Vous êtes sur la page 1sur 2

Group 4

Asheek (08) l Hashil (24) l Prashant (47) l Pratima (48)

Summary: The Influence of Price Discount Framing on the Evaluation of

Product Bundle

The emphasis on using bundling as a strategy for extracting consumer surplus has led to the
development of methods for identifying the optimal composition and pricing of bundles for a
given distribution of consumer preferences. Constructing attractive bundle offers depends on
more than an understanding of the distribution of consumer preferences. Consumers are also
sensitive to the framing of price information in a bundle offer.
Bundle offers consisting of two or more products often include a price discount. The impact of
the price discount on the perceived attractiveness of the bundle has been shown to depend on
which product is discounted. It has been argued that discounts are more effective when they are
assigned to the product that will receive the most weight in the overall evaluation of the bundle.
We propose that the perceived value of the discount may also depend on a referent specific to
each product.

The studies are used to provide evidence that

(1) price discount framing effects can be explained by reference dependence and
(2) that reference dependence and product importance independently contribute to price
discount framing effects.

Multiproduct bundling involves the selling of two or more products or services at a price that is
equal to, or lower than, the combined prices of the individual products.

The Economics of Bundling

Firms engage in bundling because it is an effective strategy for extracting consumer surplus in a
market of heterogeneous buyers

Weighted Additive Model

The differential benefit of assigning a discount to one or another product in the bundle to the
unequal weight consumers use to sum the values of the individual product offers included in the

Reference-Dependent Model

The model relies on a value function that has three characteristics.

1. the value function defines gains and losses relative to a reference point rather than a final
state of wealth (i.e., reference dependence).
2. The value function has diminishing marginal returns for gains (i.e., concavity) relative to
a referent and increasing marginal costs for losses (i.e., convexity) relative to a referent
(i.e., diminishing sensitivity).
3. The value function is steeper for losses than it is for gains (i.e., loss aversion). In
addition, compound prospects are assumed to consist of independent values that can be

The reference-dependent model provides an alternative explanation of why people prefer a

bundle that assigns the price discount to one or another product in the bundle.

When price discounts are assigned to an individual product in a bundle, the value of these
discounts are referent dependent. Price referents anchor the value of a market-priced product
offer on a value function, and price discounts are valued as movements along the value

If the value of bundled offers depends on product-specific referents, then it is important to

anticipate how these referents will be generated, their level of specificity, and the extent to
which they will remain stable. The results suggest that people use a referent based on an
integration of the product attributes (i.e., reference price), as opposed to an array of referents
for individual product at-tributes.

To appreciate this distinction, consider two different assumptions about how people assess
the attractiveness of an offer for a single product. An offer’s value could be determined by
comparing each attribute of the offer to its own referent using a value function and then
summing these referent-based values.

When both of the products in the bundle have an offer price above the consumer’s reference
prices, the price discount should be segregated and partially as-signed to each product. When
both of the products in the bundle have an offer price below the consumer’s reference prices,
the price discount should be listed as a separate item. In each case, the goal is to let the price
discount alter value from a point on the steepest portion the value function.