THE IMPACT OF E-COMMERCE ON TRANSPORT

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					        JOINT OECD/ECMT SEMINAR

               PARIS - 5/6 juin 2001




THE IMPACT OF E-COMMERCE ON TRANSPORT




                   Session 4 :

    TRANSPORT AND LOCAL DISTRIBUTION



          E-commerce and urban transport


                Michael BROWNE
             University of Westminster
                      London
                 United Kingdom
                                                   TABLE OF CONTENTS




1.   INTRODUCTION................................................................................................................. 3

2.   E-COMMERCE: BACKGROUND, DEVELOPMENTS AND TRENDS .......................... 3

     2.1. Rapid growth and forecasts............................................................................................ 4
     2.2. Types of goods purchased.............................................................................................. 4
     2.3 Logistics costs and efficiency ........................................................................................ 5


3.   IMPACTS OF E-COMMERCE ON LOGISTICS AND THE SUPPLY CHAIN ................ 6

     3.1. B2B e-commerce............................................................................................................ 6
     3.2. B2C e-commerce............................................................................................................ 8


4.   DISTRIBUTION OPERATIONS AND VEHICLE REQUIREMENTS
     THE IMPLICATIONS FROM GROWTH IN E-COMMERCE......................................... 12


5.   TOTAL VEHICLE ACTIVITY IN B2C E-COMMERCE: OFFSETTING
     ADDITIONAL DELIVERY TRIPS BY REDUCED CAR TRAVEL ............................... 14

     5.1. Three case studies of transport implications of home delivery.................................... 14
     5.2. Factors that will influence vehicle trips and kilometres for home delivery ................. 16


6.   CITY SIZE, POPULATION DENSITY AND UPTAKE OF E-COMMERCE
     IMPLICATIONS FOR COMMERCIAL VEHICLE ACTIVITY ...................................... 18


7.   POLICY ISSUES AND QUESTIONS................................................................................ 21

     7.1. Environmental and social impacts of home deliveries................................................. 21
     7.2. Further Discussion of Parking Issues in Residential Streets ........................................ 22
     7.3. The potential importance of legislation........................................................................ 24


8.   CONCLUDING REMARKS .............................................................................................. 24




                                                                     2
                                          1. INTRODUCTION



     The rise of what has been referred to as the ‘information society’ is leading to changes in lifestyle
for many people and in some cases changing the fundamental mechanisms of the economy. The
growing importance of the information society does not necessarily mean that movement of goods and
people will decrease although flows will almost certainly change – for example, deliveries of goods by
van to the home may replace the need for a trip by car. Developments in e-commerce are an essential
element of the information society.

     Delivering to consumers homes is not a new phenomenon. However, the potentially dramatic
changes in patterns of movement resulting from growth in e-commerce is particularly important for
transport. If e-commerce grows significantly then the volumes of products that will need to be
delivered to consumers homes will also increase. This growth in home delivery will, in turn, result in
changes in vehicle activity towns and cities and these changes will be especially evident in residential
areas.

      This paper reviews the distribution implications of e-commerce involving the physical movement
of goods within supply chains and including delivery to the consumer with particular reference to
changes in distribution and transport activity in urban areas. The opening section of the paper
examines the growth in e-commerce. The paper then goes on to consider the broad impacts of e-
commerce on the supply chain before turning to the distribution operations in urban areas. The
potential trade-off between increased delivery to homes and reduced car trips is then discussed and
this section is followed by an illustration of the potential increases in vehicle activity in cities resulting
from growth in e-commerce. The penultimate section of the paper considers policy issues and
questions. The final section contains a summary of the main conclusions arising from the paper.




            2. E-COMMERCE: BACKGROUND, DEVELOPMENTS AND TRENDS



     Although the internet and technology in a wider sense are important, e-commerce is not just a set
of technologies or business methods, it is a view of business and of value creation which leads to
revolutionary change. The fundamental importance of the developments in e-commerce for supply
chains has been noted (DTI/Foresight, 2000a) :

     “... by 2010 all but the most traditional of businesses will have redesigned their supply and
     distribution chains to take account of electronic commerce. Those which have not will long since
     have been out of business.”




                                                      3
     Discussions of e-commerce often refer to the distinction between business to business (B2B)
e-commerce and business to consumer (B2C) e-commerce. The B2C e-commerce market is usually
discussed as if it is separate from the B2B market. In some ways this can hide the important links
between B2B and B2C e-commerce. The changes that will result from growing use of e-commerce in
the B2B market could feed through into changes in the way products move through supply chains to
final consumers. To some extent, electronic channels blur the boundaries of the B2C and B2B
markets and enable the emergence of new consumer-to-business relationships.


2.1. Rapid growth and forecasts

     The rapid development of e-commerce and the resulting uncertainty about the emerging patterns
is evident when forecasts of growth are considered. Estimates of growth vary considerably from one
report to another. In many cases this is due to methodological issues about sampling, extrapolation
techniques and so on. However, in other cases it is a question of definition -- for example, should EDI
transactions be included in the scope of a forecast about B2B growth? During the latter part of 2000
and into 2001 there was also considerable media speculation about the extent to which the likely
growth of e-commerce had been exaggerated. As Table 1 shows, the range of forecasts is rather wide.


                  Table 1: Forecasts of worldwide e-commerce revenues for 2003

             Source                                                    Forecast
                                                                      ($ billion)
             OECD                                                        1000
             Intel                                                       1000
             Deloitte & Touche                                           1100
             Emarketer                                                   1244
             IDC                                                         1317
             Active Media                                                1324
             Forrester – low- (excluding EDI)                            1800
             Forrester – high - (including EDI)                          3200

             Source: Giesen, 2000.

     B2B e-commerce is currently estimated to have a significantly greater value than B2C
e-commerce, and this difference is expected to increase over time. However, so far much more has
been written about the physical distribution and transport implications of B2C e-commerce. To some
extent this is because it is perceived by the media as a more interesting aspect of e-commerce since it
touches peoples personal lives so directly but it is also in part because the implications for transport
and distribution of the potential changes are much clearer. Nevertheless as the paper will argue many
uncertainties remain about the implications of growth in B2C e-commerce from the perspective of
transport and distribution.


2.2. Types of goods purchased

     The relative maturity of different e-commerce and home delivery sectors varies. For example,
large items delivered to home and the traditional home shopping markets are far greater in value at
present than the e-commerce home delivery grocery market. However, large items and traditional


                                                   4
home shopping are relatively mature markets, whereas grocery home delivery is a relatively new
market with significant growth potential.

      Table 2 illustrates the categories of goods that are currently purchased most frequently on-line.
Although this can be expected to change in the long term, it provides a useful snapshot of the physical
distribution demands that will be placed on those providing B2C services.


                   Table 2. Categories of goods purchased by on-line shoppers

            Product categories                                Bought by % of on-line
                                                                    shoppers
            Books                                                     66%
            CDs, recorded music                                       58%
            Computers and related products                            38%
            Air travel reservations                                   26%
            Videos, filmed entertainment                              19%
            Flowers                                                   18%
            Event tickets (sport, entertainment)                      17%
            Food, drink                                               13%
            Men’s clothing                                            12%
            Women’s clothing                                          12%

           Source: Ernst & Young, 2000.


     The importance of delivery and collection can be seen by reference to many recent presentations
on e-commerce -- for example:

    “23 per cent of on-line shoppers say easier delivery/collection options would encourage them to
spend more on-line” (respondents were given a choice of factors). (Source: PA Consulting, 2000.)

     Much of the early discussion about B2C e-commerce was concerned with the design of web-sites
and how best to attract customers. The focus has shifted and there is at present more interest in how
best to manage order fulfilment. So far most of this concern about delivery operations has focused on
achieving customer satisfaction in terms of providing reliable deliveries in a manner that suits the
client. It is no surprise that this part of the home shopping supply chain is receiving attention, given
the problems that many companies in the US and UK experienced in providing high-quality delivery
operations in the run up to Christmas 1999 and Christmas 2000. The potential effect of poor or failed
deliveries on a customer’s continued use of home shopping services are significant.


2.3. Logistics costs and efficiency

     Importantly, because much of the B2C distribution activity has a start or end point in urban areas,
these areas will potentially be subject to profound changes. The position is complicated because on the
one hand if growth in e-commerce does not happen as predicted then the resulting changes will be
small. On the other hand if growth does occur in line with even the more modest forecasts then the
degree of implied change in goods flows is considerable. It is further complicated because for B2C
e-commerce to prove profitable and appealing it will require very efficient, reliable and low-cost

                                                   5
freight transport services. In addition the costs for order picking will need to be low – this could be a
particular barrier to e-commerce grocery/food services. While freight transport services tend to be
relatively low-cost, it remains to be seen whether these services can achieve the required level of
efficiency and reliability that will be required by customers with ever-increasing service level
expectations. It is possible that e-commerce deliveries that are able to make use of existing physical
distribution channels will prove more successful, at least in the short-term, than those that require new
physical distribution channels to be established. This is due to the fact that these existing distribution
channels already receive high product throughput (helping to reduce unit costs) and achieve a
relatively high level of efficiency.

     In thinking about the logistics costs of B2C e-commerce, it is important to remember that the
costs associated with order picking and delivery to the customer's home are not new costs. These
activities and costs existed prior to the introduction of e-commerce. The difference in an e-commerce
environment is that rather than these activities and costs being borne by the customer they are now
borne by the e-commerce company. Therefore, e-commerce involves a redistribution of costs rather
than the creation of new costs. In fact, it may be the case that order picking and transport costs are
lower when performed by or on behalf of an e-commerce company than when carried out by the
consumer (especially when taking into account the customer's value of time). The concern for e-
commerce companies is whether these costs are recoverable (i.e. whether the customer is prepared to
pay a price that fully covers the cost of these activities).




        3. IMPACTS OF E-COMMERCE ON LOGISTICS AND THE SUPPLY CHAIN



     This section of the paper is divided into two parts -- first the implications of growth in B2B
e-commerce are reviewed and this is followed by the impact of B2C e-commerce. The section on B2C
e-commerce is longer and more detailed because more has been established about the patterns of
physical distribution and the extent of change that may be expected and the implications for urban
transport are clearly of considerable importance.


3.1. B2B e-commerce

      At present the pattern of the business relationships between industrial companies is typically
tightly structured and there has been a growing emphasis on long-term business relationships and
working with supply chain partners. The physical transport links within a supply network are often
well established and sometimes complex with a variety of partners and contractors involved. The
creation of more open and information rich markets holds out the prospect of more rapid change and
also the possibility that physical transport links will need to be much more responsive to change. In
this more flexible environment it is possible to foresee a pattern of demand for and supply of transport
capacity that changes rapidly and where the origins and destinations of products may also change at
short notice. Although the nature of these new markets is not yet clear it seems likely that in some
cases there will be a dominant player, while in others the market will be based around a broader
equality between the members. The key point for physical distribution patterns is the potential
development of a network in which the origins and destinations of product flows could change rapidly



                                                    6
and where the consignment size, frequency of collection and delivery and the velocity in the supply
chain differ from the existing pattern.

     The emergence of supply chain communities will have a major impact on logistics functions of
inventory management and transport. The typical pattern of manufacturing and retailing leads to
waves of products moving along the supply chain - for example -- a manufacturer of electrical goods
places orders for components on suppliers who then ship them to the assembly plant. On-line
communities could act like a hub -- thus a retailer could place continuous orders with manufacturers to
accommodate changes in consumer demand, and manufacturers, in turn, would place a steady flow of
orders with suppliers. This in turn will lead companies to review their distribution systems. Among
the implications are:

      real-time demand rather than forecasts will drive these new supply chain models;
      a reduction in aggregate inventory held by all trading partners -- in many current supply
       chains stock is held at each link;
      shared information about demand and inventory should also smooth out the peaks and
       troughs in replenishment flows;
      supply chain communities should achieve more inventory turns.

    These trends will encourage further developments such as cross-docking initiatives -- with an
impact on distribution centre design as well as transport requirements.

     The impact of B2B e-commerce on vehicle trips and vehicle fleet requirements is somewhat
uncertain (Browne, 2000). On the one hand, it can be argued that attempts to meet real-time demand
could result, at least initially, in more frequent, smaller shipments. However, on the other hand there is
strong argument that the emergence of supply chain communities using computer intelligence to share
information will lead to greater visibility and transparency, and that this will lead to opportunities to
consolidate orders, and thereby improve commercial vehicle utilisation and reduce freight costs.

     It is also apparent that the development of freight exchanges could spur more competition for
freight among carriers by facilitating on-the-spot bidding for shipments. Furthermore, if supply chain
communities decide to manage their distribution activities as a group, it might benefit the third-party
logistics industry as they will have the opportunity to consolidate products from multiple vendors.

      The switch in emphasis from the individual company to a group approach may have a major
impact on distribution. The development of supply chain communities may result in new group
distribution strategies as companies apply their collective computer intelligence to develop an
integrated response strategy that would juggle production capacity and inventory availability to meet
fluctuating demand (Cooke, 2000).

     Many of the above developments will have implications for intra-urban and longer distance
transport movements. However, the start and end points of many B2B trips are in urban areas and
therefore there are implications for urban transport since in many instances the road capacity (and
capacity of other modes) has to be shared among a range of competing users. Depending on the effect
of growth in B2B on logistics and delivery systems it could result in changes in commercial vehicle
(truck and van) trip generation, size of vehicle used and the timing of operations.




                                                    7
3.2. B2C e-commerce

     By contrast with the B2B e-commerce sector, B2C has received rather more attention and more
of that has been paid to issues relating to the order fulfilment process (especially the delivery to the
final consumer). The focus on business sector varies somewhat from one country to another -- for
example, in the UK and USA there has been much interest in grocery retailing developments.

      Already current consumer e-commerce is weighted towards certain goods and services. New
areas of consumer interest are unpredictable, but examples could include entertainment
(e.g. multi-player games, and event participation), gambling, buying and selling shares, and grocery
shopping. The type of product involved will have an important bearing on the requirements for
distributing that product to the customer.

     The following section discusses: (i) existing and emerging home delivery systems, (ii) the need
for the customer to be present at the time of delivery and (iii) the potential importance of collection
and delivery points. Each of these issues has implications for the scale and location of distribution and
transport activity. They are closely linked to where people live and work and thus in turn they have
implications for urban land use and travel patterns.

3.2.1      Home delivery of products

     Two factors are of special importance when considering delivery of products to consumers:

         Whether the physical distribution channel will need to change;
         Whether the product requires that the customer is present at time of delivery.

      In B2C e-commerce the type of product can result in a need for change in the physical
distribution channel (i.e. the way and place in which the product is stored, picked and transported to
the customer’s home):

         for certain products there is no physical delivery (such as in the case of downloading
          software or music);
         for many products there are existing physical distribution channels along which the products
          can flow (e.g. books purchased over the internet are handled by existing physical distribution
          channels of express companies and postal networks and ‘white goods’ such as refrigerators
          are usually delivered to consumers’ homes even if they are purchased conventionally in a
          store);
         for some products there is no existing physical distribution channel and it is necessary to
          establish an entirely new means of supplying goods to customers (e.g. grocery home
          shopping which requires investment in and the operation of entirely new vehicle fleets).

     The number of hubs and depots operated depends on several factors such as size of demand,
geographical spread of population, size of country, and domestic or international operation. This
system accounts for most non-food products purchased via e-commerce.

     In the case of grocery e-commerce provided by existing store-based grocery retailers, in which
there are no existing physical distribution channels for the home delivery operation, the company has
to decide where to locate storage, order processing, picking and delivery activities. Broadly speaking,
two logistics models are in current use (see Figures 1 and 2).



                                                    8
 locating e-commerce operations at existing retail stores;
 locating e-commerce operations in order fulfilment centres, which are specially designed for,
  and dedicated to, e-commerce orders.


                   Figure 1: Logistics model for store-based picking



                   Suppliers



           Existing RDCs



                  Stores                                          Customer



                                                           Customer

           Customer




                  Figure 2: Logistics model with e-fulfilment centre



                   Suppliers                                   Van centre


                                            Order picking
          Existing RDCs                                              Customer
                                            centre


                 Stores
                                                                   Customer
                                          Van centre


          Customer                      Customer                  Customer




                                            9
Order fulfilment centres are more expensive to establish than simply using existing retail facilities.
However, store-based operations tend to prove less operationally efficient, and can negatively affect
the shopping experience of those customers who continue to visit the store. Order fulfilment centres
tend to cover a much wider catchment area than existing retail stores. As a consequence, this results in
either: (i) relatively long trip lengths for delivery vehicles, or (ii) the need to introduce an additional
tier of small depots at which goods are transferred from larger vehicles to local delivery vans.

      The new physical distribution channels being operated by grocery e-commerce companies are
likely to become blurred as retailers continue to experiment in order to find the best methods for their
operations and markets. It will certainly lead to the emergence of hybrid models – fulfilment centres
will be built when there is sufficient density of sales to justify them and these will run alongside the
store picking approach. The new physical distribution channels may continue to operated on a
dedicated basis (i.e. only for the supply of one e-commerce grocery company's products) or some
facilities including e-fulfilment centres and delivery vehicles will be shared between companies. It is
sometimes argued in conventional grocery retail logistics that there are relatively few benefits from
sharing because the volumes generated by large grocery retailers are sufficient to justify dedicated
systems. In the case of the home delivery of e-commerce orders this may not be such a valid argument.

3.2.2     Whether the customer has to be present at time of delivery

     In the case of e-commerce deliveries made to customers’ homes a key issue in planning the
delivery is whether or not the customer has to be at home to receive the delivery. If it is necessary for
the customer to be present this necessitates greater planning in order to ensure that a satisfactory
proportion of deliveries are successful. Unsuccessful deliveries lead to higher operating costs and/or
poor customer image of the company. Deliveries attempted when the customer is not at home result in
the need to call again, while failure to deliver at a time agreed with the customer could threaten a
customer's repeated use of the e-commerce company. This aspect is also important in relation to peaks
in delivery times.

     Some e-commerce products are small enough to fit through letterboxes or into mailboxes at
customer's homes and can be delivered whether or not the customer is at home at the time of delivery.
These products tend to be distributed to customers via existing national postal networks.

     The delivery of groceries to customers' homes tends to take place on a pre-arranged day and
within a given time-window. By putting in place these arrangements with customers it is possible to
significantly increase the number of successful deliveries. This is important in the case of grocery and
other products that physically deteriorate over time.

     Deliveries of non-food products tend to be less tightly scheduled with the customer. In the case
of some deliveries (such as furniture and white goods) a day for delivery is agreed in advance, and in
some cases a day and time-window is agreed. This tends to be more common for the delivery of large,
heavy items, as it is very inefficient to have to load and unload these types of goods from vehicles
more than necessary. However, in many instances of non-food delivery, especially those made by
postal or express companies, no arrangement about day or time of delivery is made with the customer.

     Figure 3 shows the product and delivery factors that determine whether or not the customer has to
be present to receive the delivery.




                                                    10
         Figure 3: Factors affecting whether customer has to be present during delivery


                              Where is the point
                              of delivery?




               Collection                           Customer’s
               and delivery                         home
               point (CDP)

                                                   Can the goods fit
                                                   through mailbox?



                                               Yes                  No



                                                              Is there a storage
                                                              box?



                                                            Yes                No




                 No need for customer to                               Need for customer to be
                 be present at time of                                 present at time of delivery
                 delivery




     Using secure storage boxes to receive deliveries when the occupier is absent would allow
delivery companies to optimise transport routes and schedules and thereby achieve better vehicle and
driver productivity as well as reducing the total transport requirement for each unit delivered. This
option has been tested in the United States, and property developers in Europe are reported to be
installing these devices in some new houses.

     For grocery deliveries, such a storage device would need to be temperature controlled, unless the
goods were delivered in an insulated box. Food safety and legal liability issues would need to be
addressed before such systems become commonplace. Research in Finland (Punakivi and Saranen,
2000) has illustrated the potential improvements in transport efficiency that may result from this type
of approach.

     If a suitable storage device can be designed, its use could be encouraged by policy makers
through the planning process. It could, for instance, be made a compulsory component of any new
housing developments.

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3.2.3       Collection and delivery points

     Increased use of collection and delivery points (CDPs) would enable delivery efficiencies to be
achieved. As with storage boxes, such a facility would allow the option of optimising routes and
schedules for deliveries. Goods could be stored until it was convenient for the customer to collect
them, or the operator of the CDP could deliver as part of a local delivery round. There is also scope for
the CDP to act as a central facility for the management of any returned goods. The exact facilities
required would depend on local circumstances (DTI/Foresight, 2000b). Examples of possible CDP
locations include:

           Workplaces;
           Local stores or petrol/filling stations;
           Park and Ride sites;
           Out of town shopping centres;
           Local urban delivery centres;
           Leisure facilities (swimming pools, sports clubs);
           Schools;
           Rail Stations.

     One of the important points about the use of CDPs is that they would have an impact on the
optimum size of commercial vehicle for the particular type of operation. Overall it would also change
the mix of vehicles required to service any given distribution system or network.

      An important aspect of CDPs is that they would potentially generate significant numbers of
vehicle trips both by companies delivering to the CDP and by consumers collecting from them. While
it could be argued that if they were sited at places that already generate trips then this would not add to
the total volume this is a point that will be of concern to those responsible for urban planning.

     In addition, some CDPs may have undesired and unforeseen implications for mode choice – for
example, if the CDP is sited at a workplace then it may encourage consumers to travel to work by car
(rather than public transport) on the days when they need to return home with heavy items delivered to
the CDP at their place of work.




              4. DISTRIBUTION OPERATIONS AND VEHICLE REQUIREMENTS:
                   THE IMPLICATIONS FROM GROWTH IN E-COMMERCE



     Despite the growing amount of market information available about e-commerce there is less data
on physical distribution operations including vehicle fleets and operations. Much of the interest in this
area has been restricted to B2C e-commerce and within that it has tended to focus on the extent to
which shopping trips in cars made by individual consumers would be or could be replaced by home
delivery trips (probably using small trucks or vans).

     The potential for reductions in total vehicle kilometres resulting from growth in e-commerce and
resulting deliveries to homes has been noted (see for example: Farahmand and Young, 1998; Cairns,

                                                     12
1999; Karamitsos, 2000; Punakivi and Saranen, 2000). This type of information, often produced by
modelling, is now more widely discussed. However, the optimistic assertions of trip and distance
reductions depend very much on the underlying assumptions (Browne and Allen, 2000). In some
instances it will be difficult to achieve high levels of vehicle utilisation, and a proportion of goods will
need to be returned which will require additional trips. Also, the propensity of individuals to make
additional non-shopping trips has yet to be fully explored. Nevertheless, e-commerce may well have a
role to play in helping to reduce urban congestion levels. Estimates of the potential savings vary
significantly and are discussed more fully in Section 4 (below).

     The previous section of this paper argued that the growth of e-commerce could have impacts on
the physical distribution networks required to move goods from producers to consumers. Before
reviewing the trade-off between trips by goods vehicles and trips by individuals it is interesting to
consider how the changes in physical distribution networks will in turn influence the commercial
vehicle users’ requirements in terms of:

         Total fleet capacity
         Fleet activity (trips/kilometres)
         Fleet mix
         Technology/development

      The extent to which vehicle fleet sizes, mix and activity change will depend on e-commerce
growth rates. The rapid development of e-commerce has led to uncertainty about its future rate of
growth, with estimates of growth varying considerably from one report to another. B2B e-commerce
may well continue to grow in value over the next five years and beyond, however the rate of growth is
difficult to predict. There is far less certainty about the future of B2C e-commerce. Its future will be
closely tied to the issue of whether B2C e-commerce proves to be profitable in the next few years.
Therefore, B2C e-commerce could either continue to grow (i.e. a continuation of the current trend) or,
alternatively, it may reach a peak and then remain stable or even begin to diminish, continuing to
flourish only in certain niche sectors in which it achieves satisfactory profitability.

     Two factors are important in considering the implications of growth in B2C e-commerce:

     (i) that a number of channels already exist which are able to deliver goods direct from supplier to
          consumer;
     (ii) even predictions of explosive growth by 2005 generally assume a market of less than 20% of
          retail purchases through e-commerce. The implications of these two factors are:

     At very high levels of growth there would be extra demands for vehicles to deliver in residential
areas; some of this growth could be accommodated by existing parcels delivery operations but some
new services would develop.

     There are expectations that, in many cases, vehicles delivering in residential areas would be
mainly small vehicles. The regulatory regimes in terms of operating licences are more relaxed for
vehicles of this size and the requirements for specially trained drivers are less of a constraint; for
example, car-derived vans and even some larger vehicles can be driven by those possessing an
ordinary driving licence.

     At low levels of growth in B2C e-commerce (i.e. below 5% of total retail sales) there would be a
correspondingly limited change in vehicle requirements. However, even at low levels of uptake there



                                                    13
may some increase in demand for smaller vehicles to make the local deliveries to homes and to drop-
off and collection points.




 5. TOTAL VEHICLE ACTIVITY IN B2C E-COMMERCE: OFFSETTING ADDITIONAL
                DELIVERY TRIPS BY REDUCED CAR TRAVEL



      The traffic generation effects and environmental impacts associated with the growth in B2C
e-commerce are currently not well understood. Some studies have examined the effect on vehicle trip
generation and have calculated that that the number of van trips and vehicle kilometres required to
make home deliveries will be far lower than those previously performed by customers in their cars.
Such studies have tended to conclude that the uptake of e-commerce opportunities will help to ease
traffic congestion and the environmental impacts of road traffic in urban areas. They therefore view
e-commerce and the resulting increase in home shopping and deliveries as phenomena that should be
encouraged. The findings of three such studies are summarised below.


5.1.      Three case studies of transport implications of home delivery

      Farahmand and Young (1998) modelled the vehicle trip effects of home delivery for a typical UK
grocery store with gross floor area of 2 500 m2, and a typical DIY store with gross floor area of
10 000 m2. They assumed pre-home delivery weekday PM peak hour trip rates of 18 trips per 100 m2
for the grocery store and 10.2 trips per 100 m2 for the DIY store, that 10% of shoppers at both stores
would switch to home shopping, and that delivery vehicles would carry nine customers’ loads on each
round trip. The results of their modelling are shown in Table 3.


                                        Table 3. Summary of results

                            Total trips          Total trips generated           Reduction in vehicle
                          generated prior          in home delivery               kilometres for trips
                              to home                   system                 previously made by home
                             deliveries                                              shoppers (%)
 Grocery store                   450                        410                              87

 DIY store                       1020                       930                              87

(1) It is important to note that the 87 per cent reduction in vehicle kilometres refers to the comparison between
    the 10 per cent of trips previously made by car which, as a result of the home delivery service, are now
    made by vans. It does not mean that the total vehicle kilometres travelled to and from the shops by all
    customers is reduced by 87 per cent.

Source: Based on data in Farahmand and Young, 1998.




                                                       14
     Cairns (1999) modelled grocery home deliveries in Witney in Oxfordshire in the UK. Her
findings indicated that if 10-20% of total shoppers were to use home shopping, the switch from
customer car journeys to multi-drop van deliveries could lead to a 7-16% reduction in trip numbers (as
vans replace car trips) and a 70-80% reductions in vehicle kilometres (for those customers using the
home shopping service), even if each delivery van only carried eight loads of shopping. Cairns notes
that even “if deliveries have to be within tight time constraints, there are still likely to be savings,
since this will simply mean that more vans are required, each carrying a lower number of shopping
loads. In the worst case, of course, vans would simply act as if they were cars, carrying one load of
shopping each, and delivering to only one household. Hence, a delivery service would never generate
more travel than individual car trips, when operating from a local base, providing all users got to the
shops some other way, or ordered their shopping from home, and assuming no other changes in
customer behaviour”.

     Punakivi and Saranen (2000) modelled the potential mileage effects of grocery home shopping in
Finland. It was assumed that 1.63% of the 202,000 population spread over an area of 135 km2 used the
home shopping service. The calculations were based on actual shopping data for one week from five
grocery shops in Finland's second largest grocery chain and actual details of customers’ homes. All
orders over 150 FIM were modelled as home deliveries; 1 639 such purchases were made during the
week. Four different home delivery services were modelled; these varied in terms of how long after
the order the delivery was made and the time window offered. Table 4 shows the effect on mileage
travelled.


                Table 4. Effect of grocery home shopping on delivery van mileage

                                                                               Mileage per
                                                                                  week
                                                                               (Car = 100)
         Use of own car (current system)                                            100
         Home delivery – next day in 1 hour slots                                   46
         Home delivery – same day in three 2 hour slots                             24
         Home delivery – next day in reception box                                  13
         Home delivery – chosen day in reception box once per week                   7

         Source: Based on data in Punakivi and Saranen, 2000.

     Punakivi and Saranen also calculated the cost to the grocery chain of providing these different
customer service thresholds. It was estimated that to offer next day delivery within a one hour time
slot would be more than three times as expensive as delivery on a chosen day into a reception box at
the customers’ homes (so that the delivery could be made at any time of day) once per week.

     Reductions in vehicle emissions were also calculated by Punakivi and Saranen. For the best home
delivery scenario CO emissions would be reduced by 98%, HC by 95% and NOx by 75%.

    The three studies referred to above all indicate that home delivery could prove beneficial in
reducing vehicle trip rates and the total distance travelled. This could obviously help to reduce traffic
congestion as well as a range of environmental impacts such as fossil fuel use, pollutant emissions and

                                                   15
accident rates. However, several key assumptions are made in the above studies that have important
consequences for the trip generation and vehicle kilometre results. These are considered in the next
section.


5.2.       Factors that will influence vehicle trips and kilometres for home delivery

    A number of the assumptions made in calculations of vehicle trip reduction resulting from B2C
e-commerce are open to question and as a result it is possible to argue that the vehicle trip generation
and vehicle kilometre results tend to be underestimated. Six parameters that are likely to affect trip
generation for home delivery operations are discussed below.

       (i) How customer behaviour will change as a result of e-commerce/home shopping:

        Time savings derived from using home shopping could encourage people to make additional
         car trips for other purposes (such as leisure trips, or to visit friends and relatives). Shopping
         trips tend to have shorter trip lengths than many other journey purposes. Therefore
         substitution of car-based shopping trips for other car trips will be likely to result in an
         increase in vehicle kilometres travelled.
        Shoppers may still want to view the actual goods prior to purchase. This would involve
         travelling to the shop (either by car or some other mode). If this is carried out by car there
         may be no reduction in car-based travel together with an increase in home delivery vehicle
         traffic.

       (ii) Dedicated or shared user systems for delivery:

        If companies offering home delivery operate dedicated distribution system (as is the case for
         many companies such as department stores and supermarkets) in which their vehicles only
         deliver their own products, this can generate far greater home delivery vehicle trips and
         vehicle kilometres than if companies share their delivery systems and vehicle capacity with
         each other.
        This practice is most common for food deliveries as the grocery retailers currently operate
         their own dedicated fleets. When drop density is low this could lead to significantly
         increased vehicle movement.

       (iii) Order frequency and despatch of single items:

        Customers’ order frequency and hence vehicle trips and vehicle kilometres could actually
         rise as a result of home shopping. In the USA for example Webvan, an exclusively home
         shopping grocery company, initially offered free delivery to customers in an effort to get
         customers to try their service regardless of order size (Anon., 2000).
        Delivery charges that are not linked to order size will, naturally, encourage customers to buy
         small quantities often. Far more often in fact, because of the convenience, than they used to
         visit the supermarket.
        In many home shopping systems (especially non-food) each item on a customers’ order can
         be despatched as soon as it is available rather than waiting until the entire order is in stock
         (for example the service offered by Amazon). This strategy is often viewed by companies as
         an essential component in providing a high level of customer service. In this way, one order
         can become many separate deliveries, thereby increasing trip numbers and vehicle
         kilometres.

                                                    16
       If the delivery is being carried out on behalf of the seller by a third party distribution
        provider and a consignment containing more than one individually packaged item is sent to
        the customer, there is a significant risk of the items not being loaded onto the same home
        delivery vehicle. This results in the items being delivered separately and increases the
        vehicle trips and vehicle kilometres. This situation is most likely to occur in the case of non-
        food products as these are often delivered by third party distribution providers.

     (iv) Returned goods

       The quantity of goods sold and delivered to customers that have to be returned is an
        important factor in the vehicle trip generation and vehicle kilometres. Returns can be
        necessary for several reasons including: goods are damaged/faulty/wrong size/wrong item;
        customer decides they do not want the goods after having received them (some retailers
        allow returns in these circumstances).

     (v) Delivery time constraints and need for customer to be present

       Delivery time constraints – as noted by Cairns (1999) the tighter the delivery time
        constraints for making home deliveries, the greater the number of vans and van trips that will
        be required.
       The customer may not be at home to receive the delivery when the vehicle arrives and it may
        be necessary for the vehicle to make another attempt to deliver the goods at a later date. In
        the case of Dell Computers, for example, when its home delivery system commenced, 60-
        70% of orders had to be redelivered as the customer was not there to receive it. Dell has
        since introduced a system in which the customer is telephoned before the van is despatched
        to ensure they are in. This has helped to reduce redeliveries to 3% (Clarke, 1998). However
        most companies performing home deliveries do not currently use this system. The problem
        of customers not being at home to receive deliveries is more common for non-food deliveries
        as grocery customers tend to be informed of delivery times.

     (vi) Location of distribution depot

       Location from which home delivery trips are made – if, as assumed in the models, home
        deliveries are despatched locally to customers’ homes, then geographical distance from point
        of despatch to customers’ homes will be similar to the distances previously travelled to shops
        by customers in their cars (in fact, average trip distance for home deliveries will be shorter
        than for customers using their cars as the vans will perform multi-drop rounds). However, if
        the point of despatch for home deliveries is a significant distance from customers’ homes
        average trip lengths could in fact rise, especially if the drop density is low. This is more
        likely to happen for non-food rather than food deliveries, as food deliveries tend to be made
        from local supermarkets.

     Modelling work that included all these factors would certainly produce less favourable reductions
in vehicle trips and vehicle kilometres than the studies described earlier. For instance, let us consider
the case of shoppers who previously drove to a shop by car but who switch to using a home shopping
service and receive van deliveries. These shoppers may use some or all of the time savings derived
from home shopping to make additional car trips for other purposes. These could include, for example,
additional leisure trips to sports centres, cinemas or restaurants, or visits to friends and relatives. Data
from the UK National Travel Survey (various years) indicates that the total number of journeys that
people make by all modes has tended to remain relatively constant over time (endnote 1). This may

                                                    17
indicate that people’s propensity to travel may well result in trip substitution as a result of home
shopping.

     Shopping trips tend to have shorter trip lengths than many of these other potential journey
purposes. For example average shopping journey lengths in 1993/5 were 8.5 km compared with
17.1 km for journeys to visit friends at private homes, 10.8 km to visit friends elsewhere, 16.1 km for
entertainment and public activities and 11.1 km to participate in sport (DETR, 1996 and 1999).
Therefore, the substitution of a car-based shopping trip for a car trip with another purpose may well
result in an increase in the vehicle kilometres travelled per trip.

     However, regardless of precisely these trips are traded-off it is likely that home delivery will
result in increases in the number of goods vehicle trips in residential areas. These operations could
impose a wide range of other environmental and social impacts which may be particularly
problematical in residential areas. Section 5 considers vehicle activity for various sizes of city while
Section 6 goes on to discuss the environmental impacts arising from increased vehicle deliveries in
residential areas of towns and cities.




         6. CITY SIZE, POPULATION DENSITY AND UPTAKE OF E-COMMERCE:
                IMPLICATIONS FOR COMMERCIAL VEHICLE ACTIVITY



    Several factors will determine the number of home deliveries in a given urban area, among the
most important are:

        Population density of urban area
        Order/delivery frequency
        Number of companies offering home deliveries
        Market penetration of home shopping

     Each of these four factors is discussed in more detail blow.

1) Population density: the lower the population density, the greater the inter-drop distance (i.e. the
   average distance between each delivery), and hence the greater the number of vehicles required
   and vehicle trips and kilometres generated. The greater the physical size of the city, the greater the
   inter-drop distance, all other things being equal. The higher the population of the city, the greater
   the likelihood that the city will be able to support home delivery services of several companies
   (i.e. the greater customer base will increase the number of home delivery services it is economic to
   operate and hence the degree of competition).

2) Order frequency: the higher the order frequency, the greater the delivery density of addresses to
   be served and hence the lower the inter-delivery distance, thereby increasing the number of
   deliveries a vehicle could make in a day. However, the total number of vehicles required may be
   greater due to the number of premises needing to receive deliveries each day. It is also important
   to compare order frequency used by customer before and after any change in behaviour resulting



                                                   18
    from e-commerce and home delivery – if order frequency increases then this puts more pressure
    on the transport/distribution system.

3) Market penetration: Low market penetration for e-commerce and home delivery will lead to
   greater inter-drop distances and hence the greater the number of vehicles required and vehicle trips
   and kilometres generated.

4) Number of companies offering home delivery services: In the short term, the greater the
   number of companies offering home delivery services, the greater the number of vehicles
   operating in the city (with relatively poorer load factors) and hence the greater the trip generation
   and kilometres driven (with different companies' vehicles working in the same geographical area).

      The information in the preceding section can be used to provide an indication of the possible
changes in vehicle traffic that could result from a significant increase in e-commerce and home
delivery for both grocery and non-grocery. In the following table (Table 5) the potential for additional
home delivery trips is examined for two different hypothetical cities: a city of 200,000 people and a
city of 1 million people.

      In order to consider the number of vehicle trips and the distances covered, a series of assumptions
must be made; these assumptions are stated at the end of the paper. However it is important to notes
that in order to model a significant growth in e-commerce and home delivery it has been assumed that:
(i) 20% of households receive home deliveries of their groceries on a weekly basis, (ii) all households
receive a weekly parcel delivery (i.e. non-grocery).


   Table 5. Implications for trip numbers and vehicle distance of e-commerce home delivery

                                     Total           Vehicles         Distance per       Distance for
                                 deliveries per    operating per       vehicle per       all vehicles
                                      day              day              day (km)        per year (km)
 200 000 population city
 Grocery home deliveries              2 381               45                23             370 981
 Non-grocery home                    11 905               78                27             731 852
 deliveries
 All home deliveries                 14 286              123                 -           1 102 833

 1 000 000 population city
 Grocery home deliveries             11 905              226                23           1 854 588
 Non-grocery home                    59 524              406                40           5 717 989
 deliveries
 All home deliveries                 71 429              632                 -           7,572,576

 Key assumptions:
 Population density in both cities of 3,000 people per square km
 2.4 persons per household
 20% of households receive one grocery home delivery each week
 100% of households receive one non-grocery home delivery each week
 (See notes at end of paper for full assumptions)



                                                   19
     There are several implications that emerge from Table 6:

     The additional home delivery vehicle trips and distance covered each year are considerable
(almost 630 vans or small trucks performing 7.6 million vehicle kilometres each year in the city of 1
million population and approximately 120 vehicles performing 1.1 million vehicle kilometres in the
200,000 population city).

     However when compared to the total urban traffic levels and even the total urban commercial
vehicle traffic levels these are likely to represent relatively small increases. This proportion will of
course be dependent on the scale of market penetration and order frequency of e-commerce and home
delivery. But, even if the overall effect on urban traffic levels is relatively small, the location of this
vehicle activity is important. It will be mostly taking place in residential areas, where traditionally
commercial vehicle activity has been very limited.

     The extra vehicle trips and distance may be partly or wholly offset by the reduction in car trips
that may occur because heavy grocery shopping is delivered to the home (see earlier discussion in
Section 4.2).

      The population density of the city will affect the operational efficiency of the delivery round. In
the example we have assumed that the two cities have identical population densities. However, in
reality it is likely that a city of one million people is likely to have a higher density of settlement than
one of 200,000. As previously mentioned, higher population density would reduce distance between
each delivery address. However a higher population density city is likely to have lower average traffic
speeds and also present more parking difficulties to drivers.

      In addition to the factors discussed above there are several other factors that can affect the
efficiency of the e-commerce home delivery operation:

       size of vehicle/number of loads it can carry in one trip;
       delivery arrangements offered (e.g. is delivery just to front door into fridge);
       how long it takes to pick loads and make each delivery during round (is it easy for driver to
        locate load in back of vehicle, is it all in one compartment or several etc.);
       whether delivery firm can schedule properties in close proximity to each other to accept
        delivery on same day;
       hours available for delivery at households (affected by whether person has to be present to
        accept delivery);
       type of property delivered to (which is likely to influence parking conditions and distance
        driver has to walk from vehicle to delivery point);
       parking conditions at point of delivery (how close to the delivery point is the driver able to
        park);
       driving speed (depends on traffic levels on the roads used, and difficulty experienced
        negotiating particular types of roads such as narrow residential streets).

     Clearly the performance and impact of home delivery operations will also depend on the specific
local conditions in the urban area where the deliveries are to be made. For example, outer suburbs of
large cities are likely to offer the opportunity of higher operational efficiency to delivery firms due to
higher average traffic speeds and fewer parking problems than central and inner urban areas. The
prevailing parking conditions in any part of an urban area will be dependent on car ownership rates,



                                                    20
the types of residential properties and whether they have off-street parking spaces, and the land use
patterns in the vicinity.




                             7. POLICY ISSUES AND QUESTIONS




7.1.     Environmental and social impacts of home deliveries

      Home deliveries have environmental and social impacts that differ significantly from those of
other distribution operations. However there has been little research into these impacts other than the
studies of vehicle trips and vehicle kilometres already discussed. Many of these impacts arise from
geographical locations in which home deliveries are taking place, namely residential streets. Home
deliveries despatched from existing urban retail premises are also a new distribution phenomena, with
vehicles shuttling backwards and forwards between the shop and residential parts of the town or city
all day.

     There are several different aspects of home delivery operations that cause these social and
environmental impacts. Earlier sections of the paper have addressed the total number of vehicle trips,
average trip lengths and the vehicle kilometres travelled (which is the product of the average trip
length and the number of trips) for home deliveries. The following table (Table 6) lists other factors
associated with home delivery vehicle operations that are likely to determine their environmental and
social impact in residential areas, namely: (i) unloading in Residential Areas; (ii) the time at which
home delivery vehicle operations take place; (iii) the location of home delivery vehicle trip
generation; and (iv) speed/manner in which home delivery vehicles are driven.

     As well as imposing social and environmental impacts, home shopping deliveries can also result
in economic impacts. These can result from the delays occurring from congestion caused by home
delivery vehicles and also the problem of people taking time off work to receive home deliveries
which fail to arrive or arrive late. A recent study found that the average UK employee is losing two
days per year waiting at home for deliveries or repairmen, a third of which never arrive
(Abbey National, 1999).




                                                  21
      Table 6. Potential impacts in of growing e-commerce home delivery in residential areas

 (i) Unloading in residential areas

 Home delivery vehicles making deliveries in residential areas impact both traffic flow and the
 appearance/condition of the street. Two factors determine the nature and extent of the vehicle
 access/traffic flow problems caused by parked delivery vehicles in residential areas:

 Number of home delivery vehicles on-street in residential areas at busy times determined by:
 Number of customers using home delivery services and their order frequency;
 Extent to which retailers operate dedicated or shared home delivery systems;
 Possibility of drivers taking vehicles home each night and parking on-street.

 The period of time home delivery vehicles are on-street in residential areas determined by:
 Distance from parking space to delivery address;
 Whether or not delivery address has direct road connections (such as housing estates, etc.);
 Delivery addresses with point of delivery above ground floor (e.g. high rise flats, etc.);
 Checking/signing/putting away services offered;
 Incidences of home delivery vehicles being hemmed in by other parked cars.

 (ii) Time at which home delivery vehicle operations take place

 The time at which home deliveries are carried out has an important bearing on their impact, as this
 determines the quantity of parked vehicles and pedestrians they encounter, and the number of
 people in their homes who could be disturbed;
 Days and times when deliveries are offered (outside working hours, seven days a week preferable
 for delivery fulfilment but conflicts with vehicle nuisance and disturbance);
 Deliveries in the early morning/late night can result in noise disturbance (engine, opening and
 closing vehicle, radios, talking, etc.);
 Home deliveries tend to be made at times when the number of other parked vehicles is at its peak
 (i.e. early morning and evening).

 (iii) Location of home delivery vehicle trip generation

 Large land area will be required for depot facilities for home delivery vehicles;
 Large number of goods vehicle trips generated at and around urban home delivery facilities;
 Most home delivery trips are on residential roads (which are more sensitive than main roads).

 (iv) Speed/manner in which home delivery vehicles are driven

 Tight delivery windows may encourage inappropriate driving;
 Additional traffic hazards on residential roads – children playing, people crossing streets, etc.




7.2       Further discussion of parking issues in residential streets

      It is worth expanding on the problems experienced and caused by home delivery vehicles trying
to find parking places at UK addresses that they need to deliver to. A survey of local authorities by
TRL has shown that parking in residential areas is by far the most common parking problem
experienced by drivers. The study estimated that the number of cars parked on-street in residential
areas increased from 1.2 million in 1966 to 4.8 million in 1989. It was forecast that, taking into
account traffic forecasts and the development of new dwellings, the number of cars parked on-street


                                                    22
would increase by 50-138% between 1989 and 2025 (Balcombe and York, 1993). The opportunity to
create additional parking space in many residential areas is extremely limited as much of the housing
stock pre-dates mass car ownership (Valleley, 1997). The English House Condition Survey published
by the Department of the Environment in 1988 showed that terraced housing and flats accounted for
nearly half of the UK housing stock. In this study, 39% of the houses studied had no off-street parking
facilities (Balcombe and York, 1993).

     It is therefore often difficult for home delivery drivers to find somewhere to park near to the
delivery address. Home delivery vehicles have to find on-street parking places in residential areas and
these streets often have few, if any, available on-street spaces during the early morning and late
afternoon/evening.

     In Inner London, for example, cars are parked on-street in more than 70% of vehicle trips that
end at the driver’s home. In Liverpool the figure is 60%, in outer London the figure is 46%, and in
other UK urban areas with a population over 250,000 the figure is 40% (Valleley, 1997).

     Survey work by TRL (Balcombe and York, 1993) in eight UK urban locations found that on-
street parking spaces ranged from 0.08 to 1.1 spaces per household across the sites, with an overall
average of 0.66 spaces per household. This is the case in many residential areas in UK towns and cities
with the number of resident’s vehicles, which require on-street parking outweighing the number of
parking spaces. This work by TRL also found that at one of the eight locations studied 50% of
residents have to park their vehicles more than 50 metres from their homes due to lack of on-street
space. Rates varied by site between 10% and 35% at the other sites. Such distances from vehicle to
door would severely hamper the efficiency of home delivery operations. This could encourage
delivery drivers to park illegally outside homes that they are delivering to, thereby causing vehicle
access and traffic flow problems.

     In the TRL study carried out in 1991-92 many residents identified that car parking in their street
made deliveries to their home difficult. The proportion of car owners who parked their cars on-street
varied from 25% at one location to as many as 80% at another (Balcombe and York, 1993).

     As previously noted, the times at which home deliveries take place tend to conflict with the times
at which residents’ vehicles are parked outside their homes. The peak in departure of parked cars from
residential areas takes place between approximately 7.00 am and 9.30 am. Arrivals of cars in
residential areas looking for parking places peaks between 4.00 pm and 7.30 pm. The outcome of
these vehicle arrival and departure times is that the accumulation of parked vehicles in residential
areas builds to significant levels by 5.00 pm onwards and remains high until approximately 7.30 am.

     Delivery vehicles are likely to make these already busy streets even busier. Parked vehicles have
three key effects on flow conditions on the road:

      Parked vehicles reduce the effective road width. On residential roads the reduction in width
       usually causes conflicts between vehicles moving in opposite directions.
      Vehicles entering and leaving parking spaces interrupt traffic flow.
      Illegal stopping and parking reduces the space for moving traffic, and often prevents other
       vehicles from passing the illegally parked vehicle for the duration of its stay.




                                                  23
7.3.     The potential importance of legislation

      Three categories of legislation are important with respect to e-commerce deliveries: product-
related legislation, vehicle operating legislation and urban land use planning legislation.

     Examples of product-related legislation include health and safety regulations that set temperature
regimes required for many food products and the monitoring regimes required to ensure that these
temperatures are maintained. Legislation also governs how any dangerous goods can be transported.
Although not immediately obvious, several products commonly stocked by grocers, such as aerosols,
might be affected by this type of legislation and could require special attention.

      Vehicle operating legislation includes any controls that affect: the time at which deliveries can be
made (both in terms of vehicle access to the street concerned and unloading regulations in force on the
street); the times at which customers are permitted to visit collection and delivery points to collect
their goods, the size and/or weight of vehicles that can be used to make these deliveries.

      Urban land use planning policy can be used to control the number and location of home delivery
fulfilment facilities (and collection and delivery points) and the times at which home delivery vehicles
can operate at them. Policy makers can also decide whether there is a role for the urban authority in
the development and operation of such facilities, and whether they will be operated by one or many
companies.

     Many current policies are likely to result in making travel and transport more expensive. If these
policies make private trips in cars more expensive but make distribution trips relatively less costly
then perhaps this is a policy that would reinforce the potential benefits of e-commerce – on the other
hand if the policies make both private travel and distribution activities more expensive then there may
be a negative impact on e-commerce and the potential benefits could be lost. Deciding what is the
right policy is currently very difficult because the transport generation effects of e-commerce remain
unclear.




                                   8. CONCLUDING REMARKS



      It would seem likely that B2B e-commerce will continue to grow over the next five years and
beyond, however the rate of growth is difficult to predict. There is however, at present, far less
certainty about the future of B2C e-commerce. Its future will be closely tied to the issue of whether
B2C e-commerce proves to be profitable in the next few years. Therefore B2C e-commerce could
either continue to grow (i.e. a continuation of the current trend) or, alternatively, it may reach a peak
and then begin to diminish, with it only continuing in certain niche sectors in which it achieves
satisfactory profitability. For B2C e-commerce to prove profitable and appealing it will require very
efficient, reliable and low-cost freight transport services. In addition the costs for order picking will
need to be low – this could be a particular barrier to e-commerce grocery/food services. While freight
transport services tend to be relatively low-cost, it remains to be seen whether these services can
achieve the necessary level of efficiency and reliability that will be required by customers with ever-
increasing service level expectations.



                                                   24
      Efficiency, cost and reliability of freight transport services will also be strongly influenced by
trends in traffic congestion. Again there are many uncertainties - for example, if urban road pricing
becomes widespread by 2010 then the efficiency of goods deliveries within cities could be
significantly improved (assuming the road user charging has the effect of significantly reducing car
trips). However, if congestion worsens then a larger total fleet of vehicles will be required in order to
achieve the same amount of work as that being performed today.

     In thinking about the logistics costs of B2C e-commerce, it is important to remember that the
costs associated with order picking and delivery to the customer’s home are not new costs. These
activities and costs existed prior to the introduction of e-commerce. The difference in an e-commerce
environment is that rather than these activities and costs being borne by the customer they are now
borne by the e-commerce company. Therefore, e-commerce involves a redistribution of costs rather
than the creation of new costs. In fact, it may be the case that order picking and transport costs are
lower when performed by or on behalf of an e-commerce company than when carried out by the
consumer (especially when taking into account the customer’s value of time). The concern for e-
commerce companies is whether these costs are recoverable (i.e. whether the customer is prepared to
pay a price that fully covers the cost of these activities).

      This paper has illustrated that there are a number of traffic, environmental and social impacts
associated with home deliveries. In terms of traffic generation, it is possible that home shopping could
lead to reductions in vehicle trips and vehicle kilometres travelled, but this is highly dependent on the
efficiency with which home delivery systems are organised and whether customers carry out other
non-shopping vehicle trips with the time they save from not having to travel to shops. Care therefore
needs to be taken in modelling the traffic generation effects of home shopping.

     There is a need to better understand: (i) the total weight and volume of different categories of
products that flow into residential properties, and (ii) the vehicle trips (by cars and commercial
vehicles) carried out in order to move these products to residential households. Food is likely to
account for a significant proportion of the total weight and volume of product flowing to residential
properties each year (flows out of the home are mainly waste which would include packaging). The
importance of different categories of goods flow over the doorstep in terms of weight/volume, is not
necessarily the same as the importance in terms of trip generation. For example, food shopping is
often performed in a single trip per week for households with children and car, while there may well
be several person or vehicle trips for other types of shopping. Therefore food shopping may be more
important in weight/volume terms than in trip generation terms for households.

      One of the main issues associated with the environmental and social impacts of home deliveries
is the location in which the delivery vehicles will be operating, namely residential streets. While the
number of home deliveries remain relatively low, these impacts may not be very pronounced.
However, if home deliveries increase significantly (and there is every possibility that they will) these
impacts will become far more severe. As well as causing social and environmental impacts for
residents, home deliveries will also cause major problems for the companies performing these trips as
the delivery efficiency could fall sharply and the operational costs could rise significantly. Clearly
there is a need for policy makers and companies to give more thought to how best to overcome some
of the problems associated with home delivery. If this thought is applied now, it will be possible to
generate sensible solutions before the problems escalate, for example:

    Companies could work together to consolidate deliveries for particular streets or areas, thereby
improving vehicle load factors, increasing drop densities and reducing the number of vehicles that
need to enter the street. This could prove especially effective for non-food deliveries.


                                                   25
     Companies could use environmentally cleaner and quieter vehicles to reduce some of the
pollutant and noise impacts caused. Where appropriate, bicycles with trailers could be used instead of
goods vehicles or as part of a joint operation with conventional distribution vehicles (this approach is
already used by some companies).

      Customers could be encouraged to install secure delivery boxes outside their homes so that
deliveries could be made at any time of day regardless of whether the customer is at home. However
this approach could only be used for smaller deliveries, and not all properties have space for such
facilities. It also raises the problem of how customer signatures would be obtained.

      Deliveries could be made to collection points such as filling stations, high street collection points,
rail stations or workplaces rather than to customers’ homes. This would help to reduce the need for
delivery vehicles to operate on residential roads. It would also assist in reducing delivery failures due
to the customer not being at home. It would however be likely to require both a delivery vehicle trip
and a car trip, so there is the possibility of greater trip generation than in the home delivery system.
Total trip length may also increase depending on location of collection point relative to customers’
home and how customer makes these collection trips (i.e. whether collection of goods is the sole trip
purpose or if collection is carried out as part of a combined trip).

      Companies could put in place appropriate delivery charges that reflect the quantity ordered and
the speed of order fulfilment. Without such an approach there may well be a rapid increase in vehicle
trips involving the delivery of minimal quantities of goods.

     In addressing appropriate regulations to deal with externalities imposed by commercial vehicle
operations, policy makers should consider concentrating on policy measures related to specific
outcomes rather than measures that insist on the use of particular technologies (e.g. specific power
sources or vehicle designs). By acting in this way there are likely to be more innovative and creative
solutions.

     Clearly the performance and impact of home delivery operations will also depend on the specific
local conditions in the urban area where the deliveries are to be made. For example, outer suburbs of
large cities are likely to offer the opportunity of higher operational efficiency to delivery firms due to
higher average traffic speeds and fewer parking problems than central and inner urban areas. The
prevailing parking conditions in any part of an urban area will be dependent on car ownership rates,
the types of residential properties and whether they have off-street parking spaces, and the land use
patterns in the vicinity.

      When examining the social and environmental impacts of B2C e-commerce, transport activity it
is important to make sure that a comparison is made with the impacts of the system it has replaced, as
this system will also have imposed environmental impacts. Although this is a very obvious point, e-
commerce is too often thought of as an entirely new activity that can be assessed in isolation. The
transport activity in the entire supply chain for e-commerce needs to be compared with the transport in
the traditional retailing system it has replaced. In some cases these supply chains will only differ
between the retailer's shop and the customer's home (in terms of how the movement between shop and
home takes place with, for example, a van trip replacing a car trip). However, in other cases far greater
divergence may occur upstream in the supply chain.




                                                    26
                                              NOTES


1.   Data from the UK National Travel Survey (various years) indicates that the total number of
     journeys that people make by all modes has tended to remain relatively constant over time:
     1024 journeys per person in 1985-86, 1091 journeys in 1989-91, 1053 journeys in 1993-95,
     1051 journeys in 1996-98.

2.   Assumptions made in Table 6:

     The full assumptions made in the calculations shown in Table 6 are as follows:

        population density in both cities of 3,000 people per square km
        2.4 persons per household
        20% of households receive one grocery home delivery each week
        100% of households receive one non-grocery home delivery each week
        Delivery addresses are grouped together, so that the distance between deliveries is minimised
        12 grocery deliveries per vehicle
        150 grocery deliveries per vehicle
        Loading time of 20 minutes at start of round
        Unloading time of 15 minutes at end of round
        Stem distance for non-grocery deliveries in 1 million pop. city (round trip) of 26 km
        Stem distance for grocery deliveries in 1 million pop. city (round trip) of 12 km
        Stem distance for non-grocery deliveries in 200,000 pop. city (round trip) of 12 km
        Stem distance for grocery deliveries in 200,000 pop. city (round trip) of 12 km
        Time taken to pick grocery delivery from vehicle, make delivery and return to vehicle of
         7 minutes
        Time taken to pick non-grocery delivery from vehicle, make delivery and return to vehicle of
         3.5 minutes
        Average vehicle speed on stem journey of 25 km per hour
        Average vehicle speed between deliveries of 5 km per hour (takes account of finding parking
         space)
        Winding factor on roads of 0.3
        Home deliveries are made seven days per week
        Vehicles operating 13 hours per day, 350 days per year




                                                 27
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                                                28
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