doi: 10.3934/jimo.2022087
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Retailer's willingness to adopt blockchain technology based on private demand information

1. 

School of Business Administration, Hunan University, Changsha 410082, China

2. 

Hunan Trillion Trust Information Technology Co. Ltd, Changsha 410005, China

*Corresponding author: Feimin Zhong (zhongfeimin@hnu.edu.cn)

Received  September 2021 Revised  April 2022 Early access June 2022

Fund Project: This research is supported by the National Natural Science of China under Grants (No:71771082, 71850012, 72171077), Hunan Provincial Key Laboratory (No. 2020TP1013), National Social Science Foundation of China (No.19AZD014)

This paper considers a supply chain that includes one supplier and one retailer, in which the retailer has a more accurate demand forecast. The blockchain technology can verify the authenticity of the information, then the retailer can choose to truly share the demand information with the supplier by adopting such a costly technology. We discuss three scenarios based on signaling game: the retailer bears all the cost (no subsidy), the supplier bears part of the cost by providing direct subsidy or wholesale discount, respectively. Specifically, in a demand information asymmetric setting, we mainly focus on exploring the conditions of retailer adopting blockchain technology and the supplier's subsidy strategy choice, and further verify the robustness of the model by considering the retailer's risk aversion or multiple suppliers. In all scenarios, we find that the retailer will apply threshold strategy to adopt blockchain technology. The retailer's willingness to adopt blockchain technology is negatively correlated with the corresponding adoption cost, the supplier's profit level, and positively correlated with the number of suppliers. Additionally, we find the supplier can profit from providing subsidies when the cost of adopting blockchain technology is around a medium level, and the direct subsidy is superior to wholesale discount. More surprisingly, we find subsidies may work to the disadvantage of the subsidized party. Specifically, compared to no subsidy, we find the direct subsidy and the wholesale discount can increase the retailer's willingness to adopt blockchain technology, but hurt the retailer's as well as the supply chain's profits.

Citation: Zhongbao Zhou, Xingfen Liu, Feimin Zhong, Yuan Cao, Long Zheng. Retailer's willingness to adopt blockchain technology based on private demand information. Journal of Industrial and Management Optimization, doi: 10.3934/jimo.2022087
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T. Avinadav and N. Shamir, The effect of information asymmetry on ordering and capacity decisions in supply chains, European Journal of Operational Research, 292 (2021), 562-578.  doi: 10.1016/j.ejor.2020.11.004.

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P. BasuQ. Liu and J. Stallaert, Supply chain management using put option contracts with information asymmetry, International Journal of Production Research, 57 (2019), 1772-1796.  doi: 10.1080/00207543.2018.1508900.

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Carrefour, Managing our supply chain, 2021. Available from: URL https://www.carrefour.com/sites/default/files/2021-07/16_Mobiliser%20notre%20chai%CC%82ne%20d_approvisionnement_UK_0.pdf.

[5]

J. A. ChangM. N. KatehakisJ. J. Shi and Z. Yan, Blockchain-empowered newsvendor optimization, International Journal of Production Economics, 238 (2021), 108144.  doi: 10.1016/j.ijpe.2021.108144.

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J. ChodN. TrichakisG. TsoukalasH. Aspegren and M. Weber, On the financing benefits of supply chain transparency and blockchain adoption, Management Science, 66 (2020), 4378-4396.  doi: 10.1287/mnsc.2019.3434.

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T. M. Choi, Supply chain financing using blockchain: Impacts on supply chains selling fashionable products, Annals of Operations Research. doi: 10.1007/s10479-020-03615-7.

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L. Y. ChuN. Shamir and H. Shin, Strategic communication for capacity alignment with pricing in a supply chain, Management Science, 63 (2017), 4366-4388. 

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P. De Giovanni, Blockchain and smart contracts in supply chain management: A game theoretic model, International Journal of Production Economics, 228 (2020), 107855. 

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L. Dignan, Ibm food trust blockchain network available, carrefour joins retailer roster, 2022. Available from: URL https://www.zdnet.com/article/ibm-food-trust-blockchain-network-available-carrefour-joins-retailer-roster/.

[12]

Z.-P. FanX.-Y. Wu and B.-B. Cao, Considering the traceability awareness of consumers: Should the supply chain adopt the blockchain technology?, Annals of Operations Research, 309 (2022), 837-860.  doi: 10.1007/s10479-020-03729-y.

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X. GanS. P. Sethi and J. Zhou, Commitment-penalty contracts in drop-shipping supply chains with asymmetric demand information, European Journal of Operational Research, 204 (2010), 449-462.  doi: 10.1016/j.ejor.2009.11.008.

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H. Lee, V. Padmanabhan and S. Whang, Information distortion in a supply chain: The bullwhip effect, Management Science, 50 (2004), 1875–86.

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J. Lei and M. Xue, Drop-shipping or batch ordering: Contract choice in the presence of information sharing and quality decision, Journal of Management Science and Engineering. doi: 10.1016/j.jmse.2021.11.002.

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M. LiX. Zhang and B. Dan, Competition and cooperation in a supply chain with an offline showroom under asymmetric information, International Journal of Production Research, 58 (2020), 5964-5979.  doi: 10.1080/00207543.2019.1661536.

[26]

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[27]

X. LiJ. Chen and X. Ai, Contract design in a cross-sales supply chain with demand information asymmetry, European Journal of Operational Research, 275 (2019), 939-956.  doi: 10.1016/j.ejor.2018.12.023.

[28]

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[29]

Z. Li, S. M. Gilbert and G. Lai, Supplier encroachment as an enhancement or a hindrance to nonlinear pricing, Production and Operations Management, 24 (2015), 89–109.

[30]

Q. Liao and Y. Zhou, Supply chain coordination with option contract and demand information asymmetry, in 4th International Conference on Operations and Supply Chain Management/15th Annual Meeting of the Asia-Pacific-Decision-Sciences-Institute, Operations and Supply Chain Management in China, 4, 2010

[31]

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[32]

A. LiuT. LiuJ. Mou and R. Wang, A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management, Journal of Management Science and Engineering, 5 (2020), 172-194.  doi: 10.1016/j.jmse.2020.06.001.

[33]

Z. LiuS. Hua and X. Zhai, Supply chain coordination with risk-averse retailer and option contract: Supplier-led vs. retailer-led, International Journal of Production Economics, 223 (2020), 107518.  doi: 10.1016/j.ijpe.2019.107518.

[34]

S. Minner and S. Transchel, Order variability in perishable product supply chains, European Journal of Operational Research, 260 (2017), 93-107.  doi: 10.1016/j.ejor.2016.12.016.

[35]

K. J. Mizgier, Global sensitivity analysis and aggregation of risk in multi-product supply chain networks, International Journal of Production Research, 55 (2017), 130-144.  doi: 10.1080/00207543.2016.1198504.

[36]

S. Nasser and D. Turcic, Temporary contract adjustment to a retailer with a private demand forecast, Management Science, 65 (2019), 209-229. 

[37]

O. Ozer and W. Wei, Strategic commitments for an optimal capacity decision under asymmetric forecast information, Management Science, 52 (2006), 1238–1257.

[38]

Plxelplex, How Walmart strives for food quality and safety using blockchain technology solutions, 2020. Available from: URL https://pixelplex.io/blog/walmart-strives-for-food-safety-using-blockchain/.

[39]

H. PunJ. M. Swaminathan and P. Hou, Blockchain adoption for combating deceptive counterfeits, Production and Operations Management, 30 (2021), 864-882. 

[40]

S. Saha and S. Goyal, Supply chain coordination contracts with inventory level and retail price dependent demand, International Journal of Production Economics, 161 (2015), 140-152.  doi: 10.1016/j.ijpe.2014.12.025.

[41]

N. Shamir and H. Shin, Public forecast information sharing in a market with competing supply chains, Management Science, 62 (2016), 2994-3022. 

[42]

B. ShenC. Dong and S. Minner, Combating copycats in the supply chain with permissioned blockchain technology, Production and Operations Management, 31 (2022), 138-154.  doi: 10.1111/poms.13456.

[43]

M. M. S. Sodhi and C. S. Tang, Research opportunities in supply chain transparency, Production and Operations Management, 28 (2019), 2946-2959.  doi: 10.1111/poms.13115.

[44]

T. SundC. LööfS. Nadjm-Tehrani and M. Asplund, Blockchain-based event processing in supply chains–A case study at IKEA, Robotics and Computer-Integrated Manufacturing, 65 (2020), 101971.  doi: 10.1016/j.rcim.2020.101971.

[45]

S. van EngelenburgM. Janssen and B. Klievink, A blockchain architecture for reducing the bullwhip effect, Lecture Notes in Business Information Processing, 319 (2018), 69-82.  doi: 10.1007/978-3-319-94214-8_5.

[46]

D. Xing and T. Liu, Sales effort free riding and coordination with price match and channel rebate, European Journal of Operational Research, 219 (2012), 264-271.  doi: 10.1016/j.ejor.2011.11.029.

[47]

D. YangT. XiaoT. M. Choi and T. C. Cheng, Optimal reservation pricing strategy for a fashion supply chain with forecast update and asymmetric cost information, International Journal of Production Research, 56 (2018), 1960-1981.  doi: 10.1080/00207543.2014.998789.

[48]

T. ZhangP. Li and N. Wang, Multi-period price competition of blockchain-technology-supported and traditional platforms under network effect, International Journal of Production Research, 0 (2021), 1-15.  doi: 10.3390/e24040557.

[49]

W.-G. ZhangQ. ZhangK. J. Mizgier and Y. Zhang, Integrating the customers' perceived risks and benefits into the triple-channel retailing, International Journal of Production Research, 55 (2017), 6676-6690.  doi: 10.1080/00207543.2017.1336679.

[50]

Z. ZhouX. LiuF. Zhong and J. Shi, Improving the reliability of the information disclosure in supply chain based on blockchain technology, Electronic Commerce Research and Applications, 52 (2022), 101121.  doi: 10.3390/e24040557.

show all references

References:
[1]

T. AvinadavT. Chernonog and T. Ben-Zvi, The effect of information superiority on a supply chain of virtual products, International Journal of Production Economics, 216 (2019), 384-397.  doi: 10.1016/j.ijpe.2019.07.004.

[2]

T. Avinadav and N. Shamir, The effect of information asymmetry on ordering and capacity decisions in supply chains, European Journal of Operational Research, 292 (2021), 562-578.  doi: 10.1016/j.ejor.2020.11.004.

[3]

P. BasuQ. Liu and J. Stallaert, Supply chain management using put option contracts with information asymmetry, International Journal of Production Research, 57 (2019), 1772-1796.  doi: 10.1080/00207543.2018.1508900.

[4]

Carrefour, Managing our supply chain, 2021. Available from: URL https://www.carrefour.com/sites/default/files/2021-07/16_Mobiliser%20notre%20chai%CC%82ne%20d_approvisionnement_UK_0.pdf.

[5]

J. A. ChangM. N. KatehakisJ. J. Shi and Z. Yan, Blockchain-empowered newsvendor optimization, International Journal of Production Economics, 238 (2021), 108144.  doi: 10.1016/j.ijpe.2021.108144.

[6]

J. ChodN. TrichakisG. TsoukalasH. Aspegren and M. Weber, On the financing benefits of supply chain transparency and blockchain adoption, Management Science, 66 (2020), 4378-4396.  doi: 10.1287/mnsc.2019.3434.

[7]

T. M. Choi, Supply chain financing using blockchain: Impacts on supply chains selling fashionable products, Annals of Operations Research. doi: 10.1007/s10479-020-03615-7.

[8]

L. Y. ChuN. Shamir and H. Shin, Strategic communication for capacity alignment with pricing in a supply chain, Management Science, 63 (2017), 4366-4388. 

[9]

M. CohenT. HoZ. Ren and C. Terwiesch, Measuring imputed cost in the semiconductor equipment supply chain, Management Science, 49 (2003), 1653-1670.  doi: 10.1287/mnsc.49.12.1653.25115.

[10]

P. De Giovanni, Blockchain and smart contracts in supply chain management: A game theoretic model, International Journal of Production Economics, 228 (2020), 107855. 

[11]

L. Dignan, Ibm food trust blockchain network available, carrefour joins retailer roster, 2022. Available from: URL https://www.zdnet.com/article/ibm-food-trust-blockchain-network-available-carrefour-joins-retailer-roster/.

[12]

Z.-P. FanX.-Y. Wu and B.-B. Cao, Considering the traceability awareness of consumers: Should the supply chain adopt the blockchain technology?, Annals of Operations Research, 309 (2022), 837-860.  doi: 10.1007/s10479-020-03729-y.

[13]

X. GanS. P. Sethi and J. Zhou, Commitment-penalty contracts in drop-shipping supply chains with asymmetric demand information, European Journal of Operational Research, 204 (2010), 449-462.  doi: 10.1016/j.ejor.2009.11.008.

[14]

S. HAIG, Nike explores blockchain for supply chain data collection, 2020. Available from: URL https://cointelegraph.com/news/nike-explores-blockchain-for-supply-chain-data-collection.

[15]

C.-C. HsiehC.-H. Wu and Y.-J. Huang, Ordering and pricing decisions in a two-echelon supply chain with asymmetric demand information, European Journal of Operational Research, 190 (2008), 509-525.  doi: 10.1016/j.ejor.2007.06.019.

[16]

L. HughesY. K. DwivediS. K. MisraN. P. RanaV. Raghavan and V. Akella, Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda, International Journal of Information Management, 49 (2019), 114-129.  doi: 10.1016/j.ijinfomgt.2019.02.005.

[17]

Z.-Z. Jiang, J. Zhao, Z. Yi and Y. Zhao, Inducing information transparency: The roles of gray market and dual-channel, Annals of Operations Research. doi: 10.1007/s10479-020-03719-0.

[18]

S. John, How Walmart keeps its prices so low, 2020. Available from: URL https://www.businessinsider.com/walmart-low-price-strategy-tips-2019-4.

[19]

L. C. Johnsen, G. Voigt and C. J. Corbett, Behavioral contract design under asymmetric forecast information, Decision Sciences, 50 (2019), 786–815. doi: 10.1111/deci.12352.

[20]

E. Katok and S. Villa, Centralized or decentralized transfer prices: A behavioral approach for improving supply chain coordination, Manufacturing & Service Operations Management, 24 (2022), 143-158.  doi: 10.1287/msom.2020.0957.

[21]

Y. Kim, Retailers' endogenous sequencing game and information acquisition game in the presence of information leakage, International Transactions in Operational Research, 28 (2021), 809-838.  doi: 10.1111/itor.12844.

[22]

G. KongS. Rajagopalan and H. Zhang, Revenue sharing and information leakage in a supply chain, Management Science, 59 (2013), 556-572. 

[23]

H. Lee, V. Padmanabhan and S. Whang, Information distortion in a supply chain: The bullwhip effect, Management Science, 50 (2004), 1875–86.

[24]

J. Lei and M. Xue, Drop-shipping or batch ordering: Contract choice in the presence of information sharing and quality decision, Journal of Management Science and Engineering. doi: 10.1016/j.jmse.2021.11.002.

[25]

M. LiX. Zhang and B. Dan, Competition and cooperation in a supply chain with an offline showroom under asymmetric information, International Journal of Production Research, 58 (2020), 5964-5979.  doi: 10.1080/00207543.2019.1661536.

[26]

Q. Li and J. Zhou, A horizontal capacity reservation game under asymmetric information, International Journal of Production Research, 57 (2019), 1103–1118. doi: 10.1080/00207543.2018.1501165.

[27]

X. LiJ. Chen and X. Ai, Contract design in a cross-sales supply chain with demand information asymmetry, European Journal of Operational Research, 275 (2019), 939-956.  doi: 10.1016/j.ejor.2018.12.023.

[28]

Z. Li, S. M. Gilbert and G. Lai, Supplier Encroachment Under Asymmetric Information, Management Science, 60 (2014), 449–462.

[29]

Z. Li, S. M. Gilbert and G. Lai, Supplier encroachment as an enhancement or a hindrance to nonlinear pricing, Production and Operations Management, 24 (2015), 89–109.

[30]

Q. Liao and Y. Zhou, Supply chain coordination with option contract and demand information asymmetry, in 4th International Conference on Operations and Supply Chain Management/15th Annual Meeting of the Asia-Pacific-Decision-Sciences-Institute, Operations and Supply Chain Management in China, 4, 2010

[31]

Q. Lin and J. He, Supply chain contract design considering the supplier's asset structure and capital constraints, Computers and Industrial Engineering, 137 (2019), 106044.  doi: 10.1016/j.cie.2019.106044.

[32]

A. LiuT. LiuJ. Mou and R. Wang, A supplier evaluation model based on customer demand in blockchain tracing anti-counterfeiting platform project management, Journal of Management Science and Engineering, 5 (2020), 172-194.  doi: 10.1016/j.jmse.2020.06.001.

[33]

Z. LiuS. Hua and X. Zhai, Supply chain coordination with risk-averse retailer and option contract: Supplier-led vs. retailer-led, International Journal of Production Economics, 223 (2020), 107518.  doi: 10.1016/j.ijpe.2019.107518.

[34]

S. Minner and S. Transchel, Order variability in perishable product supply chains, European Journal of Operational Research, 260 (2017), 93-107.  doi: 10.1016/j.ejor.2016.12.016.

[35]

K. J. Mizgier, Global sensitivity analysis and aggregation of risk in multi-product supply chain networks, International Journal of Production Research, 55 (2017), 130-144.  doi: 10.1080/00207543.2016.1198504.

[36]

S. Nasser and D. Turcic, Temporary contract adjustment to a retailer with a private demand forecast, Management Science, 65 (2019), 209-229. 

[37]

O. Ozer and W. Wei, Strategic commitments for an optimal capacity decision under asymmetric forecast information, Management Science, 52 (2006), 1238–1257.

[38]

Plxelplex, How Walmart strives for food quality and safety using blockchain technology solutions, 2020. Available from: URL https://pixelplex.io/blog/walmart-strives-for-food-safety-using-blockchain/.

[39]

H. PunJ. M. Swaminathan and P. Hou, Blockchain adoption for combating deceptive counterfeits, Production and Operations Management, 30 (2021), 864-882. 

[40]

S. Saha and S. Goyal, Supply chain coordination contracts with inventory level and retail price dependent demand, International Journal of Production Economics, 161 (2015), 140-152.  doi: 10.1016/j.ijpe.2014.12.025.

[41]

N. Shamir and H. Shin, Public forecast information sharing in a market with competing supply chains, Management Science, 62 (2016), 2994-3022. 

[42]

B. ShenC. Dong and S. Minner, Combating copycats in the supply chain with permissioned blockchain technology, Production and Operations Management, 31 (2022), 138-154.  doi: 10.1111/poms.13456.

[43]

M. M. S. Sodhi and C. S. Tang, Research opportunities in supply chain transparency, Production and Operations Management, 28 (2019), 2946-2959.  doi: 10.1111/poms.13115.

[44]

T. SundC. LööfS. Nadjm-Tehrani and M. Asplund, Blockchain-based event processing in supply chains–A case study at IKEA, Robotics and Computer-Integrated Manufacturing, 65 (2020), 101971.  doi: 10.1016/j.rcim.2020.101971.

[45]

S. van EngelenburgM. Janssen and B. Klievink, A blockchain architecture for reducing the bullwhip effect, Lecture Notes in Business Information Processing, 319 (2018), 69-82.  doi: 10.1007/978-3-319-94214-8_5.

[46]

D. Xing and T. Liu, Sales effort free riding and coordination with price match and channel rebate, European Journal of Operational Research, 219 (2012), 264-271.  doi: 10.1016/j.ejor.2011.11.029.

[47]

D. YangT. XiaoT. M. Choi and T. C. Cheng, Optimal reservation pricing strategy for a fashion supply chain with forecast update and asymmetric cost information, International Journal of Production Research, 56 (2018), 1960-1981.  doi: 10.1080/00207543.2014.998789.

[48]

T. ZhangP. Li and N. Wang, Multi-period price competition of blockchain-technology-supported and traditional platforms under network effect, International Journal of Production Research, 0 (2021), 1-15.  doi: 10.3390/e24040557.

[49]

W.-G. ZhangQ. ZhangK. J. Mizgier and Y. Zhang, Integrating the customers' perceived risks and benefits into the triple-channel retailing, International Journal of Production Research, 55 (2017), 6676-6690.  doi: 10.1080/00207543.2017.1336679.

[50]

Z. ZhouX. LiuF. Zhong and J. Shi, Improving the reliability of the information disclosure in supply chain based on blockchain technology, Electronic Commerce Research and Applications, 52 (2022), 101121.  doi: 10.3390/e24040557.

Figure 1.  Equilibrium point $ \xi_i $ (where $ i = 0, 1, 2 $) with different values of $ CR $ and $ M $
Figure 2.  The retailer's expected profit $ \Pi_r $ under different scenarios
Figure 3.  Direct subsidy $ H $ and wholesale discount $ \delta $
Figure 4.  Sketch of the active region for the direct subsidy and wholesale discount
Figure 5.  Rough sketch structure of different threshold when $ M $ is in an intermediate range
Figure 6.  $ \Pi_s $ difference between three scenarios with different values of $ CR $ and $ M $
Figure 7.  $ \Pi_r $ difference between three scenarios with different values of $ CR $ and $ M $
Figure 8.  The profit ratio $ \rho \left({\Pi^{ds}}/{\Pi^{cs}}, {\Pi^{A}}/{\Pi^{cs}}, {\Pi^{B}}/{\Pi^{cs}}, {\Pi^{C}}/{\Pi^{cs}}\right) $
Figure 9.  Profits as a function of risk-adjusted profit margin
Figure 10.  Profits as a function of degree of forecast information asymmetry
Figure 11.  The decision-making process
Table 1.  Number of suppliers
The retailer Number of suppliers from 'qcc.com' Number of suppliers from 'tianyancha.com' Average number of suppliers Whether to use blockchain technology (using 1, not 0)
Wal-Mart 154 134 144 1
YONGHUI 47 47 47 1
Amazon 15 14 14.5 1
China Resources Vanguard Shop 18 12 15 0
Minnings 14 24 19 0
Miniso 12 9 10.5 0
Lianhua Supermarket 7 5 6 0
Watsons 5 6 5.5 0
Metro AG 33 31 32 0
RT-MART 54 54 54 0
Hyper-mart 75 57 66 0
Auchan 45 33 39 0
Wumart 7 6 6.5 0
JIAJIAYUE 43 29 36 0
The retailer Number of suppliers from 'qcc.com' Number of suppliers from 'tianyancha.com' Average number of suppliers Whether to use blockchain technology (using 1, not 0)
Wal-Mart 154 134 144 1
YONGHUI 47 47 47 1
Amazon 15 14 14.5 1
China Resources Vanguard Shop 18 12 15 0
Minnings 14 24 19 0
Miniso 12 9 10.5 0
Lianhua Supermarket 7 5 6 0
Watsons 5 6 5.5 0
Metro AG 33 31 32 0
RT-MART 54 54 54 0
Hyper-mart 75 57 66 0
Auchan 45 33 39 0
Wumart 7 6 6.5 0
JIAJIAYUE 43 29 36 0
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