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Open AccessOpen Access JUSTC Management Science and Engineering 14 July 2022

Delivery mode selection of home furnishing e-retailer based on a combination of logistics delivery and installation service

  • International Institute of Finance, School of Management, University of Science and Technology of China, Hefei 230026, China

Cite this:
https://doi.org/10.52396/JUSTC-2021-0282
More Information
  • Author Bio:

    Yaliang Chen is a master’s student in the School of Management at the University of Science and Technology of China. Her research interests include logistic service and supply chain management

    Manman Wang received her Ph.D. degree from the University of Science and Technology of China (USTC) in 2021. She is currently a postdoctoral researcher of operations management at the School of Management, USTC. Her research interests include sustainable operations and the reverse supply chain management

  • Corresponding author: E-mail: wmm2016@mail.ustc.edu.cn
  • Received Date: 31 December 2021
  • Accepted Date: 05 May 2022
    • Available Online: 14 July 2022
    Abstract

  • Abstract

    With the increasing demand for online home-furnishing products, product delivery services, especially installation services, have become increasingly regarded as bottlenecks and key factors for success. Meanwhile, customers have different preferences for a combination of delivery modes because of separated or synchronized logistics delivery from installation services. It is essential for online home-furnishing e-retailers to self-build or outsource installation services. This study investigates the optimal delivery mode selection of home-furnishing e-retailers in a home-furnishing supply chain consisting of a home-furnishing e-retailer, a third-party installation service provider (ISP), and a third-party logistics service provider (LSP). Specifically, we explore three alternative modes: (ⅰ) The home-furnishing e-retailer undertakes the installation service (Mode E); (ⅱ) the ISP undertakes the installation service (Mode I); (ⅲ) the LSP undertakes the installation service (Mode L). The results reveal that the self-build mode does not always generate the highest installation service level, and the integrated delivery mode may generate the highest installation service level when the cost performance of the installation service is relatively low. Moreover, optimal delivery mode selection depends on the installation service’s cost performance. When the installation service’s cost performance is relatively low, the e-retailer and the LSP reach a “win-win” situation from the integrated delivery mode. When the installation service’s cost performance is relatively high and the self-build fixed cost is low, the e-retailer and the LSP reach a win-win situation from the self-build mode. Interestingly, compared with the outsourced integrated service mode, the self-build integrated service mode is not a better choice for the e-retailer if the self-build fixed cost is too high. Our study contributes to the growing literature on home furnishing and guides the implementation of delivery strategies for large-product online retailers.

    Graphical abstract

    The overall framework of our delivery selection model.

    Abstract

    With the increasing demand for online home-furnishing products, product delivery services, especially installation services, have become increasingly regarded as bottlenecks and key factors for success. Meanwhile, customers have different preferences for a combination of delivery modes because of separated or synchronized logistics delivery from installation services. It is essential for online home-furnishing e-retailers to self-build or outsource installation services. This study investigates the optimal delivery mode selection of home-furnishing e-retailers in a home-furnishing supply chain consisting of a home-furnishing e-retailer, a third-party installation service provider (ISP), and a third-party logistics service provider (LSP). Specifically, we explore three alternative modes: (ⅰ) The home-furnishing e-retailer undertakes the installation service (Mode E); (ⅱ) the ISP undertakes the installation service (Mode I); (ⅲ) the LSP undertakes the installation service (Mode L). The results reveal that the self-build mode does not always generate the highest installation service level, and the integrated delivery mode may generate the highest installation service level when the cost performance of the installation service is relatively low. Moreover, optimal delivery mode selection depends on the installation service’s cost performance. When the installation service’s cost performance is relatively low, the e-retailer and the LSP reach a “win-win” situation from the integrated delivery mode. When the installation service’s cost performance is relatively high and the self-build fixed cost is low, the e-retailer and the LSP reach a win-win situation from the self-build mode. Interestingly, compared with the outsourced integrated service mode, the self-build integrated service mode is not a better choice for the e-retailer if the self-build fixed cost is too high. Our study contributes to the growing literature on home furnishing and guides the implementation of delivery strategies for large-product online retailers.

    • Public Summary

    • For the e-retailer, when the installation service’s cost performance (τ) is relatively high, the e-retailer will choose Mode E if and only if the self-built fixed cost (F) is relatively low, otherwise, the e-retailer will choose Mode L.
    • The e-retailer and the LSP reach a win-win situation from the Mode L when the installation service’s cost performance (τ) is relatively low. The e-retailer and the LSP reach a “win-win” situation from the Mode E when the installation service’s cost performance (τ) is relatively high and the self-built fixed cost (F) is low.
    • Compared with the Mode L, the Mode S cannot be a better choice for the e-retailer if the self-built fixed (F) cost is too high.

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    • References(50)
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    Punakivi M, Hinkka V. Selection criteria of transportation mode: A case study in four Finnish industry sectors. Transport Reviews, 2006, 26 (2): 207–219. doi: 10.1080/01441640500191638
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    Arya A, Mittendorf B, Sappington D E M. The make-or-buy decision in the presence of a rival: Strategic outsourcing to a common supplier. Management Science, 2008, 54 (10): 1747–1758. doi: 10.1287/mnsc.1080.0896
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    [48]
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    Figure  1.  The sequence of events.

    Figure  2.  Installation service levels in different modes.

    Figure  3.  Retail prices in different modes.

    Figure  4.  The home-furnishing e-retailer’s preference: interactions between $ \tau $ and $ F $.

    Figure  5.  LSP’s profits in different modes.

    [1]
    Li X, Li Y, Cai X, et al. Service channel choice for supply chain: Who is better off by undertaking the service? Production and Operations Management, 2016, 25 (3): 516–534. doi: 10.1111/poms.12392
    [2]
    Vakulenko Y, Shams P, Hellström D, et al. Online retail experience and customer satisfaction: The mediating role of last mile delivery. The International Review of Retail, Distribution and Consumer Research, 2019, 29 (3): 306–320. doi: 10.1080/09593969.2019.1598466
    [3]
    Ali O, Côté J F, Coelho L C. Models and algorithms for the delivery and installation routing problem. European Journal of Operational Research, 2021, 291 (1): 162–177. doi: 10.1016/j.ejor.2020.09.011
    [4]
    Audy J F, D’Amours S. Impact of benefit sharing among companies in the implantation of a collaborative transportation system—an application in the furniture industry. In: Camarinha-Matos L M, Picard W editors. Pervasive Collaborative Networks. Boston, MA: Springer US, 2008: 519–532.
    [5]
    Audy J F, D’Amours S, Rousseau L M. Cost allocation in the establishment of a collaborative transportation agreement—An application in the furniture industry. Journal of the Operational Research Society, 2011, 62 (6): 960–970. doi: 10.1057/jors.2010.53
    [6]
    Yu Y, Wang X, Zhong R Y, et al. E-commerce logistics in supply chain management: Implementations and future perspective in furniture industry. Industrial Management & Data Systems, 2017, 117: 2263–2286. doi: 10.1108/imds-09-2016-0398
    [7]
    Marino G, Zotteri G, Montagna F. Consumer sensitivity to delivery lead time: A furniture retail case. International Journal of Physical Distribution & Logistics Management, 2018, 48 (6): 610–629. doi: 10.1108/ijpdlm-01-2017-0030
    [8]
    Goyal M, Cook J, Kim N, et al. Hyperconnected city logistics for furniture and large appliance industry: Simulation-based exploratory investigation. In: 3rd International Physical Internet Conference. Atlanta, USA: IPIC, 2016.
    [9]
    Luo H, Tian S, Kong X T R. Physical Internet-enabled customised furniture delivery in the metropolitan areas: Digitalisation, optimisation and case study. International Journal of Production Research, 2021, 59 (7): 2193–2217. doi: 10.1080/00207543.2020.1832271
    [10]
    Coelho L C, Gagliardi J P, Renaud J, et al. Solving the vehicle routing problem with lunch break arising in the furniture delivery industry. Journal of the Operational Research Society, 2016, 67 (5): 743–751. doi: 10.1057/jors.2015.90
    [11]
    Li W, Li K, Kumar P N R, et al. Simultaneous product and service delivery vehicle routing problem with time windows and order release dates. Applied Mathematical Modelling, 2021, 89: 669–687. doi: 10.1016/j.apm.2020.07.045
    [12]
    Bae H, Moon I. Multi-depot vehicle routing problem with time windows considering delivery and installation vehicles. Applied Mathematical Modelling, 2016, 40: 6536–6549. doi: 10.1016/j.apm.2016.01.059
    [13]
    Chang S, Dong Y, Wang X. Optimal shipping policy in retail competition and its effect on customers. Electronic Commerce Research and Applications, 2021, 45: 101020. doi: 10.1016/j.elerap.2020.101020
    [14]
    Wang H, Lee C Y. Production and transport logistics scheduling with two transport mode choices. Naval Research Logistics, 2005, 52: 796–809. doi: 10.1002/nav.20116
    [15]
    Choi T M. Internet based elastic logistics platforms for fashion quick response systems in the digital era. Transportation Research Part E: Logistics and Transportation Review, 2020, 143: 102096. doi: 10.1016/j.tre.2020.102096
    [16]
    Stecke K E, Zhao X. Production and transportation integration for a make-to-order manufacturing company with a commit-to-delivery business mode. Manufacturing & Service Operations Management, 2007, 9 (2): 206–224. doi: 10.1287/msom.1060.0138
    [17]
    Li F, Xu Z, Chen Z L. Production and transportation integration for commit-to-delivery mode with general shipping costs. INFORMS Journal on Computing, 2020, 32 (4): 1012–1029. doi: 10.1287/ijoc.2019.0935
    [18]
    Punakivi M, Yrjölä H, Holmström J. Solving the last mile issue: Reception box or delivery box? International Journal of Physical Distribution & Logistics Management, 2001, 31 (6): 427–439. doi: 10.1108/09600030110399423
    [19]
    Wang X, Zhan L, Ruan J, et al. How to choose “last mile” delivery modes for e-fulfillment. Mathematical Problems in Engineering, 2014, 2014: 417129. doi: 10.1155/2014/417129
    [20]
    Tiwapat N, Pomsing C, Jomthong P. Last mile delivery: Modes, efficiencies, sustainability, and trends. In: 2018 3rd IEEE International Conference on Intelligent Transportation Engineering (ICITE). Singapore: IEEE, 2018: 313–317.
    [21]
    Devari A, Nikolaev A G, He Q. Crowdsourcing the last mile delivery of online orders by exploiting the social networks of retail store customers. Transportation Research Part E: Logistics and Transportation Review, 2017, 105: 105–122. doi: 10.1016/j.tre.2017.06.011
    [22]
    Lou Y, Feng L, He S, et al. Logistics service outsourcing choices in a retailer-led supply chain. Transportation Research Part E:Logistics and Transportation Review, 2020, 141: 101944. doi: 10.1016/j.tre.2020.101944
    [23]
    Wang X, Xie J, Fan Z P. B2C cross-border E-commerce logistics mode selection considering product returns. International Journal of Production Research, 2021, 59 (13): 3841–3860. doi: 10.1080/00207543.2020.1752949
    [24]
    Büyüközkan G, Feyzioğlu O, Nebol E. Selection of the strategic alliance partner in logistics value chain. International Journal of Production Economics, 2008, 113 (1): 148–158. doi: 10.1016/j.ijpe.2007.01.016
    [25]
    Özcan E, Ahiskali M. 3PL service provider selection with a goal programming model supported with multicriteria decision making approaches. Gazi University Journal of Science, 2020, 33: 413–427. doi: 10.35378/gujs.552070
    [26]
    Göl H, Çatay B. Third–party logistics provider selection: Insights from a Turkish automotive company. Supply Chain Management: An International Journal, 2007, 12 (6): 379–384. doi: 10.1108/13598540710826290
    [27]
    Punakivi M, Hinkka V. Selection criteria of transportation mode: A case study in four Finnish industry sectors. Transport Reviews, 2006, 26 (2): 207–219. doi: 10.1080/01441640500191638
    [28]
    Arya A, Mittendorf B, Sappington D E M. The make-or-buy decision in the presence of a rival: Strategic outsourcing to a common supplier. Management Science, 2008, 54 (10): 1747–1758. doi: 10.1287/mnsc.1080.0896
    [29]
    Bolandifar E, Kouvelis P, Zhang F. Delegation vs. control in supply chain procurement under competition. Production & Operations Management, 2016, 25 (9): 1528–1541. doi: 10.1111/poms.12566
    [30]
    Kayış E, Erhun F, Plambeck E L. Delegation vs. control of component procurement under asymmetric cost information and simple contracts. Manufacturing & Service Operations Management, 2013, 15 (1): 45–56. doi: 10.1287/msom.1120.0395
    [31]
    Wang Y, Niu B, Guo P. The comparison of two vertical outsourcing structures under push and pull contracts. Production and Operations Management, 2014, 23 (4): 610–625. doi: 10.1111/poms.12025
    [32]
    Yu Y, Xiao T. Pricing and cold-chain service level decisions in a fresh agri-products supply chain with logistics outsourcing. Computers & Industrial Engineering, 2017, 111: 56–66. doi: 10.1016/j.cie.2017.07.001
    [33]
    Zhang Y, He Z, He S, et al. Manufacturer warranty service outsourcing strategies in a dual–channel supply chain. International Transactions in Operational Research, 2020, 27 (6): 2899–2926. doi: 10.1111/itor.12769
    [34]
    Wang M, Yang F, Xia Q. Design of the reverse channel for the third-party remanufacturing considering consumer education. RAIRO - Operations Research, 2021, 55 (6): 3513–3540. doi: 10.1051/ro/2021153
    [35]
    Liu W, Liu Y, Zhu D, et al. The influences of demand disruption on logistics service supply chain coordination: A comparison of three coordination modes. International Journal of Production Economics, 2016, 179: 59–76. doi: 10.1016/j.ijpe.2016.05.022
    [36]
    Song Z, He S. Contract coordination of new fresh produce three-layer supply chain. Industrial Management & Data Systems, 2019, 119 (1): 148–169. doi: 10.1108/imds-12-2017-0559
    [37]
    Hu Y, Qu S, Li G, et al. Power structure and channel integration strategy for online retailers. European Journal of Operational Research, 2021, 294 (3): 951–964. doi: 10.1016/j.ejor.2019.10.050
    [38]
    Zheng S, Yu Y, Ma B. The bright side of third-party marketplaces in retailing. International Transactions in Operational Research, 2022, 29 (1): 442–470. doi: epdf/10.1111/itor.12992
    [39]
    Liao T H, Keng C J. Online shopping delivery delay: Finding a psychological recovery strategy by online consumer experiences. Computers in Human Behavior, 2013, 29 (4): 1849–1861. doi: 10.1016/j.chb.2013.03.004
    [40]
    Patrício L, Fisk R P, Falcão e Cunha J, et al. Multilevel service design: From customer value constellation to service experience blueprinting. Journal of Service Research, 2011, 14 (2): 180–200. doi: 10.1177/1094670511401901
    [41]
    Qin X, Liu Z, Tian L. The optimal combination between selling mode and logistics service strategy in an e-commerce market. European Journal of Operational Research, 2021, 289 (2): 639–651. doi: 10.1016/j.ejor.2020.07.029
    [42]
    Tsay A A, Agrawal N. Channel dynamics under price and service competition. Manufacturing & Service Operations Management, 2000, 2 (4): 372–391. doi: 10.1287/msom.2.4.372.12342
    [43]
    Chen X, Luo Z, Wang X. Compete or cooperate: Intensity, dynamics, and optimal strategies. Omega, 2019, 86: 76–86. doi: 10.1016/j.omega.2018.07.002
    [44]
    Jain A, Bala R. Differentiated or integrated: Capacity and service level choice for differentiated products. European Journal of Operational Research, 2018, 266 (3): 1025–1037. doi: 10.1016/j.ejor.2017.10.053
    [45]
    Yu Y, Xiao T. Analysis of cold-chain service outsourcing modes in a fresh agri-product supply chain. Transportation Research Part E:Logistics and Transportation Review, 2021, 148: 102264. doi: 10.1016/j.tre.2021.102264
    [46]
    Xia Y, Xiao T, Zhang G P. Service investment and channel structure decisions in competing supply chains. Service Science, 2019, 11 (1): 57–74. doi: 10.1287/serv.2018.0235
    [47]
    Liu W H, Xie D, Xu X C. Quality supervision and coordination of logistic service supply chain under multi-period conditions. International Journal of Production Economics, 2013, 142 (2): 353–361. doi: 10.1016/j.ijpe.2012.12.011
    [48]
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