Optimal subsidy strategies in a smart supply chain driven by dual innovation

Abstract: Due to the deep integration of modern information technology, supply chain management has moved into a new stage of a smart supply chain. Considering the dual smart innovation of the manufacturer's production and retailer’s service, the manufacturer-led Stackelberg game model is constructed in the smart supply chain. Under the single and coordinated government subsidy strategies, the optimal decisions of the smart supply chain are researched, and the impacts of manufacturers' risk aversion on the government subsidy strategies and supply chain decisions are analysed. In addition, the efficiencies of different government subsidy strategies are compared and analysed by numerical simulation. Finally, the results show that: (i) The moderate risk aversion by the manufacturer can improve social welfare and help provide consumers with more affordable products. (ii) The government expenditure and product prices are highest under the coordinated subsidy strategy. (iii) Subsidising manufacturers is more beneficial than subsidising retailers among the two single government subsidy strategies. (iv) In general, the coordinated government subsidy strategy is more effective than the single subsidy strategy for the innovative development of a smart supply chain. In conclusion, the research provides a significant practical reference for jointly building the smart supply chain.

How to cite this paper

 Xin, B & Xu, Y. (2022). Optimal subsidy strategies in a smart supply chain driven by dual innovation.International Journal of Industrial Engineering Computations , 13(4), 557-572.

Refrences

Abdel-Basset, M., Manogaran, G., & Mohamed, M. (2018). Internet of Things (IoT) and its impact on supply chain: A framework for building smart, secure and efficient systems. Future Generation Computer Systems, 86(9), 614-628.
Abdelkafi, N. and Pero, M. (2018). Supply chain innovation-driven business models: Exploratory analysis and implications for management, Business Process Management Journal, 24(2), 589-608.
Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157-177.
Cao, Y., Li, Q. S., & Hu, H. L. (2019). Research on the influence of different government subsidy strategies on the green decision-making of supply chain. Chinese Journal of Management, 16(2), 297-316.
Chai, J.W., Qian, Z.F., Wang, F., & Zhu, J. (2021). Process innovation for green product in a closed loop supply chain with remanufacturing, Annals of Operations Research1-25.
Chen, J., Wei, H., & Chen, J.X. (2020). Determination of strategy against natural risks for farm and sideline products in risk-averse preference: External purchasing or agricultural insurance?, Journal of Industrial Engineering and Engineering Management, 34, 175-190.
Cohen, M.C., Lobel, R., & Perakis, G. (2016). The Impact of Demand Uncertainty on Consumer Subsidies for Green Technology Adoption. Management Science, 62, 1235-1258.
Fu, D.X., Zhang, Z.Y., & Yuan, B.Y. (2019). Research on Green Supply Chain Pricing Decision Considering Risk Aversion under Government Subsidies. Operations Research and Management Science, 28, 33-40.
Gao, D., Xu, Z.D., Ruan, Y.L.Z., & Lu, H.Y. (2017). From a systematic literature review to integrated, definition for sustainable supply chain innovation (SSCI). Journal of Cleaner Production, 142, 1518-1538.
Ghosh, D., & Shah, J. (2015). Supply chain analysis under green sensitive consumer demand and cost sharing contract, International Journal of Production Economics, 164, 319-329.
Hie, G., Yue, W., & Wang, S. (2015). Qptimal selection of cleaner products in a green supply chain with risk aversion. Journal of Industrial and Management Optimization, 11, 515-528.
Hong, Z.F., & Guo, X.L. (2019). Green product supply chain contracts considering environmental responsibilities, Omega-International Journal of Management Science, 83, 155-166.
Isaksson, O.H.D., Simeth, M., & Seifert, R.W. (2016). Knowledge spillovers in the supply chain: Evidence from the high tech sectors. Research Policy, 45, 699-706.
Ivanov, D. A., Arkhipov, A. V., & Sokolov, B. N. (2004, August). Intelligent supply chain planning in virtual enterprises. In Working Conference on Virtual Enterprises (pp. 215-223). Springer, Boston, MA.
Jamil, F., Hang, L., Kim, K., & Kim, D. (2019). A Novel Medical Blockchain Model for Drug Supply Chain Integrity Management in a Smart Hospital, Electronics, 8, 505-537.
Kouvelis, P., Xiao, G., & Yang, N. (2021). Role of Risk Aversion in Price Postponement Under Supply Random Yield, Management Science, 67, 4826-4844.
Liu, C., Ji, H., & Wei, J. (2021). Smart Supply Chain Risk Assessment in Intelligent Manufacturing. Journal of Computer Information Systems, 1-13.
Liu, Y., Gao, Y., & Cao, W. (2018). Study on the Factors Affecting the Technological Innovation of Logistics Equipment Manufacturers from the Perspective of Supply Chain, IOP Conference Series Earth and Environmental Science, 189, 062054.
Luomaranta, T., & Martinsuo, M. (2019). Supply chain innovations for additive manufacturing. International Journal of Physical Distribution & Logistics Management, 50, 54-79.
Ma, Y.H., & Lu, H.Y. (2018). Smart supply chain promotes tructural reform of the supply front -- Taking Jingdong mall as an example. Enterprise Economy, 37, 188-192.
Mahmood, I.P., & Rufin, C. (2005). Government's Dilemma: The Institutional Framework for Imitation and Innovation. The Academy of Management Review, 30, 338-360.
Meng, L.J., Huang, Z.Q., Zhang, B.Y., & Yang, Y.X. (2021). Model of Considering the Government Consumption-subsidy Policy For Consumer in the Closed-Loop Supply Chain. Chinese Journal of Management Science, 29, 148-160.
Palmisano, S.J. (2008). A smarter planet: the next leadership agenda, IBM. November 6, 1-8.
Ramanathan, U. (2017). How Smart Operations Help Better Planning and Replenishment?: Empirical Study – Supply Chain Collaboration for Smart Operations. Operations and Service Management.
Reimann, M., Xiong, Y., & Zhou, Y. (2019). Managing a closed-loop supply chain with process innovation for remanufacturing. European Journal of Operational Research, 276, 510-518.
Shang, W.F., & Teng, L.L. (2020). Game Strategy Considering Government Subsidies and Sales Efforts in Retailer-led Green Supply Chain. Systems Engineering, 38, 40-50.
Sun, D., & Yu, Y. M. (2018). determination of the government’s optimal subsidy policy in the green product market. Journal of Management, 15(1), 118-126.
Todo, Y., Matous, P., & Inoue, H. (2016). The strength of long ties and the weakness of strong ties: Knowledge diffusion through supply chain networks. Research Policy, 45(9), 1890-1906.
Wan, X., & Qie, X. (2020). Poverty alleviation ecosystem evolutionary game on smart supply chain platform under the government financial platform incentive mechanism. Journal of Computational and Applied Mathematics, 372, 112595.
Wang, M., Asian, S., Wood, L.C., & Wang, B. (2020). Logistics innovation capability and its impacts on the supply chain risks in the Industry 4.0 era, Modern Supply Chain Research and Applications, 2, 83-98.
Wen, X.Q., Cheng, H.F., Cai, J.H., & Lu, C. (2018). Government Subside Policies and Effect Analysis in Green Supply Chain, Chinese Journal of Management Science, 15, 625-632.
Wu, L.F., Yue, X.H., Jin, A., & Yen, D.C. (2016). Smart supply chain management: a review and implications for future research. International Journal of Logistics Management, 27, 395-417.
Yi, Y.Y., & Li, J.X. (2018a). Cost-Sharing Contracts for Energy Saving and Emissions Reduction of a Supply Chain under the Conditions of Government Subsidies and a Carbon Tax. Sustainability, 10, 33.
Yi, Y.Y., & Li, J.X. (2018b). The effect of governmental policies of carbon taxes and energy-saving subsidies on enterprise decisions in a two-echelon Supply chain. Journal of Cleaner Production, 181, 675-691.
Yu, J.J., Tang, C.S., & Shen, Z.J.M. (2018). Improving Consumer Welfare and Manufacturer Profit via Government Subsidy Programs: Subsidizing Consumers or Manufacturers?, M&Som-Manufacturing & Service Operations Management, 20, 752-766.
Zhang, K.Y., Li, C.X., Yao, J.M., & LI, J.X. (2019). Decision-making and coordination of green supply chain with risk aversion un-der government subsidies. Journal of Shandong University(Natural Science, 54, 35-51.
Zhang, X.M., Zhu, J.H., Dan, B., LIU, M.L., & Lei, T. (2021). Incentive contract for fresh produce freshness-keeping investment considering subsidies and public welfare. Systems Engineering-Theory & Practice, 1-18.