the carriers' carrier consolidation approach in ...€¦ · logistics distribution model, case...

Thecarriers'carrierconsolidationapproachinsustainableurbanlogistics:

Trials,benefitsandfuturegrowth

JacquesLeonardi,UK

2017 METRANSInternationalUrbanFreightConferenceLosAngeles,18-20October2017

Hypotheses and Lead Questions

• Following hypothesis and questions build the starting point of this study: Ø How to scale-up the use of electric vehicles instead of diesel

vans to reduce air pollutants and carbon emissions?Ø Is the carriers’ carrier approach to parcel deliveries business

reducing the total freight distance for retail and e-commerce clients, by changing from outer London depots to centrally located logistics distribution centres in London?

Ø Is there a difference in consolidating deliveries of carriers and retail clients into one single van delivery trip to reduce the number of vehicle movements, associated congestion and air pollution?

Hypothesis, questions & objectives

• Initial hypothesis: The aim of this study was to demonstrate the benefits for public sector and private business, which are occurring when using a carriers’ carrier approach to grow consolidation and electric vehicles in city centers

• The study assessed the potential for: Ø re-timing of e-commerce B2C activity, away from peak hours

Ø re-routing of journeys away from the most congested roads and pollution hot spots

Ø improving the logistics efficiency (time and distance per parcel)

Ø reduction in emissions (CO2, diesel particulates, NOX)

• Objective of this study is to verify/falsify this hypothesis and answer the question: what are the benefits for public sector and private business, which are occurring when using a carriers’ carrier approach to grow consolidation and electric vehicles in city centers

3

Approach and Methods

4

Freightefficiencyoptimisation

ClimateChangemitigation

Internaliseexternalcosts

Improvebusinessmodel

Mini-miserisks

Theoreticalframework

Conceptualandmathematicalframework

Conceptualandmathematicalmodelsfortestingconsolidatedurbanfreightdeliveries

WithoneCarrier

withCarriers

Customeroriented

Before-afterTests &trials

Impactassessment,datamonitoringand

reporting

Legacy(scale-up)&futurescenario

Calculations&validation

withRetailers

Selection of businesses

• TheLondonparcelsdeliverybusinessGnewt CargotestedelectricvehiclesandlogisticsconsolidationinCentralLondonduringtheone-yeartrialsfrom1stJuly2015to30June2016.

• Thecustomerswerecarriersandretailers,payingthesamepriceperparcelthanforothersubcontractors

• Carriers:– Hermes– TNTUK– DX

• Retailers:– Farmdrop (Foode-commerce)– Emakers (e-commercedeliverybusiness)– Spicers(leadinguk wholesaleofficesuppliers)

Central London Delivery Area

Typicalgeolocationof100%electricdeliveryfleet

onanaverageday

BermondseySE1

WardensGroveSE1

SouthwarkSE1

HolbornWC1

PrincesStreetW1

LocationofGnewt Cargourbandistributioncenters

usedin2015-2016

Trial: parcels delivery business Gnewt Cargo in Central London

Alast-milelogisticproviderusinga100%ELECTRICfleetandcentrallylocatedurbanlogisticsconsolidationcenters

Over

100electricvehiclesfleet

Deliveredover

2,634,000items2016

zeroemission

Market Size

Business Performance & Citylogistics Indicators

KPI,Business&Citylogistics EfficiencyDataforClientA,July2015- June2016

Results: Main benefits

• thecarrier’scarrierapproach,bywhichtheoperatorcarriesparcelsfordifferentcarriercustomers;thismakesadifferenceintermsoflogisticsefficiency,highloadfactor,muchshorterdistanceperparcel,muchbetterperformanceintimeandcostsperparcel,whencomparedtoadistributionsystemforasingleclient.

• theuseofthecitycentredepotasbaseforafleetofelectricvehicles;thislowersemissionsbecauseitreplacespollutingdieseltrucksandvanswithzeroemissionvehiclesforalltripstothefinalrecipientsoftheparcels,locatedinthemostpollutedareasofthecitycentre.

• theuseofdieseltrucksatnighttobringtheparcelstoCentralLondonduringalowtraffic,lowemissiontime;thissolutioncompletelyavoidstheusualpeaktraffictimeinthemorningsonthecongestedarterialroadstowardscitycentre.

Logistics distribution model, case 1

Zara$$LSP$

depot$

Pull&Bear$LSP$

depot$

Gnewt$Consolida7on$

Centre$

Retail$logis7cs:$single<carrier$deliveries$

Farmdrop$depot$

Pull&Bear$LSP$

depot$

Street$1$ Street$2$ Street$3$ Street$1$ Street$2$ Street$3$

BEFORE&star%ng(using(Gnewtcargo( AFTER&star%ng(using(Gnewtcargo(

LSP$Depot$Enfield$

Farmdrop$depot$

LSP$Depot$Enfield$

Zara$LSP$

depot$

Diesel$van$round,$peak$$$$Electric$van$round,$peak$

Truck$trip$off<peak$Key$


Energy use analysis of the Client B demonstration with and without Gnewt Cargo

Without Gnewt: Diesel

van

With Gnewt: Diesel truck

With Gnewt: Nissan

eNV200

With Gnewt: Total

Without-With

reduction %

Distance km 16436 595 14054 14649 11 Electric energy used kWh 2473 kWh/km 0,176 Conversion factor goe/kWh 85.984523 Total period litres 1479 112 112 92 Conversion factor goe/litre 845 845 Total energy use kgoe 1250 95 213 307 75 Results energy per km goe/km 76 159 31 90 Results energy per parcel goe/parcel

97 7 16 24 75


Gnewt depotWestCentralSt.

Carrierlogistics:single-carrierdeliveries

TNTDepotBarking

Street1 Street2 Street3 Street1 Street2 Street3

BEFOREstartingusingGnewtcargo AFTERstartingusingGnewtcargo

Dieselvanround, peakElectricvanround,peak

Trucktripoff-peakKey

TNTDomesticDepot

Northampton

TNTInternational

DepotStansted

TNTInternational

DepotLuton

TNTDomesticDepot

Northampton

TNTdepotBermondsey

Logistics distribution model, case 2distance analysis

Logistics distribution model, case 2Overall analysis of efficiency & benefits

0

20

40

60

80

100

120

Reductioninthenumberofvehicletrips

Reductionintotalkilometres

travelled

ReductioninNOx(ing

NOx/parcel)

ReductioninPM(ing

PM10/parcel)

ReductioninCO2emissions(inCO2e/parcel)

Reductionintotaltransportenergyuse

Reductioninemptyvehicledistance

%reduction AchievedQ1 Target(final)Q1(financialyear2016/2017)

1stJuly2015– 30June2016(n=13,358)onepoint=averagedistanceinmetresperparcelforonedeliveryround=onedriver,onevan,onefullworkingday,7days/week,fulldaydistance,

onlypaid(successfuldeliveriesandcollections)unitscounted

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000

6500

7000

0 2000 4000 6000 8000 10000 12000

Metres/parcel

ID of Delivery round

Average119metres/parcels

Potentialforfutureefficiencyimprovements

Business & Citylogistics EfficiencyKPI: Metres per parcel delivered



Business & Citylogistics EfficiencyKPI: Completion rate

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 2000 4000 6000 8000 10000 12000

% of succesfully completed deliveries

ID of Delivery round

Annualaverage87%

Dailyaveragetrendline



Business & Citylogistics EfficiencyKPI: Working time per parcel

00:00

00:28

00:57

01:26

01:55

02:24

02:52

03:21

0 2000 4000 6000 8000 10000 12000

Timeperparcel

Average6 min. /parcel

• Hypotheses verified?• Questions answered?• How other papers compare?

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Discussion

Final re-considering of initial projecthypothesis, questions & objectives

• Initial hypothesis: Is it possible to scale-up the carriers’ carrier business model to obtain a better efficiency of urban distribution?

• Objective of this study was to verify/falsify this hypothesis and answer the question: Øwhat could be the future upscaling of urban

distribution centers and electric vehicle use ?ØUsing one specialist carrier and a fully market

oriented business approach

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In theory yes

Concluding remarks

Résumé:• Trials:differentbusinessmodelsweretested,correspondingto

thedifferenttypesofpotentialfutureclients• Results:Onmostcasestestedthedistancedrivenareshorter,the

emissionsreduced,thedaytimetrafficdecreased,theoveralltimespentperparceldecrease

• Limitations:– Inoneexample,itwaspossibletoreducetailpipeemissionstozero.Onlythelifecycleemissionsofelectricvansproductionandroadsurfacedust&PMemissionsremain.

– Itremainsaverydifficultbusinessenvironmentforanindependentsubcontractor,andtoincreasethemarketshare

How other papers compare?

• Overview,review& prospectivepaperswereessentialotherwisethetrialswouldhavebeenmeaningless

• Noliteratureontestingdifferentclientsandbusinessmodelsbenefitingcitylogistics efficiencywithanapproachofrealbusinesstrialdata?

• Findingsofthisresearchobtainadistancereductionbetween11%and67%

• Decisionmakersandmodellingauthorsworkingwithassumptions(suchasRizet etal2014)findanincreaseintotaldistanceandcostsduetosmallercapacityvehiclesandadditionalloading/unloadingactivities

Approaches required in future

• Work together with research, industry and publicauthorities to:ØFind suitable, central consolidation centre locations at

prices lower than the real estate marketØFurther test different business models with different clients,

different citiesØ Introduce bigger electric vans and trucksØObtain good quality before-after data

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