Pricing and Supply Chain Management in Electronic
Commerce
Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
University of Rochester
Rochester NY
14627
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Trends in Supply Chains & Electronic Commerce
• ECR, CRP
• New Distribution Channels
• Outsourcing of Supply Activities
Pricing Issues Are Important In All of These
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Economic Factors Driving Supply Chain DevelopmentsComplementarities Between
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Economic Trends Driving These Developments
• Lower IS Costs – IS Costs Drive
• Search and information costs• Monitoring and control costs
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Economic Trends Continued
• More Efficient Operations Technologies– BPR– JIT
• Innovative Contracts– Redefining Services– Longer Term Relationships– Joint Investments and Risk Sharing
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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How Pricing/Contracting Interacts With Supply Chains In
Electronic Commerce
• Why Have New Contracting Forms Arisen In Supply Chains?
• What Are Pricing Opportunities With ELP?
• How Do New Distribution Channels Affect Technology Adoption and Pricing Policies?
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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We Present Three Case Studies
• ECR For Custom Manufacturer– New Contract Relationship
• P&G ELP Pricing Policy – Use of Uniform Delivered Pricing
• Distribution Channels For Banking Services– Electronic Channels & Branches– Pricing These Services
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Case Study I: Central Printers
• Largest Printer of Canned Labels In US
• Has Adopted A Number of Innovative Supply Chain Strategies
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Central Printers, Continued
• Before:
• Printer --- Super Market Chain --- Packer
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Central Printers, Continued, • After:
• Printer --- Super Market Chain --- Packer
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Key Changes That Central Printer Made
• Eliminated One-Echelon
• Changed Contract Agreement– Printer Managed (and Owned) Inventory For
Client– Service Terms plus Price Negotiated– Obsolescence Costs Imposed on Client
• Improved Operational Capability
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Improvement Required New Contract Arrangement
• Key Change Was Central Printer Guaranteeing Service Level
• Central Printer Needs To Make Both The Capacity and The Inventory Decision
• An Agency Conflict Occurs If Central Printers Makes Inventory Decision For Client
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Generalization• An “Agency” Problem Exists When One
Party Makes Production Decisions and Another Makes Inventory Level Decision
• Typical Decisions Made In Chain– Supplier: Wholesale Price
Factory Inventory– Customer Retail Price
Local Inventory
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Examples of Literature
– Kandel 1990 – Lariviere and Porteus 1995 – Zipkin and Cashon 1997– Anupindi and Bassock 1998
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Key Problem: “Double Marginalization”
• To Maximize Chain Profit, Agent’s Profit Incentives Must Be Aligned;
• Decentralized Decisions Are Suboptimal
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Problems Creating Alignment
• Differences in Profit Margins
• Differences In Inventory Holding Costs and Stockout Costs
• Differences In Information About The Demand Distribution
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Typically
• Decentralized Inventory Decisions– Reduce Chain Profit Due to
• High Prices• Low Service Levels• Low Inventory
• Independent of the Agency Problem– Inventory Stocking Locations Not Optimized
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Solutions• Service Levels Are Set With Penalties For
Stockouts
• Return Policy For Output
• Producer Makes Production and Inventory Decisions– Vendor Managed Inventory– Consignment System
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Case Study II: P&G’s ELP Pricing Policy
• Identical Delivered Prices To All Customers– Formerly, Customers Paid Freight
• Fixed Prices With Allowances For Yearly Volume– Eliminated Forward Buying– Reduced Variability in Factory Loading– Reduced Billing Errors
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Case Study, Continued
• We Study The Effect of ELP On Pricing Strategy and Profits
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Example: Sunny Delight
*
*
* *
x
Analysis: Let A Firm Have Three Plants
• It Sets A Mill Price From One of ThemProfile of Prices and Costs
mill site
factory 2 factory 1 factory 3
delivered mill price
mill price
t1t’
We Assume Demand Drops With Price
mill site
factory 2 factory 1 factory 3
delivered mill price
demand
mill price
Pattern of Costs, Demand Under Mill Pricing
mill site
factory 2 factory 1 factory 3
delivered mill price
demand
mill price
t1t’
Pattern of Margins, Demand Under Mill Pricing
mill site
factory 2 factory 1 factory 3
delivered mill price
demand
mill price
t1t’
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Now, Let Us Evaluate ELP-
• Every Customer Pays The Same Delivered Price
Pattern of Margins, Demand Under Uniform Pricing
mill site
factory 2 factory 1 factory 3
delivered mill price
demand
mill price
t1t’
Uniform Price
Uniform Demand
Pattern of Costs, Demand Under Uniform Pricing
mill site
factory 2 factory 1 factory 3
delivered mill price
demand
mill price
t1t’
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Profits Increase With Uniform Pricing
• Further Opportunities Due To– Optimization of Plant/Warehouse Locations– Avoidance of Product Diversion to Other
Channels/Customers
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Case Study III: Home Banking Services
• Banks Have The Opportunity Of A New Distribution Channel
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Opportunity of New Distribution Channels
• Reduces Bank Long Term Cost
• Increases Service Level To Some Segments and Allows New Products That This Segment Favors
• Threat Potential Entry By E-Banks Sidestepping Traditional Retail Banking
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Creation of Pricing and Segmentation Strategies For
Home Banking Is A Key Issue
• This Is Also A Key Issue For Many Firms Selling Products Into Supply Chains
• Especially Supply Chains That The Firm Does Not Have Control Over
Table: Segmentation of Bank CustomersHigh-Profit Caut ious Professional Homet own
Balances High High Med/ Low Med/ LowBranch-basedt ransactions
Low/M ed high Low High
Usage ofelect ronicsystems (ATM,direct deposit ,etc ...)
Med/H igh Low High Low
Usage of fee-generatingservices
High Low Med/H igh Low
Profitability High Marginal High/M edium Unprof it able
Segmentation Is A Key Issue
• Example of Segmentation Model:
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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A Model of Bank Distribution System Design
• Two Segments – E (Disposed To Electronic Distribution)– B (More Comfortable With Branch Based)
• Two Distribution Channels:
–e- Electronic Distribution
–b-Branch or ATM Distribution
Each Segment Values Distribution Channel Differently
• Utility of e by B = - Price(e)
• Utility of b by E = - Price(b)- travel cost*distance
• Utility of b by B = - Price(b) - travel cost*distance
• Utility of e by E = - Price(e)
RBeUB
e
UEb RE
b
UBb RB
b
UEe RE
e
Individual Rationality
• Customers Are Offered Services By Non-Bank Providers
• Net Utility To Customer Must Exceed This Utility:
Max(UEb ,UE
e ) ≥ UE
Max(UBb ,UB
e ) ≥ UB
Incentive Compatibility
• If Branch and Electronic Services Are Offered, – Then Pricing Decisions Must Induce The
Segments To Purchase The Appropriate Product:
UEe ≥ UE
b
UBb ≥ UB
e
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Profit Maximization and Market Entry
• Banks Decide on Branch Locations
• Banks Decide Whether to Offer Branch and Electronic Services, and Their Prices
• Bank’s Objective Is To Maximize Profit
• There Will Be Entry and Expansion Into The Market So Long As Profit Opportunity Exists
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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We Seek To Find The Equilibrium Number and Type of
Banks Assuming:
• Profit Maximizing Behavior
• Incentive Compatibility and Individual Rationality of Customers
• Free Entry
Results
• Industry Channel Choice– Considering Cost/Transaction
Electronic
Mixed
0.5 0.75 10.25
0.25
0.5
0.75
1
1.25
1.5
1,75
2
2.25
2.5
ce
cb
2.75
3
Thisregion notallowed inmodel
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Mixed Delivery System Blocks Entry
• A Prediction of the Model Is That E-Banks Will Not Succeed
05/24/10 ©Professor Phillip J. LedererWilliam E. Simon Graduate School of Business Administration
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Avenues For Further Research
• Explore the Impact of Partition of Decisions on Inventory/Capacity /Stocking Locations on Chain Performance
• Empirical Research on Use of Uniform Pricing
• Further Exploration of Channel Pricing Models Considering IR/IC
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