Management Science | PubsOnLine


Management Science

Revenue Management and Market Analytics

Department Editors:  Omar Besbes and Gabriel Weintraub

  Revenue management has traditionally been concerned with managing scarce capacity by using pricing mechanisms and demand management as an operational tool. The practice of revenue management is taking hold in many industries and takes various forms: capacity allocation controls, dynamic pricing, dynamic bundling, bargaining and negotiated pricing, customized pricing, assortment optimization, auctions, and so on. From industries such as airlines, hotels and rentals, these days we also see such practices in e-commerce, taxis, energy, railways, and road pricing. 
The rise of platforms is another new phenomenon. Recent trends point to an unprecedented level of control over the design, implementation, and operation of markets: more than ever before, we are able to engineer the platforms governing transactions among market participants. As a consequence, market operators or platforms can control a host of variables such as pricing, liquidity, visibility, information revelation, terms of trade, and transaction fees. On its part, given these variables, market participants often face complex problems when optimizing their own decisions. Operational study of these platforms and their design is still in their infancy and we encourage submissions studying these markets, both from the perspective of the market operator and the market participants.

We seek well-written papers that are connected to reality, improve our understanding of the application domain at-hand, and ideally have a possibility of implementation. We look for a mix of approaches including modeling, theoretical, empirical, or computational. The paper should score high on most of the following criteria: (1) How realistic and significant is the application studied?; (2) How original/creative is the approach adopted?; (3) How significant would be its impact on practice? 

Associate Editors:  Itai Ashlagi, Santiago Balseiro, Kostas Bimpikis, Rene Caldentey, Felipe Caro, Arnoud den Boer, Karan Girotra, Stefanus Jasin, Jun Li, Ilan Lobel, Brendan Lucier, Vahideh Manshadi, Marcelo Olivares, Saša Pekeč, Sridhar Seshadri, Huseyin Topaloglu, Senthil Veeraraghavan, Fanyin Zheng.



Manufacturing & Service Operations Management

Service, Platforms, and Revenue Management

Area Editors:  Mor Armori, Marcelo Olivares, and Guillaume Roels

The Department of Services, Platforms, and Revenue Management seeks manuscripts that offer enduring knowledge to improve our understanding of the design, performance, and their key drivers of service systems, platform management, and revenue management. The services or platforms of interest could involve interactions among businesses and/or consumers, or be internal to an organization.

We value novel research questions, impactful contributions, and rigorous execution. A strong motivation derived from real world applications is necessary, along with a clear contribution to knowledge and/or a demonstration of managerial relevance. We embrace a variety of methods, including analytical modeling, empirical methods, lab and field experiments, and numerical methods (simulation, machine learning). Given the cross-functional nature of services, we are very much open to interdisciplinary contributions that use or integrate methods and/or knowledge from different fields (e.g., social sciences and engineering).

Industries of interest could range from physical to information-based services, the decisions could range from strategic to operational, and the scope of analysis could range from macroscopic (e.g., industries, organizations) to meso and microscopic (e.g., teams, individuals). Topics include: wait time and capacity management, pricing and revenue management, service contracting, digital platform management and scaling, marketplaces, e- and m-commerce, process design and digitalization, service quality management, servicization and productization, access and location, network management, customer/employee experience management, people operations and organizational design, service design and innovation, peer-to-peer services, crowdsourcing, service globalization, sustainable and/or ethical issues in services.

Relative to the other departments for which there is potential overlap (e.g., healthcare, analytics, innovation), we value contributions that are more practice-driven than methodological and that are generalizable beyond a single domain of application.



Manufacturing & Service Operations Management

Analytics in Operations

Area Editors:  Melvyn Sim, and Huseyin Topaloglu

Combined power of algorithms, data and computation has enabled analytics to be indispensable for solving challenging problems in operations such as, among others, the sharing economy, online markets, public policy, healthcare, transportation logistics, and supply chains. Accordingly, the Department seeks papers that use mathematical modeling and analysis to drive decision-making in data-rich environments. We are particularly interested in papers that have strong methodological contributions with a clear path to making an impact in the practice of data-driven decision-making.

Our understanding of analytics, in terms of both methodology and application areas, is broad. We welcome papers with focus on optimization, stochastic analysis, and data-intensive methods. Application areas of interest range from business applications in online platforms, retail and operations to societal applications in healthcare and politics. The department looks for papers that excel in both their methodological contributions and their ability to incorporate large-scale data into the decision-making process, as opposed to papers that purely use standard tools to test hypotheses on the data. We value demonstrating the effectiveness of the proposed methodology on real-world data, but do not put it forth as a requirement for all papers submitted to the department. Nevertheless, the submitted work should have a clear path to contributing to the science of data-driven decision-making. While management insight is appreciated, we understand that a novel algorithmic approach may not immediately translate into management insight.

Naval Research Logistics (NRL) - Wiley Online Library


Naval Research Logistics

Revenue Management and Marketplace Design (Officially sponsored by the INFORMS RMP section)

Department Editor:  René Caldentey

The Revenue Management and Marketplace Design (RMMD) department seeks to publish papers at the forefront of advancing the theory and practice of Revenue Management and Dynamic Pricing and its linkage to the growing area of marketplace innovation and the sharing economy.

Revenue Management and Dynamic Pricing (RMDP) is a multidisciplinary research area that combines operations research, stochastic optimization, economics, marketing and data analytics to solve problems related to the management and pricing of scarce and perishable resources. Revenue Management has had a transforming impact on the transportation (airlines, railway, rental car), hospitality (hotels, cruise lines, casinos) and retail (apparel, consumer goods) industries. However, the rise of online marketplaces and Internet exchanges is rapidly expanding the scope of RMDP to a broad range of applications including media and Internet advertising, sharing economy markets, labor and procurement platforms, healthcare exchanges, to name a few.

The RMMD department is committed to publishing and disseminating the best articles that provide original theoretical results and advance the state-of-the-art of the models and methods used to solve real problems. We particularly welcome papers that explore emerging issues in the field and the connection between RMDP and marketplace design.

Associate Editors: Victor Araman, Ozan Candogan, Pavithra Harsha, and Stefanus Jasin.

Operations Research | PubsOnLine


Operations Research

Revenue Management and Market Analytics

Area Editors:  Ramesh Johari and Gustavo Vulcano

The Revenue Management and Market Analytics area considers articles at the forefront of advancing the theory and practice of pricing and revenue optimization, and design and operation of market platforms.

Rapid changes in information, communication, and computing technology that are altering all aspects of our economic interactions. Not only do these advances enable us to collect ever more detailed data on customer and firm behavior, but they also enable much finer grained optimization of all the determinants of market outcomes. As a consequence, market operators or platforms can control a host of variables such as pricing, liquidity, search and matching, information revelation, terms of trade, and transaction fees. Analogously, market participants have far greater control over bidding, pricing, assortment optimization, and revenue optimization. These forces are being borne out in the rise of online marketplaces across a wide range of industries: more than ever before, we are able to engineer the platforms governing transactions among market participants.

These forces are evident in the spectrum of academic research pushing beyond traditional models of pricing and revenue management: more sophisticated models of consumer choice and behavioral biases; real-time pricing decisions (e.g., as in ride-sharing and ad auctions); fine-grained, dynamic search and matching algorithms; novel rating and review systems; dynamic bundling (and unbundling) of products; personalized assortments and discounts; etc.

We seek high-impact papers with deep roots in real problems, with a slight preference for (but not limited to) significant methodological or analytical contributions. We also welcome papers that excel in their modeling and/or computational approach to solving a relevant practical problem, supported by a well-documented numerical study, ideally based on real data.

Associate Editors: Omar Besbes, Kostas Bimpikis, Rene Caldentey, William Cooper, Jose Correa, Vivek Farias, Vineet Goyal, Ming Hu, Nicole Immorlica, Srikanth Jagabathula, Yash Kanoria, Ilan Lobel, Paat Rusmevichientong, and Huseyin Topaloglu.

Production and Operations Management - Wiley Online Library


Production and Operations Management

Revenue Management Department

Department Editor: Dan Zhang


The Revenue Management Department welcomes research that uses operations research, econometrics, and behavioral and analytics tools to study how to better match the supply of a good or service with its demand over time. The scope of the department spans traditional areas of pricing and revenue optimization, such as transportation and hospitality, and emerging applications in retail analytics, healthcare, web advertising, sharing economy, and online matching markets, etc. Recent developments in the field allow finer control of many variables besides pricing and capacity; examples include information structure, liquidity, matching mechanism, etc.

Submitted papers are expected to disseminate innovative research and application in pricing and revenue optimization. They can be (but are not limited to) i) novel applications of revenue management in traditional and emerging application domains, ii) economic models, iii) methodological contribution to the solutions of existing problems, and iv) behavioral and empirical studies that validate existing theory or examine market phenomena. We encourage submissions that explore the interplay between revenue management and manufacturing, service operations, and supply chain management. Papers need to be well written, make a significant contribution to the field, be methodologically sound, and be of practical relevance.

Senior Editors: Goker Aydin, Rene Caldentey, Stefanus Jasin, Sumit Kunnumkal, Ilan Lobel, Georgia Perakis, Robert L. Phillips, Paat Rusmevichientong, Kalyan Talluri, Huseyin Topaloglu, Zizhuo Wang