IDEAS home Printed from https://ideas.repec.org/a/inm/ormsom/v24y2022i5p2425-2443.html

Last Mile Innovation: The Case of the Locker Alliance Network

Author

Listed:
  • Guodong Lyu

    (Institute of Operations Research and Analytics, National University of Singapore, Singapore 117602; Department of Analytics and Operations, NUS Business School, National University of Singapore, Singapore 119245)

  • Chung-Piaw Teo

    (Institute of Operations Research and Analytics, National University of Singapore, Singapore 117602; Department of Analytics and Operations, NUS Business School, National University of Singapore, Singapore 119245)

Abstract

Problem definition : The Singapore government has recently proposed the concept of “Locker Alliance” (LA), an interoperable network of public lockers in residential areas and hot spots in community, to improve the efficiency of last mile parcel delivery operations. This is to complement the existing infrastructure, composed mainly of proprietary lockers and collection points in commercial areas set up by large delivery companies. How do we determine the density and coverage of the LA network to promote adoption of locker pickup in Singapore? What will be the impact on the delivery profile in the central business district, far from the residential areas? Academic/practical relevance : We discuss the operational challenges associated with the problem of public locker installation in a city, following a new smart nation initiative in Singapore. We used data analytics to address the following questions: What are the chances that a customer will choose to pick up the parcel from a locker, over home or office deliveries, based on walking distance (to lockers) and a variety of other features? Without knowing the transit routes of the customers, how do we design the LA network to ensure that the lockers will be well utilized? Methodology : We use a set of locker usage data from a commercial courier company to calibrate a locker choice model to determine the impact of walking distance on locker pickup intentions. We use the current (observed) parcel delivery profile to develop a facility location model for the LA network. We use this model to extrapolate and approximate the true adoption and new delivery profiles when the LA network is built. Results : Contrary to conventional wisdom, our model does not always place lockers near areas with peak parcel volume (in preexisting data) because the LA lockers provide another option for customers to pick up from lockers near residential areas. Furthermore, the model suggests that a coverage of 250 meters is appropriate for the LA network in Singapore. Managerial implications : Commercial parcel locker installation has traditionally focused on hot spots in the transit routes of the citizens in the city. The LA network is the first attempt in Singapore to allow public lockers in residential areas. This paper develops an analytical method to determine network density and coverage based on a locker choice model and argues how useful insights can be gleaned from the model, despite not having the full transit route information of all citizens in the city.

Suggested Citation

  • Guodong Lyu & Chung-Piaw Teo, 2022. "Last Mile Innovation: The Case of the Locker Alliance Network," Manufacturing & Service Operations Management, INFORMS, vol. 24(5), pages 2425-2443, September.
    • Handle: RePEc:inm:ormsom:v:24:y:2022:i:5:p:2425-2443
    DOI: 10.1287/msom.2021.1000
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/msom.2021.1000
    Download Restriction: no
    File URL: https://libkey.io/10.1287/msom.2021.1000?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
    ---><---

    References listed on IDEAS

    as
    1. Aros-Vera, Felipe & Marianov, Vladimir & Mitchell, John E., 2013. "p-Hub approach for the optimal park-and-ride facility location problem," European Journal of Operational Research, Elsevier, vol. 226(2), pages 277-285.
    2. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    3. Chloe Kim Glaeser & Marshall Fisher & Xuanming Su, 2019. "Optimal Retail Location: Empirical Methodology and Application to Practice," Service Science, INFORMS, vol. 21(1), pages 86-102, January.
    4. Vineet Goyal & Retsef Levi & Danny Segev, 2016. "Near-Optimal Algorithms for the Assortment Planning Problem Under Dynamic Substitution and Stochastic Demand," Operations Research, INFORMS, vol. 64(1), pages 219-235, February.
    5. Martin Savelsbergh & Tom Van Woensel, 2016. "50th Anniversary Invited Article—City Logistics: Challenges and Opportunities," Transportation Science, INFORMS, vol. 50(2), pages 579-590, May.
    6. Luigi Ranieri & Salvatore Digiesi & Bartolomeo Silvestri & Michele Roccotelli, 2018. "A Review of Last Mile Logistics Innovations in an Externalities Cost Reduction Vision," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    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. Srishti Arora & Vivek Choudhary & Pavel Kireyev, 2025. "Don’t Fake It If You Can’t Make It: Driver Misconduct in Last-Mile Delivery," Management Science, INFORMS, vol. 71(5), pages 3790-3808, May.
    2. Liu, Xiaodi & Pang, Qiwei & Yuen, Kum Fai & Wang, Xueqin, 2025. "Transforming last-mile delivery into marketplaces of logistics services: An investigation on consumer participation motives, resources, and contextual differences," Journal of Business Research, Elsevier, vol. 200(C).
    3. Ma, Bohao & Teo, Chee-Chong & Wong, Yiik Diew, 2024. "Location analysis of parcel locker Network: Effects of spatial characteristics on operational performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    4. Fabian Akkerman & Peter Dieter & Martijn Mes, 2025. "Learning Dynamic Selection and Pricing of Out-of-Home Deliveries," Transportation Science, INFORMS, vol. 59(2), pages 250-278, March.
    5. Zhang, Yali & Ding, Zhenbin & Sun, Jun & Chen, Delin & Goh, Mark & Yang, Zhaojun, 2026. "Evolving last-mile logistics: Where unmanned delivery fits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 206(C).
    6. Bruno, Giuseppe & Diglio, Antonio & Piccolo, Carmela & Pipicelli, Eduardo, 2025. "Solutions for sustainable last-mile delivery: Pick-up points location with customers’ choice," Research in Transportation Economics, Elsevier, vol. 113(C).
    7. Sina Mohri, Seyed & Ghaderi, Hadi & Van Woensel, Tom & Mohammadi, Mehrdad & Nassir, Neema & Thompson, Russell G., 2024. "Contextualizing alternative delivery points in last mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    8. Orhan, Cosku Can & Wallace, Stein W., 2025. "E-commerce shipments in an X-minute city: Informing authorities on freight transport through parcel lockers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 199(C).
    9. Trilce Encarnación & Johanna Amaya, 2025. "Determinants of parcel locker adoption for last‐mile deliveries in urban and suburban areas," Transportation Journal, John Wiley & Sons, vol. 64(1), January.

    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. Georg Bechler & Claudius Steinhardt & Jochen Mackert, 2021. "On the Linear Integration of Attraction Choice Models in Business Optimization Problems," SN Operations Research Forum, Springer, vol. 2(1), pages 1-13, March.
    2. Daniela Paddeu & Paulus Aditjandra, 2020. "Shaping Urban Freight Systems via a Participatory Approach to Inform Policy-Making," Sustainability, MDPI, vol. 12(1), pages 1-15, January.
    3. Laurent Alfandari & Alborz Hassanzadeh & Ivana Ljubić, 2021. "An Exact Method for Assortment Optimization under the Nested Logit Model," Working Papers hal-02463159, HAL.
    4. Kokkinou, Alinda & Quak, Hans & Mitas, Ondrej & Mandemakers, Albert, 2024. "Should I wait or should I go? Encouraging customers to make the more sustainable delivery choice," Research in Transportation Economics, Elsevier, vol. 103(C).
    5. Woonghee Tim Huh & Joseph Paat & Maurice Queyranne, 2026. "Performance of the Offer-Everything Policy," Operations Research, INFORMS, vol. 74(1), pages 141-160, January.
    6. Zhaohui (Zoey) Jiang & Jun Li, 2025. "Instrumenting While Experimenting: An Empirical Method for Competitive Pricing at Scale," Operations Research, INFORMS, vol. 73(5), pages 2477-2495, September.
    7. Patrick Klein & Bastian Popp, 2022. "Last-Mile Delivery Methods in E-Commerce: Does Perceived Sustainability Matter for Consumer Acceptance and Usage?," Sustainability, MDPI, vol. 14(24), pages 1-27, December.
    8. Yi-Chun Akchen & Felipe Caro, 2026. "On Size Substitution and Its Role in Assortment and Inventory Planning," Manufacturing & Service Operations Management, INFORMS, vol. 28(2), pages 624-642, March.
    9. Jingwei Zhang & Will Ma & Huseyin Topaloglu, 2025. "Technical Note—Leveraging the Degree of Dynamic Substitution in Assortment and Inventory Planning," Operations Research, INFORMS, vol. 73(3), pages 1248-1259, May.
    10. Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "Dynamic Assortment Optimization for Reusable Products with Random Usage Durations," Management Science, INFORMS, vol. 66(7), pages 2820-2844, July.
    11. Asma Troudi & Sid-Ali Addouche & Sofiene Dellagi & Abderrahman El Mhamedi, 2018. "Sizing of the Drone Delivery Fleet Considering Energy Autonomy," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    12. Xingxing Chen & Jacob Feldman & Seung Hwan Jung & Panos Kouvelis, 2022. "Approximation schemes for the joint inventory selection and online resource allocation problem," Production and Operations Management, Production and Operations Management Society, vol. 31(8), pages 3143-3159, August.
    13. Ali Aouad & Danny Segev, 2023. "The Stability of MNL-Based Demand Under Dynamic Customer Substitution and Its Algorithmic Implications," Operations Research, INFORMS, vol. 71(4), pages 1216-1249, July.
    14. Alfandari, Laurent & Hassanzadeh, Alborz & Ljubic, Ivana, 2020. "An Exact Method for Assortment Optimization under the Nested Logit Model," ESSEC Working Papers WP2001, ESSEC Research Center, ESSEC Business School, revised 2020.
    15. Fernanda Alves de Araújo & João Gilberto Mendes dos Reis & Marcia Terra da Silva & Emel Aktas, 2022. "A Fuzzy Analytic Hierarchy Process Model to Evaluate Logistics Service Expectations and Delivery Methods in Last-Mile Delivery in Brazil," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    16. Amr Farahat & Joonkyum Lee, 2018. "The Multiproduct Newsvendor Problem with Customer Choice," Operations Research, INFORMS, vol. 66(1), pages 123-136, January.
    17. Arash Asadpour & Rad Niazadeh & Amin Saberi & Ali Shameli, 2023. "Sequential Submodular Maximization and Applications to Ranking an Assortment of Products," Operations Research, INFORMS, vol. 71(4), pages 1154-1170, July.
    18. Julia Heger & Robert Klein, 2024. "Assortment optimization: a systematic literature review," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1099-1161, December.
    19. Evelyne Tina Kassai & Muhammad Azmat & Sebastian Kummer, 2020. "Scope of Using Autonomous Trucks and Lorries for Parcel Deliveries in Urban Settings," Logistics, MDPI, vol. 4(3), pages 1-25, August.
    20. Neves-Moreira, Fábio & Amorim, Pedro, 2024. "Learning efficient in-store picking strategies to reduce customer encounters in omnichannel retail," International Journal of Production Economics, Elsevier, vol. 267(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:inm:ormsom:v:24:y:2022:i:5:p:2425-2443. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.