Dynamic Pricing of a Web Service in an Advance Selling Environment

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

doi:10.1155/2015/783149

Cited by 5 publications

(2 citation statements)

References 54 publications

(64 reference statements)

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“…There are little achievements addressing pricing problem of perishables in advance selling strategy. Safari et al (2015) developed a continuous time optimal control model for identifying pricing strategies for the web service classes based on maximum principle and proposed an algorithm to obtain the optimal pricing policy. From above literature review, we found that it is of great necessity to further carry out our research on pricing of perishable items with the consideration of an advance selling strategy.…”

Section: Review Of Previous Workmentioning

confidence: 99%

A two-period pricing model for perishable items

Wang

Zhao

2018

IJSTM

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This paper presents a two-period pricing model for perishable items via an advance selling strategy deployed within electronic businesses. This model is proposed by classifying consumers based on their shopping habits: strategic consumers and conventional consumers. The model was developed both with and without a consumer order cancellation variable. Numerical computation and sensitivity analysis were conducted to test and justify the theoretical model. The results demonstrate that the ratio of potential consumers in an advance selling period to that in regular selling period is the main factor affecting pricing decisions. Consumers' perception of price fairness and order cancellation have effect on sellers' total revenue. The best revenue and price is obtained by adjusting the length of the advance selling period.

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Section: Review Of Previous Workmentioning

confidence: 99%

A two-period pricing model for perishable items

Wang

Zhao

2018

IJSTM

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“…Dynamic schemes models are believed to be more powerful and flexible than static pricing strategies and have been used in many areas of industry in addition to telecom (see rf. 5,6,7 ), such as retailing, manufacturing, airlines, and ebusiness 8,9 . To illustrate, well-known all-you-cansend (or flat rate) pricing policy is a static scheme in which the customer leases bandwidth at a fixed price for a fixed contract period 10,11 .…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Stochastic Capacity Acquisition and Allocation Model for Bandwidth Brokers under Fuzzy Volume Based Pricing Scheme

Turan¹,

Kasap²,

et al. 2016

IJCIS

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In this paper, bandwidth acquisition and allocation problem of a telecommunications Bandwidth Broker (BB) is analyzed under uncertain end-user capacity requests and pay-per-byte (volume) based pricing policy. Furthermore, related objective function coefficients such as revenue and costs are modeled as fuzzy numbers in order to cope with vague market conditions. By integrating fuzzy mathematical programming and two-stage stochastic programming techniques, deterministic equivalent of single objective profit maximization problem of BB is obtained solved to optimality. In addition, infrastructure related performance measures such as delay and jitter amounts in the network are modelled via stochastic parameters that obey some known probability distributions. Two performance statistics namely fuzzy Expected Value of Perfect Information (EVPI) and fuzzy Value of Stochastic Solution (VSS) are defined to demonstrate the efficiency of proposed methodology compared to deterministic approach. In addition, several secondary performance measures such as expected capacity utilization, expected demand fulfilment ratio and capacity loss are calculated under different problem settings. In conclusion, numerical experiments showed that fuzzy stochastic method provides more profit depending upon problem size in compression with deterministic strategy.

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Resale or agency: pricing strategy for advance selling in a supply chain considering consumers’ loss aversion

Zhang

Zhao

2021

IMA Journal of Management Mathematics

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Advance selling activities are becoming more popular, especially in online retailing of new products. During the advance selling process, consumers may be loss averse. This influences the pricing strategy of the members of the supply chain. Using prospect theory and game theory, and considering consumers’ loss aversion, this paper studies the pricing strategy of advance selling in a supply chain consisting of a manufacturer and an e-retailer under a resale contract or an agency contract. The study finds that as consumers’ loss aversion increases, supply chain members set lower prices. Consumers’ loss aversion has a positive impact on the member who directly prices to consumers, but it has a negative impact on the indirect member. Advance selling under an agency contract makes it easier to achieve a Pareto improvement than that under the resale contract. When the unit order fulfilment cost is low, the e-retailer prefers the agency contract.

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Dynamic Pricing of a Web Service in an Advance Selling Environment

Cited by 5 publications

References 54 publications

A two-period pricing model for perishable items

A two-period pricing model for perishable items

Stochastic Capacity Acquisition and Allocation Model for Bandwidth Brokers under Fuzzy Volume Based Pricing Scheme

Resale or agency: pricing strategy for advance selling in a supply chain considering consumers’ loss aversion

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