Optimal price regulation in a growth model with monopolistic suppliers of intermediate goods

In this paper we investigate the trade-off faced by regulators who must set a price for an intermediate good somewhere between the marginal cost and the monopoly price. We utilize a growth model with monopolistic suppliers of intermediate goods. Investment in innovation is required to produce a new intermediate good. Marginal cost pricing deters innovation, while monopoly pricing maximizes innovation and economic growth at the cost of some static inefficiency. We demonstrate the existence of a second-best price above the marginal cost but below the monopoly price, which maximizes consumer welfare. Simulation results suggest that substantial reductions in consumption, production, growth, and welfare occur where regulators focus on static efficiency issues by setting prices at or near marginal cost.

Electricity market price spike forecast with data mining techniques

Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

Understanding consumer evaluation criteria for repurchase in a performing arts context

The purpose of this paper is to examine consumers' experience of a performing arts service to identify the predictors of audience behaviour especially as related to positive repurchase intention. Experiential service settings such as the performing arts have been cited in recent research as service contexts that may challenge current theory that repurchase intention is driven by service quality and customer satisfaction. It is posited that consumer emotions and the hedonic nature of the consumption experience may complicate the evaluation process to repurchase intention in a setting such as the performing arts. Qualitative semi-structured indepth interviews were undertaken of twenty-six performing arts consumers using a pool of questions and prompts developed from a review of the extant literature. Transcribed field notes were examined for key words and phrases and data was divided into the main emergent themes related to each of the questions and also coded for confirmation and is-confirmation of the extant literature constructs and relationships. The dimensions of service experience,price, service quality, target goal-directed emotions and non-target appraisal emotions were identified as driving repurchase intention in a performing arts setting. Customer satisfaction in this setting appears to result from emotional factors rather than expectancy dis-confirmation. This research supports the notion that an experiential consumption experience such as the performing arts will challenge the current theory of the drivers of repurchase intention and suggests that a more thorough large scale examination of these dimensions in this service setting is warranted.