Optimal real-time pricing model based on dynamic programming methods

У цій статті проведено аналіз сучасних методологічних підходів до дослідження проблем динамічного ціноутворення, виявлено їх обмеження і критичні питання щодо практичної реалізації. Більшість робіт передбачає безперервний перегляд цінової політики та обізнаність продавця у функції попиту, що зазвичай важко зустріти на практиці. З огляду на це автором запропонована власна модель динамічного прайсингу в дискретному часі з періодичним коригуванням цінової політики. Модель враховує також параметричну («ідеальну») криву продажів і функцію розподілу купівельних цін. Ці характеристики оцінюються за допомогою історичних даних. Завдання моделі - запропонувати оптимальну ціну пропозиції, яка б дозволяла продавати товар згідно темпу параметричної кривої і максимізувала прибуток підприємства. Запропонована методика була успішно протестована для випадку продажу туристичних турів. Подальша розробка моделі передбачає використання байєсівських мереж для калібрування оцінок її параметрів.This article analyzes the modern methodological approaches to the study of dynamic pricing problems. It reveals their limitations and critical implementation issues. Most of the working papers suppose the continuous review of pricing policies and the knowledge of the demand function. Such hypothesis is rarely possible in practice. This is why the author suggests his own discrete-time dynamic pricing model with periodic adjustment of the pricing policy. The model also takes into account the parametric ("ideal") sale curve and the distribution function of consumer prices. These characteristics are estimated by analysing historical data. The goal of this model is to identify an optimal price. The given price would allow to carry out the sale in accordance to parametric sale curve and to maximize the profit of the firm. This technique has been successfully tested for the case of the package holiday industry. Further development of the model involves the use of Bayesian learning to calibrate the estimation of its parameters.В статье проведен анализ современных методологических подходов к исследованию проблем динамического ценообразования, выявлены их ограничения и критичные вопросы реализации. Большинство подходов предусматривает непрерывный пересмотр ценовой политики и осведомленность продавца о функции спроса, что редко предоставляется возможным на практике. В виду этого авторами предложена собственная модель динамического прайсинга в дискретном времени с периодической корректировкой ценовой политики. Модель учитывает также параметрическую («идеальную») кривую продаж и функцию распределения покупательских цен. Эти характеристики оцениваются при помощи исторических данных. Задача модели – выявить оптимальную цену предложения, которая бы позволяла осуществлять продажи согласно темпу параметрической кривой и максимизировала прибыль предприятия. Описанная методика была успешно протестирована для случая продаж туристических туров. Дальнейшая разработка модели предполагает применение обучения байесовских сетей для калибровки оценок её параметров

PENURUNAN DAYA BELI VS PANIC BUYING DI TENGAH PANDEMI COVID-19. BAGAIMANA TINJAUAN SYARIAHNYA?

Penelitian ini dilakukan untuk mengetahui perilaku konsumsi masyarakat di saat mengahadapi pandemi covid-19. Data menunjukkan bahwa pandemi ini berdampak sistemik tak terkecuali di bidang ekonomi. Di satu sisi sebagian masyarakat mengalami penurunan daya beli karena menurunannya penghasilan dan PHK, di sisi lain terjadi panic buying. Panic buying dan pile up terjadi selama pandemi covid-19, tak terkecuali di Indonesia. Panic buying dan pile up dilakukan dengan berbagai alasan, yg secara umum adalah untuk proteksi diri dari penularan virus covid-19. Penelitian dilakukan dengan metode kualitatif analitis, dengan mempelajari perilaku (behavioral analitic) masyarakat dalam mengkonsumsi pada masa pandemi. Kemudian mengulas tinjauan secara syariah.Kata kunci: perilaku konsumen, panic buying, pandemi covid-1

Pricing Strategies in Dual-online Channels Based on Consumers’ Shopping Choice

AbstractBesides an official website mall (OWM), retail stores on the third party e-commerce platform(3PEP) is an another important online channel that manufacturers adopt to sell online. How to properly price products in these two channels simultaneously is a tough problem to firms and gains much attention by researchers. In this paper, we analyze their channel choice, and give demand functions of the two channels based on the consumers’ segmentation and preference. Then we design a sale model including two online channels: OWM and a retail store on 3PEP. According the Stackelberg game theory, we calculate and discuss the optimal pricing strategies of the manufacturer and retailer in three feasible regions. The result shows that manufacturers emphasizing channel sales prefer to choose pricing strategies that helps two online channels share the online market. But some manufacturers think adjusting the OWM's price and the wholesale price to control the retailer's pricing strategies is reasonable and necessary, even if nobody will prefer the OWM

Dynamic pricing with the counter-conformity, conformity and non-conformity of consumer behavior

Confronted with well-informed consumers, the firms have to take everything into consideration. Through the classic game theory, pricing mechanism is discussed with different characteristics of consumer behavior. The consumer population is heterogeneous along two dimensions: they may have an inclination towards the obedience of the public and different degrees of patience. After introducing the price deviation variables, we demonstrate that heterogeneity in both inclination and patience is important because they jointly determine the structure of optimal pricing policies. The numerical example shows that the markdown degree, the expected purchasing amount of consumers and the expected profits of the firm are increasing with the increase of the proportion of counter-conformity consumers. And we also examine whether the discount rate of capital, counter-conformity consumers and myopic consumers will have an impact on the sales. In particular, when the discount rate and the proportion of the conformity customers are too high, the expected profits of the firm are increasing mildly with the increase of the proportion of myopic customers. Therefore, the discount rate and characteristics of consumer behavior should be considered together to maximize the revenue of firms

Name-Your-Own Price Auction Mechanisms – Modeling and Future Implications

A popular method for selling excess inventory over the Internet is via a Name-Your-Own Price auction, where the bidder bids on an item and the seller immediately decides on whether or not to accept the bid. The analytical modeling of such auctions is still in its infancy. A number of papers have appeared over the last few years making various assumptions about buyers and sellers. The intent of this article is to carefully delineate the various assumptions and modeling approaches and, consequently, suggest avenues for further research

Pricing Perishables with Uncertain Demand, Substitutes, and Consumer Heterogeneity

Within the marketing window for perishables such as food products, demand uncertainty is complicated by price sensitivity and propensity to postpone purchase that is heterogeneous across consumers. These features pose substantial challenges to retailers when pricing multiple products over time and across consumer segments. Getting the dynamic profile of prices right has implications for performance of vertical food chains ranging from revenues to food waste. This paper proposes an approach to dynamic pricing that is demonstrated to improve performance within this setting

Tourism in the Digital Age: E-booking Perspective

Digitization in the tourism sector beside hospitality information systems application as its integral part has also led to the application of on-line booking systems, which enable the booking of the desired tourist arrangement via the Internet. Consequently, the emergence of the e-booking concept has made it possible reducing administrative and operational costs, since the e-booking system is also used on smartphones with appropriate applicative support. This paper aims to point out the importance of e-booking in the digital age of tourism, especially from monitoring the most common destinations, customer preferences and performing predictive analytics by collecting large amounts of data. In this way, the implementation of big data and cloud computing concept enhances tourism services, since it is possible to analyse destination history and tourist potential of the client via the Internet. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

Market Basket Analysis to Identify Customer Behaviours by Way of Transaction Data

Transaction data is a set of recording data result in connections with sales-purchase activities at a particular company. In these recent years, transaction data have been prevalently used as research objects in means of discovering new information. One of the possible attempts is to design an application that can be used to analyze the existing transaction data. That application has the quality of market basket analysis. In addition, the application is designed to be desktop-based whose components are able to process as well as re-log the existing transaction data. The used method in designing this application is by way of following the existing steps on data mining technique. The trial result showed that the development and the implementation of market basket analysis application through association rule method using apriori algorithm could work well. With the means of confidence value of 46.69% and support value of 1.78%, and the amount of the generated rule was 30 rules

The Forty-year History of Revenue Management: Bibliometric Analysis

This paper presents research trends, leading publishers, influential articles, and shifting concerns in the field of Revenue Management for over forty years based on bibliometric analysis. Bibliometric data was retrieved from Web of Science core collection with a well-defined strategy. The data was processed using Network Analysis Interface for Literature Studies Project scripts. Subject-wise and year-wise research trends were presented. The shifting concerns in RM in terms of topic, method, and domain were highlighted using keyword analysis. In general, RM showed an increasing number of published papers with exponential manner every year. The research core in RM covered the three major decisions in RM including pricing, quantity control, and structural decision. It was highlighted that RM’s concern has shifted from single-firm decision to be more consumer- and competition-centric. The data showed that the needs of empirical study and more advanced quantitative methods for complex and real-time problems were urged. In addition, the adoption of RM was extended for industries with semi-flexible capacity. The top influential publishers were Decision Sciences, Operations Research, Management Science, and Management Science Manufacturing & Service Operations Management