Game Theoretic Models for Revenue Management in the Presence of Networks
网络存在下收入管理的博弈论模型
基本信息
- 批准号:RGPIN-2017-05467
- 负责人:
- 金额:$ 2.04万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2018
- 资助国家:加拿大
- 起止时间:2018-01-01 至 2019-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Revenue management (RM) is defined as “charging the right price to the right customer at the right time” and pertains to the ability of companies to profitably manage their demand. Supply chain management (SCM) puts emphasis on the supply and matching it with demand. The proposal seeks to advance analytic models for RM and SCM and techniques to increase the efficiency of companies facing dynamic decisions in an interconnected (networked) world. The connections come in various forms including the flows of information and physical goods, competition or partnerships between companies, complementary or substitute products, customer-supplier relations and influences of the end-consumers on one another.***Companies make many decisions that affect customer demand, including decisions regarding prices, inventories, assortments, features and quality of products, and special offers such as low-priced combinations (bundles) of products. Successful use of these instruments requires detailed mathematical models of customer behavior, often down to the individual level, that cover customer choice among products, demand evolution due to customer learning, strategic timing of purchases (called strategic behavior), and changes in demand due to the number of users for similar products. The latter phenomenon, called “network externality,” arises because the value of a product or service for a given customer is affected by the presence and behavior of other customers. The presence of many rational decision makers in combination with networks requires network-based extensions of game theoretic and other SCM and RM models. ***The fast-paced and competitive marketplace compels companies to use as complete and current a view of the market as possible, and to actively leverage emerging “Big Data” technologies in operations. These technologies help to collect, store, and effectively process large Volumes of data that may arrive at high Velocity from a Variety of data sources, as well as to address the problems arising from the data Veracity (four V's of Big Data). Given this challenging environment, this research program will ***1. Help companies make operational decisions in the presence of networks of various types and under intense competition. ***2. Provide insight into how operational decisions are affected by strategic and choice customer behavior, in particular, when customers have limited information and learn over time. ***3. Leverage Big Data tools in the operational decisions of businesses affected by the above issues. ***4. Advance game theoretic and large-scale stochastic optimization models for SCM and RM. ***The outcomes of the program are important for industry practitioners, decision makers, and academic researchers in RM and SCM. They provide ample opportunities for training of HQP in advanced business Analytics.
收入管理(RM)被定义为“在正确的时间向正确的客户收取正确的价格”,涉及公司以盈利方式管理其需求的能力。供应链管理(SCM)强调供应及其与需求的匹配。该提案旨在推进 RM 和 SCM 的分析模型以及技术,以提高在互联(网络)世界中面临动态决策的公司的效率。这种联系有多种形式,包括信息和实物商品的流动、公司之间的竞争或伙伴关系、互补或替代产品、客户与供应商关系以及最终消费者之间的影响。***公司做出许多影响客户需求的决策,包括有关价格、库存、品种、产品功能和质量的决策,以及低价产品组合(捆绑)等特殊优惠。成功使用这些工具需要详细的客户行为数学模型,通常深入到个人层面,涵盖客户对产品的选择、客户学习导致的需求演变、购买的战略时机(称为战略行为)以及由于类似产品的用户数量而导致的需求变化。后一种现象称为“网络外部性”,其出现是因为特定客户的产品或服务的价值受到其他客户的存在和行为的影响。许多理性决策者与网络的结合需要基于网络的博弈论和其他 SCM 和 RM 模型的扩展。 ***快节奏且竞争激烈的市场迫使公司尽可能使用完整和最新的市场观点,并在运营中积极利用新兴的“大数据”技术。这些技术有助于收集、存储和有效处理可能从各种数据源高速到达的大量数据,并解决数据真实性(大数据的四个V)引起的问题。鉴于这种充满挑战的环境,该研究计划将***1。帮助企业在各种类型的网络和激烈的竞争中做出运营决策。 ***2.深入了解战略和选择客户行为如何影响运营决策,特别是当客户信息有限且随着时间的推移而学习时。 ***3.在受上述问题影响的企业的运营决策中利用大数据工具。 ***4.先进的 SCM 和 RM 博弈论和大规模随机优化模型。 ***该项目的成果对于 RM 和 SCM 领域的行业从业者、决策者和学术研究人员非常重要。它们为总部高级业务分析方面的培训提供了充足的机会。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Levin, Yuri其他文献
Cargo Capacity Management with Allotments and Spot Market Demand
- DOI:
10.1287/opre.1110.1023 - 发表时间:
2012-03-01 - 期刊:
- 影响因子:2.7
- 作者:
Levin, Yuri;Nediak, Mikhail;Topaloglu, Huseyin - 通讯作者:
Topaloglu, Huseyin
Cosmic strings and primordial black holes
宇宙弦和原初黑洞
- DOI:
10.1088/1475-7516/2018/11/008 - 发表时间:
2018 - 期刊:
- 影响因子:6.4
- 作者:
Vilenkin, Alexander;Levin, Yuri;Gruzinov, Andrei - 通讯作者:
Gruzinov, Andrei
Spinning black holes as cosmic string factories
旋转黑洞作为宇宙弦工厂
- DOI:
10.1103/physrevd.103.083019 - 发表时间:
2021 - 期刊:
- 影响因子:5
- 作者:
Xing, Hengrui;Levin, Yuri;Gruzinov, Andrei;Vilenkin, Alexander - 通讯作者:
Vilenkin, Alexander
Network Cargo Capacity Management
- DOI:
10.1287/opre.1110.0929 - 发表时间:
2011-07-01 - 期刊:
- 影响因子:2.7
- 作者:
Levina, Tatsiana;Levin, Yuri;Nediak, Mikhail - 通讯作者:
Nediak, Mikhail
Conversion Measure of Faraday Rotation-Conversion with Application to Fast Radio Bursts
- DOI:
10.3847/1538-4357/ab0fa3 - 发表时间:
2019-05-01 - 期刊:
- 影响因子:4.9
- 作者:
Gruzinov, Andrei;Levin, Yuri - 通讯作者:
Levin, Yuri
Levin, Yuri的其他文献
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{{ truncateString('Levin, Yuri', 18)}}的其他基金
Game Theoretic Models for Revenue Management in the Presence of Networks
网络存在下收入管理的博弈论模型
- 批准号:
RGPIN-2017-05467 - 财政年份:2021
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Game Theoretic Models for Revenue Management in the Presence of Networks
网络存在下收入管理的博弈论模型
- 批准号:
RGPIN-2017-05467 - 财政年份:2020
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Large-scale customer analytics methodologies in financial services
金融服务中的大规模客户分析方法
- 批准号:
507687-2016 - 财政年份:2019
- 资助金额:
$ 2.04万 - 项目类别:
Collaborative Research and Development Grants
Game Theoretic Models for Revenue Management in the Presence of Networks
网络存在下收入管理的博弈论模型
- 批准号:
RGPIN-2017-05467 - 财政年份:2019
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Large-scale customer analytics methodologies in financial services
金融服务中的大规模客户分析方法
- 批准号:
507687-2016 - 财政年份:2018
- 资助金额:
$ 2.04万 - 项目类别:
Collaborative Research and Development Grants
Game Theoretic Models for Revenue Management in the Presence of Networks
网络存在下收入管理的博弈论模型
- 批准号:
RGPIN-2017-05467 - 财政年份:2017
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Large-scale customer analytics methodologies in financial services
金融服务中的大规模客户分析方法
- 批准号:
507687-2016 - 财政年份:2017
- 资助金额:
$ 2.04万 - 项目类别:
Collaborative Research and Development Grants
Game-theoretic models in revenue management and dynamic pricing
收益管理和动态定价中的博弈论模型
- 批准号:
261512-2009 - 财政年份:2015
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Game-theoretic models in revenue management and dynamic pricing
收益管理和动态定价中的博弈论模型
- 批准号:
261512-2009 - 财政年份:2012
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Game-theoretic models in revenue management and dynamic pricing
收益管理和动态定价中的博弈论模型
- 批准号:
261512-2009 - 财政年份:2011
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
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网络存在下收入管理的博弈论模型
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