A Joint Optimal Model of Pricing, Rebate Value, and Redemption Hassle-Reference-Cited by-同舟云学术

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A Joint Optimal Model of Pricing, Rebate Value, and Redemption Hassle

Published:2019-04-05 Issue:5 Volume:50 Page:1060-1092
ISSN:0011-7315
Container-title:Decision Sciences
language:en
Short-container-title:Decision Sciences

Author:

Zhang Zelin¹,Popkowski Leszczyc Peter²^ORCID,Qu Riliang³,Joseph Kissan⁴

Affiliation:

1. Department of MarketingRenmin University of China Beijing China

2. UQ Business SchoolUniversity of Queensland. St Lucia Queensland 4072 Australia

3. Department of MarketingCentral University of Finance and Economics Beijing China

4. Department of MarketingUniversity of Kansas Lawrence KS 66049

Publisher

Wiley

Subject

Management of Technology and Innovation,Information Systems and Management,Strategy and Management,General Business, Management and Accounting

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/deci.12365

Reference47 articles.

1. A model for optimizing the refund value in rebate promotions

2. Pricing and rebate policies for the newsvendor problem in the presence of a stochastic redemption rate

3. The effectiveness of manufacturer vs. retailer rebates within a newsvendor framework

4. Riding successive product diffusion waves. Building a tsunami via upgrade-rebate programs

5. Measuring utility by a single-response sequential method

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1. Competitive Strategy of Cash-back Website Platform Based on Referral Reward Program;2023 7th International Conference on Business and Information Management (ICBIM);2023-08-18

2. Analysis of online rebates and commission formats in a retailer‐Stackelberg supply chain with cashback website;Decision Sciences;2022-11-14

3. Manufacturer rebate strategy under chain to chain competition;Journal of the Operational Research Society;2022-06-08

4. Research on Platform Operation Strategy Considering Consumers’ Hassle Costs;Sustainability;2022-02-24

5. Managing brand competition with consumer fairness concern via manufacturer incentive;European Journal of Operational Research;2021-08

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