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Unit 2
Deduction and Induction
Deduction
Form of argument that purports to be conclusive
The conclusion must necessarily follow from the reasons given
Much stronger and different bond between reasons and conclusions than is found in induction.
Premises given for the conclusion must agree with the real world
The conclusion must necessarily follow from the premises.
Examples
All employees at bank One can be trusted to observe the ethical code (Premise 1)
Sara is an employee of Bank One (Premise 2)
Sara can be trusted to observe the ethical code (Premise 3)
Inner city household interviewing is especially difficult an expensive (Premise 1)
This survey involves Inner city household interviewing
The interviewing in this survey will be especially difficult an expensive (Premise 3)
A conclusion that results from deduction is in a sense already contained in its premises.
Induction
In induction you draw a conclusion from one or particular facts or pieces of evidence.
The conclusion explains the facts, and the facts support the conclusion.
Example
Suppose your firm spends $1 million on a regional promotional campaign and sales donot increase.This is a fact, sales did not increase during or after the promotional campaign. Under such circumstances we ask, “Why didn’t sales increase?”
Regional retailers did not have sufficient stock to fill customer requests during the promotional period.
A strike by the employees of our trucking firm prevented stock from arriving in time for the promotion to be effective.
A category five hurricane closed all our retail locations in the region for the 10 days during the promotion.
Combining Deduction and Induction
Deduction and Induction are used together in research reasoning:
1. You promote a product but the sales do not increase. (Fact)
2. You ask the question “Why didn’t sales increase?” (induction)
3. You infer a conclusion (hypothesis) to answer the question: The promotion was poorly executed. (Hypothesis)
4. You use this hypothesis to conclude (deduce) that sales will not increase during a poorly executed promotion. You know from experience that in effective promotion will not increase sales. (Deduction)
Concepts
It is a generally accepted collection of meanings or characteristics associated with certain events, objects, conditions,situatuions and behaviors.
Classifying and categorizing objects or events that have common characteristics beyond any single observation creates concepts.
Constructs
An abstraction like personality is much more difficult to visualize. Such abstract concepts are often called constructs.
A construct is an image or abstract idea specifically invented for a given research and/or theory building purpose.
We build constructs by combining the simpler, more concrete concepts , especially when the idea or image we intended to convey is not subject to direct observation.
Definitions
Confusion about the meaning of concepts can destroy a research study’s value without the researcher or client even knowing it.
If words have different meanings to the parties involved then the parties are not communicating well.
Definitions are one way to reduce this danger.
Types of Definitions
1. Dictionary Definitions2. Operational Definitions In the more familiar dictionary definition,
a concept is defined with a synonym. For example, a customer is defined as a
patron; a patron, in turn, is defined as a customer or client of an establishment ; a client is defined as one who employees the services of any professional and, loosely as a patron of any shop.
Operational Definition
It is a definition, stated in terms of specific criteria for testing or measurement.
These terms must refer to empirical standards.
Whether the object to be defined is physical or highly abstract, the definition must specify the characteristics and how they are to be observed.
Variables
It is used as synonym for construct or the property being studied.
A variable is a symbol of an event, art, characteristics, trait or attribute that can be measured and to which we assign categorical values.
Independent and Dependent Variables
Researchers are most interested in relationships among variables.
For example, does a newspaper coupon (independent variable) influence product purchase (dependent variable) or can a salesperson’s ethical standards influence her ability to maintain customer relationships?
Independent Variable
IV is manipulated by the researcher, and the manipulation causes an effect on the dependent variable. We recognize that there are often several independent variables and that they are probably at least somewhat “correlated” and they are not independent among themselves.
Dependent Variable
Similarly, the term, criterion variable is used as synonymously with DV.
This variable is measured, predicted, or otherwise monitored and is expected to be effected by manipulation of an independent variable.
Extraneous Variable
An almost infinite number of extraneous variables exist that might conceivably affect a given relationship.
Some can be treated as independent or moderating variables, but most must be either assumed or excluded from the study.
Intervening Variables
An intervening variable is a conceptual mechanism through which the IV and MV might affect the DV.
It may be defined as:“that factor which theoretically affects the
observed phenomenon but cannot be seen, measured, or manipulated; its effect
must be inferred from the effects of the independent and moderator variables on
the observed phenomenon.”
Propositions and Hypothesis
We define a proposition as a statement about observable phenomena (concepts) that may be judged as true or false.
When a proposition is formulated for empirical testing, we call it a hypothesis.
As a declarative statement about the relationship between two or more variables, a hypothesis is of a tentative and conjectural nature.
Hypotheses have also been described as statements in which we assign variables to cases.
A case is defined in this sense as the entity or thing the hypothesis talks about.
The variable is the characteristic, trait, or attribute that, in the hypothesis, is imputed to the case.
For example, we might create the following hypothesis:
Brand Manager Javed (case) has a higher-than-average achievement motivation (variable).
If our hypothesis was based on more than one case, it would be a generalization. example:
Brand managers in Company Z (cases) have a higher-than-average achievement motivation (variable).
Descriptive Hypotheses
Both of the above hypotheses are examples of descriptive hypotheses.
They state the existence, size, form, or distribution of some variable. Researchers often use a research question rather than a descriptive hypothesis. For example:
Descriptive Research Questions Hypothesis
In Islamabad, (case) our potato chip market share variable) stands at 13.7 %.
Pakistani citizens (case) are facing budget difficulties (variable).
What is the market share for our potato chip in Islamabad?
Are Pakistani citizens facing budget difficulties?
Relational Hypothesis
These are statements that describe a relationship between two variables' with respect to some case.
For example, "Foreign (variable) cars are perceived by Pakistani consumers (case) to be of better quality (variable) than domestic cars."
In this instance, the nature of the relationship between the two variables ("country of origin" and "perceived quality") is not specified.
The first in terpretation (unspecified relationship) indicates a correlational relationship;
The second (predictable relationship) indicates an explanatory, or causal, relationship.
Correlation hypotheses
Correlation hypotheses state that the variables occur together in some specified manner without implying that one causes the other.
Causal Hypotheses
With explanatory (causal) hypotheses, there is an implication that the existence of of a change in one variable causes or leads to a change in the other variable.
The causal variable is typically called the independent variable (IV) and the other the dependent variable (DV).
Cause means roughly to "help make happen." So the IV need not be the sole reason for the existence of or change in the DV. Here are 3 examples of explanatory hypotheses:
1. An increase in family income (IV) leads to an increase in the percentage of income saved (DV).
2. Exposure to the company's messages concerning industry problems (IV) leads to more favorable attitudes (DV) by employees toward the company.
3. Loyalty to a particular grocery store (IV) increases the probability of purchasing the private brands (DV) sponsored by that store.
The Role of the Hypothesis
In research, a hypothesis serves several important functions:
1. It guides the direction of the study. 2. It identifies facts that are relevant and
those that are not.3. It suggests which form of research
design is likely to be most appropriate.4. It provides a framework for organizing
the conclusions of the research.
What Is a Strong Hypothesis?
A strong hypothesis should fulfill three conditions:
1. Adequate for its purpose.2. Testable.3. Better than its rivals.
Theory
A theory is a set of systematically interrelated concepts, definitions, and propositions that are advanced to explain and predict phenomena (facts).
In this sense, we have many theories and use them continually to explain or predict what goes on around us.
To the de gree that our theories are sound and fit the situation, we are successful in our explanations and predictions.
Models
The term model is used in business research and other fields of business to represent phe nomena through the use of analogy.
A model is defined here as a representation of a sys tem that is constructed to study some aspect of that system or the system as a whole.
Models differ from theories in that a theory's role is explanation whereas a model's role is representation.
UNIT 3
Unit of analysisTime and space boundaries Characteristics of interest Specific environmental conditions
POINTS TO PONDER ON RESEARCH PROBLEM
The right question must be addressed if research is to aid decision makers. A correct answer to the wrong question leads either to poor advice or to no advice.
Very often in research problem we have a tendency to rationalize and defend our actions once we have embarked upon a particular research plan. The best time to review and consider alternative approaches is in the planning stage. If this is done needless cost of false start and redoing work could be avoided.
A good starting point in problem definition is to ask what the decision maker would like to know if the requested information could be obtained without error and without cost.
Another good rule to follow is "Never settle on a particular approach" without developing and considering at least one alternative".
The problem definition step of research is the determination and structuring of the decision maker's question. It must be the decision maker’s question and not the researcher's question.
What decision do you face? If you do not have decision to make, there is no research problem.
What are your alternatives? If there are no alternatives to choose, again there is no research problem.
What are your criteria for choosing the best alternative? If you do not have criteria for evaluation, again there is no research problem.
The researcher must avoid the acceptance of the superficial and the obvious.
UNITS OF ANALYSIS
To illustrate the selection of units, consider a manufacture of small electrical motors who wishes to ascertain the extent to which its potential customers know the company exists. The potential customers are basically business entities. But the units of the universe could also be defined as purchasing departments, production departments, engineering departments, or particular individuals within one or more departments.
Who should be aware of the manufacturer's existence? In the company considering specific acts that might increase awareness levels for certain groups?
Alternatively, the basic unit of analysis could be defined in terms of transactions rather than in terms of potential buyers. With buyers as units, the universe consists of persons, groups of persons or business entities.
With transactions as units, the universe consists of activities as the focus of interest. Typically, in research, we wish to classify or measure the units according to some characteristics.
The well known management concept of a "decision-making unit" (DMU) often comes in to play in defining the units of the universe. But the DMU is usually difficult to define in an unambiguous manner.
A purchase that is a wife's decision in one family may be a husband's decision in another and a joint decision in third. How does one cope with this problem? A two step procedure is a possibility. The first stage units are families; within each family the decision maker is identified.
The units of the problem universe are the DMU's.
TIME AND SPACE COORDINATES
The time dimension of a decision problem is always the future. Look at the following questions. What should we do the first of next month in order to produce the desired effect the following month? What will consumer response be to our contemplated promotion for the month of November?
These questions indicate the futurity aspect of the time dimension of a decision problem.
Therefore, it is crucial that the decision maker and the researcher establish the appropriate time reference for the decision.
What is the appropriate time decision for the manufacturer of small electrical motors? The manufacturing company is interested in awareness at the point in time when it contemplates possible actions, either to modify that awareness level or to operate within that constraint.
1f its decision is to be implemented on January 15, 2008, it would like to know the conditions in the universe on that date. If the implementation would be delayed for 5, 10, or, 20 months, the company would like to know the state of the universe on those dates.
Large time consuming capital expenditure may be initiated in the near future, but the size of the expenditure is based upon estimates of conditions at a distant point in time.
The space refers to the geographic boundaries within which the action is to be taken. In the problem definition, these lines are rarely neat like political divisions or subdivisions. Advertising media do not stop abruptly at city or province lines.
Retailers and wholesalers usually welcome customers regardless of where the customers reside. Sales territories may, however, be established along country or province lines.
In a similar way, licensing by governmental units may determine the appropriate space coordinates. In the absence of such externally imposed constraints, the problem definition, in theory, often includes the whole earth or the total of Pakistan. Recognition of this fact in the problem definition will help evaluate the utility of a research universe that is considerably smaller.
All Units or specific Units
More often the decision maker is interested in employed housewives, or housewives from households with an automatic washer, or housewives who have tried product X.
These examples illustrate three different types of modifications applied to units: (1) a characteristic or present state of units, (2) a characteristic of an object associated with the unit rather than a more direct characteristic of the unit itself (household with automatic washer),and (3) past behavior of the unit (have tried product X).
CHARACTERISTICS OF INTEREST
The characteristics of interest identify what there is about the units that is of concern to the decision maker. These characteristics fall into two categories:
1. the dependent variables and the independent variables.
2. The dependent variables are those of interest for their own sake.
For example, in marketing, they often refer to behavior or attitude towards a firm's offering. Examples are purchases, awareness, opinions, or profits associated with consumer behavior attitude.
The independent variables included in the problem definition are those characteristics thought to be related to the dependent variables.
These variables may either be within the control of the firm (endogenous)-such as advertising, pricing or personnel changes - or beyond the control of the firm (exogenous).
Exogenous variables of potential interest cover a multitude of possibilities, varying from competitor and government actions to economic conditions to individual consumer characteristics.
Frank, Massy, and Wind have developed a 2 * 2 matrix with two principal merits: simplicity and the highlighting of measurement assumptions. This matrix is presented in Table below.
Characteristics General Situation specific
Objective (1) (3) Inferred (2) (4)
Cell (I)
General objective measures. Cell (1) for example may contain two different
types of variables: demographic and socio-economic.
The demographic are illustrated by age, sex, stage of life cycle, martial status, tenure, geographic location, and race of ethnic group.
The socio economic variables, usually stress income, education, and occupation either singly or in some combination assumed to be a measures of social class.
These variables do not relate to specific products or market activity.
Does age - a variable of cell (1) - help discriminate between product users and nonusers? Neither age nor stage of life cycle would be of interest in these examples apart from its potential relationship to specific products or companies.
Cell (2)
General inferred measures. Variables in this cell are general in character and are not directly measurable. Personality traits, intelligence, and life style are illustrations of these variables.
Disagreement concerning the proper or best measure of these characteristics is highly likely.
The inclusion of these variables in marketing research projects is usually motivated in the same way as those of cell (1): they may be related to marketing variables of more direct interest.
Therefore the marketing manager is often more concerned with their predictive power than with the purity or defensibility of their definitions.
Cell (3)
Situation specific objective measures. Variables in this category are typically behavioral with respect to the market place. Purchase behavior, brand use, store patronage and loyalty, advertising exposure, and degree of innovation are examples of these variables.
Such behavior is often an ultimate of intermediate goal of the marketing manager. Variables in this cell may be the dependent variable - the crucial "result" - measured in the research.
These variables may also be potential independent variables; prior behavior may aid in understanding or predicting later behavior either for the same variable or a related variable. For example heavy usage of product may be related to brand loyalty.
Cell (4)
Situation specific inferred measures: Attitude, intentions, perceptions, and preferences
towards specific brand, products, and companies are examples for the typical variables in this category. These variables differ from those in cell (3) because of the fact that they are neither directly measurable nor observable. Also the researchers may disagree in either the conceptual or operational definitions of variables in cell (4).
The variables in cell (4) may be of direct interest to the marketing manager. Thus these variables are "results" under test in the research; the adequacy of their definitions is therefore critical. The advertising ladder concepts incorporate variables from this cell, establishing mental states which are presumed to lead to and precede purchase and repeat purchase.
The 2 * 2 matrix can be used to identify and measure the characteristics of interest for any research problem though we have taken examples from marketing.
Characteristics of Interest versus Unit of Analysis
Confusion sometimes arises concerning the difference between the characteristic of interest and the, unit of analysis. A manufacturer of drugs is interested in rupee value sales of a particular generic drug.
The manufacturer wants to know rupee sales for a group of six cities during the period of September 2005-April 2007. Thus the time and space coordinates have been defined for the research universe.
The characteristics of interest is crucial to the management. Its value will serve as the basis for choosing among alternative actions. The unit of analysis establishes the source for the information. In many cases the unit employed is dictated by convenience rather than the "proper" problem definition.
For example, the drug company could generate aggregate sales by using the ultimate consumer as the unit instead of using the drug store.
ENVIRONMENTAL CONDITIONS
The environmental conditions specified in the research problem are of two types; (1) those beyond the firm's control and (2) those within the firm's control. The firm must adjust to the first and choose wisely with respect to the second. Neither is possible without knowing how the particular variables influence the characteristics of interest.
RESEARCH PROBLEM AS HYPOTHESIS TESTING
It is`often convenient to structure a research problem in terms of a hypothesis to be tested. The hypothesis must be agreed upon by both the manager and the researcher, although the formal statement is primarily the responsibility of the researcher. A hypothesis is simply a statement about the universe. It may or may not be true; the research is designed to ascertain the truth. Consider the following pair of hypothesis.
HO: At least 10% of the viewing audience for "children's" TV shows consists of adults.
H1 : Less than 10 % of the viewing audience for "children's" TV shows consists of adults.
The terminology "state of nature" is often used to refer to the true situation in the universe. For example, the advertising manager for a firm selling a product frequently purchased by adults is considering the possibility of advertising the product on children's TV shows.
Decision making as hypotheses testing is a two-step process with error possibilities at each step.
At step one there is the relationship between the states of nature and the action recommended. The percentage of adults in the audience may not be a proper guide to action. The number of adults may be better guide. Rupee value expenditure in the product category may be still better.
At step two there is the possibility that the research result may be erroneous with respect to the state of nature.
The sample may indicate that the percentage of adults in the audience is less than 10 %. Or the opposite error may occur. Research procedures do not yield certainty with respect to the true state of nature.
No matter how careful we are, we may conclude that HO is true when H1 is true or vice versa. This fact means the decision maker and the researcher must evaluate the seriousness of different kinds of errors.