Unbundling of Ancillary Service: How Does Price Discrimination of Main Service Matter?

Cui, Yao; Duenyas, Izak; Şahin, Özge

doi:10.2139/ssrn.2724138

Cited by 10 publications

(17 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cui et al. () consider both uniform pricing and discriminatory pricing of the core product, and show that these two pricing strategies over the core product have contrasting implications on the profitability of add‐on pricing. Geng and Shulman () show that competing firms can both lose from add‐on pricing when consumer price sensitivity is correlated with their demand of add‐ons.…”

Section: Literature Reviewmentioning

confidence: 99%

How Add‐on Pricing Interacts with Distribution Contracts

Geng

Tan

Wei

2018

Production and Operations Management

202

View full text Add to dashboard Cite

With the rise of the Internet economy, an increasing number of firms are offering their core products through online platforms, but retail add‐ons directly to consumers. Meanwhile, many online platforms have also started adopting the agency (model) contract, where the upstream firms decide the retail prices of products while the downstream platforms take a predetermined cut from each sale. This study examines the interaction between an upstream firm's add‐on strategy and a downstream online platform's distribution contract choice. We find that such a firm prefers bundling the add‐on and the core product together under the wholesale contract, but prefers retailing the add‐on separately under the agency contract. Our research thus is the first to suggest that the distribution contract can critically affect a firm's choice between add‐on pricing and bundling. On the platform side, we show that a higher commission rate does not always result in a higher profit for the platform under the agency contract. We further identify two conditions under which the platform prefers the agency contract over the wholesale contract: The commission rate for the platform cannot be too low, and the market potential of the add‐on cannot be too large. For the overall channel, we show that the interaction between add‐on pricing and distribution contracts leads to sub‐optimal channel performance. That said, it is possible for both the firm and the platform to obtain higher profits under the agency contract than under the wholesale contract. Finally, we also demonstrate the robustness of our findings under several alternative model specifications.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

How Add‐on Pricing Interacts with Distribution Contracts

Geng

Tan

Wei

2018

Production and Operations Management

202

View full text Add to dashboard Cite

show abstract

“…In fact, revenue from ancillary services in the airline industry have nearly tripled in the past decade, from 3% to 8% of total revenue [19]. Studies on this new phenomena in the airline context are ongoing [1,6]. Economics literature indicates that the practice of offering add-ons (an equivalent term for ancillaries) can raise equilibrium profits when airlines compete; and can also be used for price discrimination and customer segmentation [8].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Pricing for Airline Ancillaries with Customer Context

Shukla

Kolbeinsson

Otwell³

et al. 2019

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &Amp; Data Mining

View full text Add to dashboard Cite

Ancillaries have become a major source of revenue and profitability in the travel industry. Yet, conventional pricing strategies are based on business rules that are poorly optimized and do not respond to changing market conditions. This paper describes the dynamic pricing model developed by Deepair solutions, an AI technology provider for travel suppliers.We present a pricing model that provides dynamic pricing recommendations specific to each customer interaction and optimizes expected revenue per customer. The unique nature of personalized pricing provides the opportunity to search over the market space to find the optimal price-point of each ancillary for each customer, without violating customer privacy.In this paper, we present and compare three approaches for dynamic pricing of ancillaries, with increasing levels of sophistication:(1) a two-stage forecasting and optimization model using a logistic mapping function; (2) a two-stage model that uses a deep neural network for forecasting, coupled with a revenue maximization technique using discrete exhaustive search; (3) a single-stage end-to-end deep neural network that recommends the optimal price. We describe the performance of these models based on both offline and online evaluations. We also measure the real-world business impact of these approaches by deploying them in an A/B test on an airline's internet booking website. We show that traditional machine learning techniques outperform human rule-based approaches in an online setting by improving conversion by 36% and revenue per offer by 10%. We also provide results for our offline experiments which show that deep learning algorithms outperform traditional machine learning techniques for this problem. Our end-to-end deep learning model is currently being deployed by the airline in their booking system.

show abstract

“…Bundling has been studied in different scenarios, such as when the bundle consists of a large number of products (Armstrong 1999, Fang andNorman 2006), when information goods are considered (Bakos andBrynjolfsson 1999, Geng et al 2005), when product functionalities are considered (Chen et al 2008, McCardle et al 2007), when products have network externality (Prasad et al 2010), when online retailers adopt a dynamic customized bundle pricing strategy (Jiang et al 2011), when bundling is compared with reserved product pricing (Prasad et al 2015), and when firms (such as hotels and airlines) bundle their core products with ancillary services (Cui et al 2018, Shugan et al 2017. This stream of bundling literature explores when and how bundling allows a firm to extract more consumer surplus, that is., from a firmconsumer perspective.…”

Section: Literature Reviewmentioning

confidence: 99%

Operational Role of Retail Bundling and Its Implications in a Supply Chain

Cao

Geng

Stecke

et al. 2019

Production and Operations Management

View full text Add to dashboard Cite

We study the impacts of retail bundling on a supply chain with a manufacturer and a retailer. The retailer orders a primary product from the manufacturer before demand uncertainty materializes, and can retail it in a bundle with a secondary product afterwards. Our findings reveal three effects of bundling. First, bundling can help a retailer mitigate the adverse consequences of demand uncertainty in the primary product and price‐discriminate customers of the secondary product. Second, bundling can lower the retailer’s wholesale‐price elasticity and partition the retailer’s ordering decision into bundling and no‐bundling regions, between which there is a marked drop in the retailer’s optimal order quantity. Third, bundling affects the manufacturer’s wholesale price decision in an unexpected way: The manufacturer may lower the wholesale price when the retailer bundles. Our analysis shows bundling benefits the manufacturer, but can sometimes hurt the retailer. Further, when uncertainty in retail order is considered, while the manufacturer always benefits from retail bundling in expectation, it might be worse off with bundling depending on the realization of the uncertain market size. This explains why retail bundling has been a concern to some major manufacturers whereas they do not prohibit bundling up front.

show abstract

Unbundling of Ancillary Service: How Does Price Discrimination of Main Service Matter?

Cited by 10 publications

References 26 publications

How Add‐on Pricing Interacts with Distribution Contracts

How Add‐on Pricing Interacts with Distribution Contracts

Dynamic Pricing for Airline Ancillaries with Customer Context

Operational Role of Retail Bundling and Its Implications in a Supply Chain

Contact Info

Product

Resources

About