Lesson 2

Logistics Subsystem
1.Marketing Logistics.

2.Concepts of Logistics with respect to functions of

organization.

3.Logistics Subsystems.

4.Elements & Key factors of logistics system

5.Trade-Off Analysis

6.Types of Trade-Off Analysis

Marketing Logistics
In 1991 the Council of Logistics Management (CLM) a prestigious, professional
organization, defined logistics as “the process of planning, implementing & controlling
the efficient, effective flow the point of origin to the point of consumption for the purpose
of conforming to customer requirements”.

Logistics means the art of managing the flow of raw materials and finished goods
from the source to the user.
To get goods from where they arise to the right place in the right form, at the right
time, at the right cost.

“Logistics or physical distribution or distribution logistics is an integral part of

Marketing Process”.

Essence of logistics in marketing:

Marketing Process is successfully completed when
 Products are produced and priced to satisfy the identified needs of the segment of
buyers
Arrangements are made to supply these goods through selected distribution
channels
An awareness is created among the buyers about the availability of the goods
through information facilitation &
Goods are physically supplied to the buyers at the place & time selected by them.
Besides satisfying the customers need, the marketing process must be profitable to
the seller.

So in the Marketing sense, utility is not merely the usefulness of a product to satisfy the
customer needs but also moving the product from a manufacturing facility to the user.

Thus, Logistics is a link between the manufacturing & selling process

that leads to the creation of place and time utility.
While the production element in the marketing – mix (product, price, place &
promotion) leads to creation of ‘form’ utility by taking decisions as product line variety,
design, colour brand, service, etc. the distribution element comprising distribution
channel fixation & physical movement, creates ‘time’ & ‘place’ utility by ensuring that
the produced goods reach the place & time choosen by the buyer.

Logistics is the designing and managing of a system in order to control the flow
of material throughout a corporation. This is a very important part of an international
company because of geographical barriers. Logistics of an international company
includes movement of raw materials, coordinating flows into and out of different
countries, choices of transportation, cost of the transportation, packaging the product for
shipment, storing the product, and managing the entire process.

Marketing Trends

•
Past Expectations Today’s Expectations

•
Products Standardized Products Customized Products

•
Forms Predefined Often Configurated

•
Time Now as available When wanted

•
Quality Acceptable Exceed Expectations

•
Price Low Competitive

•
Value Added Minimal Complex
Services

Relevance of Logistics in Export Management

International trade is becoming a more important part of the GNP in the

industrially advanced countries. Many firms in these countries have production centers
world wide for markets all over the world. Lack of local resources, small size of home
market and many other reasons has resulted in functional centers being maintained in
various countries.
Issues associated with international transportation of finished goods are
essentially the same as those that apply to transportation in domestic trade. But, under
international operations, goods can be out of exporter's control for longer period of time,
more documentation is required, packaging may be more costly and shipping insurance is
more costly.

The transportation alternatives include ocean shipping and containerization as

well as airfreight. The basic activities involved in the flow of goods, like transportation,
warehousing and holding of inventories, should be integrated in a systems approach. The
systems approach would recognize the trade-offs, such that sometimes more expensive
airfreight may be opted for, instead of less expensive ocean shipping, because of savings
in warehouse and inventory costs.
In the field of exports, it should
be noted that transport systems in developing countries are generally not as efficient as in
the industrially advanced countries. Transportation is often considered to be the most
important single determinant of plant location.

Firms in international trade also try to reduce amount of unnecessary product

packaging, since packing material can account for almost 40 per cent of the weight of the
products shipped. A company can reduce inland transportation charges by locating its
distribution facilities adjacent to container ports or airports. The burden of documentation
can be eased through computerization.
Export management
involves marketing in overseas market. Hence the discussions on the interface of logistics
with marketing holds good for the relevance of logistics in export management. Yet, in
addition, export management has certain unique features, as discussed above, to be
understood in the context of relevance of logistics to export management.

Importance of Logistics as a strategic resource:

Logistical Management includes the design and administration of systems to

control the flow of material, work-in-progress and finished inventory to support business
unit strategy.

Discussion of the concept of logistics, its place in the value-chain process leading
to profitability, its contribution as one of the primary functions and its interface with
other functions of the firm bring outs its importance as a strategic resource. However, to
be of a real strategic influence, a good amount of competency has to be achieved and a
well-defined logistical mission and objectives has to be committed to, by every one in the
firm, especially the top management.

1. Logistical competency: Logistics involves detailed and complex work. Logistical

management starts with how logistical competency fits into a firm's overall strategic
positioning. It is fundamentally important to view logistics as to how it can be exploited
as a core competency. For logistical competency to develop, it is important to develop an
integrated framework that defines and relates key concepts. This integration should be in
such a way that competitively superior logistical performance contributes to overall
enterprise strategy.
Logistical competency is a relative assessment of a firm's capability to provide
competitively superior customer service at the lowest possible total cost. This typically
means that logistical performance is dedicated to supporting any or all marketing and
manufacturing requirements in a manner that exploits delivery capability. In short, the
strategy is to provide superior service at a total cost below industry average.

Alternative logistical capabilities, emphasizing flexibility, time-based

performance, operational control, postponement capabilities, and most of all a
commitment to perfect service performance typically characterize the service platform of
superior logistic achievers.

So friends we can say that all enterprises must perform logistics to achieve their
basic business goals. One of several competencies required to create customer value is
logistics. When logistics becomes a cornerstone of basic business strategy, it must be
managed as a core competency.

2.The Logistical Mission: Logistics exists to satisfy customer requirements by

facilitating relevant manufacturing and marketing operations. The challenge is to balance
service expectations and cost expenditures in a manner that achieves business objectives.
Basic logistical service is measured in terms of
1. Availability
2. Operational performance, and
3. Service reliability

1.Availability means having inventory to consistently meet customer material or

product requirements.
2.Operational performance deals with the elapsed time from order receipt to delivery.
Operational performance involves delivery speed and consistency. A firm's operational
performance can be viewed in terms of how flexible it is in accommodating unusual and
unexpected customer requests.
3.Service reliability involves the quality attributes of logistics. For logistics
performance to continuously meet customer expectations, it is essential that management
be committed to continuous improvement.

Do you know in 1956, in an effort to explain conditions under which high-cost air
transport could be justified, Lewis, Culliton and Steele conceptualized the total cost of
logistics.

Total cost was positioned to include all expenditures necessary to perform

logistical requirements. The authors illustrated an electronic parts distribution strategy
wherein the high variable cost of direct factory to customer air transport was more than
offset by reductions in inventory and field warehouse costs. They concluded that the least
total cost logistical way to provide desired customer service was to centralize inventory
in one warehouse and make deliveries using air transportation.
The concept of total cost, although basic, had not previously been applied to
logistical analysis. Managers typically focused on minimizing functional cost, such as
transportation, with the expectation that such effort would achieve the lowest combined
cost. The total-cost concept opened the door to examining how functional costs
interrelate.

The appropriate level of logistics cost expenditure must be related to desired

service performance. The simultaneous attainment of high availability, operational
performance, and reliability is expensive. A significant managerial challenge stems from
the fact that logistical cost and increased performance have a no proportional
relationship.

The typical logistical system in an enterprise seeks to develop and implement an

overall logistical competency that satisfies key customer expectations at a realistic total-
cost expenditure.

Overall, logistical management is concerned with operations and coordination.

Operations deal with strategic movement and storage. To complete the total operations
mission. Attention must be directed to integrating physical distribution, manufacturing
support, and procurement into a single logistical process. These three areas, functioning
as an integrated and coordinated process, can best provide operational management of
materials; semi finished components, and finished products moving between locations,
supply sources, and customers of an enterprise.

The mission of the logistical system is measured in terms of total cost and
performance. Performance measurement is concerned with the availability of
inventory, operational capability, and quality of effort. Logistical costs are directly
related to desired level of performance. As a general rule, the greater the desired
performance, the higher the total logistics cost. The key to effective logistical
performance is to develop a balanced effort of service performance and total-cost
expenditure.

The strategic integration of logistics is fundamental to an enterprise's success.

While a firm may not select to differentiate competitively on the basis of logistical
competency, it must perform logistical responsibilities as part of the fundamental
process of creating customer value. The relative importance that a firm places on
logistical competency will determine the degree of emphasis on achieving internal and
external integration.

Flexibility is key to logistical competency. Logistical flexibility results from

integration and from implementing time-based control techniques.
 There are four logistics concepts:
- the systems concept
- the total cost concept
- the after-tax concept
- the trade-off concept

The systems concept is based on all functions of a organization working together

in order to maximize benefits. This concept sometimes requires certain components of
the organization to operate suboptimally in order to achieve maximum goals of the
system.

The total cost concept is based on the systems concept, however goal achievement
is measured in terms of cost.

A variation of the total cost concept is the after-tax concept. This goal of this concept is
after-tax profit. This concept is becoming very popular because of the many different
national tax policies.

The trade-off concept links the system together in a way that is very efficient, but
can have trade-offs that might be inefficient. The advantages of such high efficiency must
be weighed against the risk involved.

Logistics is a system having number of components, which can be combined in

different proportions to achieve a set objective.

Long-term objective is profitability, short-term objective is to survive competition

by recovering marginal costs.

• Physical Supply or Management of flow of raw materials, spare parts,

Logistics sub-systems:-

• Physical distribution or management of finished goods from the factory to the

consumable stores and machinery & tools from suppliers.

• Logistical Controls for managing the logistics system, it helps an efficient co-
buyers &

•
ordination of physical supply & distribution sub-systems.

Objective of an ideal logistic system is to ensure flow of supply to the buyer:-

In Correct Quantity
At Desired location
At Required time
At useable condition
At the lowest total cost

Thus the objectives encompass efforts to coordinate physical distribution and

material management in order to save money or improve service.
Elements of logistics system:-
Transportation
Warehousing
Inventory Management
Packing & Utilization &
Information & Communication

When economists originally discussed supply-and-demand relationships, facility

location and transportation cost differentials were assumed either nonexistent or equal
among competitors.

Given a facility network and information capability, transportation is the

operational area of logistics that geographically positions inventory. Because of its
fundamental importance and visible cost, transportation has received considerable
managerial attention over the years. Almost all enterprises, big and small, have managers
responsible for transportation. Finding and managing the desired transportation mix is a
primary responsibility of logistics.

Network of three of the functional areas of logistics - information, transportation,

and inventory - can be engineered into a variety of different operational arrangements.
Each arrangement will have the potential to achieve a level of customer service at an
associated total cost; In essence, these three functions combine to create a system
solution for integrated logistics. The final functions of logistics - warehousing, material
handling, and packaging - also represent an integral part of an operating solution.
However, these functions do not have the independent status of the three previously
discussed. Warehousing, material handling and packaging are an integral part of other
logistics areas. For example, merchandise typically needs to be warehoused at selected
times during the logistics process. Transportation vehicles require material handling for
efficient loading and unloading. Finally, the individual products are most efficiently
handled when packaged together into shipping cartons or other types of containers.

Logistics is viewed as the competency that links an enterprise with its customers
and suppliers. Information from and about customers flows through the enterprise in the
form of sales activity, forecasts, and orders. The whole process is viewed in terms of two
interrelated efforts, inventory flow and information flow.

Information flow is a key element of logistics operations. Paper-based

information flow, increases both operating cost and decreases customer satisfaction.
Electronic information movement and management provide the opportunity to reduce
logistics expense through increased coordination and to enhance service by offering
better information to customers.
Information flow was often overlooked because it was not viewed as being
important to customers. The Council of Logistics Management recognized this change
in 1988 when it incorporated "material, in-process, finished goods and information"
into its definition of logistics.
 Transportation is a key activity in the logistics value chain as it moves product
through the various stages of production and ultimately to the consumer. The primary
functions include product movement, product storage and integration of international
production and distribution operations. The major transportation principles involve
economies of scale and economies of distance.

While effective distribution systems should not be designed to hold inventory for
an excessive length of time, there are occasions when inventory storage is justified.

While the traditional warehousing role has been to maintain a supply of goods to
protect against uncertainty, contemporary warehousing offers many other value-added
services. These services can be described in terms of economic and service benefits.
Economic benefits include consolidation, break bulk and cross-dock,
processing/postponement, and stockpiling. Service benefits include spot stocking,
assortment, mixing, product support, and market presence

The handling of products is a key to warehouse productivity. Handling activities

include receiving, in storage handling, and shipping. Packaging has a significant impact
on the cost and productivity of the logistical system. An integrated logistics approach to
packaging operations can yield dramatic savings.

A marketing mix is a compilation of activities designed to attract customers

while simultaneously achieving business objectives. The so-called four P's -
products/service, promotion, price, and place - constitute a generic marketing mix. The
key to formulating an effective mix strategy is to integrate resources committed to these
activities into an effort that maximizes customer impact. Logistics ensures that customer
requirements involved in timing and location of inventory and other related services are
satisfactorily performed. Thus, the output of logistical performance is customer service.
Logistical competence is a tangible way to attract customers who place a premium on
time and place-related performance.

Thus the discussion on the objectives, logistics interface with marketing and the
system elements brings out the depth of the scope of logistics in the efficient functioning
of any business entity. The key to excellent logistics is to achieve integration of both
internal and external operations. Such integration requires clear identification concerning
the role that logistical competency is expected to play in overall enterprise strategy.

Key Factors

Involved in efficient and effective and effective logistics system are

Shippers (users of logistics)

Suppliers (of logistics services)

Carrier (rail, road, sea, water, pipeline)
Warehouse Providers
 Freight forwarders
Terminal operators (port, stevedores, etc
Government (regulator of logistics)

TRADE-OFF ANALYSIS
Trade-off analysis is a family of methods by which respondents' utilities for
various product features (usually including price) are measured. In some cases, the
utilities are measured indirectly. In this case, respondents are asked to consider
alternatives and state a likelihood of purchase or preference for each alternative. As the
respondent continues to make choices, a pattern begins to emerge which, through
complex multiple regression (and other) techniques, can be broken down and analyzed as
to the individual features that contribute most to the purchase likelihood or preference.
The importance or influence contributed by the component parts. i.e., product features,
are measured in relative units called "utils" or "utility weights."

In other cases, respondents are asked to tell the interviewer directly how
important various product features are to them. For example, they might be asked to rate
on a scale of 1 to 100 various product features, where 1 means not at all important to their
purchase decision and 100 means extremely important to their purchase decision.

Trade-off analyses produce several types of information. First, they tell us what
features (and levels of features) are most valued by customers. Second, they allow us to
model how likely people will be to purchase various configurations of products, the share
of revenue these products will most likely receive and what role price plays in the
assessment of acceptability.

There are four main types of trade-off:

Conjoint
Discrete Choice
Self-explicated
Hybrid

One additional model, the MACROModel©2, will be discussed which does not
fall into any of the above four categories.

We will discuss each of these trade-off types after reviewing a few basic concepts.

Experimental Design
A critical issue in most trade-off methods is the selection of product attributes to
be combined together to create each product configuration to be tested.

If every possible combination of attributes were included in the study, the study
would be said to be using a complete or full factorial design. This is desirable but very
seldom practical. For example, if we had 6 attributes with 3 levels each, the total number
of possible combinations would be 36 or 729. This is much too large to ask one
respondent to rate (and 6 attributes with 3 levels each is untypical modest).

When a fractional factorial design is used, only a fraction of the total possible
number of product combinations needs to be tested. For the above example, a fractional
factorial design could be generated (usually with the help of a computer) that would
require perhaps as few as 14 product configurations to be rated. It must be kept in mind,
however, that whenever a fractional factorial design is used, some information will be
lost. It is the job of the researcher creating the experimental design to ensure that the
information being sacrificed (usually higher order interaction effects) does not
compromise the project's ability to answer the research objectives.

Bridging
Occasionally, even with the most efficient fractional factorial design, we still end
up with more products than can be practically accommodated. One possible solution to
that problem is bridging3. Bridging allows the attributes to be divided into two or more
sets (with some attributes common to all sets). Each set of attributes is treated like its
own trade-off study. A fractional factorial design is created for each set of attributes.
Respondents are asked to rate or rank two smaller sets of products rather than one large
set. The utilities are calculated for each trade-off exercise independently and bridged
together to create one final set of utilities.

Cognitive and Non-cognitive Behavior

Critical to the selection of an appropriate trade-off technique is the issue of which
type of behavior, cognitive or non-cognitive, best represents the behavior being
measured. Cognitive behavior is behavior that is based on rational, conscious decision-
making. Such factors as price, functionality or durability are typically cognitive. Non-
cognitive behavior is behavior that is based on less tangible or even less conscious factors
such as status, aspiration, insecurity, perceived taste, etc. One might argue that the
selection of a life insurance policy, a computer or a water heater are all cognitive
decisions and that the selection of a beer, a skin cream or a pair of pants are all non-
cognitive. One might also argue that all decisions made by humans are non-cognitive.

However, trade-off techniques that employ direct questions (self-explicated and

hybrid) all assume that the behavior being modeled is cognitive, because at least some of
the product features are being rated in a way that requires both awareness and honesty
from the respondent. That is, the respondent must be aware of the degree to which a
product feature affects his or her purchase decision and also be willing to admit to that
degree of affect.

Additionally, any data collection methods that rely on verbal or written

descriptions of product features all assume that the behavior being modeled is cognitive,
because the process of understanding a verbal or written description is itself a cognitive
behavior.

Non-cognitive trade-off models should be based on an indirect trade-off technique

(conjoint or discrete choice) and data collection that relies on experience rather than
language to communicate the product choices. For example, if you are modeling the pant
selection process, show respondents a variety of pants that they can see and touch. A
consumer may respond to the phrase "light blue pants" very differently than he or she
would to a particular pair of light blue pants.

The Four Main Types of Trade-Off

I. Conjoint
Conjoint analysis is the original trade-off approach and uses linear models. There
is metric conjoint, where respondents monadically rate various product configurations,
and non-metric conjoint, where respondents rank a set of product configurations. There
are also full-profile conjoint, partial-profile conjoint and pairwise conjoint. Full-profile
conjoint uses all product features in every product configuration. Partial profile conjoint
uses a smaller subset of available product features in the product configurations. Pairwise
conjoint requires the respondent to rate their preference for one product over another in a
paired comparison. We will only discuss conjoint methods in general in this paper.

Conjoint models are simply regression models which are constructed for each
individual respondent. Typically, each respondent rates or ranks 20 to 30 product
configurations. Each product configuration contains different levels of the product
attributes being tested. If the product levels are varied appropriately (the role of
experimental design), a regression model can be estimated for each individual, using the
product ratings as cases. The coefficients from the model are the utilities or utils.

A conjoint approach should be used if a limited number of attributes needs to be

tested and utilities need to be estimated for individual respondents, e.g., conjoint-based
segmentation.

II. Discrete Choice

Discrete choice differs from conjoint in that respondents are shown a set of
products from which they pick the one they most want to buy or none if they are not
interested in any of the choices shown (rather than rate or rank choices). Respondents are
shown several sets of choices sequentially. For each choice set, they are asked to pick one
or none. This is in contrast to most forms of conjoint where respondents are not allowed
to choose none of the product options (MACRO incorporates no-buy choices into its
conjoint models). The discrete choice procedure has the advantage of being more like the
actual purchase decision process than do any of the data collection methods used in most
conjoint studies.
 Also, in conjoint methods, the mathematical models constructed to simulate
market behavior are based on linear regression models. In discrete choice, the basis is the
multinomial logit model4, which is non-linear. Another analytical difference is that, in
conjoint procedures, the utility weights are estimated for each respondent individually.
These weights can often provide the basis for a very powerful customer segmentation.
Most commercially available forms of discrete choice do not allow this option, although
this may be rapidly changing.

Further, because discrete choice models are generally estimated at the aggregate
level, there exists the possibility that respondents will have strong but opposite
preferences to one another. These preferences will effectively cancel each other out when
the model is constructed at the aggregate level, yielding the incorrect conclusion that
respondents had no strong preference. This is sometimes referred to as the heterogeneity
problem.

There are two basic forms of discrete choice: classic and exploding data5. Classic
discrete choice involves showing a respondent a series of sets of products (as described
above). In exploding data discrete choice, respondents are asked to rank order a set of
products based on purchase interest (similar to non-metric conjoint). This rank-ordered
data set can be transformed into a format suitable for logit model estimation. Exploding
data discrete choice has the advantage of more efficient data collection over classic
discrete choice. The exploding data approach creates many times more data points (or
cases) than the classic approach with the same interview length.

Discrete choice should be used if the primary objective of the study is to estimate
market share or price sensitivity, a limited number of attributes need to be tested and the
sample population is known to be homogeneous with respect to all product attributes.

III. Self-Explicated
Conjoint and discrete choice both determine respondents utilities indirectly.
Self-explicated determines respondents' utilities directly. With self-explicated
scales, respondents are asked directly how important all levels of all attributes are to their
purchase interest. Despite its conceptual simplicity, self-explicated models have been
shown to be comparable to conjoint models.

Self-explicated conjoint analysis requires respondents to reveal their utilities

directly. Accordingly, standard questionnaire methods can be used to collect the
information. The technique involves the following steps:

• Respondent are informed about all the attributes and their levels,
and the respondents are then asked to identify attribute levels that are totally
unacceptable to them
• From among the acceptable levels of the attributes, respondents are
asked to indicate which are the most preferred and least preferred levels of each
attribute
 • Using the respondents' most important attribute as an anchor, elicit
importance ratings for the other attributes (on a 0 - 100 scale)
• For each attribute, rate the desirability of the different acceptable
levels with the attribute
• Utilities for acceptable attribute levels are obtained by multiplying
the importance rating and the desirability ratings

The utilities are then entered into a choice simulator program, and choice
information similar to other conjoint programs can be obtained.
]
Self-explicated approaches are useful when there are a large number of attributes
and the decision process being modeled is cognitive.

IV. Hybrid
Hybrid models are models that use a combination of the above techniques. The
most famous hybrid model is ACA, Adaptive Conjoint Analysis.

Adaptive Conjoint Analysis

In this procedure, a computer program prompts the interviewer with questions.
The procedure is as follows:

Respondents are first walked through a battery of feature-importance ratings and

rankings; second, through a series of pairwise trade-offs of different product
configurations. The product configurations shown to any one respondent may not include
all of the attributes being tested.

The configurations to be paired are based on the answers to the importance

questions and rankings asked in the beginning of the interview. Items that are considered
of little importance show up in the comparisons less often. Items that are considered of
greater importance show up in the comparisons more often.

For each pair of products being tested, the respondent is to indicate which product
they prefer and the degree to which they prefer it.

The software continues prompting with pairwise comparisons

of product configurations until enough data has been collected to estimate conjoint
utilities for each level of each feature. Since the procedure is adaptive, only a fraction of
the total number of possible product combinations is tested.

ACA is an approach that is appropriate for building

preference models of cognitive behavior with large numbers of attributes. It may not be
as useful when price sensitivity, non-cognitive purchase decisions or interaction terms are
to be modeled.
Cake Method© and Logit-Cake Method©
Other hybrid models include the Cake Method©8 and the Logit-Cake Method©9.
Both of these models have been developed by MACRO Consulting and were designed to
overcome weaknesses in other models.

Cake Method©
The Cake Method© is a unique, proprietary approach to conjoint analysis which
offers several advantages over other conjoint methods:

A large number of product features (50 or more) can be included in the model
First order interactions can be estimated at both the disaggregate and aggregate
levels

There is complete control over the experimental design, in a full-profile format

Since product combinations are specified, via traditional experimental design,
before the interview takes place, physical exhibits can be easily incorporated into the
interview

The approach involves a specific data collection procedure as well as a unique

analytic protocol. The basic outline of the approach is to:

• Collect self-explicated scales on most of the product attributes

tested
• Conduct a full-profile conjoint exercise with a limited number of
product attributes, some of which are common to the self-explication exercise
• Estimate conjoint utilities for each respondent
• Bridge self-explicated scales to utility weights

The Cake Method© should be used when there are a large number of attributes,
utilities need to be estimated for individuals, interaction terms need to be measured and
the purchase decision is at least partially cognitive.

Logit-Cake Method©
The Logit-Cake Method© is a unique, proprietary approach to choice-based trade-
off analysis which offers several advantages over other conjoint methods:

• A large number of product features (50 or more) can be included in

the model
• The heterogeneity problem long associated with aggregate logit
models is avoided
• The traditional advantages of logit models over conjoint models
are maintained
 • First order interactions can be estimated
• There is complete control over the experimental design, in a full-
profile format
• Since product combinations are specified, via traditional
experimental design, before the interview takes place, physical exhibits can be
easily incorporated into the interview

The approach involves a specific data collection procedure as well as a unique

analytic protocol. The basic outline of the approach is to:

• Collect self-explicated scales on all product attributes tested

• Conduct a full-profile choice-based exercise with a subset of
product attributes
• Segment the sample based on self-explicated scales
• Estimate logit models for each respondent cluster
• Bridge self-explicated scales to logit-based utility weights

The Logit-Cake Method© should be used when there are a large number of
attributes, market share and price need to be estimated, interaction terms need to be
measured and the purchase decision is at least partially cognitive.

MACROModel©
One other model will be discussed in this paper. It does not fall into any of the
four main types of trade-off models. In fact, it is not strictly speaking a trade-off model
because it does not estimate utilities for any product attributes. The MACROModel© was
developed by MACRO Consulting to address a specific research methods need that
frequently occurs in new product development and packaging.

The MACROModel© is a unique approach to new product screening which offers

several advantages over other methods:

• A large number of concepts or packages (50 or more) can be

screened at one time
• Price sensitivity can be calculated for every new product concept
screened
• Price/volume can be individually optimized for every product
concept tested
• New product concepts can be screened and/or completely rank
ordered on consumer appeal, market share, unit volume, gross dollar volume or
gross profits

The approach involves a specific data collection procedure as well as a unique

analytic protocol. The basic outline of the approach is to:
 • Sort a stack of new product concepts cards (all new product
concepts, each at three price points) into two piles: would definitely buy and
would not buy. Note: Stack would contain several existing products as reference.
• Have them rank order the would buy pile on a continuum from
most want to buy to least want to buy.
• Note: If the number of items to be sorted is too large for one
sorting exercise, the task can be broken down into several smaller exercises, with
two or three items common across sorting tasks. After the data are collected for
all respondents for the various sorting exercises, a bridging technique can be used
to incorporate the data from the separate exercises into one rank ordering of all of
the items used in the study.
• Once the data are combined into one rank order data set for each
respondent, the MACROModel© (a first choice share of preference model) can be
constructed.

The MACROModel© should be used when the product is too complex to

decompose into attributes, e.g., packaging graphics, when a large number of highly
different products are to be included, e.g., new product screening, when price sensitivity
needs to be measured and when products will be screened based on their revenue
potential.

Conclusion
There are a variety of approaches to trade-off analysis, each with its advantages
and disadvantages. Which trade off procedure is best is dependent on the issues and
constraints of each marketing problem. The marketing problem should be discussed with
a researcher who is knowledgeable in all appropriate methodologies before a research
approach is selected.

Thus trade-off are necessary . The aspects of trade-off analysis are

o Within One logistics Elements :- Trade-off that occurs within a
single element
Between logistics Element:- Trade-off that are possible by
considering the impact of one on the other
Interface between company functions:- These trade-off are
brought about through impact on production.
Between the Company & other organizations:- These trade-
off benefit all concerned organizations.

Forms of logistics management.

1.Centralized logistics management

Centralized logistics management provides that managers that also head other
divisions of the company head the logistics operations. This type of management helps
avoid internal problems by having a central manager that ultimately decides how logistics
and operations are coordinated.

2.Decentralized logistics management

Decentralized logistics management is based on the fact that a company needs to

have a division that helps control the local-adaptation needs. Dealing with different
cultures requires input from the local branch. The managers that deal with the cultural
differences on a daily basis normally know what works and what don’t.

3.Outsourcing

Outsourcing is the final option for logistics management. When this happens,
transportation firms concentrate on logistics, and the company can concentrate on it's
production. There are many cost savings using this type of program, however that lack of
control can negatively effect many companies.

International logistics requires many different options and requirements to be met

in order for a company to operate internationally. It's like a big puzzle that must be put
together, in order for all the goals to be met. As described above, there are many options
to consider, and sometimes what appears to be an option really isn't. It is not difficult to
hit a road block, and you must start over with a new plan. Once the logistics plan is in
place, you must constantly look for improvements in order to maximize profits and goals.

Source for trade off analysis

1
An edited version of this article was published in the February, 1998 issue of
Quirk’s Marketing Research Review.
2
P. Richard McCullough, MACROModel©-A Price Sensitivity and Volumetric
Approach to New Product Concept Screening, Mountain View, CA, 1995. A MACRO
white paper.
3
Pierre François, Douglas L. MacLachlan and Anja Jacobs, Bridging Designs for
Conjoint Analysis: The Issue of Attribute Importance, Leuven, Belgium, 1991-2. An
unpublished paper.
4
R. Duncan Luce, Individual Choice Behavior: A Theoretical Analysis, New
York: John Wiley, 1959.

Richard R. Batsell and Abba M. Krieger, Least-Squares Parameter Estimation

For Luce-Based Choice Models, June, 1979.
5
Randall G. Chapman and Richard Staelin, Exploiting Rank Ordered Choice Set
Data Within the Stochastic Utility Model, Journal of Marketing Research, August, 1982.
 6
V. Srinivasan, A Conjunctive-Compensatory Approach To The Self-Explication
of Multiattributed Preferences, Decision Sciences, 1988, vol. 19.
7
ACA is a product of Sawtooth Software, Inc., Sequim, WA. Sawtooth Software
offers a broad range of trade-off software products.
8
P. Richard McCullough, The Cake Method©-A Proprietary Hybrid Conjoint
Approach to Trade-off, Mountain View, CA, 1997. A MACRO white paper.
9
P. Richard McCullough, The Logit-Cake Method©-A Proprietary Hybrid
Choice-Based Approach to Trade-off, Mountain View, CA, 1997. A MACRO white
paper.

QUESTIONS FOR SELF-ANALYZATION:

Q1 What is the relation between Marketing and Logistics. Quote a Suitable example to
prove the relationship.

Q2.What are the subsystems of Logistics Management?Expain the importance of about

each system with respect to the importance in business.

Q3 What do you understand by Trade-Off Analysis. Explain the various techniques used
to do the same. Also explain the importance of trade-off analysis.