Price Discrimination Flashcards
Price Discrimination
a. Different units of a product are sold at different prices
b. Exploits differences in utility / willingness-to-pay
c. Goal: generate higher profit
Degrees of Price Discrimination (Pigou):
a. First degree: each customer pays as much as she is willing to pay (= perfect price discrimination)
b. Second degree: different prices are offered, and each customer self-selects one
c. Third degree: the company identifies and separates segments, and offers different prices to these segments
Types of Price Discrimination
- 1st degree - Negotiations, Auctions
- 2nd degree - Performance-based, Volume-based (nonlinear pricing), Regional
- 3rd degree - Regional, Person-based, Time-based, Multi-person pricing
Price Discrimination Based on Customer Segments
- Customers / segments differ in their willingness-to-pay
- Aggregation across customers results in the following price response function for the complete market: Q = 100 – 10 ∙ P
Price Discrimination Based on Customer Segments - Success factors
a. Information about the willingness-to-pay of different customers / segments
b. Ability to separate customers / segments (avoid arbitrage)
Bundling
- Bundling = Sales of different products as a bundle
- Types:
a. Pure bundling
b. Mixed bundling - Examples:
a. Opera: Season ticket
b. Restaurant: 3 course menu
c. Vacation package: flight + hotel
d. Trade show: booth space + services for exhibitors
Profitability of Bundling
a. Takes advantage of the asymmetry of willingness-to-pay
b. Additional utility through integration of products
e. g., purchase of booth & services as a bundle
c. Cost advantages
d. Price perception (integration of losses)
Pure vs. Mixed Bundling
- Mixed bundling often more profitable
a. Fewer legal restrictions
b. Higher profit, if
i. Willingness-to-pay differs across customers
ii. Competition - Pure Bundling more profitable for new products
a. –> brings all customers in contact with the new product
Nonlinear Pricing - general idea
a. Price per unit is different for different quantities
b. Second degree price discrimination (customers choose which quantity to buy)
c. Profitable because marginal utility decreases with increasing quantity
Nonlinear Pricing - Forms
a. Flat rate
b. All-units quantity discount
c. Two-part tariff
d. Optional (block) tariff
e. Price points
Biases in Tariff Choice
- Assumption so far: Customers maximize their consumer surplus
- However:
a. Some customers choose a flate rate, although they would pay less with a linear tariff (given the same number of articles).
b. Other customers prefer a linear tariff, although they would pay less with a flat rate.
Causes of
Causes of a flat rate bias:
a. Taxi meter effect
b. Self-control effect
c. Insurance effect
d. Habit effect
Causes of a Pay-per-use bias:
a. Flexibility effect
b. Habit effect
Implementation of Price Discrimination
- Avoid arbitrage, e.g.,
a. Exporting (discrimination by country)
b. Resale by the buyers (nonlinear pricing) - Measurement of willingness-to-pay at the individual level (nonlinear pricing: for different numbers of units)
- Optimization
- Communication
- Competitive reactions
- Legal aspects
Methods for Measuring Individual Willingness to pay
- Transaction Data:
a. Actual market transactions
b. Simulated test markets - Survey Data / Auctions / Lotteries:
Direct Elicitation
a. Open Ended: „How much are you willing to pay for product X? _______ €“
b. Closed Ended: „ Would you buy product X at the following prices?
i. 2.00 € yes/no
ii. 2.50 € yes/no
iii. 3.00 € yes/no
iv. …
c. Problems:
i. Difficult to state WTP directly (easier to trade-off with other product attributes)
ii. Hypothetical bias
Conjoint Analysis – Basics
a. Indirect Measurement of preferences: Trade-offs between product attributes
i. e.g.: What‘s more important – a lower price or a preferred brand?
b. Assumption: additive utility function
i. total utility = sum of part-worths for attribute levels
c. Products are presented to consumers who rank / rate / choose
i. derive preferences for attributes and their levels
d. Procedure:
i. Choose attributes and their levels
ii. Design stimuli
iii. Let respondents evaluate stimuli –> different types of conjoint analysis
iv. Estimate utility function
Types of Conjoint Analysis
a. Traditional conjoint analysis
i. Respondents rank order or rate stimuli
ii. Hardly used any more
b. Choice-based conjoint analysis (CBC)
i. Respondents choose one product from a choice set (no-choice option necessary for determining WTP)
ii. More realistic task than ranking or rating
c. Adaptive Conjoint Analysis (ACA)
i. 1st step: direct elicitation (= self-explicated approach) –> choose most important attributes
ii. 2nd step: conjoint analysis with pairwise comparisons
iii. Used when many attributes are relevant
Vickrey Auctions
a. Traditional auctions:
i. English auction: increasing bids, highest bidder wins
ii. Dutch auction: lower price until first bidder accepts
iii. Problem: no incentive to bid true WTP
b. Vickrey auction (Vickrey 1961) = sealed bid second price auction
i. All bidders hand in a sealed bid
ii. The highest bidder wins
iii. Price for winner = second highest bid
c. Vickrey auction is incentive compatible
i. –> bidders have incentive to bid true WTP
BDM
a. Procedure:
i. Participant states his WTP
ii. Lottery determines price
iii. If price < stated WTP, participant has to buy product for this price
b. Properties:
i. Incentive-compatible like Vickrey auction
ii. Easier to apply because each participant can be surveyed individually
Incentive-Aligned CBC
a. Procedure
i. Explain procedure to respondents
ii. Elicit preferences with CBC
iii. Use estimated part-worths to determine WTP for a real product
iv. Apply BDM to determine if and at what price respondent has to purchase product
b. Properties:
i. Incentive compatible like Vickrey auction and BDM
ii. Indirect measurement of WTP
Drivers & Implication
- Drivers: „hypothetical bias“ is larger for …
a. Indirect measurement than for direct measurement
b. Products with higher value
c. Specialty goods > shopping goods > convenience goods - Implication: Direct measurement seems to work well in practice, even though indirect measurement is more theoretically sound!
