973 resultados para Quantity-Discount


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We consider an economic order quantity model where the supplier offers an all-units quantity discount and a price sensitive customer demand. We compare a decentralized decision framework where selling price and replenishment policy are determined independently to simultaneous decision making. Constant and dynamic pricing are distinguished. We derive structural properties and develop algorithms that determine the optimal pricing and replenishment policy and show how quantity discounts not only influence the purchasing strategy but also the pricing policy. A sensitivity analysis indicates the impact of the fixed-holding cost ratio, the discount policy, and the customers' price sensitivity on the optimal decisions.

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This paper studies the issue of how traded quantities affect trade prices, which has been relatively unexplored in the trade literature. By reproducing previous literatures' regressions which are based on the general equilibrium trade theories, incorporating the role of traded quantities, this paper shows a possibility of prevalence of the second degree price discrimination (quantity discount) in international trade, rather than the pricing behaviour of the general equilibrium theories.

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ste trabalho objetiva identificar a percepção dos gestores de controladoria de indústrias sobre os aspectos estratégicos e econômicos da decisão de bonificação em quantidade de produto. A premissa é que os resultados econômicos gerados pela decisão de desconto no preço e de bonificação em quantidade de produto são iguais, considerando a mesma quantidade de produto entregue ao cliente. Com base no banco de dados da FIPECAFI- FEA-USP, analisaram-se 91 questionários encaminhados a controllers atuantes em diversos setores. Os resultados revelam: 1) um número muito significativo de empresas da amostra selecionada adota a bonificação em produtos; 2) a área comercial é a principal responsável por essa decisão; e 3) identificação da percepção dos controllers sobre aspectos decisórios de bonificação em quantidade de produtos.

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This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.

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In this paper I offer an 'integrating account' of singular causation, where the term 'integrating' refers to the following program for analysing causation. There are two intuitions about causation, both of which face serious counterexamples when used as the basis for an analysis of causation. The 'process' intuition, which says that causes and effects are linked by concrete processes, runs into trouble with cases of misconnections', where an event which serves to prevent another fails to do so on a particular occasion and yet the two events are linked by causal processes. The chance raising intuition, according to which causes raise the chance of their effects, easily accounts for misconnections but faces the problem of chance lowering causes, a problem easily accounted for by the process approach. The integrating program attempts to provide an analysis of singular causation by synthesising the two insights, so as to solve both problems. In this paper I show that extant versions of the integrating program due to Eells, Lewis, and Menzies fail to account for the chance-lowering counterexample. I offer a new diagnosis of the chance lowering case, and use that as a basis for an integrating account of causation which does solve both cases. In doing so, I accept various assumptions of the integrating program, in particular that there are no other problems with these two approaches. As an example of the process account, I focus on the recent CQ theory of Wesley Salmon (1997).

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A semi-empirical linear equation has been developed to optimise the amount of maltodextrin additive (DE 6) required to successfully spray dry a sugar-rich product on the basis of its composition. Based on spray drying experiments, drying index values for individual sugars (sucrose, glucose, frutose) and citric acid were determined, and us;ng these index values an equation for model mixtures of these components was established. This equation has been tested with two sugar-rich natural products, pineapple juice and honey. The relationship was found to be valid for these products.

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Methods We performed a detailed analysis of one 15q single nucleotide polymorphism (SNP) (rs16969968) with smoking behaviour and cancer risk in a total of 17 300 subjects from five LC studies and four upper aerodigestive tract (UADT) cancer studies. Results Subjects with one minor allele smoked on average 0.3 cigarettes per day (CPD) more, whereas subjects with the homozygous minor AA genotype smoked on average 1.2 CPD more than subjects with a GG genotype (P < 0.001). The variant was associated with heavy smoking (> 20 CPD) [odds ratio (OR) = 1.13, 95% confidence interval (CI) 0.96-1.34, P = 0.13 for heterozygotes and 1.81, 95% CI 1.39-2.35 for homozygotes, P < 0.0001]. The strong association between the variant and LC risk (OR = 1.30, 95% CI 1.23-1.38, P = 1 x 10(-18)), was virtually unchanged after adjusting for this smoking association (smoking adjusted OR = 1.27, 95% CI 1.19-1.35, P = 5 x 10(-13)). Furthermore, we found an association between the variant allele and an earlier age of LC onset (P = 0.02). The association was also noted in UADT cancers (OR = 1.08, 95% CI 1.01-1.15, P = 0.02). Genome wide association (GWA) analysis of over 300 000 SNPs on 11 219 subjects did not identify any additional variants related to smoking behaviour. Conclusions This study confirms the strong association between 15q gene variants and LC and shows an independent association with smoking quantity, as well as an association with UADT cancers.

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The theoretical framework that underpins this research study is based on the Prospect Theory formulated by Kahneman and Tversky, and Thaler's Mental Accounting Theory. The research aims to evaluate the consumers' behavior when different patterns of discount are offered (in percentage and absolute value and for larger and smaller discounts). Two experiments were conducted to explore these patterns of behavior and the results that were obtained supported the view that the framing effect was a common occurrence. The patterns of choice of individuals in a sample were found to be different due to changes in the ways discounts were offered. This can be explained by the various ways of presenting discount rates that had an impact on the influence of purchase intentions, recommendations and quality perception.

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This work focuses on the appraisal of public and environmental projects and, more specifically, on the calculation of the social discount rate (SDR) for this kind of very long-term investment projects. As a rule, we can state that the instantaneous discount rate must be equal to the hazard rate of the public good or to the mortality rate of the population that the project is intended to. The hazard can be due to technical failures of the system, but, in this paper, we are going to consider different independent variables that can cause the hazard. That is, we are going to consider a multivariate hazard rate. In our empirical application, the Spanish forest surface will be the system and the forest fire will be the fail that can be caused by several factors. The aim of this work is to integrate the different variables that produce the fail in the calculation of the SDR from a multivariate hazard rate approach.

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We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that the firms produce differentiated goods and that there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

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In this paper, we consider a Stackelberg duopoly competition with differentiated goods and with unknown costs. The firms' aim is to choose the output levels of their products according to the well-known concept of perfect Bayesian equilibrium. There is a firm ( F1 ) that chooses first the quantity 1 q of its good; the other firm ( F2 ) observes 1 q and then chooses the quantity 2 q of its good. We suppose that each firm has two different technologies, and uses one of them following a probability distribution. The use of either one or the other technology affects the unitary production cost. We show that there is exactly one perfect Bayesian equilibrium for this game. We analyse the advantages, for firms and for consumers, of using the technology with the highest production cost versus the one with the cheapest cost.

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We consider a quantity-setting duopoly model, and we study the decision to move first or second, by assuming that. the firms produce homogeneous goods and that. there is some demand uncertainty. The competitive phase consists of two periods, and in either period, the firms can make a production decision that is irreversible. As far as the firms are allowed to choose (non-cooperatively) the period they make the decision, we study the circumstances that favour sequential rather than simultaneous decisions.

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In this paper, we consider a Stackelberg duopoly competition with differentiated goods, linear and symmetric demand and with unknown costs. In our model, the two firms play a non-cooperative game with two stages: in a first stage, firm F 1 chooses the quantity, q 1, that is going to produce; in the second stage, firm F 2 observes the quantity q 1 produced by firm F 1 and chooses its own quantity q 2. Firms choose their output levels in order to maximise their profits. We suppose that each firm has two different technologies, and uses one of them following a certain probability distribution. The use of either one or the other technology affects the unitary production cost. We show that there is exactly one perfect Bayesian equilibrium for this game. We analyse the variations of the expected profits with the parameters of the model, namely with the parameters of the probability distributions, and with the parameters of the demand and differentiation.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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The monitoring data collected during tunnel excavation can be used in inverse analysis procedures in order to identify more realistic geomechanical parameters that can increase the knowledge about the interested formations. These more realistic parameters can be used in real time to adapt the project to the real structure in situ behaviour. However, monitoring plans are normally designed for safety assessment and not especially for the purpose of inverse analysis. In fact, there is a lack of knowledge about what types and quantity of measurements are needed to succeed in identifying the parameters of interest. Also, the optimisation algorithm chosen for the identification procedure may be important for this matter. In this work, this problem is addressed using a theoretical case with which a thorough parametric study was carried out using two optimisation algorithms based on different calculation paradigms, namely a conventional gradient-based algorithm and an evolution strategy algorithm. Calculations were carried for different sets of parameters to identify several combinations of types and amount of monitoring data. The results clearly show the high importance of the available monitoring data and the chosen algorithm for the success rate of the inverse analysis process.