[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i22p6693-6706.html
   My bibliography  Save this article

Smart box-enabled product–service system for cloud logistics

Author

Listed:
  • Yingfeng Zhang
  • Sichao Liu
  • Yang Liu
  • Rui Li
Abstract
Modern logistics takes significant progress and rapid developments with the prosperity of E-commerce, particularly in China. Typical challenges that logistics industry is facing now are composed by a lack of sharing, standard, cost-effective and environmental package and efficient optimisation method for logistics tasks distribution. As a result, it is difficult to implement green, sustainable logistics services. Three important technologies, Physical Internet (PI), product–service system (PSS) and cloud computing (CC), are adopted and developed to address the above issues. PI is extended to design a world-standard green recyclable smart box that is used to encapsulate goods. Smart box-enabled PSS is constructed to provide an innovative sustainable green logistics service, and high-quality packaging, as well as reduce logistics cost and environmental pollution. A real-time information-driven logistics tasks optimisation method is constructed by designing a cloud logistics platform based on CC. On this platform, a hierarchical tree-structure network for customer orders (COs) is built up to achieve the order-box matching of function. Then, a distance clustering analysis algorithm is presented to group and form the optimal clustering results for all COs, and a real-time information-driven optimisation method for logistics orders is proposed to minimise the unused volume of containers. Finally, a case study is simulated to demonstrate the efficiency and feasibility of proposed cloud logistics optimisation method.

Suggested Citation

  • Yingfeng Zhang & Sichao Liu & Yang Liu & Rui Li, 2016. "Smart box-enabled product–service system for cloud logistics," International Journal of Production Research, Taylor & Francis Journals, vol. 54(22), pages 6693-6706, November.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:22:p:6693-6706
    DOI: 10.1080/00207543.2015.1134840
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2015.1134840
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2015.1134840?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Yingfeng & Zhang, Geng & Du, Wei & Wang, Junqiang & Ali, Ebad & Sun, Shudong, 2015. "An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 282-292.
    2. Rochdi Sarraj & Eric Ballot & Shenle Pan & Benoit Montreuil, 2012. "Analogies between Internet network and ‎logistics service networks: challenges ‎involved in the interconnection," Post-Print hal-00733525, HAL.
    3. Zhong, Ray Y. & Huang, George Q. & Lan, Shulin & Dai, Q.Y. & Chen, Xu & Zhang, T., 2015. "A big data approach for logistics trajectory discovery from RFID-enabled production data," International Journal of Production Economics, Elsevier, vol. 165(C), pages 260-272.
    4. Subramanian, Nachiappan & Abdulrahman, Muhammad D. & Zhou, Xiaolai, 2014. "Integration of logistics and cloud computing service providers: Cost and green benefits in the Chinese context," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 86-98.
    5. Shenle Pan & Michele Nigrelli & Eric Ballot & Rochdi Sarraj & Yanyan Yang, 2015. "Perspectives of inventory control models in the Physical Internet: A simulation study," Post-Print hal-01112144, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Binni & Wang, Pong & Tu, Yiliu, 2021. "Customer satisfaction service match and service quality-based blockchain cloud manufacturing," International Journal of Production Economics, Elsevier, vol. 240(C).
    2. Tan, Jianhua & Wang, Xiongyuan & Chan, Kam C., 2020. "Does a national reform of a logistics system matter in corporate cash management? Evidence from logistics service standardization in China," Pacific-Basin Finance Journal, Elsevier, vol. 63(C).
    3. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    4. Shenle Pan & Ray Zhong & Ting Qu, 2019. "Smart product-service systems in interoperable logistics: Design and implementation prospects," Post-Print hal-02316272, HAL.
    5. Shenle Pan, 2019. "Opportunities of Product-Service System in Physical Internet," Post-Print hal-02155622, HAL.
    6. Yu Zhang & Nan Liu, 2021. "Optimal Internet of Things Technology Adoption Decisions and Pricing Strategies for High-Traceability Logistics Services," Sustainability, MDPI, vol. 13(19), pages 1-33, September.
    7. Yingfeng Zhang & Dong Xi & Haidong Yang & Fei Tao & Zhe Wang, 2019. "Cloud manufacturing based service encapsulation and optimal configuration method for injection molding machine," Journal of Intelligent Manufacturing, Springer, vol. 30(7), pages 2681-2699, October.
    8. Sunida Tiwong & Sakgasem Ramingwong & Korrakot Yaibuathet Tippayawong, 2020. "On LSP Lifecycle Model to Re-design Logistics Service: Case Studies of Thai LSPs," Sustainability, MDPI, vol. 12(6), pages 1-17, March.
    9. Kurtz, Julian & Zinke-Wehlmann, Christian & Lugmair, Nina & Schymanietz, Martin & Roth, Angela, 2023. "Characterising smart service systems – Revealing the smart value," SMR - Journal of Service Management Research, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 7(2), pages 112-128.
    10. Yu Gong & Lujie Chen & Fu Jia & Richard Wilding, 2019. "Logistics Innovation in China: The Lens of Chinese Daoism," Sustainability, MDPI, vol. 11(2), pages 1-21, January.
    11. Masoud Zafarzadeh & Magnus Wiktorsson & Jannicke Baalsrud Hauge, 2021. "A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective," Logistics, MDPI, vol. 5(2), pages 1-32, April.
    12. Xinyang Xu & Yang Yang, 2022. "Analysis of the Dilemma of Promoting Circular Logistics Packaging in China: A Stochastic Evolutionary Game-Based Approach," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
    13. Jesús García-Arca & José A. Comesaña-Benavides & A. Trinidad González-Portela Garrido & J. Carlos Prado-Prado, 2020. "Rethinking the Box for Sustainable Logistics," Sustainability, MDPI, vol. 12(5), pages 1-22, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Hui & Gong, Qiguo & Wang, Shouyang, 2017. "Information processing structures and decision making delays in MRP and JIT," International Journal of Production Economics, Elsevier, vol. 188(C), pages 41-49.
    2. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid & Zied Babai, M., 2023. "Network inventory deployment for responsive fulfillment," International Journal of Production Economics, Elsevier, vol. 255(C).
    3. Ray Qing Cao & Dara G. Schniederjans & Vicky Ching Gu, 2021. "Stakeholder sentiment in service supply chains: big data meets agenda-setting theory," Service Business, Springer;Pan-Pacific Business Association, vol. 15(1), pages 151-175, March.
    4. Gunasekaran, Angappa & Subramanian, Nachiappan & Papadopoulos, Thanos, 2017. "Information technology for competitive advantage within logistics and supply chains: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 14-33.
    5. Hao Zhang & Jie He & Xiaomeng Shi & Qiong Hong & Jie Bao & Shuqi Xue, 2020. "Technology Characteristics, Stakeholder Pressure, Social Influence, and Green Innovation: Empirical Evidence from Chinese Express Companies," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    6. Dev, Navin K. & Shankar, Ravi & Swami, Sanjeev, 2020. "Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system," International Journal of Production Economics, Elsevier, vol. 223(C).
    7. Weihua Liu & Shangsong Long & Yanjie Liang & Jinkun Wang & Shuang Wei, 2023. "The influence of leadership and smart level on the strategy choice of the smart logistics platform: a perspective of collaborative innovation participation," Annals of Operations Research, Springer, vol. 324(1), pages 893-935, May.
    8. Rui Ren & Wanjie Hu & Jianjun Dong & Bo Sun & Yicun Chen & Zhilong Chen, 2019. "A Systematic Literature Review of Green and Sustainable Logistics: Bibliometric Analysis, Research Trend and Knowledge Taxonomy," IJERPH, MDPI, vol. 17(1), pages 1-25, December.
    9. Yun Liu & Zhe Yan & Yijie Cheng & Xuanting Ye, 2018. "Exploring the Technological Collaboration Characteristics of the Global Integrated Circuit Manufacturing Industry," Sustainability, MDPI, vol. 10(1), pages 1-23, January.
    10. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    11. Ting Qu & Matthias Thürer & Junhao Wang & Zongzhong Wang & Huan Fu & Congdong Li & George Q. Huang, 2017. "System dynamics analysis for an Internet-of-Things-enabled production logistics system," International Journal of Production Research, Taylor & Francis Journals, vol. 55(9), pages 2622-2649, May.
    12. Kozjek, Dominik & Vrabič, Rok & Eržen, Gregor & Butala, Peter, 2018. "Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources," International Journal of Production Economics, Elsevier, vol. 200(C), pages 181-191.
    13. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    14. Orji, Ifeyinwa Juliet & Kusi-Sarpong, Simonov & Huang, Shuangfa & Vazquez-Brust, Diego, 2020. "Evaluating the factors that influence blockchain adoption in the freight logistics industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    15. Fahim, Patrick B.M. & Rezaei, Jafar & Montreuil, Benoit & Tavasszy, Lorant, 2022. "Port performance evaluation and selection in the Physical Internet," Transport Policy, Elsevier, vol. 124(C), pages 83-94.
    16. Julian Marius Müller & Daniel Kiel & Kai-Ingo Voigt, 2018. "What Drives the Implementation of Industry 4.0? The Role of Opportunities and Challenges in the Context of Sustainability," Sustainability, MDPI, vol. 10(1), pages 1-24, January.
    17. Teoman, Seyhan, 2020. "Achieving The Customized “Rights” Of Logistics By Adopting Novel Technologies: A Conceptual Approach And Literature Review," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 11(2), pages 231-242.
    18. Morett, Emilio & Tappia, Elena & Melacini, Marco, 2021. "Scheduling mobile robots in part feeding systems," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 129-149, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    19. Raut, Rakesh D. & Mangla, Sachin Kumar & Narwane, Vaibhav S. & Dora, Manoj & Liu, Mengqi, 2021. "Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    20. Sanjeev Yadav & Sunil Luthra & Dixit Garg, 2022. "Internet of things (IoT) based coordination system in Agri-food supply chain: development of an efficient framework using DEMATEL-ISM," Operations Management Research, Springer, vol. 15(1), pages 1-27, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:54:y:2016:i:22:p:6693-6706. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.