Skip to main content
SpringerLink
Log in

Research on a Dynamic Decision Mechanism of Demand Oriented Supply Chain Cooperation Behavior

  • Published:
Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Abstract

To solve the problem of supply chain management and decision-making under the restriction of the government and social group, we use the cooperative game theory method to seek a way to develop the enterprise. According to the general market competition in game analysis for product manufacturing enterprises as representatives for further discussion under the constraints of the government and social consumer groups, we examine the dynamic decision-making process of supply chain management, the attitudes adopted by the enterprises toward the government and consumer groups in the game for obtaining greater benefits, and the development of enterprises for providing creativity as well as theory and methodology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

c f :

The fixed cost of unit product

c v :

The variable cost of unit product

c i :

The unit variable cost when providing the product

ci,o :

The fixed costs of production

D :

Manufacturer’s forecast of product demand

e :

The sum of funds and manpower invested by the government

E[Co.]:

The total expected return that an enterprise obtains in market activities

Ei [Co.]:

The expected return of an enterprise under constraints

E[Govt.]:

The total expected benefit that the government obtains in market activities

Ei [Govt.]:

The expected benefit of the government under constraints

E[Cons.]:

The total expected benefit that consumer groups obtain in market activities

Ei [Cons.]:

The expected benefit of consumer groups under constraints

F(e):

The expected benefit to consumer groups after the government takes measures

G(p, q, t):

The benefit function brought by the product price, quantity and quality when consumer groups buy products

H(xi, qi):

Consumer group benefit function from enterprises fulfilling their social responsibilities

m :

The proportion of high-end consumers who purchase high-end products in the market to the total number of high-end consumers

n :

The proportion of low-end consumers who purchase low-end products in the market to the total number of low-end consumers

p :

Product price

q :

Production output

q o :

Actual production of products on market demand

q i :

The number of products produced by a single enterprise

Q :

The total volume of products provided by enterprises

S(qi):

The level of grade developed by the government

t i :

The integrated utility of product

T(xi):

The distribution function of the reward or punishment on enterprises developed by the government

U :

Expected benefits of manufacturers

W(e):

The expected benefit obtained after the government takes some measures

x i :

The degree of social responsibility performed by enterprises

X 0 :

Government tolerance of the enterprise

X̄ :

The upper limit of the government’s reward or punishment on enterprises

X̲ :

The lower limit of the government’s reward or punishment on enterprises

References

  1. PEIRIS K D A, JUNG J, GALLUPE R B. Building and evaluating ESET: A tool for assessing the support given by an enterprise system to supply chain management [J]. Decision Support Systems, 2015, 77: 41–54.

    Article  Google Scholar 

  2. LEE T, NAM H. An empirical study on the impact of individual and organizational supply chain orientation on supply chain management [J]. The Asian Journal of Shipping and Logistics, 2016, 32(4): 249–255.

    Article  Google Scholar 

  3. LI J Z, XIONG N X, PARK J H, et al. Intelligent model design of cluster supply chain with horizontal cooperation [J]. Journal of Intelligent Manufacturing, 2012, 23(4): 917–931.

    Article  Google Scholar 

  4. TALEIZADEH A A, SOLEYMANFAR V R, CHOI T M. Optimal pricing and alliance strategy in a retailer-led supply chain with the return policy: A game-theoretic analysis [J]. Information Sciences, 2017, 420: 466–489.

    Article  Google Scholar 

  5. CHO S H, TANG C S. Advance selling in a supply chain under uncertain supply and demand [J]. Manufacturing & Service Operations Management, 2013, 15(2): 305–319.

    Article  Google Scholar 

  6. MASTEIKA I, CEPINSKIS J. Dynamic capabilities in supply chain management [J]. Procedia-Social and Behavioral Sciences, 2015, 213: 830–835.

    Article  Google Scholar 

  7. BESKE P. Dynamic capabilities and sustainable supply chain management [J]. International Journal of Physical Distribution & Logistics Management, 2012, 42(4): 372–387.

    Article  Google Scholar 

  8. WADHWA S, SAXEN A A, CHAN F T S. Framework for flexibility in dynamic supply chain management [J]. International Journal of Production Research, 2008, 46(6): 1373–1404.

    Article  Google Scholar 

  9. GENC T S, GIOVANNI P D. Trade-in and save: A two-period closed-loop supply chain game with price and technology dependent returns [J]. International Journal of Production Economics, 2017, 183: 514–527.

    Article  Google Scholar 

  10. MENA C, HUMPHRIES A, CHOI T Y. Toward a theory of multi-tier supply chain management [J]. Journal of Supply Chain Management, 2013, 49(2): 58–76.

    Article  Google Scholar 

  11. KUMAR D, SINGH J, SINGH O P, et al. A fuzzy logic based decision support system for evaluation of suppliers in supply chain management practices [J]. Mathematical and Computer Modelling, 2013, 58(11/12): 1679–1695.

    Article  Google Scholar 

  12. NAINI S G J, ALIAHMADI A R, JAFARI-ESKANDARI M. Designing a mixed performance measurement system for environmental supply chain management using evolutionary game theory and balanced scorecard: A case study of an auto industry supply chain [J]. Resources, Conservation and Recycling, 2011, 55(6): 596–603.

    Google Scholar 

  13. JENA S K, SARMAH S P. Price competition and cooperation in a duopoly closed-loop supply chain [J]. International Journal of Production Economics, 2014, 156: 346–360.

    Article  Google Scholar 

  14. LI S X, HUANG Z M, ASHLEY A. Vertical cooperative advertising in a manufacturer-retailer supply channel [J]. Applications of Management Science, 2006, 12: 157–173.

    Google Scholar 

  15. MAZDEH M M, KARAMOUZIAN A. Evaluating strategic issues in supply chain scheduling using game theory [J]. International Journal of Production Research, 2014, 52(23): 7100–7113.

    Article  Google Scholar 

  16. MA W M, ZHAO Z, KE H. Dual-channel closed-loop supply chain with government consumption-subsidy [J]. European Journal of Operational Research, 2013, 226(2): 221–227.

    Article  MathSciNet  Google Scholar 

  17. MADANI S R, RASTI-BARZOKI M. Sustainable supply chain management with pricing, greening and governmental tariffs determining strategies: A game-theoretic approach [J]. Computers & Industrial Engineering, 2017, 105: 287–298.

    Article  Google Scholar 

  18. HEYDARI J, GOVINDAN K, JAFARI A. Reverse and closed loop supply chain coordination by considering government role [J]. Transportation Research Part D, 2017, 52: 379–398.

    Article  Google Scholar 

  19. ALJAZZAR S M, JABER M Y, GOYAL S K. Coordination of a three-level supply chain (supplier-manufacturer-retailer) with permissible delay in payments and price discounts [J]. International Journal of Systems Science: Operations & Logistics, 2016, 3(3): 176–188.

    Google Scholar 

  20. GOVINDAN K, FATTAHI M, KEYVANSHOKOOH E. Supply chain network design under uncertainty: A comprehensive review and future research directions [J]. European Journal of Operational Research, 2017, 263(1): 108–141.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Economics & Management, China University of Petroleum (East China), Qingdao, Shandong, 266580, China

    Xiaodong Lü  (吕肖东) & Hao Ding  (丁 浩)

  2. School of Marxism, Shanghai Jiao Tong University, Shanghai, 200030, China

    Lin Quan  (全 林)

Authors
  1. Xiaodong Lü  (吕肖东)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hao Ding  (丁 浩)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lin Quan  (全 林)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lin Quan  (全 林).

Additional information

Foundation item: the National Natural Science Foundation of China (No. 71801224), the Natural Science Foundation of Shandong Province (No. ZR2017MG017), and the Soft Science Research Program of Shandong Province (No. 2019RKE28015)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lü, X., Ding, H. & Quan, L. Research on a Dynamic Decision Mechanism of Demand Oriented Supply Chain Cooperation Behavior. J. Shanghai Jiaotong Univ. (Sci.) 25, 127–136 (2020). https://doi.org/10.1007/s12204-020-2157-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12204-020-2157-4

Keywords

CLC number

Document code

Search

Navigation