Optimization and analysis of the profitability of tariff structures with two-part tariffs

Schlereth, Christian; Stepanchuk, Tanja; Skiera, Bernd

doi:10.1016/j.ejor.2010.03.038

Cited by 38 publications

(35 citation statements)

References 32 publications

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“…This exponential increase might explain why most studies consider only one or two pricing plans. Schlereth, Stepanchuk & Skiera (2010) show that simulated annealing reduces this shortcoming and can easily optimize four plans. Additionally, they show that two optional two-part pricing plans are frequently sufficient to skim the market.…”

Section: Counterfactual Simulationsmentioning

confidence: 98%

“…Furthermore, service providers frequently must choose a particular number of plans, which involves a trade-off between offering more plans to attain better market segmentation (Maskin & Riley, 1984;Murphy, 1977) and offering fewer plans to avoid confusing the consumers and minimize the administrative costs for managing the plans (Hui et al, 2007). Extant recommendations only apply to two-part pricing plans (e.g., Murphy, 1977;Schlereth et al, 2010).…”

Section: Comparison With Other Pricing Plansmentioning

confidence: 99%

“…Consequently, we have little knowledge about how pricing plans compare to one another, despite the great importance of such understanding for service providers that must determine which type and number of pricing plans to use. We follow Schlereth et al (2010) and develop a simulated annealing algorithm to optimize bucket pricing and three-part pricing plans. We then extend this application to compare their profitability.…”

Section: Counterfactual Simulationsmentioning

confidence: 99%

“…(13) is nonlinear and nonconvex, with many local maxima. We implemented and extensively tested various heuristic search methods; simulated annealing provides the best search performance (see also Schlereth et al, 2010). It randomly accepts solutions with a decreasing objective functional value and can thus overcome local maxima.…”

Section: Comparison Of Pricing Recommendations Across Different Servimentioning

confidence: 99%

See 3 more Smart Citations

Measurement of consumer preferences for bucket pricing plans with different service attributes

Schlereth

Skiera

2012

International Journal of Research in Marketing

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Section: Counterfactual Simulationsmentioning

confidence: 98%

Section: Comparison With Other Pricing Plansmentioning

confidence: 99%

Section: Counterfactual Simulationsmentioning

confidence: 99%

Section: Comparison Of Pricing Recommendations Across Different Servimentioning

confidence: 99%

See 2 more Smart Citations

Measurement of consumer preferences for bucket pricing plans with different service attributes

Schlereth

Skiera

2012

International Journal of Research in Marketing

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“…Because consumers' tariff choice affects their usage, the billing rate, and the company's profits, setting optimal prices is of great importance. Yet companies often experiment with different pricing schemes at great cost rather than make sound evidence-based decisions supported by market research (Essegaier, Gupta, and Zhang 2002;Schlereth, Stepanchuk, and Skiera 2010). Standard economic theory assumes that a consumer chooses a tariff that minimizes the billing rate given his expected usage (Brown and Sibley 1986).…”

Section: Introductionmentioning

confidence: 99%

Tariff-Specific Preferences and Their Influence on Price Sensitivity

Wołk

Skiera

2010

Bus Res

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Research on the capacity cost allocation and the electricity capacity price optimization method for a power system based on the BARY‐GA algorithm

Liu,

et al. 2023

Energy Science & Engineering

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Under the new power system, a high proportion of new energy is widely connected to the power grid, and it is necessary to increase investment in centralized and distributed energy storage, flexible resource regulation, and transmission and distribution grids, resulting in an increase in power system costs. The current electricity capacity price does not reflect the economic value of the added system adequately, and flexible capacity is needed to ensure the safety of the power grid under the new power system. In the context of the transformation of the new power system and investment function, it is increasingly difficult to recover the costs according to the traditional electricity price. It is necessary to establish a coordinated development mechanism for the electricity capacity price and the electricity price that recovers the fixed costs according to the investment function to ensure a reasonable return on investment in flexible resources and to provide effective investment signals. Therefore, this work first studied and proposed a mechanism for the formation of capacity and electricity prices based on the proportion of allowed income and fixed costs at different voltage levels and calculates the level of electricity capacity (demand) prices and electricity consumption prices. Then, using the BARY curve, genetic algorithm, and clustering of user load rates, a collaborative mechanism between the electricity capacity price and the electricity price was designed. With the goal of optimizing the electricity capacity price and considering constraints such as the flexibility and reliability of the new power system, the ratio of the capacity cost allocated to the electricity capacity price by voltage level users to the capacity cost allocated to the electricity price was calculated, and the optimal combination of electricity capacity price and electricity price for different load‐rate intervals was determined. Finally, the effectiveness of the model was verified through numerical simulations. On the basis of the investment characteristics of the new power system, suggestions for a capacity pricing mechanism under the new power system were proposed from the perspectives of transfer capacity function, transfer electricity function, grid reliability, and environmental and social benefits.

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Optimization and analysis of the profitability of tariff structures with two-part tariffs

Cited by 38 publications

References 32 publications

Measurement of consumer preferences for bucket pricing plans with different service attributes

Measurement of consumer preferences for bucket pricing plans with different service attributes

Tariff-Specific Preferences and Their Influence on Price Sensitivity

Research on the capacity cost allocation and the electricity capacity price optimization method for a power system based on the BARY‐GA algorithm

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