Hamburg International Conference of September Risk and Capacity Management in Logistics Networks

Transcription

1 Hamburg International Conference of Logistics 2008 Logistics Networks & Nodes September 2008 Risk and Capacity Management in Logistics Networks Prof. Dr. S. Zelewski, PIM, University Duisburg-Essen/Germany Prof. Dr. M. Klumpp, KCL, FOM Essen/Germany* Dr. S. Hohmann, IPLPerseco Duisburg/Germany *Presenting Author, 1

2 Agenda 1. Background International SCM & Logistics 2. Practical Problem Description 3. Case Study Setting & Results 4. Model Suggestion & Example 5. Conclusions 2

3 1. Background Global SCM Company A (Procurement, Europe) Supply Chain Co-operation Company B (Supplier, Asia) Capacity Adjustment by Reservations, Delays, Cancellations and Cancellation Fees, Nontarif Measurements Operator, i.e. Logistics Services Provider Transport Way e.g. Hong Kong Antwerp Logistics Capacities Risks - Planning - Scheduling - Fulfillment - Event Management 3

4 2. Practical Management Problem IPLPerseco offers fully globally leveraged Promotion + Packaging g + Purchasing Services to its customers in Europe receiving more than 720 million promotional items in 44 countries and 1,250 million packaging items in 25 countries p.a. handling 3,000 import containers annually (Far East, China, Vietnam) and 100 export containers (40 ). Carriers use guarantee for space commitments (p.a.) and fixed allocations (weekly). Unused allocations may result in carriers reducing overall space commitment. In case no other sea freight slot is available sea/air or air freight has to be used. Alternatives can be calculated as follows: On the transport route South of China Central Europe costs for a 40 feet container are about 2,300 $ for sea transport, 20-30,000 $ for sea/air transport (e.g. Dubai) and 40-50,000 $ for air transport. 4

5 Sample Characteristics: 3. Case Study Research and Data Altogether th 33 business cases reported / represented Therein: 8 logistics service providers 4 industry OEM 4 trading companies Industries: Automotive, textile, defense, general industry, services Sizes: More than 50% larger than 500 employees 5

6 3. Case Study Research and Data 6

7 3. Case Study Research and Data 7

8 3. Case Study Research and Data > In General: Meager Use of Formalized Steering Instruments 8

9 4. Model Suggestion Background: Shapley Value Usually a Shapley-Value l defines the additional gain (e.g. cost savings) by including a further partner into a co-operation (e.g. in order to reach economies of scale in transport t and storage). A modified Shapley Value is suggested here in order to model the exclusion of one partner because of capacity restrictions in a logistics setting (transport or storage) wherein this value would indicate the excess burden for an excluded partner as he would be obliged to procure spot market transport or storage capacities. 9

10 4. Model Suggestion Formalized Model for Marginal Coalitions / Capacity Management 10

11 4. Model Example Four companies na 1-4 with specific transport demands. Capacity demand d in total t with 13 exceeding supply (10). accessible capacity ka = 10 missing capacity Δka = 3 na 1 = 6 na 2 = 4 na 3 = 2 na 4 = 1 11

12 4. Model Example Coalition S_n Transport Demand of Coalition S_n Coalitionion S_n \ {1} Transport Demand of Coalition S_n \ {1} Additional Spot Market Costs K(S_n) - K(S_n\{1) for Transport Demand of Partner P_1 Weighting g(s_n) of Coalition S_n Shapley Value Fraction as g(s_n) * K(S_n) - K(S_n\{1}) S_1 1={1234}13 {1,2,3,4} 13 > ka {234} {2,3,4} 7 ka 120 1/4 30 S_2 = {1,2,3} 12 > ka {2,3} 6 ka 120 1/12 10 S_3 = {1,3,4} 9 ka {3,4} 3 ka 0 1/12 0 S_4 = {1,2,4} 11 > ka {2,4} 5 ka 120 1/12 10 S_5 = {1,2} 10 ka {2} 4 ka 0 1/12 0 S_6 = {1,3} 8 ka {3} 2 ka 0 1/12 0 S_7 = {1,4} 7 ka {4} 1 ka 0 1/12 0 S_8 = {1} 6 ka {} 0 ka 0 1/4 0 Modified Shapley 50 Value SW_1 Coalition S_n Transport Demand of Coalition S_n Coalitionion S_n \ {2} Transport Demand of Coalition S_n \ {2} Additional Spot Market Weighting g(s_n) of Shapley Value Costs K(S_n) - K(S_n\{1) Coalition S_n Fraction as g(s_n) * for Transport Demand of K(S_n) - K(S_n\{2}) Partner P 12 {2} Partner P_12 S_1 = {1,2,3,4} 13 > ka {1,3,4} 9 ka 80 1/4 20 S_2 = {1,2,3} 12 > ka {1,3} 8 ka 80 1/12 6 2/3 S_3 = {1,2,4} 11 > ka {1,4} 7 ka 80 1/12 6 2/3 S_4 = {2,3,4} 7 ka {3,4} 3 ka 0 1/12 0 S_5 = {1,2} 10 ka {1} 6 ka 0 1/12 0 S_6 = {2,3} 6 ka {3} 2 ka 0 1/12 0 S_7 = {2,4} 5 ka {4} 1 ka 0 1/12 0 S_8 = {2} 4 ka {} 0 ka 0 1/4 0 Modified Shapley 33 1/3 Value SW_2 12

13 4. Model Example Coalition S_n Transport Coalitionion Transport Additional Spot Market Weighting g(s_n) of Shapley Value Demand of S_n \ {3} Demand of Costs K(S_n) - K(S_n\{1) Coalition S_n Fraction as g(s_n) * Coalition S_n Coalition S_n for Transport Demand of K(S_n) - K(S_n\{3}) \ {3} Partner P_ 13 S_1 = {1,2,3,4} 13 > ka {1,2,4} 11 > ka 0 1/4 0 S_2 = {1,2,3} 12 > ka {1,2} 10 ka 40 1/12 3 1/3 S_3 = {1,3,4} 9 ka {1,4} 7 ka 0 1/12 0 S_4 = {2,3,4} 7 ka {2,4} 5 ka 0 1/12 0 S_5 = {1,3} 8 ka {1} 6 ka 0 1/12 0 S_6 = {2,3} 6 ka {2} 4 ka 0 1/12 0 S_7 = {3,4} 3 ka {4} 1 ka 0 1/12 0 S_8 = {3} 2 ka {} 0 ka 0 1/4 0 Modified Shapley Value SW_3 3 1/3 Coalition S_n Transport Coalitionion Transport Additional Spot Market Weighting g(s_n) of Shapley Value Demand of S_n \ {4} Demand of Costs K(S_n) - K(S_n\{1) Coalition S_n Fraction as g(s_n) Coalition S_n Coalition S_n for Transport Demand of * K(S_n) - \{4} Partner P_14 K(S_n\{4}) S_1 = {1,2,3,4} 13 > ka {1,2,3} 12 > ka 0 1/4 0 S_2 = {1,2,4} 11 > ka {1,2} 10 ka 20 1/12 1 2/3 S_3 = {1,3,4} 9 ka {1,3} 8 ka 0 1/12 0 S_4 = {234} {2,3,4} 7 ka {2,3} 6 ka 0 1/12 0 S_5 = {1,4} 7 ka {1} 6 ka 0 1/12 0 S_6 = {2,4} 5 ka {2} 4 ka 0 1/12 0 S_7 = {3,4} 3 ka {3} 2 ka 0 1/12 0 S_8 = {4} 1 ka {} 0 ka 0 1/4 0 Modified d Shapley Value 1 2/3 SW_4 13

14 5. Conclusions a) Settings with capacity demand > supply in logistics networks distinctively different from standard d situations ti b) Existing models do not provide sufficient management guidance to handle such situations c) The presented modified Shapley value may yprovide a sufficient and innovative approach towards rational solutions d) LSP may align reaction tools accordingly - though in business practice price transparency may not be given e) Further research is needed to establish benchmarking values and comparison conditions in order to provide pricing ranges 14

15 Hamburg International Conference of Logistics 2008 Logistics Networks & Nodes September 2008 Risk and Capacity Management in Logistics Networks Prof. Dr. S. Zelewski, PIM, University Duisburg-Essen/Germany Prof. Dr. M. Klumpp, KCL, FOM Essen/Germany* Dr. S. Hohmann, IPLPerseco Duisburg/Germany *Presenting Author, Thank you very much for your attention. 15