Skip to main content
SpringerLink
Log in

Levers of logistics service providers’ efficiency in urban distribution

  • Published:
Operations Management Research Aims and scope Submit manuscript

Abstract

This paper identifies the most important factors that influence the productivity of the urban fleet of a Logistics Service Provider (LSP). Through a regression analysis on a dataset from distribution warehouses of a single LSP, three main levers are shown to have significant impacts on productivity, namely the network design, the vehicle loading strategy, and the business environment wherein the operations are carried out. This paper contributes to bridge the gap about the lack of works addressing the efficiency of LSPs operating in urban areas, by performing a detailed empirical analysis instead of taking an aggregated company perspective.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Anand N, Quak HJ, Van Duin JHR, Tavasszy LA (2012) City Logistics modeling effort: Trends and gaps- A review. Proc-Soc Behav Sci 39:101–115

    Article  Google Scholar 

  • Ballantyne EEF, Lindhom M (2013) Using due diligence to improve the urban freight planning process. Proceedings of 18th Annual Logistics Research Network Conference. Aston & Birmingham City Universities, UK

  • Bard JF, Nananukul N (2009) The integrated production–inventory–distribution–routing problem. J Sched 12(3):257–280

    Article  Google Scholar 

  • Benjelloun A, Cranic TG (2009) Trends, challenges and perspectives in City Logistics. Proceedings of Transport and land use interaction, Tralsu, Bucarest, Romania, 269–284

  • Boccia M, Crainic TG, Sforza A, Sterle C (2010) A metaheuristic for a two echelon location-routing problem. Lecture Notes in Computer Sciences 6049:288–300. Springer Berlin Heidelberg

  • Browne M, Gomez M (2011) The impact on urban distribution operations of upstream supply chain constraints. Int J of Phys Distrib Logist Manag 41:896–912

    Article  Google Scholar 

  • Cachon GP (2014) Retail store density and the cost of greenhouse gas emissions. Manag Sci 60(8):1907–1925

    Article  Google Scholar 

  • Chandraprakaikul W, Suebpongsakorn A (2012) Evaluation of logistics companies using data envelopment analysis. Proceedings of Conference of Logistics and Industrial Informatics, Smolnenice, Slovakia, 5–7 September 2012, 81–86

  • Crainic TG, Ricciardi N, Storchi G (2004) Advanced freight transportation systems for congested urban areas. Transp Res Part C 12:119–137

    Article  Google Scholar 

  • De Marco A, Mangano G, Michelucci FV, Zenezini G (2016) Using the private finance initiative for energy efficiency projects at the urban scale. Int J Energy Sect Manag 10(1):99–117

    Article  Google Scholar 

  • Desaulniers G, Lavigne J, Soumis F (1998) Multi-depot vehicle scheduling problems with time windows and waiting costs. Eur J Oper Res 111(3):479–494

    Article  Google Scholar 

  • Domingues ML, Reis V, Macário R (2015) A comprehensive framework for measuring performance in a third party logistics provider. Transp Res Proc 10:662–672

    Article  Google Scholar 

  • Ducret R, Delaître L (2013) Parcel delivery and urban logistics-changes in urban courier, express and parcel services: the French case. In 13th World Conference on Transport Research, July 15–18, 2013-Rio de Janeiro, Brazil

  • Edwards J, McKinnon A, Cherrett T, McLeod F, Song L (2010) Carbon Dioxide Benefits of Using Collection - Delivery Points for Failed Home Deliveries in the United Kingdom. Transp Res Rec: J Transp Res Board 2191:136–143

    Article  Google Scholar 

  • Ehmke JF, Mattfeld DC (2012) Vehicle routing for attended home delivery in city logistics. Proc – Soc Behav Sci 39:622–632

    Article  Google Scholar 

  • Ehmke JF, Meisel S, Mattfeld DC (2012a) Floating car base travel times for city logistics. Transp Res Part C 21:338–352

    Article  Google Scholar 

  • Ehmke JF, Steinert A, Mattfeld DC (2012b) Advanced routing for city logistics service providers based on time-dependent travel times. J Comput Sci 3:193–205

    Article  Google Scholar 

  • Ehmke JF, Campbell AM, Thomas BW (2016) Vehicle routing to minimize time-dependent emissions in urban areas. Eur J Oper Res 251:478–494

    Article  Google Scholar 

  • Ellinger AE, Ketchen DJ, Hult GTM, Elmadağ AB, Richey RG (2008) Market orientation, employee development practices, and performance in logistics service provider firms. Ind Mark Manag 37(4):353–366

    Article  Google Scholar 

  • Eurostat (2015) E-commerce statistics for individuals. Available at: http://ec.europa.eu/eurostat/ Accessed 17 November 2016

  • Everitt BS (2002) Cambridge dictionary of statistics -2nd Edition

  • Fawcett SE, Cooper MB (1998) Logistics performance measurement and customer success. Ind Mark Manag 27:341–357

    Article  Google Scholar 

  • Federgruen A, Tzur M (1999) Time-partitioning heuristics: application to one warehouse, multiitem, multiretailer lot-sizing problems. Nav Res Logist 46(5):463–486

    Article  Google Scholar 

  • Figliozzi MA (2007) Analysis of the efficiency of urban commercial vehicle tours. Data collection, methodology, and policy implications. Transp Res Part B 41:1014–1032

    Article  Google Scholar 

  • Figliozzi MA (2010) The impacts of congestion on commercial vehicle tour characteristics and costs. Transp Res Part E 46:496–506

    Article  Google Scholar 

  • Freight Best Practice (2006) Key Performance Indicators for the Next-day Parcel Delivery Sector, Department for Transport programme, UK. http://www.freightbestpractice.org.uk Accessed 17 November 2016

  • Gallmann F, Belvedere V (2011) Linking service level, inventory management and warehousing practices: A case-based managerial analysis. Oper Manag Res 4:28–38

    Article  Google Scholar 

  • Gevaers R, Van de Voorde, Vanelslander T (2010) Characteristics and typology of last-mile logistics from an innovation perspective in an urban context. Proceedings of World Conference on Transportation Research Society, 2010, Lisbon, Portugal

  • Ghinea C, Dragoi EN, Comanita ED, Gavrilescu M, Campean T, Curtenanu S, Gavrilescu M (2016) Forecasting municipal solid waste generation using prognostic tools and regression analysis. J Environ Mng 182(1):80–93

    Article  Google Scholar 

  • Glock CH, Kim T (2015) Coordinating a supply chain with a heterogeneous vehicle fleet under greenhouse gas emissions. Int J Logist Manag 26(3):494–516

    Article  Google Scholar 

  • Graham DJ (2008) Productivity and efficiency in urban railways: Parametric and non-parametric estimates. Transp Res Part E 44:847–899

    Article  Google Scholar 

  • Gunasekaran A, Patel C, Tirtiroglu E (2001) Performance measures and metrics in a supply chain environment. Int J of Oper Prod Manag 21:71–87

    Article  Google Scholar 

  • Hamdan A, Rogers KJ (2008) Evaluating the efficiency of 3PL logistics operations. Int J of Prod Econ 113:235–244

    Article  Google Scholar 

  • Hamzaoui S, Ben-Ayed O (2011) Parcel distribution timetabling problem. Oper Manag Res 4:138–149

    Article  Google Scholar 

  • Harding FE (1998) Logistics service provider quality private measurement, evaluation, and improvement. J Bus Logist 19:103–120

    Google Scholar 

  • Hesse M (2002) Shipping news: The implications of electronic commerce for logistics and freight transport. Resour Conserv Recycl 36:211–240

    Article  Google Scholar 

  • Hoff A, Andersson H, Christiansen M, Hasle G, Lokketangen A (2010) Industrial aspects and literature survey: Fleet composition and routing. Comput Oper Res 37:2041–2061

    Article  Google Scholar 

  • Holguín-Veras J, Wang Q, Xu N, Ozbay K, Cetin M, Polimeni J (2006) The impacts of time of day pricing on the behavior of freight carriers in a congested urban area: Implications to road pricing. Transp Res A Policy Pract 40:744–766

    Article  Google Scholar 

  • ISTAT, Istituto Nazionale di Statistica, 2011. Atlante Statistico dei Comuni. http://www.istat.it/it/archivio/113712. Accessed 26 Feb 2014

  • Jayaraman V (1998) Transportation, facility location and inventory issues in distribution network design: An investigation. Int J Oper Prod Manag 18(5):471–494

    Article  Google Scholar 

  • Kayakutlu G, Buyukozkan G (2011) Assessing performance factors for a 3PL in a value chain. Int J Prod Econ 131:441–452

    Article  Google Scholar 

  • Koç Ç, Bektaş T, Jabali O, Laporte G (2016) The impact of depot location, fleet composition and routing on emissions in city logistics. Transp Res Part B 84:81–102

    Article  Google Scholar 

  • Krauth EH, Moonen V, Popova V, Shut M (2005) Performance indicators in logistics service provision and warehouse management – a literature review and framework. Euroma International Conference, Budapest, Hungary, 19–22 June 2005, 19–22

  • Kuhlang P, Edtmayr T, Sihn W (2011) Methodical approach to increase productivity and reduce lead time in assembly and production-logistics processes. CIRP J Manuf Sci Technol 4:24–32

    Article  Google Scholar 

  • Kuhn H, Sternbeck MG (2013) Integrative retail logistics: An exploratory study. Oper Manag Res 6:2–18

    Article  Google Scholar 

  • Kuse H, Endo A, Iwao E (2010) Logistics facility, road network and district planning: Establishing comprehensive planning for city logistics. Proc-Soc Behav Sci 2:6251–6263

    Article  Google Scholar 

  • Lai K, Ngai EWT, Cheng TCE (2004) An empirical study of supply chain performance in transport logistics. Int J Prod Econ 87:321–331

    Article  Google Scholar 

  • Leonardi J, Browne M, Allen J, Bohne S, Ruesch M (2014) Best practice factory for freight transport in Europe: demonstrating how ‘good’urban freight cases are improving business profit and public sectors benefits. Proc-Soc Behav Sci 125:84–98

    Article  Google Scholar 

  • Liao CN, Kao HP (2014) An evaluation approach to logistics service using fuzzy theory, quality function development and goal programming. Comput Ind Eng 68:54–64

    Article  Google Scholar 

  • Lin ETJ, Lan LW, Hsu CST (2010) Assessing the on-road route efficiency for air-express courier. J Adv Transp 44:256–266

    Article  Google Scholar 

  • Männel D, Bortfeldt A (2016) A hybrid algorithm for the vehicle routing problem with pickup and delivery and three-dimensional loading constraints. Eur J Oper Res 254:840–858

    Article  Google Scholar 

  • Min H, Joo SJ (2003) Benchmarking the operational efficiency of major US trucking firms using data envelopment analysis. J Transp Manag 14:22–34

    Google Scholar 

  • Min H, Joo SJ (2006) Benchmarking the operational efficiency of major third-party logistics providers using data envelopment analysis. Supply Chain Manag: An Int J 11:259–265

    Article  Google Scholar 

  • Min H, Joo SJ (2009) Benchmarking third-party logistics providers using data envelopment analysis. Benchmarking: An Int J 16:572–587

    Article  Google Scholar 

  • Minitab (2016) Why Minitab https://www.minitab.com/en-us/academic/why-minitab. Accessed 24 Oct 2016

  • Muñuzuri J, Cortès P, Guarix J, Onieva L (2012) City Logistics in Spain: Why it might never work. Cities 29:133–141

    Article  Google Scholar 

  • Muñuzuri J, Grosso R, Cortés P, Guadix J (2013) Estimating the extra costs imposed on delivery vehicles using access time windows in a city. Comput Environ Urban Syst 41:262–275

    Article  Google Scholar 

  • Neirotti P, De Marco A, Cagliano AC, Mangano G, Scorrano F (2014) Current trends in Smart City initiatives: some stylised facts. Cities 38:25–36

    Article  Google Scholar 

  • Panayides PM, So M (2005) Logistics service provider–client relationships. Transp Res E 41:179–200

    Article  Google Scholar 

  • Ross AD, Miller SR, Carpenter M (2010) When methods and theories collide: Toward a better understanding of improving unit performance in multimarket firm. Oper Manag Res 3:172–183

    Article  Google Scholar 

  • Russo F, Comi A (2011) A model system for ex-ante assessment of city logistics measures. Res Transp Econ 31:81–87

    Article  Google Scholar 

  • Soderberg L, Bengtsoon L (2010) Supply Chain Management maturity and performance in SMEs. Oper Manag Res 3:90–97

    Article  Google Scholar 

  • Stainer A (1997) Logistics - a productivity performance perspective. Supply Chain Manag: An Int J 2:53–62

    Article  Google Scholar 

  • Tabachnick BG, Fidell LS (2001) Using Multivariate Statistic, 3rd edn. HarperCollins, New York

    Google Scholar 

  • Tamagawa D, Taniguchi E, Yamada T (2010) Evaluating city logistics measures using a multi-agent model. Proc-Soc Behav Sci 2:6002–6012

    Article  Google Scholar 

  • Taniguchi E, Shimamoto H (2004) Intelligent transportation system based dynamic vehicle routing and scheduling variable travel times. Transp Res Part C 12:235–250

    Article  Google Scholar 

  • Taniguchi E, Tamagawa D (2005) Evaluating city logistics measures considering the behavior of several stakeholders. J East Asia Soc Transp Stud 6:3062–3076

    Google Scholar 

  • Tukey JW (1977) Exploratory Data Analysis. Addinson-Wesley, Reading

    Google Scholar 

  • Villarreal B, Garza-Reyes JA, Kumar V (2016) A lean thinking and simulation based approach for the improvement of routing operations. Ind Manag Data Syst 116(5):903–925

    Article  Google Scholar 

  • Visser J, Nemoto T, Browne M (2014) Home Delivery and the Impacts on Urban Freight Transport: A Review. Proc - Soc Behav Sci 125:15–27

    Article  Google Scholar 

  • Wanke PF (2013) Physical Infrastructure and shipment consolidation efficiency drivers in Brazilian ports: a two stage network- DEA approach. Transp Policy 29:145–163

    Article  Google Scholar 

  • Wanke PF, Correa H (2012) Supply chain management and logistics complexity: a contingency approach. Int J Logist Econ Glob 4:239–271

    Google Scholar 

  • Wasner M, Zäpfel G (2004) An integrated multi-depot hub-location vehicle routing model for network planning of parcel service. Int J Prod Econ 90:403–419

    Article  Google Scholar 

  • Witkowski J, Kiba-Janiak M (2012) Relation between city logistics and quality of life as an assumption for referential model. Proc – Soc Behav Sci 39:568–581

    Article  Google Scholar 

  • Witlox F (2007) Logistics systems for sustainable cities. Cities 24:462–463

    Article  Google Scholar 

  • Yu M, Qi X (2014) A vehicle routing problem with multiple overlapped batches. Transp Res Part E 61:40–55

    Article  Google Scholar 

Download references

Acknowledgements

The authors wish to acknowledge the anonymous company for intense collaboration and permission for publication.

Author information

Authors and Affiliations

  1. Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Torino, TO, Italy

    Anna Corinna Cagliano, Alberto De Marco, Giulio Mangano & Giovanni Zenezini

Authors
  1. Anna Corinna Cagliano
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alberto De Marco
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giulio Mangano
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Giovanni Zenezini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Giovanni Zenezini.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical responsibility of authors

The authors declare that:

• The manuscript has not been submitted to more than one journal for simultaneous consideration.

• The manuscript has not been published previously

• The study is not split up into several parts to increase the quantity of submissions and submitted to various journals or to one journal over time

• No data have been fabricated or manipulated (including images) to support our conclusions

• No data, text, or theories by others are presented as if they were our own

• Consent to submit has been received explicitly from all co-authors, as well as from the responsible authorities - tacitly or explicitly - at the institute/organization where the work has been carried out, before the work is submitted.

• Authors whose names appear on the submission have contributed sufficiently to the scientific work and therefore share collective responsibility and accountability for the results

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cagliano, A.C., De Marco, A., Mangano, G. et al. Levers of logistics service providers’ efficiency in urban distribution. Oper Manag Res 10, 104–117 (2017). https://doi.org/10.1007/s12063-017-0125-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12063-017-0125-4

Keywords

Search

Navigation