Journal of Service Science and Management, 2011, 4, 507-512
doi:10.4236/jssm.2011.44058 Published Online December 2011 (
Copyright © 2011 SciRes. JSSM
Study on Revenue Management Considering
Strategic Customer Behavior
Chuiri Zhou1, Yu Wu2
1School of Management, USTC, Hefei, China; 2School of Management, USTC, Hefei, China.
Received September 14th, 2011; revised October 20th, 2011; accepted November 18th, 2011.
This article reviews the literatures of revenue management and introd uces the status of traditional research about per-
ishable products in this field. We analyze revenue management considering strategic customer behavior and the related
researches about dynamic pricing, finally we discuss the existing problems and suggest several future research direc-
Keywords: Strategic Customer Behavior, Revenue Management, Perishable Products, Dynamic Pricing
1. Introduction
Littlewood rule proposed by Littlewood in 1972 is con-
sidered as the beginning of research about perishable
products and service inventory management, and then it
evolved into modern revenue management (RM). From
the area of passenger transportation, revenue manage-
ment technology covers a variety of areas, including ser-
vices, manufacturing, and the growth trend continues.
Revenue management adopt a certain mechanism and
strategy, making supply limited and changing market
demands to achieve a balance, the goal of revenue man-
agement is to make an inventory distribution in different
price levels and achieve maximize revenues. The repre-
sentative book in this field is The Theory and Practice of
Revenue Management (Talluri and Ryzin 2005) [1], which
discusses the problem of revenue management compre-
hensively and deeply.
Some scholars in China also have done productive work
in revenue management. Professor Zhou Jing [2] ex-
pounds the model and method of revenue management.
The domestic research on the revenue management ma-
inly concentrated in the industries of shipping [3], avia-
tion [4-5], and car rental [6] or perishable products [7-8].
Lan Boxiong and Zhang Li [9] build an optimization
model of revenue management in high-speed railway line
for passenger traffic. Xu Yaqing etc [10] study the reve-
nue management problems under the situation of buyer
pricing and the seller pricing resp ectively und er th e back-
ground of a famous reverse auction site, research the Ran
Lun etc [11] analyses a single product dynamic pricing in
a robust model.
We found that the traditional literature and practice of
operation management usually consider the demand of
customer as exogenous (Shen and Su, 2007) [12]. For
example, assume the customer’s demand as a distribution
process, or specific function of price or other product att-
ributes (for example. quality). This structure of model ca-
tches customer demand in macro levels, customers are
unified and no difference. In this framework, customers
are passive and don’t participate in any decision-making
process, customer demand is only decided by some initial
assumptions of function or some distribution functions.
But in practice, customer demand is not always exo-
genous, customer decision making is not passive. They
have more options and initiative. In economy society,
customers can actively value products and then make
choices. Especially in the modern society, customers can
obtain the information through a lot of channels, infor-
mation b ecome mu ch tran sparen t, and cu stomers b ecome
more and more shrewd. Vendors want to sell products in
a high price, customers will wait for a lower price. A ze-
ro-sum game pricing decision is naturally unavoidable,
vendors always improve price strategy to get as much
profit as possible and customers always adjusted their
purchase plan to save more money.
Customers can choose whether and when to buy the
products. Vendors increasingly recognize that modern cu-
stomers are willing to wait to buy the products at lower
prices, namely, customers would make a choice between
buying at full price in the current and waiting for future
Study on Revenue Management Considering Strategic Customer Behavior
markdown, and we call these people as strategy custom-
ers. The consumers who are either to purchase immedia-
tely or to leave at once without buying, we call them
myopic consumers [13]. Although str ategic consumer be-
havior could potentially be a much broader concept, We
shall mostly use the term “strategic customer behavior”
to refer to the behavior of inter-temporal substitution be-
havior, when strategic customer realize the product they
want to buy maybe markdown in the future, they will
determine the time to purchase by considering the ex-
pectation of availability.
Ignoring the strategic customer decision-making pro-
cess may have a serious consequences, Aviv and Pazgal
[14] report that loss would reach to 20% because of ig-
noring strategic customer behavior, Besanko and Winston
[15] assesses the loss of profits would as high as 60%.
In recent years, strategic customer behavior aroused the
attention of operation manage ment researchers, such lite-
rature discussed revenue management theory of perish-
able products when facing strategies customers [12]. The
authors of such literatures are scholars in international
top business schools, such as the university of California,
Berkeley, Carnegie Mellon university, university of Chi-
cago, Colombia university ect, the paper mainly publi-
shed in many important international operation manage-
ment journal, for example, Management Science, Produ-
ction and Operations ManagementOperations Research,
Manufacturing & Service Operations Management.
2. Revenue Management Strategy of
Perishable Products
Early research on revenue management considering stra-
tegic customer behavior firstly concerned about the cus-
tomer’s response to the seller’s strateg ic pricing. Most of
these articles assume that the company make dynamic
pricing decision according to some established policies
(such as EMSR or GVR policy), then they analyse stra-
tegic customer’ optimal policy in this Setting. Wilson
and Anderson (2006) investigate the revenue implica-
tions of this kind of strategic waiting behavior and how
to set booking limits optimally. Zhou, Fan and Cho (2005)
focus on the optimal purchasing strategy of a single stra-
tegic customer facing the GVR policy, they derive the
threshold nature of the optimal purchasing policy and
find that strategic behavior may benefit the seller. As-
vanunt and Kachani (2006) formulate the customer’s
purchasing problem as an optimal stopping problem and
derive optimal conditions from both the EMSR and the
GVR pricing policies, and points out that if the seller
who does not consider strategic customer behavior will
cause significant loss. Because the EMSR and GVR po-
licies are derived under the assumption of myopic cus-
tomers, when the customers are strategic, this assumption
will have defects.
The existing revenue management literatures facing
strategic customer behavior are designed aiming at cus-
tomer’s strategic behavior. As Talluri and Van Ryzin [16]
put forward, the model considering strategic customer
behavior is fundamentally a kind of mechanism design
problem. According to the view, we group the relevant
literatures into following six categories.
2.1. Dynamic Pricing
Facing the customer’s strategic behavior, researchers still
focus on dynamic pricing which is th e traditio n al revenue
management strategy. However, it makes strategy design
more complex as the increasingly factors influencing dy-
namic pricing when the customer chooses the time of
purchase strategically.
One of The earliest papers which analyses optimal
dynamic pricing policy about strategic customer behavior
is proposed by Aviv and Pazgal [14]. They study the op-
timal pricing of selling limited quantity of seasonal goods
to the strategic customers, the seller as Stackelberg leader
announcing price, the customer as the follower deciding
their purchase behavior. They proved the existence of a
subgame-perfect Nash equilibrium and they assert that the
equilibrium is unique when vendor’s strategy is given.
Then Su [17] extended the research scope beyond price
mechanism, considering the heterogeneous of customers,
he find that whatever price up or down, optimal price pa-
th are dependent on customer constitutes in market. This
article mainly considers the valuations and waiting cost
in different customers, proving that the two together de-
termine the optimal pricing strategy. It also po int out that
strategic customer behavior not necessarily hurt the seller,
when supply is limited. Strateg ic low-valuation customer
will help the seller get higher profits from strategic high-
valuation one.
Elmalghraby et al. [18] investigate the optimal mark-
down mechanism in the presence of rational customers
with multiunit demands, comparing the different optimal
markdown mechanism in two different environment set-
tings, and find the differences in seller’s profits and the
optimal single product price. Levin et al. [19-21] resear-
ch the dynamic pricing of monopolistic company selling
a perishable product to the strategic customers. Gallien
[22] find that when selling limited inventory products to
arriving customers in a finite period, optimal price should
increase over time. Liu Xiaofeng and Huang Pei [23]
study the optimal dynamic pricing strategy based on stra-
tegic customers.
2.2. Capacity Rationing
Sellers often cause rationing risk (inventory shortag e) in-
tentionally because the shortage threaten will motivate
Copyright © 2011 SciRes. JSSM
Study on Revenue Management Considering Strategic Customer Behavior509
customers early buying in a high price, we call this strat-
egy as capacity rationing. Liu and Van Ryzin [24] study a
two stage capacity control model. The price in the second
stage is lower than that in the first stage, the customers
have different valuations to products, and they know the
product price path and full rate in each stage. Through
the capacity rationing, vendo rs can control fu ll rate, so as
to control the customer’s rationing risk. Liu and Van
Ryzin analyse and find that the option of capacity which
can bring seller largest benefit, and they also find th at the
optimal capacity quantity is influen ced between the price
changing range and the customer’s risk aversion degree
Zhang and Cooper [25] consider a two stage framewo-
rk in which capacity rationing is observable, and prove
the advantage of capacity rationing. It indicates that the
seller may limit quantities in the second stage when
company sells a single product through a two stage fra-
mework. Given a fixed inventory, the impact of rationing
is different when price is flexible or be fixed at a certain
level. For a fixed price, restricting availability at clear-
ance price can be advantageous to the firm even when
there is leftover inventory that will o therwise be wasted.
Su and Zhang [26] study how the availability of produ-
cts attracts the consumers, they put forward two strate-
gies to improve the seller’s profits. One is to use com-
mitment and the other one is to use availability guaran-
tees. They also prove that when seller uses a combination
of these two strategies can achieve optimal results. But
the article assumes that the consumers are perfect ra-
tional and they form rational expectations and make op-
timal decisions with perfect accuracy. It is actually not
inconsistent with the reality, and the article considers that
the consumers should be regarded as limited rational
decision makers in researc hes in the future .
2.3. Posterior Price Matching (Posterior PM)
Posterior PM policy is a market strategy which provided
by seller. If the seller decreases the price within a spe-
cific period, the customer will be promised to get the
price lower than the former price. The posterior PM po-
licy can effectively change customer’s buying behavior,
enticing customers to buy early.
Levin et al. [19] analyses revenue management of a
monopoly sellers who provide posterior price matching
policy, and probes in to the optimal strategy of price path
and price matching. Bu t they don’t consider the strategic
customer behavior.
Later Xu [27] study the posterior PM policy consider-
ing the strategic customers, discusses the optimum design
of compensation rate. But Xu assume that the quantity o f
customer is fixed, it has not taken demand uncertainty
and inventory investment decisions into account.
Assuming that ve ndors cannot guarantee the price path,
but may practice posterior price matching strategy, Lai et
al. [28] study the impact of posterior PM policy on cus-
tomer purchase behavior, vendor’s price, inventory stra-
tegy and expected profit. They find that the PM policy
reduces the strategic customer’s incentive of waiting, and
allows sellers to raise prices in regular selling season.
When the proportion of strategic customer is not small
and product evaluation is not very low or very high over
time, PM policy can greatly increase vendor’s profits.
The study found that this policy is insen sitive to the pro-
portion of consu mers who claim the refund. This implies
that a Pareto improvement for both the seller’s and the
custom er ’s p ayoff is possible unde r the PM polic y.
2.4. Advance Selling
Sellers can divide sale period into two stages, advance
selling period and spot markets period. The price at two
stages are different and the customers can make choice
when to buy.
Tang et al. [29] discusses the advance selling strategy.
At first, demand is uncertainty, retailer develops a pro-
gram called an “advance booking discount” (ABD) pro-
gram that entices customers to commit to their order at a
discount price prior to the selling season. It improves the
forecast and enables the retailer to place a more accurate
order at the beginning of the selling season, which in turn
reduces over-stock and under-stock costs and improves
customer service levels. The article evaluates the benefits
of the ABD program and characterizes the optimal dis-
count price that maximizes the retailer’s expected profit.
But they did not consider customer strategy behavior.
Seller needs not only select price but also make sure
providing how many products for advance selling when
facing the strategic customers. Yu et al. [30] consider a
seller with limited capacity who offer a single product to
customers at two stages. They find that the benefit of ad-
vance selling depend on factors such as unit cost, capaci-
ty level, advance and spot market size, and customer be-
havior. Particularly, they analyze when the seller should
order advance selling and whether advance price adds a
premium or a discount to the spot price, especially as a
function of available capacity and customer behavior.
2.5. Display Formats
An important factor should to be considered by strategic
customers in the purchase decisions is the availability of
product in the future, and the sales mechanism will in-
fluence the customer’s estimate of product availability.
Yin et al. [31] consider a retailer who sells a limited in-
ventory of a product over a finite selling season, using
one of two inventory display formats: Display All (DA)
and Display One (DO). Under the DA format, the retailer
Copyright © 2011 SciRes. JSSM
Study on Revenue Management Considering Strategic Customer Behavior
displays all available units so that each arriving customer
has perfect information about the actual inventory level.
Under the DO format, the retailer displays only one unit
at a certain time so that each arriving customer knows the
exact about product availability but not the actual inven-
tory level. We find that the DO format could potentially
create an increasing perception of scarcity among cus-
tomers, and hence it is better than the DA format.
Jerath et al. [32] also discusses the issues of product
availability. They use Hotelling model comparing the be-
nefits of using two ways, last-minute selling directly and
opaque intermediary. The article argues that last-minute
sales directly is preferred over selling through an opaque
intermediary when consumer’s valuation is high, other-
wise, opaque selling will d ominate. Moreover, opaque se-
lling becomes more and more preferred over direct last-
minute selling when demand increases. If there is no de-
mand uncertainty, firms will never use direct last-minute
2.6. Quick Response Mechanism
Quick response inventory practice (the joint of such as-
pects, reducing production leadtime, advanced informa-
tion system and continuous demand forecast improve-
ment) is usually applied to correct the negative influence
of supply and demand mismatch. Cachon and Swinney
[12] define the quick response as ability of adding in-
ventory after updating the demand information, and fur-
ther discuss the value of quick response. They divide the
customers into three kinds, bargain-hunters, myopic con-
sumers and strategic consumers.
Considering the future price, product availability and
other customer behavior, sellers and customers could ma-
ke optimal decision under rational expectations when they
find there are strategic customers in the market. Sellers
will reduce inventory and markdown, and they can con-
trol strategic customer behavior’s negative effects by qui-
ck response to impro ve b en efits.
Swinney [33] believe that the value of quick response
system is generally lower with strategic customers than
with myopic customers in the setting of product value is
uncertainty. When product prices are fixed, the seller
may reduce valuations uncertainty through advance sell-
ing, and quick response may reduce the possibility of
advance selling, with rapid fulfillment capabilities, the
firm loses its ability to credibly restrict inventory to cre-
ate a stock-out risk, and thus may reduce its overall prof-
itability in certain situations. Cachon and Swinney [34]
take the famous fashion enterprise Zara as background
context, discuss the influence of fast fashion system on
strategic customer purchase behavior. This paper compa-
res four different potential operation system: traditional
systems (with standard design efforts and slow produc-
tion), rapid production systems, enhanced design systems,
and fast fashion systems (with both enhanced design and
rapid production), and ch aracterize equilibrium in ventory
levels, prices, and consumer purchasing behavior in each
case. They finally find that the relationship between rapid
production and enhanced design is complemented but not
substituted because of multiple forces such as sales,
prices, and markdown costs.
3. Revenue Management Strategy of
Durable Products
The above revenue management object of our studies is
the perishable products. And the opposite of perishable
products is durable produ cts. Durable products means the
goods can be used for a long time after one purchase,
such as automobile, housing, etc. One product is durable
goods for consumers, but it may be perishable product
for manufacturers. For instance, to the most real estate
developers, because of its cost of funds and the loan re-
payment pressure, developers sell the housing as a per-
ishable product while customers consider it durable goods.
Another example is automobile, due to the rapid devel-
opment of new technology and new car introduced con-
tinuously, each type of car has the perishable product’'s
attributes in selling process. Durable products have per-
ishable product’s properties in sales management, we
consider that we can use revenue management methods
to study durable products, and in the current studies ther e
are only small literatures study the problems of durables
revenue management.
Desai et al. [35], Arya and Mittendorf [36] discuss ma-
nufacturers’ revenue management of durable-goods in the
presence of the strategic customers. They focus on dis-
cussing the influence of sales channel to the revenue of
manufacturer. After comparing the centralized channels
and decentral channels, they find that in certain condi-
tions, the decentral channels can increase the manufac-
turers’ profits if manufacturers could promise seller fu-
ture wholesale prices. Arya and Mittendorf also consider
that decentral channels will bring robust revenue relative
to the manufacturer’s promise.
The above researches about durable products mainly
discussed how to determine the dynamic pricing in long-
term selling period, they all assume that the supply of
products is infinite and they don’t take inventory con-
straint into account.
4. Conclusions and Prospect
The revenue management research considering strategic
consumer behavior is an emerging research field, the
existing researches have not been formed systematically,
and many aspects need to be further developed.
First, the customer’s behavior we have discussed in the
Copyright © 2011 SciRes. JSSM
Study on Revenue Management Considering Strategic Customer Behavior511
articles is too simple, which mainly be concerned about
strategic behavior, and yet there are still many other fac-
tors influencing the customer’s demand and these various
factors are being influenced each other. Secondly, the
existing research about the design of revenue manage-
ment mechanism is focused on a specific aspect of cus-
tomer behavior, the theoretical research haven’t formed
systematically. Since revenue management is manage-
ment of demand, future research can be deepened from
the aspect of customer behavior. We can classify the cu-
stomer’s behavior motivation, and design a revenue ma-
nagement mechanism based on a various customer be-
havior motivation, which will make the revenue man-
agement mechanism designing more systematic. In addi-
tion, the research method we used needs to be improved.
It has appeared experimental research method in behav-
ioral operations management literature, yet which make
theoretical research going further. However, we have not
yet seen the research about revenue management mecha-
nism based on the customer behavior till now. Because
of the behavior complexity, the models established by the
hypotheses need to be verified by experiments.
Revenue management is a promising field of study. Su
and Zhang [26] consider that model formulating with cu-
stomer behavior in all kinds of operation management
studies will be a fruitful topic in the future. Dana [37] al-
so proposed that revenue management researchers should
consider creating a more accurate customer behavior mo-
del. Meanwhile, Dana believes that the research about
revenue management considering customer behavior will
be very exciting in the next ten years.
5. Acknowledgements
This work was supported by Ministry of Education PR
China HCSSF(10YJC630415), USTCYF(2010) and ANSF
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