão da demanda e, conseqüentemente, redução dos custos de importação e dos índices de stockout.
The main objective of this dissertation is the presentation of basic forecasting methods and their implementation in a case study in supply chain. The first chapter points out the importance of forecasting in this context and describes the company selected for the case study and some of its internal processes that will be under scrutiny in the case study presented in this dissertation. The second chapter discusses the concepts and models of forecasting and reviews some of the major techniques in the field. In chapter three, standard forecasting techniques are apllied to real data (ten time series) from the company and select the most appropriate model in each case. Model adjustment is performed through the Forecast Pro software, one of the best-known products in the market. Chapter four contains the conclusions and the evaluation of the impacts of the proposed methodology on the company s results, especially the increased accuracy of forecasting and, consequently, the reduction in the import costs and stock out index.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2003.
Includes bibliographical references.
Essay One The Impact of Shortages on Push-Pull Production Systems This paper explores the impact of endogenous customer demand on supply chain instability. It investigates how a semiconductor manufacturer's hybrid push-pull production system responds to customer demand, when inventory availability influences demand. While customers' response to variable service level represents an important concern in industry with sizable impacts on company profitability, previous models exploring supply chain instability do not address it. This research incorporates customer response in two important ways. First, a negative feedback loop of lost sales captures the effect that an initial increase (decrease) in demand leads to a decrease (increase) in the manufacturer's service level, causing customer demand to decrease (increase). Second, a positive feedback loop of production push characterizes the manufacturer increase (decrease) in capacity utilization to respond to a surge (drop) in demand, leading to high (low) production volumes and service levels, and a further increase (decrease) in demand. The manufacturer's hybrid push-pull production system is very effective in meeting customer demand. Stockouts at different stages in the supply chain, however, can shift the operation mode of the system to a defacto push system. The shift to a push system decreases the manufacturers' service level and increases demand variability. The analysis suggests that the endogenous customer demand assumption influences the shifts in modes of operation through the lost sales and production push loops, leading to higher supply chain instability than when customer demand is modeled as exogenous.
(cont.) In addition, incorporating the endogenous demand assumption leads to a different inventory and utilization policies than the ones currently adopted. First, this research finds that supply chains can operate in multiple modes, due to demand instability. It also provides policies capable of mitigating the impact from shifts in operation modes. Second, it suggests that models investigating instability in supply chains assuming exogenous demand may underestimate the amplification in demand and the value of inventory buffers. The model analyzed in this paper gives insights into the costs of lean inventory strategies in the context of hybrid production systems. Essay Two Why do Shortages Inflate to Huge Bubbles? When demand exceeds supply, customers often hedge against shortages by placing multiple orders with multiple suppliers. The resulting demand bubble creates instability leading to excess capacity, excess inventory, low capacity utilization, and financial and reputation losses for suppliers and customers. This paper contributes to the understanding of demand bubbles caused by shortages by providing a comprehensive causal map of supplier-customer relationships and a formal mathematical model of a subset of those relationships. It provides closed form solutions for supply chain dynamics when supplier capacity is fixed and simulation analysis when it is flexible. Sensitivity analysis provides a deeper understanding of structures and decision rules that contribute to bubbles and suggests policies for improvement. For instance, the ability to quickly build capacity can reduce bubble size ...
by Paulo M. Gonçalves.
Ph.D.

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 80).
This paper attempts to provide a solution to a problem facing many multinational firms: the lack of an accessible and comprehensive database for up-to-date component part forecasts. We consider this problem in the context of ABB BU DMPE. After considering various requirements and constraints regarding the consolidation of forecasting information, we propose a novel combination of standardized process and the use of certain IT tools as a first step. After a test run, we discovered that consolidation of forecasting information increases transparency within the supply chain. As a corollary result of our pilot program, we propose that prior to any attempt at consolidation, enforcement of a standardized form and method of forecasting at the local level.
by Esther Lee.
M.B.A.
S.M.

A well-known concept, both in practice and in literature is the logistics market. This market is a place where shippers’ demand for logistics services meets Logistics Service Providers’ (LSPs’) supply of such services. Although this market has been given much attention in previous research, focus has been on shippers, while the LSP perspective has to a large extent been neglected. Several logistics related trends indicate that there is an increasing need for strong relationships between LSPs and supply chains, and one such trend is the “greening” of companies and supply chains. Although it is widely recognised that transports and  logistics are a major cause of greenhouse gas emissions, environmental logistics literature has only focused on the interaction between LSPs and their customers to a very limited extent. This is despite the fact that LSPs could include so-called green categories in their offerings, just as shippers could include green categories in their demands and that this interaction could in turn contribute to a decrease of greenhouse gas emissions. The purpose of this thesis is to describe the extent to which green categories are taken into account in the logistics market and suggest explanations. This includes identifying those green categories that are relevant for the logistics market, as well as a description of matches and mismatches with regard to these green categories. The matches and mismatches are studied from both a general market perspective and a relationship perspective. Initial explanations for the matches and mismatches in the relationship perspective contribute to the final part of the purpose. There are two basic theoretical starting-points in this thesis. Firstly, it is recognised that the logistics market is important to the purpose and different ways to view this market are therefore discussed. Secondly, general environmental logistics literature provides a basis for the research into green categories that can be offered or demanded on the logistics market. In the exploratoryresearch conducted for the thesis, the insights from literature are combined with empirical datafrom a survey, a homepage scan and four case studies of buyer-supplier relationships. One main contribution of this thesis is the large number of green categories that are identified as relevant for LSPs and shippers on the logistics market. These green categories range from environmental management systems, vehicle technologies and CO2 reports, to reviews of sustainability reports, relationship specific green projects and general desires among shippers to decrease CO2 emissions. A comparison of the supply of and demand for the green categories indicates that from a general market perspective, there appear to be clear mismatches between green supply and green demand. The same comparison made from a relationship perspective also indicates severalmismatches between green supply and green demand, but the buyer-supplier relationships studied show matches between green offerings and green demands to a greater extent than the market perspective does. Interestingly, the LSPs seem to include more in their offerings than the shippers appear to include in their demands for almost all mismatches in both the market perspective and the relationship perspective. Seven propositions are made to account for the matches and mismatches between green categories in buyer-supplier relationships. Three of these propositions are related to the characteristics of those green categories that are found in the relationships. It is suggested that the tangibility level of green categories influences the occurrence of matches and mismatches in the relationships and the more tangible a green category is, the higher is the likelihood of a match between supply and demand in that relationship. The opposite is also suggested, as well as the idea that the more relationship specific green categories are, the fewer the mismatches that appear in that relationship. The remaining four propositions relate to the potential connection between the type of relationship between LSPs and shippers and green matches and mismatches in their relationships. It is suggested that the closer a business relationship is, 1) the greater the number of green categories it has 2) the better green categories are communicated 3) the greater the number of matches compared to mismatches of green categories and 4) the higher the level of green category collaboration is.

China has experienced incredible growth in the number of nongovernmental organizations (NGO) that occupy civil society. These organizations came forth at a time of rapid economic and political change. Instead of being given a supportive legal path for their work, NGOs have had to navigate the supply and demand factors in their specific situation in order to flourish. The demand side factors chiefly consist of matters pertaining to the need an NGO is meeting; and supply side factors pertain to an NGO's ability to create infrastructure to support their organization, including both the space in society to function and the processes necessary to fund their operation. By understanding the supply and demand side factors of the third sector, NGOs are able to achieve effectiveness in a variety of different capacities. In the current regulatory framework, many of these capacities are not entirely legal, but NGOs continue to find ways to make these arrangements work. Intermediary NGOs are a special type of NGO that positions itself to benefit both the donor and the beneficiary and help both overcome some of the challenges presented by the difficult regulatory environment. In doing this, intermediary NGOs fulfill a special role in meeting supply and demand in the third sector and can propose many useful solutions for philanthropy in China today.

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 52-53).
While festivals bring a reason to cheer for everyone, businesses dealing with a spike in demand for perishables may have to live with the misery of lost sales and/or expired items. In the case of the dairy industry that deals with liquid milk, both raw material, and finished goods are perishable, which implies that merely stockpiling inventory of either item, without paying attention to potential inventory losses, cannot be an optimal strategy. In developing countries, the supplier base for perishables like milk, fruits, vegetables, flowers, etc. mostly comprise of small farmers instead of corporate/professional agencies, thus leading to supply variability. During special occasions like festivals, as individuals set aside more of the raw material for their own consumption, we encounter a reduction in supply. Around the same time, we notice a spike in customer demand, leading to a demand-supply mismatch. Companies dealing with perishables need an analytical approach to manage this.
In this thesis, we present a framework to address this problem of intermittent demand-supply mismatch using a 3-stage stochastic optimization model. We decide on the sourcing targets, the production plans based on supply realized, and finally, the dispatch plan based on orders received. As a case study, we analyze the operations and data from a private dairy company in eastern India, to understand the research problem and the applicability of the resulting model. We notice the impact of demand spikes and supply reduction in two areas: we increase supply targets in the periods preceding the demand spike; and we increase supply targets in periods when supply is expected to decrease, while demand is as usual. When there are multiple festival days within the time series, the compounding of impact depends on the sequencing of the events.
Finally, when we introduce the realistic constraint that the supply target needs to be constant throughout the time series, we see a degradation in the profitability, as we need to tradeoff between lost sales and wasted products. While the focus of this case study is the dairy industry, the conclusions from this research are broadly applicable to other industries dealing with perishables.
by Vishwanathan Parameshwaran lyer Nurani.
M. Eng. in Supply Chain Management
M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program

We analyze issues arising from demand management in decentralized decision-making environments. We consider logistics systems and supply chains, where companies' operations are handled with independent entities whose decisions affect the performance of the overall system. In the first study, we focus on a logistics system in the sea cargo industry, where demand is booked by independent sales agents, and the agents' capacity limits and sales incentives are determined by a central headquarters. We develop models for the central headquarters to analyze and optimize capacity allocation and sales incentives to improve the performance of the decentralized system. We use network flow problems to incorporate agent behavior in our models, and we link these individual problems through an overall optimization problem that determines the capacity limits. We prove a worst-case bound on the decentralized system performance and show that the choice of sales incentive impacts the performance. In the second study, we focus on supply chains in the automotive industry, where decentralization occurs as a result of the non-direct sales channels of the auto manufacturers. Auto manufacturers can affect their demand through sales promotions. We use a game theoretical model to examine the impact of retailer incentive and customer rebate promotions on the manufacturer's pricing and the retailer's ordering/sales decisions. We consider several models with different demand characteristics and information asymmetry between the manufacturer and a price discriminating retailer. We characterize the subgame-perfect Nash equilibrium decisions and determine which promotion would benefit the manufacturer under which market conditions. We find that the retailer incentives are preferred when demand is known. On the other hand, when demand is highly uncertain the manufacturer is better off with customer rebates. We extend this research by analyzing a competitive setting with two manufacturers and two retailers, where the manufacturers' promotions vary between retailer incentives and customer rebates. We find an equilibrium outcome where customer rebates reduce the competitor's profits to zero. We observe in numerical examples that the manufacturers are able to increase their sales and profits with retailer incentives, although this can be at the expense of the retailers' profits under some situations.

Indigenous tourism is an expansive sector in the growing tourism industry. The Sami people living in Sápmi in northern Europe have started to engage in tourism, particularly in view of the rationalised and modernised methods of reindeer herding. Sami tourism offers job opportunities and enables the spreading of information. On the other hand, Sami tourism may jeopardise the indigenous culture and harm the sensitive environment in which the Sami live. The aim of this thesis is to analyse the supply and demand of Sami tourism in northern Sweden. This is presented in four articles. The first article analyses the potential of the emerging Sami tourism in Sweden, with special emphasis on the access to Sami tourism products. The study shows that there is a growing supply of tourism activities related to the Swedish Sami. The development of tourism is, however, restricted by factors such as the peripheral location and the lack of traditions of entrepreneurship. The second article analyse which factors influence tourists when they make their decisions about Sami tourism. In the article the respondents are requested to answer a number of hypothetical questions, ranking their preferences regarding supply, price and access. The study indicates that tourism related to the Sami and Sami culture has a considerable future potential, but also that there is a gap between supply and demand. In the third article the analysis shows that the festival in Jokkmokk, thanks to continuously added attractions, has been able to retain a rather high level of popularity, despite its peripheral location. Finally, the fourth article analyses to what extent the winter festival in Jokkmokk is a genuinely indigenous event, and to what extent it is staged. It is argued that the indigenous culture presented at the festival and in media is highly staged, although backstage experiences are available for the Sami and for the tourists who show a special interest.

The threat of climate change has led to many countries and regions adopting renewable targets. Scotland's is one of the most ambitious, with an aim to generate the equivalent to 100% of its electricity needs from renewable sources by 2020. Scotland has a very large renewable resource, primarily consisting of offshore and onshore wind, tidal stream, wave and hydro power; all of which are characterised by having variable output. Over a long period, such as a year, variability in renewable generation will average out and may meet or exceed total annual demand. This thesis investigates whether matching of demand and generation is possible within a timescale meaningful to electricity system users; that is whether renewable generation can meet electricity demand in any given hour. This was established by using historic data to create an hourly generation hindcast of Scotland's renewable generation over a 30 year climate “normal” period. These outputs are then compared to a hindcast of hourly demand based on observations over the most recent few years. The results demonstrated that it is possible for Scotland to rely entirely upon renewable generation to fulfil demand in any hour of the 30 year hindcast. However, it appears that the renewable capacity and storage currently built or within the Scottish planning system is only sufficient to match demand in 65% of the hours within the hindcast. The hindcast allows judgements to be made as to how 100% of demand could be met most effectively and provides the basis of a coherent planning strategy, with security of supply at its centre. Further wave and tidal stream capacity is shown to be of higher value than additional wind power but in the latter case, addressing the geographical diversity of wind power can enable maximise phasing between sites to increase the security of supply. Importantly this work provides a means of informing decision making about where best to develop wind, wave and tidal resources and what additional storage may be required in order to provide 100% security of supply. The results are also of particular importance to Scotland's renewable generation strategy in the case of assessing where new on- and off-shore wind farms should be developed, as wind is set to dominate Scotland's renewable portfolio for the foreseeable future.

MBA Professional Report
In light of the Navy's transformation plan, advanced business education is increasing in importance. As part of the Navy's Sea Power 21 strategy, Sea Enterprise encourages Naval Aviation to steer historical management practices towards better business practices. As pilots and Naval Flight Officers evolve from Mission Commander to Commanding Officer, they must be equipped with requisite business skill sets to engage the challenge of balancing aircraft modernization with current readiness. This project analyzes the supply and demand for postgraduate business education to determine how prepared Naval Aviation is to achieve long-term transformation objectives. The results show that 25 percent of all aviation officers (O-1 to O- 6) have a graduate business degree; 17 percent of Commanding Officers with advanced degrees have a business specialization; and 2.5 percent of aviation officer billets require a postgraduate business degree. Recommendations to better prepare the aviation community for the Sea Enterprise environment include: (1) Early emphasis of graduate business education, (2) Promote advanced business education as a major career milestone, (3) Tie first shore tour assignments to graduate business education, and (4) Increase the overall billet requirement for advanced business degrees. These improvements may greatly enhance the Navy's efforts towards achieving its transformation goals.

Enligt Carlsson och Rönnqvist (2005) och Frayret et al. (2007) blir det allt viktigare att arbeta med supply chain management inom trävaruindustrin. En utmaning är att finna ett arbetssätt för att hantera variationen i kundens efterfrågan. Idag hanteras variationen oftast genom onödigt stor lagerhållning (Lee et al., 1997b; So och Zheng, 2003).                                                                                 Syftet med studien är att utreda påverkande faktorer som bidrar till en varierande efterfrågan inom trävaruindustrin samt föreslå hur uppkomsten av dessa kan undvikas. För att svara på syftet har tre frågeställningar tagits fram och en fallstudie genomfördes på ett hyvleri. Informationsinsamlingen har skett genom intervjuer av anställda från olika avdelningar samt litteraturstudier. Studien visar att det finns flera utmaningar när det är stor variation på efterfrågan såsom brist på tillgång till prognoser och kommunikationsbrist med kunder. Det medför att planeringen av råvaruåtgången försvåras och det leder till svårigheter att uppnå leveransprecision.   Slutsatsen visar att de påverkande faktorer som bidrar till en varierad efterfrågan är prisvariationer, orderstorlek och orderfrekvens. Prisvariationer kan undvikas genom ABC-indelning av produkterna utifrån produktefterfrågan. Prognoser underlättar uppskattning av efterfrågan men för ett fungerande prognosarbete krävs samsyn, nära relation samt god kommunikation mellan kund och leverantör. Problem med orderstorlek och orderfrekvens kan reduceras om kunden får avgöra orderstorleken utan att specifika krav måste uppfyllas. Slutsatsen visar även att faktorer såsom väderlek, trender, mode, helgdagar och rotavdragets eventuella försvinnande påverkar variationen i efterfrågan.
According to Carlsson & Rönnqvist (2005) and Frayret et al. (2007) supply chain management in the wood products industry is getting more important. One of the challenges is to find a way to deal with customer’s fluctuating demand. Traditional solution to handle fluctuating demand is large inventory (Lee et al., 1997b; So & Zheng, 2003), which causes often high inventory cost for effective supply chain management.   The aim of the study is to investigate factors that affect a fluctuating demand in the wood products industry and suggest how to reduce the fluctuating demand through related factors analysis in order to improve Demand-Supply chain management efficiency. For this pursose, a case study on a planing is conducted. To collect data, interviews with employees from different departments have been made along with literature studies. The study presents that there are many challenges for the fluctuation demand such as lack of forecasts and lack of communication with customers. This, in turn, will cause problems with planning of the raw material as well as difficulties to deliver the goods on time.   The conclusion shows that the factors affecting a fluctuating demand are price variations, the orders batch size and order frequency. Price variations can be improved by ABC classification of the products by product demand. Forecasts will make the estimation of demand easier, although, in order to use forecasts properly a joint vision, close relationships and good communication with customer and supplier is required. Problems regarding batch size and order frequency can be reduced if the customer is allowed to decide the batch size with no specific requirements. The study also shows that factors such as weather, trends, fashion, holidays and disappearance of ROT work affects the fluctuating demand.

The core of this thesis comprises three previous published reports ‐ Profiling the Profession: a survey of archaeological jobs in the UK (Aitchison 1999), Archaeology Labour Market Intelligence: Profiling the Profession 200203 (Aitchison & Edwards 2003) and Archaeology Labour Market Intelligence: Profiling the Profession 200708 (Aitchison & Edwards 2008). These volumes are the only comprehensive reviews of the labour market within the archaeological sector in the UK, examining who works in all sectors of archaeology, what qualifications they hold, how they are rewarded and how they are trained. These three surveys have established a corpus of time-series datasets which demonstrate how archaeological practice and employment have evolved in the UK over the decade to 2008 and the onset of the global economic crisis in that year. The thesis contextualises these data‐rich reports with a historical and analytical account of how employment in archaeology grew from the late nineteenth century until 1990, and then examines the drivers of demand for services that lead to archaeological employment in the United Kingdom over the 20 years from 1990‐2010, and how this demand was met. Until 1990, archaeology was primarily a state‐provided or state‐sponsored activity. The sector's funding base transformed in the 1990s to become primarily reliant on private sector monies and the effects upon employment within the sector have been of the sectoral reaction to adopt an enterprise‐focussed model for delivery have been considerable. The number of people employed in archaeology grew very rapidly over this period (by approximately 4.5% per annum), with the expansion of applied, commercial archaeology representing the majority of this growth. These individuals are very highly academically qualified, but not very well rewarded financially. In order to fully explore the central issues, historical patterns and precedents are examined, focussing on particular strands of activity in detail, using case studies of organisations and particular archaeological projects.