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Price and Product Quality Decisions for a Two-Echelon Supply Chain in the Blockchain Era by:9 (Source: Crossref)
    This article is part of the issue:

    Frequent problems of counterfeiting have spawned consumer demands to monitor the entire supply chain. The application of blockchain technology with anti-counterfeiting and traceability can improve the reliability and authenticity of product information and eliminate consumer doubts about product quality. Furthermore, based on the transparency of blockchain technology, brand suppliers can independently obtain the market demand information through information sharing. This paper introduces a consumer suspicion coefficient to illustrate the application of blockchain technology in the supply chain. Considering product authenticity verification and information sharing, we study the optimal pricing and product quality decisions in a two-level supply chain under the following three scenarios: (1) no blockchain technology, a traditional supply chain, and no information sharing (case TN); (2) no blockchain technology but a traditional supply chain with information sharing (case TS); and (3) a supply chain based on blockchain technology (case BT). We find that when the consumer suspicion coefficient increases, consumers will have limited faith in the authenticity of the product, which will affect the retailer’s optimal decision and profit. By comparing the equilibrium results of several cases, we also find that demand information sharing by the retailer may not achieve a win-win outcome in a decentralized channel in the absence of blockchain technology. Under demand information sharing based on blockchain technology, however, if the consumer suspicion coefficient exceeds a certain threshold, the brand supplier and retailer can achieve a win–win outcome. In addition, the extended models reveal that in a centralized supply chain, regardless of the state of market demand, blockchain technology can always improve product quality and retail price and optimize supply chain profit.


    • Aste, T, P Tasca and TD Matteo (2017). Blockchain technologies: The foreseeable impact on society and industry. Computer, 50(9), 18–28. Crossref, ISIGoogle Scholar
    • Biswas, K, V Muthukkumarasamy and WL Tan (2017). Blockchain based wine supply chain traceability system. Future Technologies Conference, Vancouver, BC, Canada, pp. 1–7. Google Scholar
    • Bertini, M, D Halbheer and O Koenigsberg (2020). Price and quality decisions by self-serving managers. International Journal of Research in Marketing, 37(2), 236–257. Crossref, ISIGoogle Scholar
    • Bashir, I (2017). Mastering Blockchain. Birmingham: Packt Publishing. Google Scholar
    • Choi, TM (2019). Blockchain-technology-supported platforms for diamond authentication and certification in luxury supply chains. Transportation Research Part E: Logistics and Transportation Review, 128, 17–29. Crossref, ISIGoogle Scholar
    • Choi, TM, LP Feng and R Li (2020a). Information disclosure structure in supply chains with rental service platforms in the blockchain technology era. International Journal of Production Economics, 221(3), 107473. Crossref, ISIGoogle Scholar
    • Choi, TM, S Guo, N Liu and XT Shi (2020b). Optimal pricing in on-demand-service-platform-operations with hired agents and risk-sensitive customers in the blockchain era. European Journal of Operational Research, 284, 1031–1042. Crossref, ISIGoogle Scholar
    • Cui, R, G Allon, A Bassamboo and JV Mieghem (2015). Information sharing in supply chains: An empirical and theoretical valuation. Management Science, 61(11), 2803–2824. Crossref, ISIGoogle Scholar
    • Chen, RY (2018). A traceability chain algorithm for artificial neural networks using T–S fuzzy cognitive maps in blockchain. Future Generation Computer Systems, 80, 198–210. Crossref, ISIGoogle Scholar
    • Cheng, TCE and YN Wu (2005). The impact of information sharing in a two-level supply chain with multiple retailers. Journal of the Operational Research Society, 56(10), 1159–1165. Crossref, ISIGoogle Scholar
    • Cho, SH, X Fang and S Tayur (2015). Combating strategic counterfeiters in licit and illicit supply chains. Manufacturing and Service Operations Management, 17(3), 273–289. Crossref, ISIGoogle Scholar
    • Chenavaz, RY, G Feichtinger, RF Hartl and PM Kort (2020). Modeling the impact of product quality on dynamic pricing and advertising policies. European Journal of Operational Research, 284, 990–1001. Crossref, ISIGoogle Scholar
    • Feng, J and J Xie (2007). Performance-based advertising: Price and advertising as signals of product quality. Social Science Electronic Publishing, 23(3), 1030–1041. Google Scholar
    • Guan, ZL, XM Zhang, MS Zhou and YR Dan (2020). Demand information sharing in competing supply chains with manufacturer-provided service. International Journal of Production Economics, 220, 107450. Crossref, ISIGoogle Scholar
    • Hughes, L, YK Dwivedi, SK Misra, NP Rana, V Raghavan and V Akella (2019). Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda. International Journal of Information Management, 49, 114–129. Crossref, ISIGoogle Scholar
    • Ha, AY and S Tong (2008). Contracting and information sharing under supply chain competition. Management Science, 54, 701–715. Crossref, ISIGoogle Scholar
    • Ha, AY, Q Tian and S Tong (2017). Information sharing in competing supply chains with production cost reduction. Manufacturing and Service Operations Management, 19, 246–262. Crossref, ISIGoogle Scholar
    • Jiang, B, L Tian, Y Xu and F Zhang (2016). To share or not to share: Demand forecast sharing in a distribution channel. Marketing Science, 35(5), 800–809. Crossref, ISIGoogle Scholar
    • Kshetri, N (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39(4), 80–89. Crossref, ISIGoogle Scholar
    • Li, G, L Li and J Sun (2019). Pricing and service effort strategy in a dual-channel supply chain with showrooming effect. Transportation Research Part E: Logistics and Transportation Review, 126, 32–48. Crossref, ISIGoogle Scholar
    • Lee, HL, KC So and CS Tang (2000). The value of information sharing in a two-level supply chain. Management Science, 46(5), 626–643. Crossref, ISIGoogle Scholar
    • Lejarza, F and M Balde (2020). Closed-loop optimal operational planning of supply chains with fast product quality dynamics. Computers and Chemical Engineering, 132, 106594. Crossref, ISIGoogle Scholar
    • Li, X and XT Qi (2019). On pricing and quality decisions with risk aversion. Omega, 13, 102118. Google Scholar
    • Olsen, TL and B Tomlin (2020). Industry 4.0: Opportunities and challenges for operations management. Manufacturing and Service Operations Management, 22(1), 113–122. Crossref, ISIGoogle Scholar
    • Peterson, RA and AJ Jolibert (2015). A cross national investigation of price and brand as determinant of perceived product quality. Journal of Applied Psychology, 61(4), 533–536. Crossref, ISIGoogle Scholar
    • Qian, Y (2011). Counterfeiters: Foes or friends? How do counterfeits affect different product quality tiers? Northwestern University–Kellogg School of Management, Working Paper. Google Scholar
    • Rao, AR and KB Monroe (1989). The effect of price, brand name, and store name on buyers’ perceptions of product quality an integrative review. Journal of Marketing Research, 26(3), 351–357. Crossref, ISIGoogle Scholar
    • Shi, X and TM Choi (2019). Enhancing food safety by using blockchain technologies. The Hong Kong Polytechnic University, Working Paper. Google Scholar
    • Shen, B, XY Xu and Q Yuan (2020). Selling secondhand products through an online platform with blockchain. Transportation Research Part E: Logistics and Transportation Review, 142, 102066. Crossref, ISIGoogle Scholar
    • Sandeep, S and K Manjunath (2017). Performance modeling of a two-echelon supply chain under different levels of upstream inventory information sharing. Computers & Operations Research, 77, 210–225. Crossref, ISIGoogle Scholar
    • Sun, X, W Tang, J Chen, S Li and J Zhang (2019). Manufacturer encroachment with production cost reduction under asymmetric information. Transportation Research Part E: Logistics and Transportation Review, 128, 191–211. Crossref, ISIGoogle Scholar
    • Shang, W, AY Ha and S Tong (2015). Information sharing in a supply chain with a common retailer. Management Science, 62, 245–263. Crossref, ISIGoogle Scholar
    • Stevenson, M and J Busby (2015). An exploratory analysis of counterfeiting strategies: Towards counterfeit-resilient supply chains. International Journal of Operations & Production Management, 35(1), 110–144. Crossref, ISIGoogle Scholar
    • Vaio, AD and L Varriale (2020). Blockchain technology in supply chain management for sustainable performance: Evidence from the airport industry. International Journal of Information Management, 52(6), 102014. Crossref, ISIGoogle Scholar
    • Wamba, SF, MM Queiroz and L Trinchera (2020). Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation. International Journal of Production Economics, 229, 107791. Crossref, ISIGoogle Scholar
    • Wang, ZJ, TY Wang, H Hu, J Gong, X Ren and QY Xiao (2020). Blockchain-based framework for improving supply chain traceability and information sharing in precast construction. Automation in Construction, 111, 103063. Crossref, ISIGoogle Scholar
    • Yu, YG, SJ Zhou and Y Shi (2020). Information sharing or not across the supply chain: The role of carbon emission reduction. Transportation Research Part E: Logistics and Transportation Review, 137, 101915. Crossref, ISIGoogle Scholar
    • Yao, DQ and JJ Liu (2005). Competitive pricing of mixed retail and e-tail distribution channels. Omega, 33(3), 235–247. Crossref, ISIGoogle Scholar
    • Ye, TF and HQ Yang (2020). Price and quality management with strategic consumers: Whether to introduce a high or low product variant. Applied Mathematics and Computation, 386, 125541. Crossref, ISIGoogle Scholar
    • Zhang, S, B Dan and M Zhou (2019). After-sale service deployment and information sharing in a supply chain under demand uncertainty. European Journal of Operational Research, 279(2), 351–363. Crossref, ISIGoogle Scholar
    • Zhao, J, YM Zhou, ZH Cao and J Min (2020). The shelf space and pricing strategies for a retailer-dominated supply chain with consignment based revenue sharing contracts. European Journal of Operational Research, 280(3), 926–939. Crossref, ISIGoogle Scholar
    • Zhu, SX (2015). Integration of capacity, pricing, and lead-time decisions in a decentralized supply chain. International Journal of Production Economics, 164, 14–23. Crossref, ISIGoogle Scholar
    • Zhou, M, B Dan, S Ma and X Zhang (2017). Supply chain coordination with information sharing: The informational advantage of GPOs. European Journal of Operational Research, 256(3), 785–802. Crossref, ISIGoogle Scholar
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