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Study on supply chain strategy based on cost income model and multi-access edge computing under the background of the Internet of Things

  • Lu Sun
  • Yuanjun ZhaoEmail author
  • Wenqi Sun
  • Zhengkai Liu
Multi-access Edge Computing Enabled Internet of Things
  • 15 Downloads

Abstract

With the application of the Internet of Things, the cold-chain logistics efficiency of fresh agricultural product remarkably is improved, but the operating costs inevitably rise. Thus, the main bodies of circulation at various levels need to decide whether adopt the Internet of Things or not according to the cost–benefit situation. The significant boundary value closely related to the revenue decision of cold-chain logistics of fresh agricultural product was figured out by particularly analyzing the impact of the adoption of the Internet of Things on upstream and downstream wholesale prices, retail price, and order quantity decision based on the costs and revenues of the upstream and downstream of the supply chain before and after the adoption of the Internet of Things, and it was found that the overall profit boundary values of wholesaler, retailer, and supply chain are the same; the increment of retail price and retailers’ revenues is larger than that of wholesalers’ revenues, and the ascensional range of retail price is larger than that of wholesale price; the cost boundary value of order quantity in supply chain has little to do with the quality of agricultural products, but is affected by the time of circulation, and transportation and warehouse cost; the lower the cost of the Internet of Things is, the larger the impact on order quantity is. The correctness of the research results was proved by means of illustrative example. This paper provides a scientific basis for investment in the Internet of Things by enterprises engaged in cold-chain operation of fresh agricultural products.

Keywords

Multi-access edge computing Internet of Things Fresh agricultural product Cost effectiveness of cold-chain logistics 

Notes

Acknowledgements

The authors thank Project supported by Fujian Provincial Social Science Research Base Major Project (Grant No. 2016JDZ037); Xiamen University of Technology high level talent project(Grant No. YSK16009R). Ministry of Education, Humanities and Social Sciences project ‘Research on the evolution of global value chain of digital creative industry based on complex system’.

Compliance with ethical standards

Conflict of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work and there is no professional or other personal interest of any nature or kind in any product, service, and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled.

References

  1. 1.
    Tsang YP, Choy KL, Wu CH, Ho GTS, Lam HY, Tang V (2018) An intelligent model for assuring food quality in managing a multi-temperature food distribution centre. Food Control 90:81–97Google Scholar
  2. 2.
    Bogataj D, Bogataj M, Hudoklin D (2017) Mitigating risks of perishable products in the cyber-physical systems based on the extended mrp model. Int J Prod Econ 193:51–62Google Scholar
  3. 3.
    Gunasekaran A, Subramanian N, Tiwari MK (2016) Information technology governance in internet of things supply chain networks. Ind Manag Data Syst 116(7):1–32Google Scholar
  4. 4.
    Bardaki C, Kourouthanassis P, Pramatari K (2012) Deploying RFID-enabled services in the retail supply chain: lessons learned toward the internet of things. J Inf Syst Manag 29(3):233–245Google Scholar
  5. 5.
    Silva TRD, Saalmann P, Cordes AK, Giacomolli A, Pereira CE, Hellingrath B (2014) Integration architecture of intelligent maintenance systems and spare parts supply chain planning. Procedia CIRP 25:192–198Google Scholar
  6. 6.
    Miorandi D, Sicari S, Pellegrini FD, Chlamtac I (2012) Internet of things: vision, applications and research challenges. Ad Hoc Netw 10(7):1497–1516Google Scholar
  7. 7.
    Verdouw CN, Beulens AJM, van der Vorst JGAJ (2013) Virtualisation of floricultural supply chains: a review from an internet of things perspective. Comput Electron Agric 99(6):160–175Google Scholar
  8. 8.
    Verdouw CN, Wolfert J, Beulens AJM, Rialland A (2016) Virtualization of food supply chains with the internet of things. J Food Eng 176(1):128–136Google Scholar
  9. 9.
    Bendaya M, Hassini E, Bahroun Z (2017) Internet of things and supply chain management: a literature review. Int J Prod Res 55(3):1–24Google Scholar
  10. 10.
    Zanella A, Bui N, Castellani A, Vangelista L, Zorzi M (2014) Internet of things for smart cities. IEEE Internet Things J 1(1):22–32Google Scholar
  11. 11.
    Geerts GL, O’Leary DE (2014) A supply chain of things: the eaglet ontology for highly visible supply chains. Decis Support Syst 63(3):3–22Google Scholar
  12. 12.
    Perera C, Zaslavsky A, Christen P, Georgakopoulos D (2014) Context aware computing for the internet of things: a survey. IEEE Commun Surv Tutor 16(1):414–454Google Scholar
  13. 13.
    Kortuem G, Kawsar F, Sundramoorthy V, Fitton D (2009) Smart objects as building blocks for the internet of things. IEEE Internet Comput 14(1):44–51Google Scholar
  14. 14.
    Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M (2015) Internet of things: a survey on enabling technologies, protocols, and applications. IEEE Commun Surv Tutor 17(4):2347–2376Google Scholar
  15. 15.
    Huang Z, Shan G, Cheng J, Sun J (2018) TRec: an efficient recommendation system for hunting passengers with deep neural networks. Neural Comput Appl.  https://doi.org/10.1007/s00521-018-3728-2 Google Scholar
  16. 16.
    Kaur B, Singh D, Roy PP (2018) Age and gender classification using brain–computer interface. Neural Comput Appl.  https://doi.org/10.1007/s00521-018-3397-1 Google Scholar
  17. 17.
    Hamedani K, Seyyedsalehi SA, Ahamdi R (2016) Video-based face recognition and image synthesis from rotating head frames using nonlinear manifold learning by neural networks. Neural Comput Appl 27(6):1761–1769Google Scholar
  18. 18.
    Batalla JM, Gonciarz F (2018) Deployment of smart home management system at the edge: mechanisms and protocols. Neural Comput Appl.  https://doi.org/10.1007/s00521-018-3545-7 Google Scholar
  19. 19.
    Hassan MK, Desouky AIE, Badawy MM, Sarhan AM, Elhoseny M, Gunasekaran M (2018) EoT-driven hybrid ambient assisted living framework with naïve Bayes–firefly algorithm. Neural Comput Appl.  https://doi.org/10.1007/s00521-018-3533-y Google Scholar
  20. 20.
    Markakis EK, Politis I, Lykourgiotis A, Rebahi Y, Mastorakis G, Mavromoustakis CX et al (2017) Efficient next generation emergency communications over multi-access edge computing. IEEE Commun Mag 55(11):92–97Google Scholar
  21. 21.
    Welbourne E, Battle L, Cole G, Gould K, Rector K, Raymer S et al (2009) Building the internet of things using RFID: the RFID ecosystem experience. IEEE Internet Comput 13(3):48–55Google Scholar
  22. 22.
    Couprie C, Grady L, Talbot H, Najman L (2011) Combinatorial continuous maximal flows. SIAM J Imaging Sci 4(3):905–930MathSciNetzbMATHGoogle Scholar
  23. 23.
    Wit TDD (2013) Methods for characterising microphysical processes in plasmas. Space Sci Rev 178(2–4):665–693Google Scholar
  24. 24.
    Beimel A, Farràs O, Mintz Y (2016) Secret-sharing schemes for very dense graphs. J Cryptol 29(2):336–362MathSciNetzbMATHGoogle Scholar
  25. 25.
    Lattner C, Lenharth A, Adve V (2007) Making context-sensitive points-to analysis with heap cloning practical for the real world. ACM SIGPLAN Not 42(6):278–289Google Scholar
  26. 26.
    Poulin NM, Matthews JB, Skov KA, Palcic B (1994) Effects of fixation method on image cytometric measurement of dna content and distribution in cells stained for fluorescence with propidium iodide. J Histochem Cytochem 42(8):1149–1156Google Scholar
  27. 27.
    Keefe TF, Thuraisingham MB, Tsai WT (2015) Secure query-processing strategies. Computer 22(3):63–70Google Scholar
  28. 28.
    Aptoula E, Lefèvre S (2007) A comparative study on multivariate mathematical morphology. Pattern Recogn 40(11):2914–2929zbMATHGoogle Scholar
  29. 29.
    Weber RH (2010) Internet of things—new security and privacy challenges. Comput Law Secur Rev Int J Technol Pract 26(1):23–30MathSciNetGoogle Scholar
  30. 30.
    Van Eenennaam AL, Weigel KA, Young AE, Cleveland MA, Dekkers JC (2014) Applied animal genomics: results from the field. Annu Rev Anim Biosci 2(2):105–139Google Scholar
  31. 31.
    Costa MC, Monclar FR, Zrikem M (2002) Variable neighborhood decomposition search for the optimization of power plant cable layout. J Intell Manuf 13(5):353–365Google Scholar
  32. 32.
    Botta A, Donato WD, Persico V (2016) Integration of cloud computing and internet of things. Future Gener Comput Syst 56(C):684–700Google Scholar
  33. 33.
    Wang J, Zhu R, Liu S (2018) A differentially private unscented Kalman filter for streaming data in IoT. IEEE Access 6:6487–6495Google Scholar
  34. 34.
    Zhu R, Ma M, Liu L, Mao S (2017) Cooperative and intelligent sensing: a special section in iEEE Access. IEEE Access 5:27824–27826Google Scholar
  35. 35.
    Liu X, Zhu R, Jalaian B, Sun Y (2015) Dynamic spectrum access algorithm based on game theory in cognitive radio networks. ACM MONET 20(6):817–827Google Scholar
  36. 36.
    Wu B, Yan X, Wang Y, Guedes Soares C (2017) An evidential reasoning-based CREAM to human reliability analysis in maritime accident process. Risk Anal 37(10):1936–1957Google Scholar
  37. 37.
    Wu B, Zong L, Yan X, Guedes Soares C (2018) Incorporating evidential reasoning and TOPSIS into group decision-making under uncertainty for handling ship without command. Ocean Eng 164:590–603Google Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Cultural Industries and TourismXiamen University of TechnologyXiamenChina
  2. 2.School of Business AdministrationShanghai Lixin University of Accounting and FinanceShanghaiChina
  3. 3.Glorious Sun School of Business and ManagementDonghua UniversityShanghaiChina
  4. 4.College of Economics and ManagementNortheast Agricultural UniversityHarbinChina
  5. 5.College of BusinessSouthern Illinois UniversityCarbondaleUSA
  6. 6.International CollegeRenmin University of ChinaSuzhouChina

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