Points mechanisms and rewards programs

• Date: 01 June 2019
• Published date: 01 June 2019
• DOI: http://doi.org/10.1111/jems.12292

Received: 19 September 2017

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Revised: 8 September 2018

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Accepted: 15 September 2018

DOI: 10.1111/jems.12292

Points mechanisms and rewards programs

Emil Temnyalov

Department of Economics, University of

Technology Sydney, Sydney, New South

Wales, Australia

Correspondence

Emil Temnyalov, Department of

Economics, University of Technology

Sydney, Sydney 2007, NSW, Australia.

Email: emil.temnyalov@uts.edu.au

Abstract

I study points programs, such as frequent flyer and other rewards programs, as a

revenue management tool. I develop a two‐period contracting model where a

capacity‐constrained firm faces consumers who privately learn their valuations

over time. The firm cannot commit to long‐term contracts, but it can commit to

allocate any unsold capacity through a points program. This points scheme

creates an endogenous and type‐dependent outside option for consumers,

which generates novel incentives in the firm’s pricing problem. It induces the

firm to screen less ex interim, and to offer lower equilibrium prices, reversing

the intuition of demand cannibalization.

KEYWORDS

dynamic contracting, limited commitment, loyalty programs, points mechanisms, revenue

management, rewards programs

JEL CLASSIFICATION

D21, D42, D61, L86, L10, L93

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INTRODUCTION

Points programs are schemes where a firm creates a currency (e.g., frequent flyer miles or hotel guest points), designed

to influence consumers’choices and incentivize particular behavior. Such points are typically either bundled with the

purchase of another good (e.g., a flight or a hotel stay), or sold separately (e.g., through a credit card issuer or a bank).

Consumers accumulate this currency over time and eventually can redeem it for goods. Points programs are thus a type

of indirect allocation mechanism through which the firm allocates goods to some types of customers. The economics

literature on reward programs has generally focused on their role as a tool to build customer loyalty, or as a way for the

firm to introduce switching costs into the consumer’s choices. In this paper, I focus on a different, complementary

function of rewards programs as a way to implement dynamic pricing, where the firm offers consumers the option to

participate in a points program and to obtain the good through it with some probability.

Consider, for example, frequent flyer programs, one of the most well‐known types of such points mechanisms. In

practice, industry experts often describe such programs as a tool for airlines to sell “distressed inventory,”that is,

residual unsold capacity.

1

In recent decades, such programs have become one of the most significant drivers of

profitability in the airline industry, and also account for a significant share of seats.

2

Moreover, there is now a very

sizable market for airline miles: A majority of miles are in fact not earned by customers who fly with an airline, but sold

to banks, who prepurchase them from the airline and award them to their own customers as promotional incentives.

3

On average consumers collect points over a period of 30 months before they redeem them for an award seat, which

suggests that points programs also introduce a novel dynamic aspect into the firm’s pricing problem, in addition to the

usual revenue management question of how to set prices over time.

4

In the airline market, as well as in other industries

that fit my model, such as hotels and car rentals, the firm determines the rate at which points are issued, it sets the

prices that it charges for redemptions in terms of points, and it chooses how much capacity to make available for such

J Econ Manage Strat. 2019;28:436–457.wileyonlinelibrary.com/journal/jems436

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© 2018 Wiley Periodicals, Inc.

ORIGINAL ARTICLE

redemptions. Points mechanisms can therefore be a valuable revenue management and dynamic price discrimina-

tion tool.

A natural question in this setting is how the firm can use a points program in conjunction with its usual pricing

mechanism, to maximize revenues. Consider the pricing problem of a capacity‐constrained firm, as in the examples of

the airline and hotel industry. If the firm anticipates that demand in some particular period is low, it may optimally

decide to set prices such that it does not sell all of its capacity. The firm could in this case offer a points program

and allow some of its customers who participate in this program to redeem their points for some of the residual unsold

capacity. However, this introduces the possibility of demand cannibalization: Sophisticated consumers should

anticipate that they may obtain the good through the points program, which will affect the price they would be willing

to pay for the good outside of this program. The terms of the points program thus clearly affect the firm’s pricing

decisions. I show that this intuition for demand cannibalization is in fact incomplete: Although at any given price the

revenue‐generating demand for the good indeed decreases when the firm allows consumers to redeem their points for

the good, the firm’s optimal price is in fact lower when it offers this additional channel to obtain the good, and

moreover, in equilibrium the firm sells more units, in addition to whatever residual capacity is allocated through the

points program. The firm can use this as a form of endogenous pricing commitment and extract larger revenue overall,

even in the absence of competition, that is, in a setting where loyalty and switching costs cannot play any role.

I develop a screening model of points programs, to explain why such programs are profitable and how firms can

design them optimally. I consider a model where a seller, the firm (e.g., an airline), has a fixed capacity of a good to sell

to a population of buyers, the consumers. The seller and the buyers interact over two periods: Period 1 is an ex ante

contracting stage; period 2 is a standard spot market where the seller offers a mechanism to allocate its capacity among

the buyers. Consumers learn their willingness to pay over time: In period 1 they privately learn their type, a noisy signal

of their valuation for the good, whereas in period 2 they privately learn their exact valuations; the seller only knows the

distribution of buyers’valuations and types, as in the standard mechanism design problem. In this setting, I study the

problem of dynamic contracting with limited commitment: Suppose that in period 2 the seller has full commitment

regarding the contract it offers at that stage, but it cannot commit to it ex ante, in period 1. Instead, in period 1 the seller

can offer a points program to consumers, whereby it commits to allocate any unsold goods in period 2 among members

of the program. How does the ability to offer such a scheme affect the optimal mechanism in the later stage, and how

should the seller sell access to this scheme?

In my model, the points scheme provides the seller with one more tool to allocate its capacity dynamically, in

addition to the mechanism that it can offer in period 2. This is a natural way to introduce limited commitment into a

sequential screening model, which is motivated by the many examples of such points schemes in practice, such as

frequent flyer and hotel programs. This setting falls inbetween two alternative canonical assumptions regarding

commitment: In the sequential screening literature the seller is generally assumed to have full commitment, and hence

the ability to offer a two‐period mechanism; in the literature on dynamic mechanism design without commitment the

seller is assumed to have full commitment within each period, but no commitment at all regarding future periods. I

characterize the seller’s revenue from the optimal points mechanism, and find that it is larger than that in the optimal

static mechanism, but smaller than that in the optimal dynamic mechanism with full commitment. That is, the points

program provides the seller with a valuable type of commitment, which it can use to partially contract with future

buyers ex ante and increase its overall revenue. Contrarily, this type of program is not as valuable as the dynamic

mechanism that the seller would offer if it could fully commit to all future contracts ex ante.

The seller’s mechanism in period 2 has to be sequentially optimal, since the seller cannot commit to it ex ante. The

points program introduces an endogenous and type‐dependent outside option for consumers at this point: They can

obtain the good through the spot contract that the seller offers at that stage, or through the points program.

Redemptions through the points program generally involve rationing, since any residual capacity is allocated among all

members of the points program. The consumer’s trade‐off is whether to obtain the good with certainty at the seller’s

posted price, or with some probability through the points program. I show that this trade‐off separates consumer types

monotonically: In equilibrium in period 2 high types buy at the posted price, while low types choose the points lottery.

The price that the seller sets to induce such an allocation has to leave some rents to the high types, in addition to the

usual information rents that they receive due to private information. Hence by offering a points program ex ante, the

seller seemingly cannibalizes some of its demand in period 2.

Importantly, the optimal price is in fact lower than the optimal price in the standard static monopolistic screening

mechanism, andmoreover the marginal buyer type is lowerthan in the static mechanism. In other words, if the seller sells

points in period 1 it will subsequentlyoffer a contract whereby it sells moreunits in the spot market, at a lower price, and

TEMNYALOV

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