Journal of Revenue and Pricing Management最新文献_第3页

Reinforcement learning for freight booking control problems 货运预订控制问题的强化学习

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-03-16 DOI: 10.1057/s41272-023-00459-1

Justin Dumouchelle, Emma Frejinger, Andrea Lodi

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Calculation of product service systems in single and small batch production 单件和小批量生产中产品服务系统的计算

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-03-02 DOI: 10.1057/s41272-023-00455-5

Günther Schuh, Gerret Lukas, Julian Schweins, Julian Trisjono, Julius Frank

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Do petroleum price fluctuations under price deregulation cause business cycles in Ghana? 放松价格管制下的石油价格波动会导致加纳的商业周期吗？

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-02-28 DOI: 10.1057/s41272-023-00466-2

Frank Gyimah Sackey, Richard Kofi Asravor, Emmanuel Orkoh, Isaac Ankrah

{"title":"Do petroleum price fluctuations under price deregulation cause business cycles in Ghana?","authors":"Frank Gyimah Sackey, Richard Kofi Asravor, Emmanuel Orkoh, Isaac Ankrah","doi":"10.1057/s41272-023-00466-2","DOIUrl":"https://doi.org/10.1057/s41272-023-00466-2","url":null,"abstract":"In the context of volatilities in the international markets in recent times, studies regarding the complexities of oil price fluctuations have focussed on analysing the special fluctuation characteristics of oil prices in different historical perspectives. This study examines the extent to which petroleum price fluctuations under the petroleum price deregulation regime impact on business cycles in Ghana. The study uses the autoregressive distributed lag (ARDL) model with a quarterly data spanning from the first quarter of 2005 to the fourth quarter of 2022. Our empirical results show that price stability impacts positively on economic growth, both in the short and the long run, while foreign direct investment also has a positive effect on economic growth in the short run. Again, we observe that increases in inflation rate and government petroleum revenue negatively affect economic growth both in the short and the long run. To the best of the authors’ belief and knowledge, the observations and recommendations made are consistent with theory and empirical studies and contribute immensely to the discussions about price asymmetry and business cycles. It also offers a nuanced perspective on how policy makers can enact policies that ensure efficient and effective deregulation and price stability.","PeriodicalId":46686,"journal":{"name":"Journal of Revenue and Pricing Management","volume":"317 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140011031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal pricing of subscription services in the restaurant industry 餐饮业订阅服务的最优定价

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-02-13 DOI: 10.1057/s41272-023-00470-6

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How to overcome a worldwide lockdown in the hospitality sector? Lessons from revenue managers 如何克服酒店业的全球封锁？收益经理的经验教训

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-02-10 DOI: 10.1057/s41272-023-00468-0

María Dolores Flecha-Barrio, Fernando E. García-Muiña, Lydia González-Serrano, Pilar Talón-Ballestero

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Price optimization for manufacturers in a competitive retail market: imported products and online crowdfunding option 竞争激烈的零售市场中制造商的价格优化：进口产品和在线众筹选择

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-02-03 DOI: 10.1057/s41272-023-00471-5

{"title":"Price optimization for manufacturers in a competitive retail market: imported products and online crowdfunding option","authors":"","doi":"10.1057/s41272-023-00471-5","DOIUrl":"https://doi.org/10.1057/s41272-023-00471-5","url":null,"abstract":"<h3>Abstract</h3> This study explores how manufacturers in the competitive supply chain can set prices and secure funding effectively. We use game theory to look at how competition between domestic and foreign manufacturers affects pricing decisions. Our research investigates how a domestic manufacturer can improve its market share by addressing financial challenges through modern financing methods. In this scenario, a domestic manufacturer competes with a foreign one to attract a retailer’s market share and profits. The retailer decides what products to buy and how to price them based on bid prices and demand. We also consider that the domestic manufacturer will use online crowdfunding platforms to tackle its financial problem. Hence, our study sets up a supply chain where competition revolves around both operational and financial decisions. Mathematical models are developed to analyze how costs, finances, market potential, and price sensitivity impact various parts of the supply chain. The results reveal that decisions made on the crowdfunding platform significantly influence other supply chain decisions. Manufacturers and retailers need to pay attention to the financial decisions made on this platform to maximize profits. Also, domestic and foreign manufacturers should consider customer preferences for their products when setting prices. Finally, the results demonstrate that a domestic manufacturer can gain a competitive edge in the retail market by carefully considering both product pricing and financial decisions, including those made on the lending platform.","PeriodicalId":46686,"journal":{"name":"Journal of Revenue and Pricing Management","volume":"75 3 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139678438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revenue management without demand forecasting: a data-driven approach for bid price generation 无需需求预测的收入管理：数据驱动的投标价格生成方法

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-02-01 DOI: 10.1057/s41272-023-00465-3

Ezgi C. Eren, Zhaoyang Zhang, Jonas Rauch, Ravi Kumar, Royce Kallesen

{"title":"Revenue management without demand forecasting: a data-driven approach for bid price generation","authors":"Ezgi C. Eren, Zhaoyang Zhang, Jonas Rauch, Ravi Kumar, Royce Kallesen","doi":"10.1057/s41272-023-00465-3","DOIUrl":"https://doi.org/10.1057/s41272-023-00465-3","url":null,"abstract":"Traditional revenue management relies on long and stable historical data and predictable demand patterns. However, meeting those requirements is not always possible. Many industries face demand volatility on an ongoing basis, an example would be air cargo which has much shorter booking horizon with highly variable batch arrivals. Even for passenger airlines where revenue management (RM) is well-established, reacting to external shocks is a well-known challenge that requires user monitoring and manual intervention. Moreover, traditional RM comes with strict data requirements including historical bookings (or transactions) and pricing (or availability) even in the absence of any bookings, spanning multiple years. For companies that have not established a practice in RM, that type of extensive data is usually not available. We present a data-driven approach to RM which eliminates the need for demand forecasting and optimization techniques. We develop a methodology to generate bid prices using historical booking data only. Our approach is an ex-post greedy heuristic to estimate proxies for marginal opportunity costs as a function of remaining capacity and time-to-departure solely based on historical booking data. We utilize a neural network algorithm to project bid price estimations into the future. We conduct an extensive simulation study where we measure our methodology’s performance compared to that of an optimally generated bid price using dynamic programming (DP) and compare results in terms of both revenue and load factor. We also extend our simulations to measure performance of both data-driven and DP generated bid prices under the presence of demand misspecification. Our results show that our data-driven methodology stays near a theoretical optimum (< 1% revenue gap) for a wide-range of settings, whereas DP deviates more significantly from the optimal as the magnitude of misspecification is increased. This highlights the robustness of our data-driven approach.","PeriodicalId":46686,"journal":{"name":"Journal of Revenue and Pricing Management","volume":"10863 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139678344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Demand for 5G from residential customers in Germany: a quantitative online survey using the Van Westendorp method 德国居民用户对 5G 的需求：采用 Van Westendorp 方法进行的定量在线调查

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2024-01-27 DOI: 10.1057/s41272-023-00467-1

Jasmin Ebert, Peter Winzer

引用次数: 0

Optimizing online selling through an online-to-offline platform: strategic ramifications for local n stores 通过 "线上到线下 "平台优化在线销售：对本地 N 家商店的战略影响

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2023-12-15 DOI: 10.1057/s41272-023-00448-4

Ata Allah Taleizadeh, Ebrahim Salehi Darabi, Park Thaichon

{"title":"Optimizing online selling through an online-to-offline platform: strategic ramifications for local n stores","authors":"Ata Allah Taleizadeh, Ebrahim Salehi Darabi, Park Thaichon","doi":"10.1057/s41272-023-00448-4","DOIUrl":"https://doi.org/10.1057/s41272-023-00448-4","url":null,"abstract":"The goal of this research is to determine whether a local brick-and-mortar (B&M) business should implement an online-to-offline (O2O) strategy, as well as the conditions under which each mode is most effective. This research examines how an O2O platform and a B&M store's (like restaurants) decision-making processes interact in a two-echelon supply chain (SC). This research employs numerical experiments and a mathematical approach to address research issues with an online food ordering service \"Snappfood\" that delivers from over 1,500 eateries. We first look at five case studies in which the retail price of Snappfood is determined in both a normal situation (without a marketing mechanism) and one in which the store invests in local advertising to boost demand in the self-building channel. A growth in SC profits is predicted by numerical experiments conducted under this model. The findings of decentralized decision-making reveal that in self-building mode, the store decides on both retail channels and the level of local advertising investment. In turn, the O2O platform recommended a payment delay contract as a fixed operating method for working with B&M stores. This is one of the first studies to investigate at the online sales of a local B&M store, which has the unique characteristic of offering home delivery. Second, we suggest and evaluate that a B&M store can use either the self-building technique or implementing an O2O platform for online selling.","PeriodicalId":46686,"journal":{"name":"Journal of Revenue and Pricing Management","volume":"86 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138680202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic pricing of differentiated products under competition with reference price effects using a neural network-based approach 利用基于神经网络的方法，在具有参考价格效应的竞争条件下为差异化产品动态定价

IF 1.6

Journal of Revenue and Pricing Management Pub Date : 2023-12-15 DOI: 10.1057/s41272-023-00444-8

Parisa Famil Alamdar, Abbas Seifi

{"title":"Dynamic pricing of differentiated products under competition with reference price effects using a neural network-based approach","authors":"Parisa Famil Alamdar, Abbas Seifi","doi":"10.1057/s41272-023-00444-8","DOIUrl":"https://doi.org/10.1057/s41272-023-00444-8","url":null,"abstract":"In this paper, we analyze the dynamic-pricing decisions of differentiated products for retailers operating in a competitive environment, for a finite-time horizon, limited initial inventory, and in the presence of the reference effect. Customers learn from the past prices of retailers and form their estimate of sales prices, called the reference price effect, and use it to make a decision on choosing a retailer to make a purchase. The demand is uncertain, and the customer choice behavior is modeled based on a Multinomial Logit model, modified to incorporate the reference effect. The complexity of the problem increases under conditions of competition and demand uncertainty and cannot be analyzed using conventional methods. Therefore, we have used a neural network-based algorithm called Revenue-Based Neural Network (RBNN) to dynamically calculate the competitive price in order to increase the retailer’s revenue. We have analyzed the effect of competition and the performance of RBNN algorithm under two scenarios: a monopolistic situation in which a retailer uses the RBNN policy to maximize its revenue, and a duopolistic situation in which one retailer uses the RBNN strategy and the other uses an adaptive policy called Derivative Following (DF). The results of the experiments show that the pricing policy under duopolistic conditions highly affects the income of retailers in the presence of reference price. The RBNN policy outperforms the DF policy due to the learning process on the customers’ reference price. By charging higher prices in the RBNN strategy, the seller trades off the current revenue with the long-term revenue resulting from formation of higher levels of the reference price in customers’ minds and earns more revenue than its competitor overall.","PeriodicalId":46686,"journal":{"name":"Journal of Revenue and Pricing Management","volume":"14 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138680207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0