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In order for a company’s marketing objectives to become strategies, decisions must be made. These decisions frequently involve the allocation of significant resources. Important decisions should be informed decisions. Therefore, the decision problems that arise from formulating

marketing strategy may require information that marketing research can provide.

Marketing research that does not help marketers make better, more informed decisions is a waste of money. And given how expensive marketing researcher can be, the waste can be considerable. Therefore, it’s critical that the marketing decision maker and the marketing researcher have a clear understanding of the decision problem and the decision maker’s expectations for the research. To follow are factors that can affect how well the researcher comes to understand the true nature of the decision problem. Additionally, we’ll briefly look at some of the tools available to market

researchers for getting the information decision makers need.

Working with Decision Makers Understand the Decision Situation

This need for clarity between decision maker and researcher makes this first portion of the marketing research process rather interactive. To the extent that time permits, the researcher should work with the decision maker gaining an understanding of the decision situation. Decision situations can be thought of as having two parts of interest to the marketing researcher.

Nature of the decision problem. First is the nature of the problem itself. Researchers must be prepared to learn as much as possible about every pertinent aspect of the decision problem. For

example, if the decision maker’s business or industry is one unfamiliar to the researcher, s/he should spend time getting to know their products, customers, and norms of doing business. Such information will prove very valuable when the time comes to select samples, design research projects, develop questionnaires, and collect and interpret data.

Another part of understanding the decision problem is understanding the decision’s ramifications to the company. One can safely assume that if a company is willing to research a decision problem, then the problem must be relatively important. However, some decisions may carry huge consequences for the company. Researchers should be aware of what the decision

problem represents for the company’s future.

To gain the best possible

understanding of the decision problem, the researcher might wish to begin with a “situation analysis,” which is formal and systematic examination of the elements of the marketing mix. Although time and resource constraints make detailed situation analyses impractical, when conducted they can provide the researcher with the

information s/he needs to formulate the most useful research questions and avoid wasting resources on research of little or no help in solving the decision problem. At the very least, researchers should try to meet with several people familiar with the decision

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problem. This permits the researcher to get a broader view of the problem and avoid approaching it from a narrower perspective.

Internal organizational environment. The second part to a decision situation that’s of interest to the researcher is the internal organizational environment surrounding the decision. The researcher should be aware of any pressures facing the decision maker; important business decisions frequently contain an element of company politics. When working with a decision maker, it’s helpful to be aware of such matters, to the extent possible.

Another important component to the internal environment is the company’s dominant decision style. Decision makers that rely greatly on instinct or intuition may have fairly minimal information needs, while those with more deliberate decision styles may require extensive information and analysis. Clearly, how the decision maker and his or her company approach important decisions affects the nature and the scope of their information needs. Companies that encourage these different decision styles may vary in their willingness to provide resources for marketing research. Appreciate the Decision Maker’s

Perspective

Marketing decision makers

frequently view the world from perspectives that are very different from researchers. Effectively communicating with decision makers requires that researchers come to appreciate how the decision maker views their world and learn to speak the decision maker’s “language.”

Exhibit 1 on the following page gives some insight into these differences. Effective and objective researchers should view decision problems in an almost detached way, similar to that of a scientist. But decision makers become wound up in

the problems they face, often because the stakes – financial, professional and personal – may be quite high.

Importantly, researchers should not muddle the communication process with the sometimes complicated language of research methodology. Instead, speak to the decision makers in terms they understand and that relate to their particular job and industry. Because the decision maker is the

researcher’s customer, it’s incumbent upon researchers to speak to them in terms they understand rather than the other way around. Help Formulate “Information Gaps”

Simply put, an “information gap” is the difference between what a decision maker would like to know about a given decision problem and what s/he currently knows. Working with the decision maker to formulate his or her information gaps helps both parties come to understand the role that research will play in solving the decision problem.

Why information gaps are useful. First, formulating information gaps helps bring structure to the decision problem. Decision makers often present their problems to researchers in very vague and unstructured terms. For example, past “clients” for this class have presented their problems to us as “We’d like to figure out how to attract more leisure travelers to the Dayton area? (Dayton Convention and Visitors Bureau)”, “What do I have to do to increase my store revenue to a million dollars per year? (Habitat for Humanity ReStore),” or “How can we generate interest in our film festival? (Dayton Area Indian Film Festival Association)” In each of these examples, clients presented broad unfocused and seemingly difficult problems. By

working with their clients to discover what they’d like to know in order to comfortably

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Exhibit 1. Perspective Differences of Decision Makers and Researchers

Attribute Decision Maker's Perspective Researcher's Perspective

Research Motivation make symptoms disappear discover true facts Attitude Toward Knowledge wants questions answered wants to ask questions Orientation subjective and pragmatic objective and scientific Level of Involvement highly involved detached and analytical

make decisions, marketing researchers can help bring structure to decision problems. Second, information gaps help researchers as the right research questions. As will be discussed in later Web Notes, research questions guide research efforts. Indeed, as noted in Exhibit 1, an important orientation of the researcher is to ask rather than answer questions. Information gaps serve as a valuable tool in helping the researcher establish the research questions that will guide the research project. In other words, formulating information gaps helps

researchers ask the right questions to gather the right information to fill the information gaps.

Using information gaps. Now that we’ve discussed why information gaps can be useful, you’ll probably be surprised at how simple they are to identify and use. Market researchers should first encourage the decision maker to adopt a “perfect world” perspective to their information needs by asking “If you could have any and all the information you needed to confidently make this decision, what would that information look like?” The decision maker is likely to respond by saying, “One thing I’d like to know is . . .” That’s really all there is to an information gap. Of course the researcher should continue questioning the decision maker to uncover more.

Let’s consider a recent example. A few years ago, the class took the Habitat for Humanity “ReStore” as a client. The

ReStore sells donated hardware and building supplies and then uses the money to fund

Habitat’s homebuilding projects. The ReStore’s manager wanted to grow revenues to one million dollars per year. With that as his objective he needed information to help formulate a strategy. So, we asked him, “If you could have any information you needed to grow the store to a million in revenues, what would that information look like?” With a little extra prompting he replied, “I’d like to know how many people even know about our store.” “I’d like to know what kinds of projects they take on.” “I’d like to know where they currently get their building supplies.” These and other simple gaps in the decision maker’s information provided a basis for formulating research questions, which we cover in later Web Notes.

The so-called “perfect world” perspective encourages decision makers not to think too small. All too often cost

conscious decision makers will immediately constrain their own needs because they automatically assume that the information they really need will be too expensive. By starting with the optimal, researchers and decision makers can get a clearer picture of what information would be best. If the projected costs of obtaining the all the information needed to make a perfectly informed decision proves too costly, then the information needs can be prioritized and the project scaled back appropriately. Starting with the optimal and scaling back to a more reasonable scope is preferable to initially thinking too small and then wishing later that more information had been collected.

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Types of Marketing Research and Research Data

Marketing research studies and marketing research data can be classified in many different ways such as the originality of the data, the source of the data, the

research methods used to obtain the data, the numeric characteristics of the data, and so on. As you go through the course you will become familiar with the various categories of data and their strengths, limitations, and uses.

One commonly used distinction concerns the originality of the data that are collected. “Primary data” are original data that specifically address a particular decision problem. The data did not previously exist and were collected at the request of a decision maker facing some problem. “Secondary data ” are data that already exist and have already been collected to address some other situation or problem but that may be of help to the solving the decision problem at hand. Beyond primary and secondary data are “syndicated data,” which are original data collected in predetermined forms and then sold to marketers.

Primary, secondary, and syndicated data all carry their own strengths and weaknesses. Primary data have the

advantage of being original and customized to address exactly the needs of the decision maker. However, primary data can be very expensive and time consuming to collect, analyze, and report. Because secondary data already exist, they will probably not exactly address the decision problem at hand. However, secondary data can be very inexpensive – often free – and may even exist within the decision maker’s own organization. Syndicated data may be original, but they are not customized to a particular need. Moreover, they may be purchased by many companies in the same industry meaning that competitive firms

have access to them. And syndicated data can be costly.

No matter how data are collected, cost plays a necessarily important role in all market research decisions. Therefore, market researchers should always look to secondary data sources first. Doing so can save literally hundreds of thousands of dollars. The abundance of information available today is staggering and for a researcher to recommend an expensive primary research study or purchase of syndicated data without first seriously exploring secondary data sources violates even basic researcher ethical norms. Collecting Primary Data

Later Web Notes on Research Designs and Exploratory Research detail several of the most common primary data collection techniques. Therefore we only briefly go over them here.

Surveys. Surveys are the “bread and butter” of the market research industry; this primary data collection method is the most commonly used in marketing research.

Several features characterize surveys and distinguish them from other primary research methods, in particular these four:

• relatively large samples • closed ended questions • self report responses • numerical data that can be

statistically analyzed

Relatively large samples mean that sample sizes number minimally in the hundreds, maximally in the thousands. As opposed to open ended questions, closed ended questions limit respondents’ response options. Respondents are not free to

formulate their own answers but must select from a list of options. Self reports mean that

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respondents report on their own feelings, opinions, or activities.

Experimentation. In experiments, researchers manipulate certain experimental factors and measure the results that those manipulations produce on the experimental participants. “Manipulate” simply means change. Researchers change the value of one or more experimental factors and measure the effects of the change.

For example, researchers may wish to see whether the package color of a new product produces differences in the prestige with which the product is regarded. They prepare three packages, identical in every way except for color. Three groups of people each view one of the packages and then respond to questions about it.

Researchers then compare the responses to see which produced the greatest perceptions of prestige.

In this example, the package color changed from group to group; thus, this experimental factor was manipulated. After seeing their respective packages,

experimental participants provided their perceptions of product prestige, making this the variable that researchers measured. The preceding suggests some characteristics of experimentation that distinguish it from survey research.

• generally smaller samples

(though this need not be the case)

• manipulation of one or more

factors

• measurement by self-report or

observation

• numerical data that can be

statistically analyzed

Measurement by observation refers to the fact that in some experiments,

measurement occurs through observation by machine or by a researcher. For example, suppose marketers wished to know if

arranging wines on the shelf by country of origin rather than by variety produced more in-store browsing and more sales of

imported wines. They could arrange the shelves differently at two similar stores then make comparisons. Researchers could time shoppers by observing them through

security cameras or by simply watching from a discreet distance. With respect to sales, directly observing shopper purchases directly may no longer be necessary when purchases may be observed mechanically by scanning cash registers.

Focus groups and depth interviews. Generally speaking, researchers rely on these two primary data collection techniques when simply exploring a research problem in preparation for larger projects such as surveys or experiments. However, given their relatively low cost and the frequently valuable and actionable information they provide, many researchers – particularly those on tight budgets – use these methods exclusively.

Focus group interviews take place with eight to twelve participants and a moderator. The interview is a fairly

unstructured conversation about a marketing question or problem led by the moderator. During the interview, which generally lasts between sixty and ninety minutes, the moderator attempts to uncover the feelings and motivations of the participants toward the marketing question.

Depth interviews follow much the same basic approach; however the interview occurs with only one participant. Compared to focus groups, depth interviews have the advantage of exploring the thoughts and feelings of one person in much more depth and detail. However, they lack the

interaction and spontaneity associated with the multiple participants.

Generally speaking, depth interviews and focus group interviews possess the following characteristics that distinguish

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them from other primary data collection techniques:

• very small samples compared to

surveys or experiments

• open ended questions • textual data that cannot be

statistically analyzed Compared to surveys and

experimentation, the information gathered by depth interviews and focus groups tends to be richer and more truly reflective of genuine human feelings. On the other hand, depth interviews and focus groups collect data that cannot easily be statistically analyzed and cannot be scientifically generalized to a population of interest. Focus group or depth interviews may be used to help clarify research issues in preparation for a larger scale survey or experiment. Surveys and experiments, when conducted properly, do produce data that can be generalized to a larger population.

As such, these various primary data collection techniques play different parts in the overall marketing research process. Focus groups and depth interviews

frequently assist researchers in exploring the nature of a decision problem and better understand its dimensions. Surveys and experiments build on this understanding by testing hypotheses that help answer the questions needed to solve the decision problem.

Ideally, research projects combine multiple data collection methods to produce the most useful results for the decision makers who need them. In practice, however, this is often not the case. Like any business activity, the buying and selling of marketing research services represent a series of trade offs, which as you can imagine, frequently revolve around budgetary issues. As such, effective researchers learn to make the most of the

resources at their disposal; when trimming expenses becomes necessary, researchers develop a strong sense of where best to trim. Collecting Secondary Data

Because we focus on primary data collection techniques in later Web Notes, we will give more attention to secondary data collection here. As noted earlier, secondary data are data that already exist, having been previously collected for some other purpose. We’re living in what some sociologists refer to as the Information Age, which implies that our society is characterized by large quantities of data relatively easily obtainable.

This is certainly the case in developed economies. Data from studies sponsored by government, business,

education, the press, and other organizations are published in a variety of places, many available free for the asking. In fact, secondary data are becoming so easily accessible and available in such large quantities that an increasingly important job for marketing researchers is to help decision makers wade through and make sense of the data available to them.

Sources of secondary data. For purposes of this discussion, let’s divide secondary data into two basic types depending on where the secondary data originate.

First is internal secondary data, which are secondary data that originate from sources inside the decision maker’s own organization. Researchers and decision makers should regard internal secondary data as especially important because they are basically free. Therefore, when available, internal secondary data represent a

potentially valuable source of information that can reduce the expense of primary data collection and in some cases even eliminate the need for it at all.

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Internal secondary data come from a company’s own records. Well managed organizations routinely capture information during the course of business that can of great value to marketing decision makers. This information is frequently collected by computer using software designed to efficiently track businesses activities.

One source that can yield

information useful to marketers are sales records that include some customer

information. Customer names and addresses regularly appear on sales invoices. This data can reveal interesting facts about customers. For example, if the customer is a consumer, then street addresses can be used to estimate home size, income, broad areas of

employment, education levels and so forth. Over hundreds of transactions, marketers can gain good insight into their customers’ personal characteristics. When collecting such information is practical and not threatening or inconvenient to customers, marketers should collect it for additional analysis. The insights such analysis may provide can greatly improve customer service and retention.

Other internal company records that marketing decision makers may find useful are salesforce call sheets. When salespeople call on organizational buyers, they

frequently must keep a record of the sales call. These records normally include such information as the customer called on, the date and time of the call, whether or not the salesperson personally met with a buyer, who the buyer was, and the outcome of the meeting. These call sheets can contain a wealth of information about why potential customers choose to buy or not.

Customers frequently initiate contact with marketers to make inquiries or register complaints. These contacts represent another potentially valuable source of internal secondary data. These inquiries may contain important insights into what

customers are thinking and how to best meet their needs.

Relatedly, most companies track product returns and service calls. At first glance, this information might seem of better use to production departments than marketing departments. However, product returns and service calls can assist marketers in improving or enhancing product features in ways that better serve customer needs. Marketers can provide valuable input into how returns and service calls can be used to actually enhance customer loyalty.

Research has shown that when products fail altogether or require repair, customers who are treated well often develop stronger connections to that product or brand than they felt before. Customers wish to be respected and to be treated justly by the companies with whom they do business. Therefore, marketers can potentially

contribute much to designing product return or repair policies. Information regarding returns or repairs are needed to make that contribution possible.

Occasionally large companies that are comprised of multiple divisions or that operate in many locations will collect or produce information that should be shared with other divisions or locations. Market analyses, sales forecasts, product feasibility studies, and numerous other reports

frequently wind up in file cabinets when they might prove useful to other parts of the company. Indeed, large companies can produce vast quantities of information that may have been collected or assembled for one project but may be useful to another. The result of not sharing such information may be costly duplication of efforts.

The second main source of

secondary data is external secondary data, which are secondary data originating outside the decision maker’s organization. External secondary data offers nearly limitless possibilities for finding at least some

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Exhibit 2. Popular Business Directories and Surveys

Source Description

U.S. Industrial Outlook This report uses U.S. government data to profile sales and growth trends for over 400 industries.

Survey of Buying Power Subscribers to Sales and Marketing Management magazine receive this annual report on population, buying income and retail sales for cities and counties in the U.S. and Canada.

Standard and Poor’s Industry Surveys

S&P continuously monitors vital financial statistics of approximately 1500 firms in over sixty industries. Standard Directory of

Advertisers

This directory lists the advertising expenditures and media used for hundreds of U.S. companies

Media Research Report Focusing on newspaper advertising, this report lists advertising space purchased by over 200 of the nations largest newspapers.

research that can usefully inform decision problems. The availability of the World Wide Web and powerful search engines offer tools for organizing and prioritizing much of this information.

Many of the most useful external secondary data sources are specific to particular industries or business functions, so researchers should become familiar with as many of these potential sources as possible. If a researcher is completely unfamiliar with potential sources of external secondary data on a particular topic, there are a few sources that often provide a useful starting point no matter what the subject.

One place to begin searching is for government sources. The federal

government annually publishes millions of pages of material on virtually every subject imaginable. Subjects of particular interest to marketers may originate in the Department of Commerce, the Bureau of Labor

Statistics, the Treasury Department, the Federal Reserve Board, the Federal Trade Commission, and the Census Bureau among others. We will look more closely at some government sources of secondary data later when we examine population demographics.

Another source, the popular press, reports research results that serve as the basis for various news stories. The term

popular press refers to any generally available news media source easily

accessible by the general public. Even the popular press has many areas of

specialization including the popular business press, the popular family press, the popular medical press, and so on. Each of these areas reports stories often based on research that may contain information useful to marketing researchers.

Still another source is the academic press. The academic press consists of primarily of scholarly journals that report the results of basic research studies. Basic research refers to studies conducted in the name of scientific inquiry and not for the purposes of solving a particular decision maker’s problem. However, the research questions addressed by basic research may have direct applications to many problems faced by marketing decision makers. Moreover, the academic literature is very large, consisting of thousands of journals in every academic discipline. Many libraries offer powerful search engines that can help narrow the search process.

Still another source, business directories and business panel surveys, provides a wide variety of information about businesses, and business activities. Although some may be available at public or university

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libraries, most business directories and surveys must be purchased. A few of these sources are given in Exhibit 2.

Problems with secondary data. Secondary data suffer from two possible problems that could inhibit their usefulness. The difference between these two problems can be subtle, and they can occur at the same time, so marketing researchers should be aware of these problems and their effects.

The first problem potentially affecting secondary data are called

“problems of fit.” Problems of fitarise when the secondary data do not exactly match the parameters of the decision

problem. The question facing researchers and decision makers is whether the problems of fit sufficiently outweigh the value of the data in terms of its low cost and immediate availability.

Problems of fit most frequently arise when the decision problems, research questions, and variables guiding the current research differ from those that guided the research that originally produced the secondary data. For example, suppose a researcher seeks information about consumer demand for recycled paper products. Instead she finds a study that reports on increases in consumer willingness participate in recycling programs. What the researcher wants and what she finds do not exactly match, so she must decide whether increasing willingness to relates well to a demand for recycled paper products. If so, then she may be able to forego the time and expense of primary data collection.

Problems fit may also arise when the sample used in a published study differ from the people around whom the decision

problem centers. For example, suppose the marketing researcher desires information about demand for recycled paper among a population consisting of married college educated females aged 25 to 34, with annual incomes above $24,000. Suppose she finds

good information except that it applies to women over forty-five. Again, the data do not exactly fit the problem parameters but may be close enough. Whether or not it is, of course, simply requires good judgment. The second problem that can affect secondary data are called “problems of accuracy.” Problems of accuracy arise when the research study that produced the

secondary data suffers from any of several possible factors that adversely affect its credibility. That is, for whatever reason, the data may not be believable.

In general, researchers may attribute problems of accuracy to any of three

sources. One, the data may simply be too old. Changing circumstances or events occurring since publication of the original research may strongly suggest that if

identical research were conducted today, the results would be different. How old is too old depends on a variety of factors including the subject matter and the sample that provided the data. Because of these factors, wide variation may exist in when secondary data become too old to be useful. As a general rule, however, researchers should look carefully at data more than five years old.

Two, the data may be

methodologically suspect. Just because someone publishes a study does not mean that the research behind the study employed acceptable research methods. As we will discuss in the weeks ahead, bias can creep into research results from many sources. This bias may move the data further and further away from the truth, which can be disastrous for drawing valid conclusions. When evaluating secondary data,

researchers must look hard at how the data were collected, which implies that

researchers must know what constitutes good research methodology.

Three, the data may have been originally collected to advance a particular

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point of view, meaning that they may not be objective. Many organizations conduct and publish research in an attempt to lend credence to their views. For example, suppose the researcher seeking information about demand for recycled paper products finds a report published by a paper

manufacturer. Or conversely, suppose the researcher finds a report published by an environmental activist group. Might these organizations have different views on the state of recycling in the United States, and might their views be affected by the goals of their organizations? When research is conducted or chiefly sponsored by an organization with a financial, political or social agenda, the results should be viewed skeptically. This does not suggest that the results should be disregarded, of course. Researchers should simply exercise common sense when drawing their conclusions.

When secondary data suffer from problems of fit, accuracy, or both,

researchers and decision makers must weigh the severity of the problems against the potential cost and time savings of having data in hand. Very often the deciding factor will be how critical the decision problem is to the future of the firm. Clearly, the more critical the decision problem, the greater the need is for accurate data that fit the decision problem well.

Purchasing Syndicated Data

In addition to primary and secondary data, marketers should also consider

syndicated data as an important potential source of information. Syndicated data are often original data, but they are collected in standardized forms solely for the purpose of selling to users of such data. A common example of syndicated data is the Nielsen television rating information. ACNielsen Company collects TV ratings information from viewers around the country and then

sells them to television stations and to networks. Networks and stations use the ratings to make programming decisions and to set advertising rates.

Syndicated data occupies a sort of middle ground between primary and

secondary data. While the data are original like primary data, they are not collected by special order. Instead, they are purchased “off the menu.” Assuming the syndicated data are purchased from a reputable

supplier, problems of accuracy rarely arise. However, because syndicated data are not custom collected, they may suffer from problems of fit. And syndicated data suppliers will sell data to whatever firms wish to buy it, meaning the data are typically available to competing firms.

The most common types of

syndicated data are media studies, consumer panel studies, and retail scanner studies. Some syndicated data providers combine these into more comprehensive studies. Media studies typically provide audience information to advertisers and media

providers. As noted earlier, the AC Nielsen television ratings are probably the best known syndicated data source. There are others, of course. Arbitron sells data on radio audiences in similar fashion to the Nielsen television ratings. Starch Reports provides information on magazine ad readership and the Audit Bureau of Circulation collects and sells data on magazine and newspaper circulation.

Consumer panels offer long term information on consumer thinking and behaviors. A panel is a group of consumers ranging in size from several dozen to several hundred that provide information on their and their families’ purchases, media habits, demographic changes, and attitudes over extended periods of time. Some consumer panels have been in existence for decades, though obviously some attrition is to be expected. Panel participants permit their

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purchases to be tracked, their TV and radio listening to be monitored, and regularly provide responses to questions about their attitudes to everything from marketplace activities to social phenomena. Using panel data, marketers can track changes in

consumer behaviors and purchase patterns over extended periods. Panel members are typically aid by the syndicated data provider for their participation.

Consumer panels are operated by some of the same companies that provide media data. For example, AC Nielsen also operates several consumer panels that track various aspects of consumer buying

behavior. Large national polling companies such as Harris, Roper, and Gallup also operate consumer panels of varying size and focus.

Retail scanner studies are a relatively new phenomenon to marketing research, but are now a mainstay source of marketplace information. Syndicated data companies such as Nielsen and IRI gather, aggregate, and sort sales data from scanning cash register check-out systems and then correlate those figures with factors such as price, advertising, shelf location, shopping distance, and competitive climate. The data are then sold to manufacturers and retailers seeking to gain advantage and insight into their consumers preferences and habits.

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Sources

Material regarding the differing perspectives of researchers and decision makers was adapted from

Zikmund, William (2000), Business Research Methods (6th ed). Fort Worth, Texas: The Dryden Press.

Problems with secondary data was adapted from

Tull, Donald S. and Del I. Hawkins (1987), Marketing Research: Measurement and Method (4th ed.). New York: Macmillam Publishing.

Some other material was adapted from Crask, Melvin, Richard J. Fox, and Roy G. Stout (1995), Marketing Research:

Principles & Applications. Englewood Cliffs, NJ: Prentice Hall.

References

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