IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v12y2019i3d10.1007_s12063-019-00147-7.html
   My bibliography  Save this article

The dynamics of diffusion of an electronic platform supporting City Logistics services

Author

Listed:
  • Giulio Mangano

    (Politecnico di Torino)

  • Giovanni Zenezini

    (Politecnico di Torino)

  • Anna Corinna Cagliano

    (Politecnico di Torino)

  • Alberto De Marco

    (Politecnico di Torino)

Abstract

The concept of City Logistics (CL) has emerged to reduce social, economic, and environmental impacts of last-mile freight distribution in urban areas. The case of an innovative ICT platform for CL management is presented here, together with a System Dynamics model developed to explore the dynamics of diffusion of such initiative by three populations of users, namely, municipalities, own-account carriers, and logistics service providers. The model structure and parameters are shaped on diffusion models available in literature as well as participatory focus group sessions with the stakeholders. In particular, during the focus group sessions, the stakeholders used the Business Model Canvas building blocks to identify the value propositions delivered by the platform. Results show that routing efficiency, incentives to private operators for sustainable behaviours, and advertising campaigns to stimulate the cross-side effect among the stakeholders can stimulate the diffusion of this service. These results highlight a strong demand expressed by the CL stakeholders for ICT services supporting more efficient urban logistics operations, although it also confirms the need for public support for their diffusion.

Suggested Citation

  • Giulio Mangano & Giovanni Zenezini & Anna Corinna Cagliano & Alberto De Marco, 2019. "The dynamics of diffusion of an electronic platform supporting City Logistics services," Operations Management Research, Springer, vol. 12(3), pages 182-198, December.
  • Handle: RePEc:spr:opmare:v:12:y:2019:i:3:d:10.1007_s12063-019-00147-7
    DOI: 10.1007/s12063-019-00147-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-019-00147-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12063-019-00147-7?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. Stephen Ryan & Catherine Tucker, 2012. "Heterogeneity and the dynamics of technology adoption," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 63-109, March.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Niklas Arvidsson & Michael Browne, 2013. "A review of the success and failure of tram systems to carry urban freight: the implications for a low emission intermodal solution using electric vehicles on trams," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 54, pages 1-5.
    4. Edoardo Marcucci & Romeo Danielis, 2008. "The potential demand for a urban freight consolidation centre," Transportation, Springer, vol. 35(2), pages 269-284, March.
    5. Shepherd, Simon & Bonsall, Peter & Harrison, Gillian, 2012. "Factors affecting future demand for electric vehicles: A model based study," Transport Policy, Elsevier, vol. 20(C), pages 62-74.
    6. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    7. repec:hal:wpaper:halshs-00784075 is not listed on IDEAS
    8. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The impact of depot location, fleet composition and routing on emissions in city logistics," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 81-102.
    9. Nelson P. Repenning, 2002. "A Simulation-Based Approach to Understanding the Dynamics of Innovation Implementation," Organization Science, INFORMS, vol. 13(2), pages 109-127, April.
    10. Christoph H. Loch & Bernardo A. Huberman, 1999. "A Punctuated-Equilibrium Model of Technology Diffusion," Management Science, INFORMS, vol. 45(2), pages 160-177, February.
    11. Gutiérrez, R. & Nafidi, A. & Gutiérrez Sánchez, R., 2005. "Forecasting total natural-gas consumption in Spain by using the stochastic Gompertz innovation diffusion model," Applied Energy, Elsevier, vol. 80(2), pages 115-124, February.
    12. Milena Janjevic & Philip Kaminsky & Alassane Ballé Ndiaye, 2013. "Downscaling the consolidation of goods – state of the art and transferability of micro-consolidation initiatives," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 54, pages 1-4.
    Full references (including those not matched with items on IDEAS)

    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. Rui Leite & Aurora Teixeira, 2012. "Innovation diffusion with heterogeneous networked agents: a computational model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 7(2), pages 125-144, October.
    2. Karsten Kieckhäfer & Thomas Volling & Thomas Stefan Spengler, 2014. "A Hybrid Simulation Approach for Estimating the Market Share Evolution of Electric Vehicles," Transportation Science, INFORMS, vol. 48(4), pages 651-670, November.
    3. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    4. Edouard Civel & Marc Baudry, 2018. "The Fate of Inventions. What can we learn from Bayesian learning in strategic options model of adoption ?," EconomiX Working Papers 2018-47, University of Paris Nanterre, EconomiX.
    5. Langley, David J. & Hoeve, Maarten C. & Ortt, J. Roland & Pals, Nico & van der Vecht, Bob, 2014. "Patterns of Herding and their Occurrence in an Online Setting," Journal of Interactive Marketing, Elsevier, vol. 28(1), pages 16-25.
    6. Park, Hyeongjun & Park, Dongjoo & Jeong, In-Jae, 2016. "An effects analysis of logistics collaboration in last-mile networks for CEP delivery services," Transport Policy, Elsevier, vol. 50(C), pages 115-125.
    7. Yujuico, Emmanuel, 2015. "Considerations in the diffusion of a public traffic app for Metro Manila," Journal of Transport Geography, Elsevier, vol. 42(C), pages 48-56.
    8. Cowan, Kelly R. & Daim, Tugrul U., 2011. "Review of technology acquisition and adoption research in the energy sector," Technology in Society, Elsevier, vol. 33(3), pages 183-199.
    9. Delre, Sebastiano A. & Panico, Claudio & Wierenga, Berend, 2017. "Competitive strategies in the motion picture industry: An ABM to study investment decisions," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 69-99.
    10. Stefan N. Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    11. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    12. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    13. Jihane El Ouadi & Hanae Errousso & Nicolas Malhene & Siham Benhadou & Hicham Medromi, 2022. "A machine-learning based hybrid algorithm for strategic location of urban bundling hubs to support shared public transport," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3215-3258, October.
    14. Kocaman, Barış & Gelper, Sarah & Langerak, Fred, 2023. "Till the cloud do us part: Technological disruption and brand retention in the enterprise software industry," International Journal of Research in Marketing, Elsevier, vol. 40(2), pages 316-341.
    15. Dutta, Amitava & Puvvala, Abhinay & Roy, Rahul & Seetharaman, Priya, 2017. "Technology diffusion: Shift happens — The case of iOS and Android handsets," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 28-43.
    16. Fibich, Gadi & Levin, Tomer, 2020. "Percolation of new products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    17. Guseo, Renato & Schuster, Reinhard, 2021. "Modelling dynamic market potential: Identifying hidden automata networks in the diffusion of pharmaceutical drugs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    18. Anders F. Jensen & Elisabetta Cherchi & Stefan L. Mabit & Juan de Dios Ortúzar, 2017. "Predicting the Potential Market for Electric Vehicles," Transportation Science, INFORMS, vol. 51(2), pages 427-440, May.
    19. Abedi, Vahideh Sadat, 2019. "Compartmental diffusion modeling: Describing customer heterogeneity & communication network to support decisions for new product introductions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    20. Teck-Hua Ho & Shan Li & So-Eun Park & Zuo-Jun Max Shen, 2012. "Customer Influence Value and Purchase Acceleration in New Product Diffusion," Marketing Science, INFORMS, vol. 31(2), pages 236-256, March.

    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:spr:opmare:v:12:y:2019:i:3:d:10.1007_s12063-019-00147-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.