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E-raamat: Collaborative Promotions: Optimizing Retail Supply Chains with Upstream Information Sharing

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This series reports on new developments in mathematical economics, economic theory, econometrics, operations research, and mathematical systems.

Manuscripts should be no less than 150 and preferably no more than 500 pages in length.

Promotions are at the same time beloved and feared by both food retailers and branded goods manufacturers in today's retail environment. Beloved because they attract smart customers and generate an immediate effect on a brand's sale. Feared because there is uncertainty about the competitors' behavior and the actual customer demand leading to high forecast errors. For the retailer, this results in a doom loop of over-or understocking with high inventory costs in the supply chain.

Collaboration between retailers and the manufacturer disentangles the doom loop. The thesis reveals the appropriate kind and timing of information and develops a so called Competition Index. Inventory in the supply chain is eliminated and the customer is served better at a lower price. Based on a joint inventory and pricing model and an empirical analysis, it shows that the supply chain efficiency gains from collaborative promotions result in a win for customers, retailers and the manufacturer.
1 Introduction
1(4)
2 Promotions and Collaboration in Retailing
5(12)
2.1 The German Market Situation
5(1)
2.2 Promotions
6(4)
2.2.1 Definition and Impact of Promotions
7(1)
2.2.2 Retail Price Formats
8(2)
2.3 Collaboration
10(5)
2.3.1 Collaborative Planning Forecasting and Replenishment
10(2)
2.3.2 Pros and Cons of CPFR
12(1)
2.3.3 The Competition Index
13(2)
2.4 Research Questions and Methods
15(2)
3 Literature Review
17(24)
3.1 Customer Demand in Promotions
17(6)
3.1.1 Stockpiling
18(2)
3.1.2 Brand and Package Size Switching
20(1)
3.1.3 Store-Switching
21(1)
3.1.4 Decomposition of Customer Demand in Promotions
22(1)
3.2 Retailer Decisions
23(8)
3.2.1 Promotion Pricing
24(5)
3.2.2 Retailer Inventory
29(2)
3.3 Supply Chain Collaboration
31(10)
3.3.1 The Value of Information Sharing
32(6)
3.3.2 Information Sharing in a Competitive Environment
38(3)
4 Retailer Competition
41(58)
4.1 Setup of the Retailer Game
41(6)
4.1.1 Sequence of Events
42(1)
4.1.2 Retailer Promotion Strategies
43(2)
4.1.3 Customer Demand
45(2)
4.2 Optimizing the Retailer's Decisions
47(12)
4.2.1 Newsvendor Problem: The Optimal Order Quantity
47(3)
4.2.2 Nash Equilibrium: The Optimal Promotion Frequency
50(9)
4.3 Information Scenarios
59(17)
4.3.1 Information from the Competition Index
59(2)
4.3.2 No Information Sharing Scenario
61(7)
4.3.3 Information Sharing Scenario
68(8)
4.4 The Value of Upstream Information Sharing
76(14)
4.4.1 Inventory Effect
77(3)
4.4.2 Frequency Effect
80(4)
4.4.3 Profit Effect
84(2)
4.4.4 Customer Welfare
86(4)
4.4.5 Manufacturer Benefits
90(1)
4.5 Extension: Asymmetric Retailers
90(6)
4.5.1 Asymmetric Mixed Strategy Equilibrium
90(6)
4.5.2 The Value of Information Sharing
96(1)
4.6 Summary
96(3)
5 Empirical Analysis
99(28)
5.1 The Data Set
99(4)
5.1.1 Description of the Data Set
100(1)
5.1.2 Competitive Landscape
101(2)
5.2 Retailer Strategies
103(9)
5.2.1 Price Ranges
104(1)
5.2.2 Price Levels
105(3)
5.2.3 Retail Price Format
108(1)
5.2.4 Promotion Frequency
109(2)
5.2.5 Strategies of Analyzed Retail Chains
111(1)
5.3 Customer Demand
112(6)
5.3.1 Price Sensitivity of Customer Demand
112(2)
5.3.2 Decomposition of Customer Demand
114(2)
5.3.3 Segmentation-Based Retailer Strategies
116(2)
5.4 Competition Index
118(3)
5.4.1 Order Quantity
119(1)
5.4.2 Competitive Pressure and the Competition Index
119(2)
5.5 The Value of Information Sharing
121(6)
5.5.1 Retailer Benefit
121(2)
5.5.2 Cusotomer Welfare
123(1)
5.5.3 Win-Win-Win Situation
124(3)
6 Conclusion and Managerial Insights
127(4)
6.1 Impact of Customer Demand
127(1)
6.2 Strategic Options for Retailers
128(1)
6.3 Improving Supply Chain Efficiency by Collaborative Promotions
129(2)
Appendix A A Proofs and Calculations
131(18)
A.1 Best Response for the Scenario No Information Sharing
131(13)
A.2 Best Response for the Scenario Information Sharing
144(5)
References 149