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April 25, 2006
1
Teck-Hua Ho
Pricing and Consumer Search
I. Economic and Behavioral Foundations of Pricing
II. Innovative Pricing Concepts and Tools
III. Internet Pricing Models
April 25, 2006
2
Teck-Hua Ho
OutlineOutline
Convergence Hypothesis
Price Level: Bertrand Paradox
Price Dispersion: Economics of Search
Search Agents
Field Evidence on Price Levels and Dispersion
A Taxonomy of Competition
April 25, 2006
3
Teck-Hua Ho
Convergence HypothesisConvergence Hypothesis
“The explosive growth of the Internet promises a new age of perfectly competitive markets. With perfect information about prices and products at their fingertips, consumers can quickly and easily find the best deals. In this brave new world, retailers’ profit margins will be competed away, as they are all forced to price at cost.”
The Economist, November 20, 1999, p. 112.
April 25, 2006
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Teck-Hua Ho
Two Predictions about Internet Price Two Predictions about Internet Price Level and Price DispersionLevel and Price Dispersion
Prediction 1:
Price = Marginal Cost Retailers make zero profit
Prediction 2:
All retailers charge the same price Zero price dispersion
April 25, 2006
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Teck-Hua Ho
Price Level: Bertrand ParadoxPrice Level: Bertrand Paradox
A group of homogeneous consumers
There are two retailers who sell an identical good (e.g., “Strategic Pricing” book)
The two retailers have an identical marginal cost and are located next to each other. Consequently, consumers buy from the retailer who charges the lowest price
Bertrand shows that each retailer has a strong incentive to undercut the price of the other retailer (to capture the whole market) until both prices hit the common marginal cost
Price = Marginal CostRetailers make zero profit (even when there are only 2
firms competing)
April 25, 2006
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Teck-Hua Ho
Price Dispersion: Economics of Price Dispersion: Economics of SearchSearch
Price of Olympus D-360L Digital Camera:
Assume 50% of the stores price it at $300 and 50% of the stores price it at $200
The costs of search per store visit is $X
If the shopper visits only one store, she has a 50% chance of buying the product at $200 and a 50% chance of buying the product at $300. So the expected price is $250.
What is the expected price if she visits 2 stores?
April 25, 2006
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Teck-Hua Ho
Expected Price versus Number of Expected Price versus Number of SearchesSearches
She will have a 75% chance of buying the product at $200 and a 25% chance of buying it at $300. So the expected price is $225. In general, we have:
Number of Searches
Probability buying at $200
Probability buying at $300
Expected Price
1 0.5 0.5 $250
2 0.75 0.25 $225
3 0.875 0.125 $212.5
4 0.9375 0.0625 $206.25
5 0.96875 0.03125 $203.125n5.01 n5.0
April 25, 2006
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Teck-Hua Ho
Optimal Number of Search: Optimal Number of Search: The Impact of Search CostThe Impact of Search Cost
If $X is $10, what is the optimal number of search?
If $X is $5, what is the optimal number of search?
If $X is $0.25, what is the optimal number of search?
Number of Searches
Probability buying at $200
Probability buying at $300
Expected Price
1 0.5 0.5 $250
2 0.75 0.25 $225
3 0.875 0.125 $212.5
4 0.9375 0.0625 $206.25
5 0.96875 0.03125 $203.125
3
4
8
April 25, 2006
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Teck-Hua Ho
The Role of Search AgentsThe Role of Search Agents
Rental Car Company Economy Full-Size CarDollar 29.97 42.99Alamo 29.99 43.69Budget 54.99 63.99National 62.00 77.00AVIS 65.99 81.99
Travelocity (Lowest) 29.97 42.99
Encourages cross-store comparison and lowers the search costs for price information
Increases consumer price sensitivity
April 25, 2006
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Teck-Hua Ho
A Comparison of Search AgentsA Comparison of Search Agentswww.MySimon.com
www.DealTime.Com
www.Bizrate.com
Product MySimon DealTime BizRate
Canon PowerShot S2 IS
(Best)
$329.00 $329.00 $312.00
Canon PowerShot S2 IS
(Worst)
$447.00 $447.00 $399.99
Further reduces the search costs for price information!
April 25, 2006
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Teck-Hua Ho
SummarySummary
Prediction 1:
On internet, retailers who are selling identical goods and who are “next to each other” (in the e-space), engage in Bertrand price competition. Consequently, prices will be driven down to marginal cost.
Prediction 2:
On internet, search cost $0. Customers will all buy from the the cheapest stores and the more expensive stores will be driven out of the market.
April 25, 2006
12
Teck-Hua Ho
Field Evidence on Field Evidence on Price Levels and DispersionPrice Levels and Dispersion
Field study of books and CDs *Price levels: 9-16% lower on Internet than in B&MDispersion of posted prices: 25-33%, larger than in B&M (books only) Dispersion of “share-weighted” posted prices: lower than in B&MCheapest e-tailers did not get largest market share
Field study of online travel agents **The same customer request led to tickets offered with substantially
different prices and characteristics, 25% dispersionEven after controlling for differences in ticket characteristics, 20%
dispersion* Erik Brynjolfsson and Michael D. Smith, “Frictionless commerce? A comparison of Internet and conventional retailers,” Mgmt Sci, April 2000;
** Eric K. Clemons, Il-Horn Hann and Lorin M. Hitt, “The nature of competition in electronic markets: An empirical investigation of online travel agent offerings,” Working paper, The Wharton School, 1998.
April 25, 2006
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Teck-Hua Ho
Two Challenges to the PredictionsTwo Challenges to the Predictions
Non-price competition: Consumers care about other product attributes besides price. That is, products are always differentiated to some degree (e.g., brand, can be delivered sooner, better return policies, comes with superior post-sale services)
Search costs for quality information: If search costs for quality information are also lowered, customer price sensitivity may decrease. The net effect depends on the relative size of reductions in search costs for price and quality information
April 25, 2006
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Teck-Hua Ho
Search Costs versus Nature of Search Costs versus Nature of Competition Competition
Search Costs for Quality Information
Sea
rch
Co
sts
for
Pri
ce In
form
atio
n
Low High
Lo
wH
igh
Price Competition
Quality Competition
Value Competition
Minimal Competition
April 25, 2006
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Teck-Hua Ho
High Search Costs for both Price High Search Costs for both Price and Quality Informationand Quality Information B&M environment (e.g., buying a T-shirt on the streets of Bangkok,
Thailand)
April 25, 2006
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Teck-Hua Ho
Low Search Costs for both Price Low Search Costs for both Price and Quality Informationand Quality Information
www.peapod.com
06001
April 25, 2006
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Teck-Hua Ho
Field Evidence on Price Elasticity Field Evidence on Price Elasticity at Peapodat Peapod**
• Attributes for which more information is accessible online are more salient
• Sensory search attributes for which less information is available online are less salient
• Brand names are more important online, at least for products for which little attribute information is available online
• The combined effect of price and promotion is weaker online
* Alexandru Degeratu, Arvind Rangaswamy and Jianan Wu, “Consumer choice behavior in online and traditional supermarkets: The effects of brand name, price and other search attributes,” Int J of Res in Mktg, March 2000.
April 25, 2006
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Teck-Hua Ho
Wine Online: Wine Online: Experimental DesignExperimental Design
• There are 100 products (indexed by 1,2,3,…, 98, 99, 100) and 2 online stores
• Store 1 carries 1, 2, …, 39, 40, 81, 82, .., 99, 100 and store 2 carries 41,42, .., 79, 80, 81, 82, …, 99, 100
• Three independent variables; 1) Price-Usability (High or Low) 2) Quality-Usability (High or Low) and 3) Store Comparability (High or low) resulting in a 2x2x2 factorial design
• 72 participants, each is assigned to one of the 8 treatment conditions and makes 8 shopping trips
• Each product is on deal (15% lower) on four of the shopping trips
April 25, 2006
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Teck-Hua Ho
Wine Online: Wine Online: Dependent VariablesDependent Variables
Price sensitivity
Price elasticity
Quantity difference
Rated liking of the purchased wines
Retention: Willingness to subscribe to the same electronic-shopping wine service from homes
Market share of the common brands
April 25, 2006
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Teck-Hua Ho
Customer Price Sensitivity : Quality Customer Price Sensitivity : Quality UsabilityUsability
April 25, 2006
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Teck-Hua Ho
Customer Price Sensitivity:Customer Price Sensitivity:Store ComparabilityStore Comparability
April 25, 2006
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Teck-Hua Ho
Rated Liking of Purchased WinesRated Liking of Purchased Wines
April 25, 2006
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Teck-Hua Ho
RetentionRetention
Quality-Usability
Low (29%) and High (49%)
Store Comparability
Low (27%) and High (50%)
April 25, 2006
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Teck-Hua Ho
Market Share of Common Brands: Market Share of Common Brands: Distribution Distribution Common brands (Products 81, 82, …, 99, 100) Store Comparability
Low (35.9%) and High (26.2%)Benchmark 1: 33.3%
26.2 % is statistically smaller than 33.3%35.9% is not statistically different from 33.3%
Benchmark 2: 20%26.2% is statistically higher than 20.0%
What do these results mean for manufacturers?
April 25, 2006
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Teck-Hua Ho
PunchlinePunchline
Search Costs for Quality Information
Sea
rch
Co
sts
for
Pri
ce In
form
atio
n
Low High
Lo
wH
igh
PriceCompetition
Quality Competition
Value Competition
MinimalCompetition