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v.4, n.2, p. 117-129, ago. 1997
BUSINESS LOGISTICS
IMPORTANCE
AND SOME RESEARCH
OPPORTUNITIES
Invited Paper
Ronald H. Ballou
Department of Operations Research and Operations
Management
Weatherhead School of Management
Case Western Reserve University
Cleveland, Ohio U.S.A.
Abstract
Business logistics is defined and reasons are given as to why it is a vital area of
management. Political and economic trends are highlighted to show that it is even increasing
in importance. Current research in business logistics is discussed with a focus on the design
of the logistics network as it is aided by computer modeling. Research opportunities are
identified to both improve modeling for network design and better specify the information
inputs to the design process.
Key words: business logistics, survey, logistics network design.
1. Introduction
upply chain management, physical
distribution, materials management,
and even rhocrematics are names that
have been given to the field of business
logistics. Regardless of the name, business
logistics is a vital area of management
within most firms, whether they are
manufacturing or service firms. Logistics
has been defined by the Council of Logistics
Management as
...the process of planning, implementing,
and controlling the efficient, cost-
effective flow and storage of raw
materials, in-process inventory, finished
goods and related information from point
of origin to point of consumption for the
purpose of conforming to customer
requirements.
S
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The stated mission for business logistics is
...to get the right goods or services to the
right place, at the right time, and in the
desired condition, while making the
greatest contribution to the firm.
This mission is accomplished by careful
management of those activities that
significantly contribute to logistics customer
service and that are in cost tradeoff with
each other. The typical logistics activities
are shown in Figure 1.
Physical distribution
Physical supply
(Materials management)
Business logistics
Sources of
supply
Plants/
operations
Customers
• Transportation
• Inventory maintenance
• Order processing
• Acquistion
• Protective packaging
• Warehousing
• Materials handling
• Information maintenance
• Transportation
• Inventory maintenance
• Order processing
• Product scheduling
• Protective packaging
• Warehousing
• Materials handling
• Information maintenance
Figure 1 - Typical Activities in a Firm’s Immediate Supply Chain
2. Importance of Business Logistics
ogistics is important because it
creates valuevalue for customers
and suppliers of the firm, and value
for the firm’s stakeholders. Value in
logistics is expressed in terms of time and
place. Products and services have little or no
value unless they are in the possession of
customers when (time) and where (place)
they wish to consume them. To many firms
throughout the world, logistics has become
an increasingly important value-adding
process for a number of reasons.
2.1 Costs Are Significant
According to the International Monetary
Fund, logistics costs average about 12
percent of the world’s gross domestic
product. Examples of logistics costs within
individual economies show variation. The
United Kingdom has logistics costs of 16
percent of sales (MURPHY, 1972, p. 7).
Japan has physical distribution costs of 26.5
percent of sales (KOBAYASHI, 1973, p. 9).
Australia has estimated average physical
distribution costs of 14.1 percent of sales
(STEPHENSON, 1975). In the European
Economic Community, logistics costs were
21 percent on a value added basis
(KEARNEY, 1987). In the United States,
logistics costs for the typical firm are about
10.5 percent of sales (DAVIS & DRUMM,
1995). Depending on the particular industry,
logistics costs may range from 4 percent of
sales (pharmaceuticals) to over 30 percent of
sales (food and food products). It has been
noted that for many firms, after the cost of
goods sold, logistics represents the highest
cost of doing business.
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The economic forces of change are further
acting to alter logistics cost relationships and
force careful replanning of logistics systems
around the world. Trade barriers are falling
as free trade is encouraged in countries that
previously had strictly managed economies.
Tariffs are being eliminated to allow the free
flow of goods across political boundaries,
giving firms the opportunity to reposition
their logistics networks for lower costs and
higher customer service. Finally, the world
economies seem to be on a wave of
economic deregulation that will heighten
competition. Since transportation is
frequently a target for deregulation, logistics
system costs will be affected.
2.2 Globalization of Industries
The trend is towards an integrated world
economy. Firms are seeking, or have
developed, global strategies where either
their products are designed for a world
market and they are produced wherever the
low-cost raw materials, components, and
labor can be found, or they simply produce
locally and sell internationally. In either
case, supply and distribution lines are
stretched, as compared with the producer
who wishes to manufacture and sell locally.
Not only has the trend occurred naturally by
firms seeking to cut costs or expand
markets, but it is also being encouraged by
political arrangements that promote trade.
Examples are the formation of the European
Economic Community (EC92), the signing
of the North America Free Trade Agreement
(NAFTA) between Canada, United States,
and Mexico, and the creation of a new
economic trade agreement among several
countries of South America (MERCOSUL).
Globalization/internationalization of in-
dustries everywhere will depend heavily on
logistics performance and costs, as
companies take more of a world view of
their operations. As this happens, logistics
takes on increased importance within the
firm since logistics costs, especially the
transportation component, become a
significant part of the total cost structure.
For example, if a firm seeks foreign
suppliers for the materials entering its
product or foreign locations to build its
products, the motivation is to increase profit.
Material and labor costs may be reduced, but
logistics costs are likely to increase due to
increased transportation and inventory costs.
The tradeoff, as shown in Figure 2, may lead
to higher profit by reducing materials, labor,
and overhead costs at the expense of
logistics costs and tariffs. Outsourcing adds
value, but it requires more careful
management of logistics costs and product
flow times in the supply channel.
2.3 Logistics is important to strategy
Firms spend a great deal of time finding
ways to differentiate their product offerings
from those of their competitors. When
management recognizes that logistics
impacts on a significant portion of a firm’s
costs and that the result of decisions made
about the supply chain yields different levels
of customer service, it is in a position to use
this information effectively to penetrate new
markets, increase market share, and increase
profits.
To illustrate, a company selling its
merchandise through a catalog has its
inventory and operations centralized at one
location in the country. It wishes to compete
effectively with retail stores operating in
local market areas. Although the company
benefits from low overhead, buying
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120
economies, and good product availability, it
was at a disadvantage in being time
responsive to customers. To overcome the
disadvantage, the company developed a
marketing strategy based primarily on
logistics. Delivery time and its variability
were at the heart of the strategy. First, a toll-
free telephone number and 24-hour order
taking were established so that customers
could place their orders free of charge any
time of the day or night. Next, orders were
filled the same day that they were received,
even as late as 6:30PM. Finally, orders were
shipped using an overnight delivery service
such as FedEx. The result was that
customers could place orders late in the day
and receive them at their home or business
by 10:30AM the next morning. The
company was able to compete effectively on
both price and service dimensions.
Profit
G & A
Marketing
Logistics
Overhead
Materials
Labor
Tariffs
Overhead
Materials
Labor
Logistics
Marketing
G & A
Profit
Domestic sources Foreign sources
Figure 2 - Economic Benefit of Sourcing from Low-Cost Offshore Locations Rather then
from Higher-Cost Local Suppliers - Source: “International Logistics: Battleground of the
‘90s” (Chicago: A.T. Kearney, 1988)
2.4 Logistics Is Key to Customer Service
Research over the years has shown that
logistics variables are dominant in the minds
of customers when they evaluate the service
offerings for a product; see STERLING &
LAMBERT (1989), HARRINGTON &
LAMBERT (1989), LALONDE &
ZINSZER (1976), MARR (1994), BARITZ
& ZISSMAN (1983), JACKSON et al.
(1986). Frequently, one-half of the customer
service variables are logistics related and
delivery time typically ranks the highest
among all service variables. Since customers
respond to a company’s service offerings
with their patronage, revenues are a
frequently determined by logistics variables.
2.5 Customers Increasingly Want Quick Customized Response
Customers have been increasingly
sensitized to expect quick response to their
demands. Fast food restaurants, overnight
package delivery, and instant access to
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121
information on the Internet are examples of
what customers might anticipate in the way
of service from a wide range of product and
service offerings. In addition, improved
information technology and flexible manu-
facturing systems have led the marketplace
towards mass customization. Rather than
consumers having to accept the “one size
fits all” philosophy in their purchases,
suppliers are increasingly offering products
that meet individual customer needs. This
has placed growing demands on production
and logistics systems to achieve ever higher
performance levels.
3. Status of Logistics Research
ith the growing significance of
logistics among the other
activities of the firm, research
has been conducted over a broad front to
support and enhance logistics management.
Research has ranged from quantitative
modeling for decision making to
philosophical works that set the tone for
good logistics management. Within this
range, one of the most important research
areas has been the strategic planning of the
logistics network. Network design involves
establishing customer service levels, the
deployment of inventories, the location of
facilities, and the selection of the modes of
transportation. It sets the structure that
determines the overall level of logistics cost
and customer service. Because it impacts on
a significant level of company costs and it
affects the revenue-generating capabilities of
the firm, logistics network design is
typically of top management concern.
Experience shows that good network
redesign can save a company between 5 and
15 percent of its annual logistics costs.
Logistics network design can be viewed
as a triangle of logistics strategy (see Figure
3). Logistics customer service is the goal
and the result of decisions made about the
network design. Establishing the level of
customer service to be achieved in turn
defines the revenues to be generated through
logistics activities. It also defines the
combined effect of three structural
variableslocation strategy, inventory
strategy, and transportation strategy.
Customer
service goals
•Modes of
transport
•Carrier routing/
scheduling
•Shipment size/
consolidation
Transport Strategy
•Inventory
levels
•Deployment
of inventories
•Control
methods
Inventory Strategy
•Number, size, and location
of facilities
•Assignment of stocking
points to sourcing points
•Assignment of demand to
stocking points or sourcing
points
•Private/public warehousing
Location Strategy
Figure 3 - The Triangle of Logistics Strategy
W
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The three strategies are in tradeoff with
each other. That is, a good location strategy
is dependent on the manner in which
inventories are managed and on the resulting
inventory levels, and on the transportation
service selected. Inventory levels are
dependent on the number and location of
facilities as well as the transportation service
selected. And so the interdependence goes.
Hence, a triangle of logistics strategy.
Logistics network design is based on
three objectivescost minimization, capital
minimization, and logistics customer service
maximization. Not all of these objectives
can be achieved simultaneously since they
may be in conflict. For example, minimizing
costs and simultaneously maximizing
service are incompatible.
Research through the years, coupled with
advancements in computer technology, has
provided the capability to design logistics
networks with the aid of mathematical
modeling. This modeling is now so popular
with consultants and managers that few
networks are designed without the aid of
such sophisticated tools (BALLOU &
MASTERS, 1993, p. 83). The logistics
network design problem is captured in the
abstract diagram of Figure 4. The strategic
questions revolve around locating the
facilities intermediate to source and demand
points, determining the modes of
transportation, projecting the amount of
aggregate inventory in the logistics system,
and controlling the design impact on
logistics customer service.
Supply
Demand
L
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Destination nodes
Customers
Retail
outlets
Warehouses
Origin nodes
Raw material
sources
Plants
Intermediate nodes
General direction of information flow
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Figure 4 - An Abstract Diagram for a Logistics Network
Network models used commercially are
generally of two types: mathematical
programming and computer simulation.
These models follow the two basic
characteristics of the network planning
problemthe spatial and the temporal
orientations (HESKETT, 1966). Spatially
(geographical) based models have been
much more popular than temporally (time)
based ones.
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3.1 Spatial Models
Spatial models have primarily been used
to locate the facilities in the logistics network
on a geographical plane. They answer such
questions as: How many facilities are needed,
where should they be located, and what size
should they be? Logistics-related costs are
minimized, or profits maximized, subject to
geographical constraints on customer service
and restrictions on facility capacities.
A survey of commercial-grade location
model developers showed that deterministic
approaches such as linear programming,
mixed integer programming and heuristic
methods were the methods of choice
(BALLOU & MASTERS, 1993). Continuous
location methods (e.g., center-of-gravity
approaches) have been relegated to offering
suggestions for possible locations within the
deterministic algorithms. The reason for this
would seem to be that the deterministic
methods can handle most of the costs of
location with a great deal of realism and also
that restrictions can be introduced that are
not easily handled within the continuous
framework. Much of the development in the
last 20 years has focused on making location
models more user-friendly, adding features
that enhance communication, and adding
programs that facilitate data conversion to
model format. Extended solution capabili-
ties, such as adding more echelons to the
network and more facilities, source points,
and customers to be analyzed, have resulted
primarily from greater memory and
computational speed of computers. Basic
algorithmic development remains slow since
the mid-1970s (for highlights on location
model evolution in the last two decades, see
GEOFFRION & POWERS (1995)),
however, facility location remains an active
area of research, probably because manage-
ment continues to use these models and they
help solve such an important problem to top
management.
3.2 Temporal Models
When time becomes the important
variable to be managed, as is the case when
controlling inventories, choosing a trans-
portation service, or scheduling product
flow, computer simulation has been a good
model choice. Such models permit the flow
of product in the supply channel to be
observed in simulated time. Complex
product flow interactions among activities
taking place between multiple echelons can
be observed. Inventory levels, vehicle
loading and shipping patterns, out-of-stock
percentages and cost profiles are a few of
the results obtained when the pattern of
customer orders is placed on the simulated
system. The extensive information detail for
logistics channel simulators is generally not
available in spatial models where products
are grouped, costs are averaged, and the time
frame for analysis is from a month to a year.
A few simulations specifically designed
for logistics analysis have appeared over the
years (BOWERSOX et al. (1972), RONEN
(1988)). However, they have not been used
as extensively as spatial models. It also may
be the case that the general computer
simulation packages that can be adapted to
deal with logistics problems fill the need.
Little research is being conducted to develop
channel simulators specifically designed for
logistics planning. Significant data
requirements, lack of understanding of the
value of simulation results compared to
spatial model results, and limited promotion
of the methodology are some of the reasons
for the underutilization of this important
methodology.
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4. Research Opportunities
he spatial and temporal aspects of
logistics network design have not
been effectively merged into one
solution platform, although it is possible to
run such models separately and sequentially
to converge on network solutions that satisfy
both strategic and tactical dimensions.
Neither a location model nor a channel
simulator model by itself is a complete
model for logistics network design. Location
models rely on generalized inventory-
throughput relationships and assumptions
about the methods of transportation used as
inputs and give good results on location
issues. On the other hand, channel
simulators take facility locations as inputs
and provide good results on inventory and
transportation issues. The two models are
inter-related, as shown in Figure 5. Research
should be directed at bringing spatial and
temporal dimensions together, probably
within the location model framework since
it is the most popular modeling platform.
Location
model
Channel
simulator
Facility locations
Inventory/throughput
relationships
Transport modes
Figure 5 - Inter-relationship Between Location and Channel Simulator Models
4.1 Logistics Customer Service
Perhaps the research needed most in
logistics network design is to find methods
for determining the relationship between the
level of logistics customer service provided
and the revenues generated by the firm.
Current practice is to treat customer service
as a constraint on network design and
minimize costs subject to the constraint.
However, the preferred practice is to
maximize profit when both revenue and cost
are variables, since the customer service
level will be set at optimal based on
economic factors. The network design can
be quite different depending on the objective
used, that is, profit maximization versus cost
minimization.
Developing the revenue-logistics service
relationship for a particular firm can be as
difficult as determining the effectiveness of
its advertising budget or other sales efforts.
Some methods have been proposed, but
none seems very satisfactory (BALLOU,
1992, pp. 94-96). For location models, the
revenue-service relationship can be
expressed as a price function where price
declines as customers are farther from their
sourcing points. For channel simulators, the
appropriate variable might be customer
order cycle time. Research could begin with
the methods used for similar problems in
marketing.
T
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4.2 Inventory
Inventory represents a key economic
factor in network design that forces
consolidation of inventories into a small
number of locations. There has been
substantial research over the years on
controlling individual product item
inventory levels but relatively little about
estimating inventory levels when there is
more than one product item taken at a time.
The practical concerns of network design
require that many items be collected into
product families and dealt with as an
aggregate group. What is needed is to be
able to estimate inventory levels as demand
is assigned to facilities. The famous square-
root rule (for a discussion of the square-root
rule, see BALLOU (1992, pp. 447-449)) is a
good, first approximation of inventory
effects in network design which has been
refined to include safety stock effects
(BALLOU, 1981). However, these rules are
generally based on inventory control
procedures formulated around the economic
order concept. Estimating inventory levels
based on other rules found in practice would
be beneficial.
The relationship between inventory levels
in facilities and the allocated demand to
them is frequently nonlinear and concave.
Since the solution platform for location
models is typically linear or mixed integer
programming, the nonlinear relationship
causes computational difficulties. Better
methods, besides decomposing the function
into piecewise linear elements, are needed
so that the inventory relationship can easily
be incorporated into the computational
process. Too often, the inventory
consolidation effects of network design are
computed outside of the solution process to
avoid these computational difficulties.
4.3 Transportation
Two transportation problems arise in
logistics network planning as a result of
using mathematical programming to design
the network. These are the handling of
private trucking and the selection of
transportation services.
When using a linear programming-based
solution method for network planning, it is
assumed that transportation between points
on the network is one-way. For-hire
transportation fits this assumption since
rates are quoted between two specified
points. However, when transportation
involves more than one stop before the
delivery vehicle returns to its depot,
transportation costs may be in error. Since
equivalent rates must be calculated for each
transport leg from the multiple-stop routes,
the stops (customers) on the route and the
depot (facility) to which they are assigned
must be known. However, assigning
customers to facilities is the result of the
location analysis. Rates are a result of
customer allocation and customer allocation
depends on rates. Therefore, research needs
to be conducted on combining transport
routing and location-allocation analysis.
In a channel simulator, the transportation
service can be selected based on the size and
characteristics of the order when it is
presented for delivery. In a locator where
products are grouped into families of items
and transportation rates are constructed
based on average shipment size,
transportation modes are represented within
the rate data. It is then assumed that the
mode mix remains constant as reallocation
of demand occurs among facilities during
optimization. Since the various modes used
are combined into a weighted rate for
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product volume flowing from a facility, the
percentage (weights) of shipments by the
various modes should change as the network
design is being calculated. This
interdependence is an area for research in
location models.
4.4 Location
The use of location modeling has been a
dominant approach for logistics network
design. At this point in time, the
methodology which is based on linear
programming concepts is well refined and
quite robust in handling a wide range of
practical network design problems.
Problems having numerous product families,
thousands of customers, hundreds of
intermediate facilities, and 4 or more
network echelons are routinely solved. Most
of the relevant costs can be handled by the
methodology. However, designers are
always wanting to press the model’s limits
which leaves opportunities for further
research. Several of these are discussed
below.
A problem not easily handled within the
standard network model occurs when
vendors, as opposed to plants, supply the
network. Plants are usually represented by a
location that can supply product up to its
limit of capacity. In contrast, vendors supply
only a portion of their total capacity to a
particular firm’s network and ship to all
intermediate facilities a percentage of that
firm’s demand. In addition, a vendor may
ship to the network from a number of
locations. A network design involving many
vendors generally takes place for retail
oriented companies. A network design
problem occurs when optimization
methodology will allocate to some vendors
and not to others according to their costs and
capacity limitations. The allocation results
do not represent the actual flow patterns for
the vendors. Adjustments are needed in the
computational methodology.
Although logistics networks are designed
primarily with the aid of mixed integer
programming and heuristic (deterministic)
procedures (BALLOU & MASTERS, 1993),
there has been a resurgence of interest in
continuous location methods such as the
center-of-gravity approach to location. Users
seem to like the feature that the continuous
location model will give locational choices
without preselection of candidate facilities,
as is the case for deterministic methods. It is
well known that it is difficult to obtain exact
solutions to continuous models having
multiple facilities and a rich environment of
logistics costs and constraints. Currently,
continuous location models provide
candidate locations for deterministic models
to further evaluate. Research might be
directed at improving the continuous
location models for commercial-grade use
and integrating them into the deterministic
methods for facility location.
4.5 Data Issues
Much can be said about the need for
improved understanding of the data
relationships that are presented to the
network analyzers. Whereas a great deal of
research has been conducted on the methods
by which to design the network, very little
attention has been given to data elements
that are the inputs to the design process. Yet,
the solution quality of the network design is
probably more sensitive to variations in data
inputs than differences among solution
methods. Consider some of the more
important data issues (for a general
discussion of the informational issues in
GESTÃO & PRODUÇÃO v.4, n.2, p. 117-129, ago. 1997
127
network design, see BALLOU (1987) and
BALLOU (1995)).
Transport rates can be presented to a
network model as specific rates by particular
mode between defined points in the
network. For practical-size problems, this
may involve millions of rates. Alternately,
transport rate curves can be developed that
can be used for estimating rates for various
distances from a facility. These rate curves
can be developed from a sample of the
actual rates and are usually a function of
distance alone. Although a linear
relationship between rates and distance work
well for the for-hire carriers, it is not clear
that it is the best fit for small package
shipments or full vehicle load rates. Non-
uniformly applied discounts and tariffs
potentially can distort the linear relationship.
Research to find good rate relationships and
project the error that is involved in such
estimating procedures is needed (BALLOU,
1991).
Costs associated with facilities are
available through accounting reports. For
network analysis, the costs need to be
separated into fixed, storage, and handling
categories. Since the separation is arbitrary,
the network design may be dramatically
influenced by the cost allocation. For
example, while one analyst may view such
costs as trash removal, fire protection, and
telephone charges as variable with the
volume flowing through the facility, others
may see these as fixed costs. Of course, the
number of facilities in a network may be
greatly influenced by this arbitrary allocation
of expenses. Expense allocation rules need
to be tested to show just how they affect
network design and developed to provide
reasonable and consistent treatment of these
facility expenses.
When thousands of customer locations
are involved in the network design, it is
practical to aggregate them into a smaller
number of geographical clusters. This
reduces the amount of data to be handled
and the computational and computer
memory requirements. Demand clustering
can result in errors when estimating the
transportation cost to customers, since the
basis for transportation rates is the center of
the clusters and not the actual location of
each customer. Research has shown the
number of clusters needed in a network
design problem to control the transport
costing error to a given percentage
(BALLOU, 1994). More research is needed
to find improved customer clustering
algorithms to minimize the costing error.
5. Concluding Comments
usiness logistics is a vital area of
management within most firms.
Costs are a significant portion of
sales, and logistics variables are often
dominant in the company’s customer service
mix. With trends that are occurring, such as
growing international trade, increasing
customers’ desire for quick customized
response, and dismantling of trade barriers, a
good logistics strategy has become ever
more critical to maintaining a competitive
edge and penetrating new markets.
Good design of the logistics network is
one of the keys to good logistics
performance. Great strides have been made
in using the computer and mathematical
models to construct these networks.
Research opportunities exist not only to
improve the methodology for solving
network designs, but also to further improve
the cost and customer service relationships
that are the inputs to the design process.
B
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References:
BALLOU, R.H.: “Information Considerations for
Logistics Network Planning”. International
Journal of Physical Distribution and Materials
Management, Vol. 17, No. 7, pp. 3-14, 1987.
BALLOU, R.H.: “Logistics Network Design:
Modeling and Informational Considerations”.
International Journal of Logistics Management,
Vol. 6, No. 2, pp. 39-54, 1995.
BALLOU, R.H.: “Estimating and Auditing
Aggregate Inventory Levels at Multiple Stocking
Points”. Journal of Operations Management,
Vol. 1, No. 3, pp. 143-153, February 1981.
BALLOU, R.H.: “Measuring Transport Costing
Error in Customer Aggregation for Facility
Location”. Transportation Journal, Vol. 33,
No. 3, pp. 49-59, Spring 1994.
BALLOU, R.H.: “The Accuracy in Estimating Truck
Class Rates for Logistical Planning”.
Transportation Research-A, Vol. 25A, No. 6, pp.
327-337, 1991.
BALLOU, R.H.: Business Logistics Management,
3rd edition, Prentice Hall, Englewood Cliffs, NJ,
1992.
BALLOU, R.H. & MASTERS, J.M.: “Commercial
Software for Locating Warehouses and Other
Facilities”. Journal of Business Logistics, Vol. 14,
No. 2, pp. 71-107, 1993.
BARITZ, S.G. & ZISSMAN, L.: “Researching
Customer Service: The Right Way”. Proceedings
of The National Council of Physical Distribution
Management, vol. II, New Orleans, pp. 608-619,
October 25, 1983.
BOWERSOX, D.J.; HELFERICH, O.K.;
GIMOUR, P.F.; MORGAN Jr. W., MARIEN,
E.J.; LAWRENCE, M.L. & ROGERS, R.T.:
Dynamic Simulation of Physical Distribution
Systems, East Lansing, MI: Division of Research,
Graduate School of Business Administration,
Michigan State University, 1972; PIPELINE
MANAGER by Andersen Consulting.
DAVIS H.W. & DRUMM W.H.: “Physical
Distribution Cost and Service 1995”. Annual
Conference Proceedings, San Diego: Council of
Logistics Management, p. 221, 1995.
GEOFFRION, A.M. & POWERS, R.F.: “Twenty
Years of Strategic Distribution System Design:
An Evolutionary Perspective”. Interfaces, Vol.
25, No. 5, pp. 105-127, September-October,
1995.
HARRINGTON, T.C. & LAMBERT, D.M.:
“Establishing Customer Service Strategies within
the Marketing Mix: More Empirical Evidence”.
Journal of Business Logistics, Vol. 10, No. 2, pp.
44-60, 1989.
HESKETT, J.L.: “A Missing Link in Physical
Distribution System Design”. Journal of
Marketing, Vol. 30, pp. 37-41, October 1966.
JACKSON, D.W.; KEITH, J.E. & BURDICK,
R.K.: “Examining the Relative Importance of
Physical Distribution Service Elements”. Journal
of Business Logistics, Vol. 7, No. 2, pp. 14-32,
1986.
KEARNEY, A.T. “Logistics Productivity: The
Competitive Edge in Europe”. Chicago, 1987.
KOBAYASHI, I.: “Management of Physical
Distribution Cost”. Proceedings of International
Distribution Conference, Tokyo, p. 9, 1973.
LALONDE, B.J. & ZINSZER, P.H.: Customer
Service: Meaning and Measurement, Chicago:
National Council of Physical Distribution, 1976.
MARR, N.E.: “Do Managers Really Know What
Service Their Customers Require?”. International
Journal of Physical Distribution & Logistics
Management, Vol. 24, No. 4, pp. 24-31, 1994.
MURPHY, G.J.: Transport and Distribution,
Business Books, London, p. 7, 1972.
RONEN, D.: “LSLLogistic System Design
Simulation Model”. Proceedings of the
Eighteenth Annual Transportation and Logistics
Educators Conference, Boston, pp. 35-47,
October 9, 1988.
STEPHENSON, A.R.: A Regional Survey of
Physical Distribution Problems and Practice,
Productivity Promotion Council of Australia, pp.
7-10, 1975.
STERLING, J.U. & LAMBERT, D.M.: “Customer
Service Research: Past, Present, and Future”.
International Journal of Physical Distribution &
Materials Management, Vol. 19, No. 2, p. 17,
1989.
GESTÃO & PRODUÇÃO v.4, n.2, p. 117-129, ago. 1997
129
LOGÍSTICA EMPRESARIAL — IMPORTÂNCIA E ALGUMAS
OPORTUNIDADES DE PESQUISA
Artigo Convidado
Resumo
Logística empresarial é definida e algumas razões são apontadas do porquê ela é uma
área vital de administração. Tendências políticas e econômicas são evidenciadas para
mostrar que ela está ainda crescendo em importância. A pesquisa atual em logística
empresarial é discutida enfocando o projeto da rede logística e como ele é auxiliado por
modelagem computacional. Oportunidades de pesquisa são identificadas para melhorar a
modelagem do projeto da rede e melhor especificar as necessidades de informação para o
processo de elaboração do projeto.
Palavras-chave: logística empresarial, visão geral, projeto de rede logística.
