The Experts below are selected from a list of 264 Experts worldwide ranked by ideXlab platform
Raul G Sanchis - One of the best experts on this subject based on the ideXlab platform.
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consumer s response to Price Distribution and σ overload under time allocation
Journal of Computational and Applied Mathematics, 2016Co-Authors: Francisco Alvarez, Raul G SanchisAbstract:It has been recently suggested that both the number of options considered by consumers and their satisfaction when shopping respond to changes in the mean and spread of market Prices. A structured analysis of those responses is provided in this paper. A new adverse effect related with consumer's welfare is presented here, namely a consumer that searches exhaustively among all market options-called maximizer-experiences welfare loss when the dispersion of Prices is too high. In fact, her welfare exhibits an inverted- U shape with respect to the standard deviation ? of Prices so that an increase in Price spread produces more welfare for small values of ? but it has a negative effect for larger values of ? . This new phenomenon is termed ? -overload. It is also shown that a consumer that is content with shopping from a reduced sample of options-a satisficer-avoids ? -overload by adapting her search behavior to the increase in spread. A quantitative assessment of consumer's behavior and welfare with respect to changes in the mean and dispersion of Prices under different scenarios is also provided.
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choice overload satisficing behavior and Price Distribution in a time allocation model
Abstract and Applied Analysis, 2014Co-Authors: Francisco Alvarez, Raul G SanchisAbstract:Recent psychological research indicates that consumers that search exhaustively for the best option of a market product—known as maximizers—eventually feel worse than consumers who just look for something good enough—called satisficers. We formulate a time allocation model to explore the relationship between different Distributions of Prices of the product and the satisficing behavior and the related welfare of the consumer. We show numerically that, as the number of options becomes large, the maximizing behavior produces less and less welfare and eventually leads to choice paralysis—these are effects of choice overload—whereas satisficing conducts entail higher levels of satisfaction and do not end up in paralysis. For different Price Distributions, we provide consistent evidence that maximizers are better off for a low number of options, whereas satisficers are better off for a sufficiently large number of options. We also show how the optimal satisficing behavior is affected when the underlying Price Distribution varies. We provide evidence that the mean and the dispersion of a symmetric Distribution of Prices—but not the shape of the Distribution—condition the satisficing behavior of consumers. We also show that this need not be the case for asymmetric Distributions.
Francisco Alvarez - One of the best experts on this subject based on the ideXlab platform.
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consumer s response to Price Distribution and σ overload under time allocation
Journal of Computational and Applied Mathematics, 2016Co-Authors: Francisco Alvarez, Raul G SanchisAbstract:It has been recently suggested that both the number of options considered by consumers and their satisfaction when shopping respond to changes in the mean and spread of market Prices. A structured analysis of those responses is provided in this paper. A new adverse effect related with consumer's welfare is presented here, namely a consumer that searches exhaustively among all market options-called maximizer-experiences welfare loss when the dispersion of Prices is too high. In fact, her welfare exhibits an inverted- U shape with respect to the standard deviation ? of Prices so that an increase in Price spread produces more welfare for small values of ? but it has a negative effect for larger values of ? . This new phenomenon is termed ? -overload. It is also shown that a consumer that is content with shopping from a reduced sample of options-a satisficer-avoids ? -overload by adapting her search behavior to the increase in spread. A quantitative assessment of consumer's behavior and welfare with respect to changes in the mean and dispersion of Prices under different scenarios is also provided.
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choice overload satisficing behavior and Price Distribution in a time allocation model
Abstract and Applied Analysis, 2014Co-Authors: Francisco Alvarez, Raul G SanchisAbstract:Recent psychological research indicates that consumers that search exhaustively for the best option of a market product—known as maximizers—eventually feel worse than consumers who just look for something good enough—called satisficers. We formulate a time allocation model to explore the relationship between different Distributions of Prices of the product and the satisficing behavior and the related welfare of the consumer. We show numerically that, as the number of options becomes large, the maximizing behavior produces less and less welfare and eventually leads to choice paralysis—these are effects of choice overload—whereas satisficing conducts entail higher levels of satisfaction and do not end up in paralysis. For different Price Distributions, we provide consistent evidence that maximizers are better off for a low number of options, whereas satisficers are better off for a sufficiently large number of options. We also show how the optimal satisficing behavior is affected when the underlying Price Distribution varies. We provide evidence that the mean and the dispersion of a symmetric Distribution of Prices—but not the shape of the Distribution—condition the satisficing behavior of consumers. We also show that this need not be the case for asymmetric Distributions.
Xin Zhao - One of the best experts on this subject based on the ideXlab platform.
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Quantifying breakeven Price Distributions in stochastic techno-economic analysis
Applied Energy, 2016Co-Authors: Xin Zhao, Wallace E. TynerAbstract:Techno-economic analysis (TEA) is a well-established modeling process for evaluating the economic feasibility of emerging technologies. Most previous TEA studies focused on creating reliable cost estimates but returned deterministic net present values (NPV) and deterministic breakeven Prices which cannot convey the considerable uncertainties embedded in important techno-economic variables. This study employs stochastic techno-economic analysis in which Monte Carlo simulation is incorporated into traditional TEA. The Distributions of NPV and breakeven Price are obtained. A case of cellulosic biofuel production from fast pyrolysis and hydroprocessing pathway is used to illustrate the method of modeling stochastic TEA and quantifying the breakeven Price Distribution. The input uncertainties are translated to outputs so that the probability density Distribution of both NPV and breakeven Price are derived. Two methods, a mathematical method and a programming method, are developed to quantify breakeven Price Distribution in a way that can consider future Price trend and uncertainty. Two scenarios are analyzed, one assuming constant real future output Prices, and the other assuming that future Prices follow an increasing trend with stochastic disturbances. It is demonstrated that the breakeven Price Distributions derived using the developed methods are consistent with the corresponding NPV Distributions regarding the percentile value and the probability of gain/loss. The results demonstrate how breakeven Price Distributions communicate risks and uncertainties more effectively than NPV Distributions. The stochastic TEA and the methods of creating breakeven Price Distribution can be applied to evaluating other technologies.
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Quantifying Breakeven Price Distributions in Stochastic Techno-Economic Analysis — A Case of Cellulosic Biofuel Production from Fast Pyrolysis and Hydroprocessing Pathway
2016Co-Authors: Xin Zhao, Yao Guolin, Tyner WallaceAbstract:Techno-economic analysis (TEA) is a well-established modeling process in which benefit-cost analysis (BCA) is used to evaluate the economic feasibility of emerging technologies. Most previous TEA studies focused on creating reliable cost estimates but returned deterministic net present values (NPV) and deterministic breakeven Prices. Nevertheless, the deterministic results cannot convey the considerable uncertainties embedded in techno-economic variables such as capital investment, conversion technology yield, and output Prices. We obtain Distributions of NPV, IRR, and breakeven Price. The breakeven Price is the most important indicator in TEA because it is independent of scale and communicates results effectively. The deterministic breakeven Price is the Price for which there is a 50 percent probability of earning more or less than the stipulated rate of return. For an investment under relatively high uncertainty, it is unlikely that investors would provide financing to a project with a 50 percent probability of loss. The point estimate breakeven Price, therefore, does not represent the threshold under which investment would occur. In this study, we introduce the stochastic techno-economic analysis in which we incorporate Monte Carlo simulation into traditional TEA. A case of cellulosic biofuel production from fast pyrolysis and hydroprocessing pathway is used to illustrate the method of modeling stochastic TEA and quantifying the breakeven Price Distribution. The input uncertainties are translated to outputs so that the probability density Distribution of both NPV and breakeven Price are derived. Two methods, a mathematical method and a programming method, are developed to quantify breakeven Price Distribution in a way that can consider future Price trend and uncertainty. We analyze two scenarios, one assuming constant real future output Prices, and the other assuming that future Prices follow an increasing trend with stochastic disturbances. We demonstrate that the breakeven Price Distributions derived using our methods are consistent with the corresponding NPV Distributions regarding the percentile value and the probability of gain/loss.
Deyi Xu - One of the best experts on this subject based on the ideXlab platform.
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modeling land Price Distribution using multifractal idw interpolation and fractal filtering method
Landscape and Urban Planning, 2013Co-Authors: Shougeng Hu, Qiuming Cheng, Le Wang, Deyi XuAbstract:Characterizing the spatial Distribution of urban land Price is essential for improving urban planning and management, as well as for effectively modeling and predicting changes in urban land use. Previous studies have shown that in using conventional geostatistics methods to characterize the local structure of land Price, there is controversy regarding the effectiveness of interpolation. In this paper, a recently developed Multifractal Inverse Distance Weighted (MIDW) interpolation method is applied to characterize the spatial structure of land Price, and a spectrum analysis method (S–A) based on a fractal filtering technique is applied to separate the singularity from the background of land Price Distribution; these methods are applied to a study site in the city of Wuhan (China). It is shown that the MIDW interpolation method is a valid and effective alternative for characterizing land Price Distribution by comparison with ordinary IDW and Kriging methods. Based on deviation and parameters, the results of the MIDW method not only fit better with the surveyed values, but they also incorporate both the singularity and spatial association in data interpolation. The singularity of land Price, which could be attributed to local special landscapes, such as the Yangtze River and East Lake, was successfully separated from its background by the S–A method. The background, which represents the overall spatial trend of land Price Distribution, was reclassified by the fractal concentration–area method. The derived singularity and background will better aid the decision-making process for urban planning.
Wallace E. Tyner - One of the best experts on this subject based on the ideXlab platform.
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Quantifying breakeven Price Distributions in stochastic techno-economic analysis
Applied Energy, 2016Co-Authors: Xin Zhao, Wallace E. TynerAbstract:Techno-economic analysis (TEA) is a well-established modeling process for evaluating the economic feasibility of emerging technologies. Most previous TEA studies focused on creating reliable cost estimates but returned deterministic net present values (NPV) and deterministic breakeven Prices which cannot convey the considerable uncertainties embedded in important techno-economic variables. This study employs stochastic techno-economic analysis in which Monte Carlo simulation is incorporated into traditional TEA. The Distributions of NPV and breakeven Price are obtained. A case of cellulosic biofuel production from fast pyrolysis and hydroprocessing pathway is used to illustrate the method of modeling stochastic TEA and quantifying the breakeven Price Distribution. The input uncertainties are translated to outputs so that the probability density Distribution of both NPV and breakeven Price are derived. Two methods, a mathematical method and a programming method, are developed to quantify breakeven Price Distribution in a way that can consider future Price trend and uncertainty. Two scenarios are analyzed, one assuming constant real future output Prices, and the other assuming that future Prices follow an increasing trend with stochastic disturbances. It is demonstrated that the breakeven Price Distributions derived using the developed methods are consistent with the corresponding NPV Distributions regarding the percentile value and the probability of gain/loss. The results demonstrate how breakeven Price Distributions communicate risks and uncertainties more effectively than NPV Distributions. The stochastic TEA and the methods of creating breakeven Price Distribution can be applied to evaluating other technologies.