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Integration of cuckoo search and fuzzy support vector machine for intelligent diagnosis of production process quality
Assembly system with omnichannel coordination
1. | Business School, Nanjing Normal University, Qixia District, Nanjing 210023, China |
2. | Stern School of Business, New York University, 44 West Fourth Street, New York, NY 10012, USA |
3. | Supply Chain and Logistics Management Research Lab, Department of Business Administration, School of Business, Soochow University, Taipei, Taiwan |
Assembly system with omnichannel is rarely studied in literature. This paper explores the equilibrium and coordination issues for an omnichannel assembly system. Four different game-theoretical model types applying four operational strategies - a total of sixteen analytical models - are developed and analyzed for both omnichannel and pure channel modes. The numerical analysis of an electronic product assembly system provides a clearer understanding of the solutions and their effects on the profits in the assembly system for different model types and operational strategies. A further sensitivity analysis with focus on an omnichannel with offline channel subsidy (OMS) creates better insights regarding how changes of key parameters affect the assembly system profits. It is found that the omnichannel mode with or without offline channel subsidy can deliver much better operational performance to the assembly system via mutual fusion effect than that of a pure online- or offline-channel mode. Furthermore, the offline channel subsidy can amplify to a very large extent the mutual fusion effect to increase the product demand dramatically and thus improving the operational performance of the assembly system in the omnichannel business scenario. The best operational strategy for the assembly system in the omnichannel business scenario is the coordination strategy with offline channel subsidy.
References:
[1] |
G. P. Cachon and M. A. Lariviere,
Supply chain coordination with revenue-sharing contracts: Strengths and limitations, Management Science, 51 (2005), 30-44.
doi: 10.1287/mnsc.1040.0215. |
[2] |
G. Cai,
Channel selection and coordination in dual-channel supply chains, Journal of Retailing, 86 (2010), 22-36.
doi: 10.1016/j.jretai.2009.11.002. |
[3] |
S. M. Carr and U. S. Karmarkar,
Competition in multiechelon assembly supply chains, Management Science, 51 (2005), 45-59.
doi: 10.1287/mnsc.1040.0216. |
[4] |
X. Chen, X. Wang and X. Jiang,
The impact of power structure on the retail service supply chain with an O2O mixed channel, Journal of the Operational Research Society, 67 (2016), 294-301.
doi: 10.1057/jors.2015.6. |
[5] |
Z. Chen, L. Fang and S. I. Su,
The value of offline channel subsidy in bricks and clicks: An O2O supply chain coordination perspective, Electronic Commerce Research, 273 (2019), 1-45.
doi: 10.1007/s10660-019-09386-z. |
[6] |
Z. Chen and S. I. Su, Consignment supply chain cooperation for complementary products under online to offline business mode, Flexible Services and Manufacturing Journal, (2020).
doi: 10.1007/s10696-020-09376-6. |
[7] |
DT News Network, Dell EMC Believes in an Omni Channel Strategy, 2017. Available from: http://digitalterminal.in/news/dell-emc-believes-in-an-omni-channel-strategy/8853.html. Google Scholar |
[8] |
W. Duggan, What does O2O mean for the future of E-Commerce?, Yahoo Finance, (2015). Google Scholar |
[9] |
A. Dumrongsiri, M. Fan, A. Jain and K. Moinzadeh,
A supply chain model with direct and retail channels, European Journal of Operational Research, 187 (2008), 691-718.
doi: 10.1016/j.ejor.2006.05.044. |
[10] |
F. Gao and X. Su,
Omnichannel service operations with online and offline self-order technologies, Management Science, 64 (2018), 3595-3608.
doi: 10.1287/mnsc.2017.2787. |
[11] |
F. Gao and X. Su,
Omnichannel retail operations with buy-online-and-pick-up-in-store, Management Science, 63 (2016), 2478-2492.
doi: 10.1287/mnsc.2016.2473. |
[12] |
Investopedia, Online-to-Offline Commerce, 2018. Available from: https://www.investopedia.com/terms/o/onlinetooffline-commerce.asp#ixzz5GNPyJCIX. Google Scholar |
[13] |
J. Ji, Z. Zhang and L. Yang,
Comparisons of initial carbon allowance allocation rules in an O2O retail supply chain with the cap-and-trade regulation, International Journal of Production Economics, 187 (2017), 68-84.
doi: 10.1016/j.ijpe.2017.02.011. |
[14] |
Y. Jiang, L. Liu and A. Lim,
Optimal pricing decisions for an omni-channel supply chain with retail service, International Transactions in Operational Research, 27 (2020), 2927-2948.
doi: 10.1111/itor.12784. |
[15] |
L. Jiang and Y. Wang,
Supplier competition in decentralized assembly systems with price-sensitive and uncertain demand, Manufacturing & Service Operations Management, 12 (2010), 93-101.
doi: 10.1287/msom.1090.0259. |
[16] |
B. Kalkancl and F. Erhun,
Pricing games and impact of private demand information in decentralized assembly systems, Operations Research, 60 (2012), 1142-1156.
doi: 10.1287/opre.1120.1084. |
[17] |
Kjmx, Hardware cost disclosure of Huawei, apple, Samsung and Xiaomi, how much is the profit margin of each manufacturer?, Available from: http://finance.sina.com.cn/stock/relnews/us/2019-06-29/doc-ihytcerm0232231.shtml. Google Scholar |
[18] |
L. Kong, Z. Liu, Y. Pan, J. Xie and G. Yang,
Pricing and service decision of dual-channel operations in an O2O closed-loop supply chain, Industrial Management & Data Systems, 117 (2017), 1567-1588.
doi: 10.1108/IMDS-12-2016-0544. |
[19] |
M. A. Lariviere,
A note on probability distributions with increasing generalized failure rates, Operations Research, 54 (2006), 602-604.
doi: 10.1287/opre.1060.0282. |
[20] |
M. A. Lariviere and E. L. Porteus,
Selling to the newsvendor: An analysis of price-only contracts, Manufacturing and Service Operations Management, 3 (2001), 293-305.
doi: 10.1287/msom.3.4.293.9971. |
[21] |
N. M. Modak,
Exploring Omni-channel supply chain under price and delivery time sensitive stochastic demand, Supply Chain Forum: An International Journal, 18 (2017), 218-230.
doi: 10.1080/16258312.2017.1380499. |
[22] |
N. M. Modak and P. Kelle,
Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand, European Journal of Operational Research, 272 (2019), 147-161.
doi: 10.1016/j.ejor.2018.05.067. |
[23] |
M. Nagarajan and Y. Bassok, A bargaining framework in supply chains: The assembly problem, Management Science, 54 (2008), 1482-1496. Google Scholar |
[24] |
M. Nagarajan and G. Sošić, Coalition stability in assembly models, Operations Research, 57 (2009), 131-145. Google Scholar |
[25] |
A. Orendorff, O2O Commerce: Conquering Online-to-Offline Retail's Trillion Dollar Opportunity, 2018. Available from: https://www.shopify.com/enterprise/o2o-online-to-offline-commerce. Google Scholar |
[26] |
S. Panda, N. M. Modak, S. S. Sana and M. Basu,
Pricing and replenishment policies in dual-channel supply chain under continuous unit cost decrease, Applied Mathematics and Computation, 256 (2015), 913-929.
doi: 10.1016/j.amc.2015.01.081. |
[27] |
J. Paul, N. Agatz, R. Spliet and R. De Koster,
Shared capacity routing problem? An omni-channel retail study, European Journal of Operational Research, 273 (2019), 731-739.
doi: 10.1016/j.ejor.2018.08.027. |
[28] |
N. C. Petruzzi and M. Dada,
Pricing and the newsvendor problem: A review with extensions, Operations Research, 47 (1999), 183-194.
doi: 10.1287/opre.47.2.183. |
[29] |
S. Saha, N. M. Modak, S. Panda and S. S. Sana,
Managing a retailer's dual-channel supply chain under price- and delivery time-sensitive demand, Journal of Modelling in Management, 13 (2018), 351-374.
doi: 10.1108/JM2-10-2016-0089. |
[30] |
A. A. Tsay and N. Agrawal,
Channel conflict and coordination in the E-Commerce age, Production and Operations Management, 13 (2004), 93-110.
doi: 10.1007/s10436-017-0298-8. |
[31] |
USDOC, U. S., Department of Commerce Quarterly Retail Ecommerce Sales 4th Quarter 2016, Reported 2/17/17. Google Scholar |
[32] |
T. Wallace, The Complete Omni-Channel Retail Report: What Brands Need to Know About Modern Consumer Shopping Habits in 2018., Available from: https://www.bigcommerce.com/blog/omni-channel-retail/. Google Scholar |
[33] |
Y. Wang, L. Jiang and Z. J. Shen,
Channel performance under consignment contract with revenue sharing, Management Science, 50 (2004), 34-47.
doi: 10.1287/mnsc.1030.0168. |
[34] |
Y. Wang,
Joint pricing-production decisions in supply chains of complementary products with uncertain demand, Operations Research, 54 (2006), 1110-1127.
doi: 10.1287/opre.1060.0326. |
[35] |
E. Weise, In best buy deal, Amazon acknowledges you sometimes need to touch things to buy, USA TODAY. Google Scholar |
[36] |
G. Xu, B. Dan, X. Zhang and C. Liu,
Coordinating a dual-channel supply chain with risk-averse under a two-way revenue sharing contract, International Journal of Production Economics, 147 (2014), 171-179.
|
[37] |
D. Yang and X. Zhang,
Quick response and omnichannel retail operations with the ship-to-store program, International Transactions in Operational Research, 27 (2020), 3007-3030.
doi: 10.1111/itor.12781. |
[38] |
S. Yin,
Alliance formation among perfectly complementary suppliers in a price-sensitive assembly system, Manufacturing & Service Operations Management, 12 (2010), 527-544.
doi: 10.1287/msom.1090.0283. |
[39] |
F. Zhang,
Competition, cooperation, and information sharing in a two-echelon assembly system, Manufacturing & Service Operations Management, 8 (2006), 273-291.
doi: 10.1287/msom.1060.0108. |
[40] |
J. Zhang, H. Chen and X. Wu,
Operation models in O2O supply chain when existing competitive service level, International Journal of u- and e- Service, Science and Technology, 8 (2015), 279-290.
|
[41] |
J. Zhang, H. Chen, J. Ma and K. Tang, How to coordinate supply chain under O2O business model when demand deviation happens, Management Science and Engineering, 9 (2015), 24-28. Google Scholar |
show all references
References:
[1] |
G. P. Cachon and M. A. Lariviere,
Supply chain coordination with revenue-sharing contracts: Strengths and limitations, Management Science, 51 (2005), 30-44.
doi: 10.1287/mnsc.1040.0215. |
[2] |
G. Cai,
Channel selection and coordination in dual-channel supply chains, Journal of Retailing, 86 (2010), 22-36.
doi: 10.1016/j.jretai.2009.11.002. |
[3] |
S. M. Carr and U. S. Karmarkar,
Competition in multiechelon assembly supply chains, Management Science, 51 (2005), 45-59.
doi: 10.1287/mnsc.1040.0216. |
[4] |
X. Chen, X. Wang and X. Jiang,
The impact of power structure on the retail service supply chain with an O2O mixed channel, Journal of the Operational Research Society, 67 (2016), 294-301.
doi: 10.1057/jors.2015.6. |
[5] |
Z. Chen, L. Fang and S. I. Su,
The value of offline channel subsidy in bricks and clicks: An O2O supply chain coordination perspective, Electronic Commerce Research, 273 (2019), 1-45.
doi: 10.1007/s10660-019-09386-z. |
[6] |
Z. Chen and S. I. Su, Consignment supply chain cooperation for complementary products under online to offline business mode, Flexible Services and Manufacturing Journal, (2020).
doi: 10.1007/s10696-020-09376-6. |
[7] |
DT News Network, Dell EMC Believes in an Omni Channel Strategy, 2017. Available from: http://digitalterminal.in/news/dell-emc-believes-in-an-omni-channel-strategy/8853.html. Google Scholar |
[8] |
W. Duggan, What does O2O mean for the future of E-Commerce?, Yahoo Finance, (2015). Google Scholar |
[9] |
A. Dumrongsiri, M. Fan, A. Jain and K. Moinzadeh,
A supply chain model with direct and retail channels, European Journal of Operational Research, 187 (2008), 691-718.
doi: 10.1016/j.ejor.2006.05.044. |
[10] |
F. Gao and X. Su,
Omnichannel service operations with online and offline self-order technologies, Management Science, 64 (2018), 3595-3608.
doi: 10.1287/mnsc.2017.2787. |
[11] |
F. Gao and X. Su,
Omnichannel retail operations with buy-online-and-pick-up-in-store, Management Science, 63 (2016), 2478-2492.
doi: 10.1287/mnsc.2016.2473. |
[12] |
Investopedia, Online-to-Offline Commerce, 2018. Available from: https://www.investopedia.com/terms/o/onlinetooffline-commerce.asp#ixzz5GNPyJCIX. Google Scholar |
[13] |
J. Ji, Z. Zhang and L. Yang,
Comparisons of initial carbon allowance allocation rules in an O2O retail supply chain with the cap-and-trade regulation, International Journal of Production Economics, 187 (2017), 68-84.
doi: 10.1016/j.ijpe.2017.02.011. |
[14] |
Y. Jiang, L. Liu and A. Lim,
Optimal pricing decisions for an omni-channel supply chain with retail service, International Transactions in Operational Research, 27 (2020), 2927-2948.
doi: 10.1111/itor.12784. |
[15] |
L. Jiang and Y. Wang,
Supplier competition in decentralized assembly systems with price-sensitive and uncertain demand, Manufacturing & Service Operations Management, 12 (2010), 93-101.
doi: 10.1287/msom.1090.0259. |
[16] |
B. Kalkancl and F. Erhun,
Pricing games and impact of private demand information in decentralized assembly systems, Operations Research, 60 (2012), 1142-1156.
doi: 10.1287/opre.1120.1084. |
[17] |
Kjmx, Hardware cost disclosure of Huawei, apple, Samsung and Xiaomi, how much is the profit margin of each manufacturer?, Available from: http://finance.sina.com.cn/stock/relnews/us/2019-06-29/doc-ihytcerm0232231.shtml. Google Scholar |
[18] |
L. Kong, Z. Liu, Y. Pan, J. Xie and G. Yang,
Pricing and service decision of dual-channel operations in an O2O closed-loop supply chain, Industrial Management & Data Systems, 117 (2017), 1567-1588.
doi: 10.1108/IMDS-12-2016-0544. |
[19] |
M. A. Lariviere,
A note on probability distributions with increasing generalized failure rates, Operations Research, 54 (2006), 602-604.
doi: 10.1287/opre.1060.0282. |
[20] |
M. A. Lariviere and E. L. Porteus,
Selling to the newsvendor: An analysis of price-only contracts, Manufacturing and Service Operations Management, 3 (2001), 293-305.
doi: 10.1287/msom.3.4.293.9971. |
[21] |
N. M. Modak,
Exploring Omni-channel supply chain under price and delivery time sensitive stochastic demand, Supply Chain Forum: An International Journal, 18 (2017), 218-230.
doi: 10.1080/16258312.2017.1380499. |
[22] |
N. M. Modak and P. Kelle,
Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand, European Journal of Operational Research, 272 (2019), 147-161.
doi: 10.1016/j.ejor.2018.05.067. |
[23] |
M. Nagarajan and Y. Bassok, A bargaining framework in supply chains: The assembly problem, Management Science, 54 (2008), 1482-1496. Google Scholar |
[24] |
M. Nagarajan and G. Sošić, Coalition stability in assembly models, Operations Research, 57 (2009), 131-145. Google Scholar |
[25] |
A. Orendorff, O2O Commerce: Conquering Online-to-Offline Retail's Trillion Dollar Opportunity, 2018. Available from: https://www.shopify.com/enterprise/o2o-online-to-offline-commerce. Google Scholar |
[26] |
S. Panda, N. M. Modak, S. S. Sana and M. Basu,
Pricing and replenishment policies in dual-channel supply chain under continuous unit cost decrease, Applied Mathematics and Computation, 256 (2015), 913-929.
doi: 10.1016/j.amc.2015.01.081. |
[27] |
J. Paul, N. Agatz, R. Spliet and R. De Koster,
Shared capacity routing problem? An omni-channel retail study, European Journal of Operational Research, 273 (2019), 731-739.
doi: 10.1016/j.ejor.2018.08.027. |
[28] |
N. C. Petruzzi and M. Dada,
Pricing and the newsvendor problem: A review with extensions, Operations Research, 47 (1999), 183-194.
doi: 10.1287/opre.47.2.183. |
[29] |
S. Saha, N. M. Modak, S. Panda and S. S. Sana,
Managing a retailer's dual-channel supply chain under price- and delivery time-sensitive demand, Journal of Modelling in Management, 13 (2018), 351-374.
doi: 10.1108/JM2-10-2016-0089. |
[30] |
A. A. Tsay and N. Agrawal,
Channel conflict and coordination in the E-Commerce age, Production and Operations Management, 13 (2004), 93-110.
doi: 10.1007/s10436-017-0298-8. |
[31] |
USDOC, U. S., Department of Commerce Quarterly Retail Ecommerce Sales 4th Quarter 2016, Reported 2/17/17. Google Scholar |
[32] |
T. Wallace, The Complete Omni-Channel Retail Report: What Brands Need to Know About Modern Consumer Shopping Habits in 2018., Available from: https://www.bigcommerce.com/blog/omni-channel-retail/. Google Scholar |
[33] |
Y. Wang, L. Jiang and Z. J. Shen,
Channel performance under consignment contract with revenue sharing, Management Science, 50 (2004), 34-47.
doi: 10.1287/mnsc.1030.0168. |
[34] |
Y. Wang,
Joint pricing-production decisions in supply chains of complementary products with uncertain demand, Operations Research, 54 (2006), 1110-1127.
doi: 10.1287/opre.1060.0326. |
[35] |
E. Weise, In best buy deal, Amazon acknowledges you sometimes need to touch things to buy, USA TODAY. Google Scholar |
[36] |
G. Xu, B. Dan, X. Zhang and C. Liu,
Coordinating a dual-channel supply chain with risk-averse under a two-way revenue sharing contract, International Journal of Production Economics, 147 (2014), 171-179.
|
[37] |
D. Yang and X. Zhang,
Quick response and omnichannel retail operations with the ship-to-store program, International Transactions in Operational Research, 27 (2020), 3007-3030.
doi: 10.1111/itor.12781. |
[38] |
S. Yin,
Alliance formation among perfectly complementary suppliers in a price-sensitive assembly system, Manufacturing & Service Operations Management, 12 (2010), 527-544.
doi: 10.1287/msom.1090.0283. |
[39] |
F. Zhang,
Competition, cooperation, and information sharing in a two-echelon assembly system, Manufacturing & Service Operations Management, 8 (2006), 273-291.
doi: 10.1287/msom.1060.0108. |
[40] |
J. Zhang, H. Chen and X. Wu,
Operation models in O2O supply chain when existing competitive service level, International Journal of u- and e- Service, Science and Technology, 8 (2015), 279-290.
|
[41] |
J. Zhang, H. Chen, J. Ma and K. Tang, How to coordinate supply chain under O2O business model when demand deviation happens, Management Science and Engineering, 9 (2015), 24-28. Google Scholar |




Parameter/Variable | Explanations |
Unit assembly cost of the final product | |
Unit cost of the |
|
Wholesale price of the |
|
Operational cost of the online channel | |
Operational cost of the offline channel | |
Retail price of the final product in the online/offline channel | |
Stock factor | |
Positive constant number | |
Price-elasticity index of the expected demand | |
Mutual fusion coefficient between channels | |
Clearance discount price factor, and |
|
Market demand share of the online channel, and |
|
The offline channel subsidy factor, and |
|
The offline channel discount price factor, and |
|
The reaction extent of |
|
Revenue keeping rate, and |
|
The random factor defined in the range |
|
Mean value of random factor | |
Standard deviation of random factor |
Parameter/Variable | Explanations |
Unit assembly cost of the final product | |
Unit cost of the |
|
Wholesale price of the |
|
Operational cost of the online channel | |
Operational cost of the offline channel | |
Retail price of the final product in the online/offline channel | |
Stock factor | |
Positive constant number | |
Price-elasticity index of the expected demand | |
Mutual fusion coefficient between channels | |
Clearance discount price factor, and |
|
Market demand share of the online channel, and |
|
The offline channel subsidy factor, and |
|
The offline channel discount price factor, and |
|
The reaction extent of |
|
Revenue keeping rate, and |
|
The random factor defined in the range |
|
Mean value of random factor | |
Standard deviation of random factor |
Section | Channel Strategy | Game-Theoretical Decision Models | Theories Applied |
4.1 | Omnichannel mode without offline channel subsidy (OMO mode) | 4.1.1 Centralized Decision Model | OT & BC |
4.1.2 Decentralized Decision Model | SG & BC | ||
4.1.2.1 Assembler's Decision | SG & BC | ||
4.1.2.2 Suppliers' Simultaneous Decision | SG & BC | ||
4.1.2.3 Suppliers' Sequential Decision | SG & BC | ||
4.1.3 Coordination Decision Model | RSC & BC | ||
4.2 | Omnichannel | OT+SG+RSC+BC | |
mode with offline | Centralized/Decentralized/Coordination | ||
channel subsidy | Decision Models under OMS mode | ||
(OMS mode) | |||
4.3 | Pure online/offline | Centralized/Decentralized/Coordination Decision Models under POC/PFC mode | OT+SG+RSC+BC |
channel mode | |||
(POC/PFC mode) | |||
Notation: OT: Optimization Theory; BC: Bertrand Competition; SG: Stackelberg Game; RSC: Revenue Sharing Contract |
Section | Channel Strategy | Game-Theoretical Decision Models | Theories Applied |
4.1 | Omnichannel mode without offline channel subsidy (OMO mode) | 4.1.1 Centralized Decision Model | OT & BC |
4.1.2 Decentralized Decision Model | SG & BC | ||
4.1.2.1 Assembler's Decision | SG & BC | ||
4.1.2.2 Suppliers' Simultaneous Decision | SG & BC | ||
4.1.2.3 Suppliers' Sequential Decision | SG & BC | ||
4.1.3 Coordination Decision Model | RSC & BC | ||
4.2 | Omnichannel | OT+SG+RSC+BC | |
mode with offline | Centralized/Decentralized/Coordination | ||
channel subsidy | Decision Models under OMS mode | ||
(OMS mode) | |||
4.3 | Pure online/offline | Centralized/Decentralized/Coordination Decision Models under POC/PFC mode | OT+SG+RSC+BC |
channel mode | |||
(POC/PFC mode) | |||
Notation: OT: Optimization Theory; BC: Bertrand Competition; SG: Stackelberg Game; RSC: Revenue Sharing Contract |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
![]() |
Decentralized (Equilibrium) strategy | Coordination strategy | |
Suppliers' Simultaneous Actions | Suppliers' Sequential Actions | ||
- | - | ||
note: |
Parameters | Value | |
Assembly cost (USD/unit) | 50 | |
149 | ||
53 | ||
80 | ||
60 | ||
Operational cost of the online channel (USD/unit) | 26 | |
Operational cost of offline channel (USD/unit) | 39 | |
Positive constant number | 1E+18 | |
Price-elasticity index of the expected demand | 5.0 | |
Mutual fusion coefficient between channels | 0.5 | |
Clearance discount price factor | 50% | |
Market demand share of the online channel | 0.6 | |
The offline channel subsidy factor, and |
0.1 | |
The offline channel discount price factor, and |
0.9 | |
the reaction extent of |
0.5 | |
Revenue keeping rate | 0.7 | |
Mean value of random factor | 100 | |
Standard deviation of random factor | 10 |
Parameters | Value | |
Assembly cost (USD/unit) | 50 | |
149 | ||
53 | ||
80 | ||
60 | ||
Operational cost of the online channel (USD/unit) | 26 | |
Operational cost of offline channel (USD/unit) | 39 | |
Positive constant number | 1E+18 | |
Price-elasticity index of the expected demand | 5.0 | |
Mutual fusion coefficient between channels | 0.5 | |
Clearance discount price factor | 50% | |
Market demand share of the online channel | 0.6 | |
The offline channel subsidy factor, and |
0.1 | |
The offline channel discount price factor, and |
0.9 | |
the reaction extent of |
0.5 | |
Revenue keeping rate | 0.7 | |
Mean value of random factor | 100 | |
Standard deviation of random factor | 10 |
![]() |
OMO Mode | OMS Mode | ||||
Decentralized strategy | Coordination strategy | Decentralized strategy | Coordination strategy | |||
Simultaneous actions | Sequential actions | Simultaneous actions | Sequential actions | |||
99 | 99 | 99 | 99 | 99 | 99 | |
6, 418 | 1, 949 | 713 | 6, 604 | 2, 005 | 734 | |
731 | 156, 071 | 14, 385, 462 | 825 | 176, 168 | 16, 237, 802 | |
1, 238 | 305 | 104 | 1, 269 | 309 | 104 | |
1, 142 | 253 | 37 | 1, 173 | 259 | 37 | |
1, 169 | 337 | 56 | 1, 200 | 345 | 56 | |
1, 149 | 391 | 42 | 1, 180 | 400 | 42 | |
1, 023, 117 | 66, 336, 309 | 1, 566, 289, 055 | 1, 188, 375 | 77, 051, 259 | 1, 819, 283, 383 | |
795, 757 | 24, 275, 793 | 292, 452, 468 | 924, 292 | 28, 196, 932 | 339, 690, 757 | |
795, 757 | 31, 211, 734 | 104, 026, 717 | 924, 292 | 36, 253, 199 | 120, 829, 598 | |
795, 757 | 40, 129, 372 | 157, 021, 459 | 924, 292 | 46, 611, 256 | 182, 384, 299 | |
795, 757 | 51, 594, 907 | 117, 766, 094 | 924, 292 | 59, 928, 757 | 136, 788, 224 | |
4, 206, 146 | 213, 548, 114 | 2, 237, 555, 793 | 4, 885, 542 | 248, 041, 403 | 2, 598, 976, 261 | |
Range of |
[0.029646773, 0.868565973]; set at 0.7 | [0.029646773, 0.868565973]; set at 0.7 |
![]() |
OMO Mode | OMS Mode | ||||
Decentralized strategy | Coordination strategy | Decentralized strategy | Coordination strategy | |||
Simultaneous actions | Sequential actions | Simultaneous actions | Sequential actions | |||
99 | 99 | 99 | 99 | 99 | 99 | |
6, 418 | 1, 949 | 713 | 6, 604 | 2, 005 | 734 | |
731 | 156, 071 | 14, 385, 462 | 825 | 176, 168 | 16, 237, 802 | |
1, 238 | 305 | 104 | 1, 269 | 309 | 104 | |
1, 142 | 253 | 37 | 1, 173 | 259 | 37 | |
1, 169 | 337 | 56 | 1, 200 | 345 | 56 | |
1, 149 | 391 | 42 | 1, 180 | 400 | 42 | |
1, 023, 117 | 66, 336, 309 | 1, 566, 289, 055 | 1, 188, 375 | 77, 051, 259 | 1, 819, 283, 383 | |
795, 757 | 24, 275, 793 | 292, 452, 468 | 924, 292 | 28, 196, 932 | 339, 690, 757 | |
795, 757 | 31, 211, 734 | 104, 026, 717 | 924, 292 | 36, 253, 199 | 120, 829, 598 | |
795, 757 | 40, 129, 372 | 157, 021, 459 | 924, 292 | 46, 611, 256 | 182, 384, 299 | |
795, 757 | 51, 594, 907 | 117, 766, 094 | 924, 292 | 59, 928, 757 | 136, 788, 224 | |
4, 206, 146 | 213, 548, 114 | 2, 237, 555, 793 | 4, 885, 542 | 248, 041, 403 | 2, 598, 976, 261 | |
Range of |
[0.029646773, 0.868565973]; set at 0.7 | [0.029646773, 0.868565973]; set at 0.7 |
![]() |
POC Mode | PFC Mode | ||||
Decentralized strategy | Coordination strategy | Decentralized strategy | Coordination strategy | |||
Simultaneous actions | Sequential actions | Simultaneous actions | Sequential actions | |||
98 | 98 | 98 | 98 | 98 | 98 | |
2, 655 | 1, 296 | 531 | 4, 662 | 2, 276 | 932 | |
744 | 26, 812 | 2, 325, 562 | 45 | 1, 606 | 139, 293 | |
567 | 254 | 104 | 883 | 333 | 104 | |
471 | 184 | 37 | 787 | 282 | 37 | |
498 | 243 | 56 | 814 | 367 | 56 | |
478 | 264 | 42 | 794 | 418 | 42 | |
388, 834 | 6, 840, 438 | 170, 114, 826 | 40, 896 | 719, 457 | 17, 892, 172 | |
311, 067 | 2, 801, 843 | 31, 763, 295 | 32, 717 | 294, 690 | 3, 340, 769 | |
311, 067 | 3, 502, 304 | 11, 298, 353 | 32, 717 | 368, 362 | 1, 188, 327 | |
311, 067 | 4, 377, 880 | 17, 054, 118 | 32, 717 | 460, 452 | 1, 793, 701 | |
311, 067 | 5, 472, 350 | 12, 790, 588 | 32, 717 | 575, 566 | 1, 345, 276 | |
1, 633, 102 | 22, 994, 817 | 243, 021, 181 | 171, 765 | 2, 418, 526 | 25, 560, 245 | |
Range of |
[0.028147498, 0.871647411]; set at 0.7 | [0.028147498, 0.871647411]; set at 0.7 |
![]() |
POC Mode | PFC Mode | ||||
Decentralized strategy | Coordination strategy | Decentralized strategy | Coordination strategy | |||
Simultaneous actions | Sequential actions | Simultaneous actions | Sequential actions | |||
98 | 98 | 98 | 98 | 98 | 98 | |
2, 655 | 1, 296 | 531 | 4, 662 | 2, 276 | 932 | |
744 | 26, 812 | 2, 325, 562 | 45 | 1, 606 | 139, 293 | |
567 | 254 | 104 | 883 | 333 | 104 | |
471 | 184 | 37 | 787 | 282 | 37 | |
498 | 243 | 56 | 814 | 367 | 56 | |
478 | 264 | 42 | 794 | 418 | 42 | |
388, 834 | 6, 840, 438 | 170, 114, 826 | 40, 896 | 719, 457 | 17, 892, 172 | |
311, 067 | 2, 801, 843 | 31, 763, 295 | 32, 717 | 294, 690 | 3, 340, 769 | |
311, 067 | 3, 502, 304 | 11, 298, 353 | 32, 717 | 368, 362 | 1, 188, 327 | |
311, 067 | 4, 377, 880 | 17, 054, 118 | 32, 717 | 460, 452 | 1, 793, 701 | |
311, 067 | 5, 472, 350 | 12, 790, 588 | 32, 717 | 575, 566 | 1, 345, 276 | |
1, 633, 102 | 22, 994, 817 | 243, 021, 181 | 171, 765 | 2, 418, 526 | 25, 560, 245 | |
Range of |
[0.028147498, 0.871647411]; set at 0.7 | [0.028147498, 0.871647411]; set at 0.7 |
Parameters | Original Value | Range | ||
Offline channel subsidy factor | 0.1 | 0.01 | [0, 0.5] | |
Price-elasticity index of the expected demand | 5.0 | 0.01 | [4.5, 5.5] | |
Mutual fusion coefficient between channels | 0.5 | 0.01 | [0.1, 0.9] |
Parameters | Original Value | Range | ||
Offline channel subsidy factor | 0.1 | 0.01 | [0, 0.5] | |
Price-elasticity index of the expected demand | 5.0 | 0.01 | [4.5, 5.5] | |
Mutual fusion coefficient between channels | 0.5 | 0.01 | [0.1, 0.9] |
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