Determining strategy of pricing for a web service with different QoS levels and reservation level constraint

Safari, Ehram; Babakhani, Masoud; Sadjadi, Seyed Jafar; Shahanaghi, Kamran; Naboureh, Khadijeh

doi:10.1016/j.apm.2014.11.054

Cited by 10 publications

(10 citation statements)

References 36 publications

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“…Although customers can play an active role in co-creating value, they may also experience discomfort and incompetence when asked to collaborate with service providers (Sjödin and Kristensson, 2012). Because value is context- and process-dependent, the provider tends to develop flexible pricing strategies such as dynamic pricing in which the provider adjusts prices to the consumers based on the value customers may perceive in the exchange (Safari et al , 2015; Ødegaard and Wilson, 2016).…”

Section: Services and Value Of Servicesmentioning

confidence: 99%

Towards an approach for monetary valuation of services

Hsiao

2018

IJQSS

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Purpose The purpose of this study is to suggest possible approach which can be applied to estimate the monetary value of the ancillary services in today’s multichannel environment where consumers tend to exhibit cross-channel purchase behavior across the online and offline. Design/methodology/approach This study conducts literature reviews to identify ancillary services and discuss their service paths across online and offline channels based on service-dominant logic. It then proposes discrete choice modeling approach with stated preference data to estimating the implicit value of services. Findings By examining consumer decision-making process, some ancillary services attached to the products/services that consumers target at are revealed and discussed. By applying the discrete choice modeling approach which have been widely applied in the marketing and transportation area to describe consumers’ multichannel choices, it is believed that the implicit value that consumers are willing to pay for having those ancillary services can be estimated. Originality/value Value is generally considered transitory, stochastic and multidimensional and understood imprecisely. Past research recognized the importance of value to the service industry, but failed to give it a widely accepted definition. Issues on the value of time, value of information and value of services have been widely discussed in the literature, but most of them remained unsolved. The approach proposed by this study to estimating the value of services seems practicable and is worth a further validation by empirical study.

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Section: Services and Value Of Servicesmentioning

confidence: 99%

Towards an approach for monetary valuation of services

Hsiao

2018

IJQSS

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“…The research on this pricing has been beginning in last decade and critically improves to fit in dynamical situation in wireless network [11] By considering the linearity factor, acceptance factor, elasticity price, the provider able to maximize the price for user and class. Pricing strategy proposed by [21] By considering the optimal pricing strategy for specific service as function of time. Their proposed model was created then comparing with the existing approaches available.…”

Section: Literature Reviewmentioning

confidence: 99%

Nonlinear Programming Approach of Wireless Pricing Models

Irmeilyana

Puspita

Indrawati

2015

EECSI

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The pricing for wireless networks is developed to obtain surplus from subscribers. The linearity factors, elasticity price, price factors are discussed. the new approach of wireless pricing model proposed by previous research are approached by considering the model as the nonlinear programming problem that can be solved optimally using LINGO 13.0. The problem is considered to be nonlinear programming that can be solved using optimization tools. The solutions are expected to give some information about the connections between the acceptance factor and the price. The models attempt to maximize the total price for a connection based on QoS parameter. The maximum goal to maximum price is achieved when the provider set the increment of price change due to QoS change and amount of QoS value. The linearity parameter set up for most cases is obtained in ceiling value. Linear price factor ranges between the prescribed value especially cases when we increase the price change due to QoS change and increase the amount of QoS values. I.

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“…The usual economic strategy to handle consumer demand for IT services such as network resources and web service with disparate QoS is dynamic pricing in which the price continuously varies over the time based on the value that the users consider to the service. 5,6 Using this method, the provider can create a balance between the supply and demand of the web service. Besides, the provider can efficiently manage limited resources such as storage throughput, network bandwidth, and CPU time.…”

Section: Introductionmentioning

confidence: 99%

A robust optimization formulation for dynamic pricing of a web service with limited total shared capacity

Safari

Roshanaei

Rastpour

2022

Optim Control Appl Methods

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This article provides a robust optimization formulation to tackle the demand uncertainty in the web service dynamic pricing problem where a provider offers a web service with different service levels (i.e., web service classes) to manage capacity and maximize profit. Consumers may buy their required web service through a reservation system and have the right with no obligation to cancel their purchases as long as they pay the penalty. In this article, we develop a robust optimization formulation for the model in which the demand of a service class is a linear function of the price; the total shared capacity of the provider for the web service is limited; the demand function coefficients and cancelation rate are time-dependent. We demonstrate that the robust formulation is of the equivalent order of complexity as the nominal problem. Eventually, we obtain the optimality condition and some managerial insights into the problem according to the maximum principal and provide an algorithm to find the optimal pricing policy as a function of the time on a finite time horizon. Numerical analyses are performed to evaluate the effect of uncertainty on the objective function. Furthermore, the proposed algorithm is compared with some existing approaches.The preliminary results show that the proposed algorithm offers better results than other algorithms such as QCP, NLP, GA, and SA in terms of time and accuracy.

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Determining strategy of pricing for a web service with different QoS levels and reservation level constraint

Cited by 10 publications

References 36 publications

Towards an approach for monetary valuation of services

Towards an approach for monetary valuation of services

Nonlinear Programming Approach of Wireless Pricing Models

A robust optimization formulation for dynamic pricing of a web service with limited total shared capacity

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