Given the naturalistic setting of field experiments, this category generally provides greater external validity than do those experiments conducted within a laboratory environment. In some cases the marketing researcher seeks to exclude extraneous factors that can confound the results of an experiment. However, this is not always possible since it is difficult to determine when certain types of extraneous variable is in operation and even more difficult to measure them.
In these circumstances, the researcher will seek to control confounding variables in a different way. Internal validity History: The term 'history' has been used to describe events that happen whilst the experiment is underway and serve to distort experimental results. Pretest effect: It is sometimes considered necessary to take some preliminary measures before the main experiment is carried out.
For instance, a company wishing to promote monogerm sugar beet seed in Pakistan wanted to first establish how much farmers already knew about the different types of seed available. A particular district was chosen as a test area and a pretest was undertaken where a sample of farmers from that area were asked to list the types of seed of which they were aware.
The farmers were also asked to list the brands of sugar beet seed with which they were familiar. This constituted the 'before' measure. A little later a promotional campaign was launched within the test area and after a period of time the sample of farmers were again visited and asked to identify the brands of seed with which they were familiar.
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It is likely that any increase in awareness of the company's brand was due, in part at least, to the heightened awareness of issues relating to seeds caused by the pretest activity. That is, the pretest is likely to increase interest in matters relating to seeds and therefore make farmers more attentive to the brand promotion than they otherwise might be. Experiments requiring the cooperation of respondents over a substantial period of time are most likely to suffer from maturation effects.
Consumer and farmer panels are examples of experimental instruments that demand longer term participation by panel members. Suppose that a farmer panel were established to measure the level of adoption of new marketing practices or technologies promoted by agricultural extension officers.
As the years pass the marketing extension officer has noted that farmers on the panel appear to be adopting fewer of the innovations being proposed by the extension service. However, the lower rates of adoption may not be explained by either the marketing extension service becoming less effective in communicating the benefits of innovative marketing practices and technologies nor by current innovations being somehow less appropriate or offering more marginal benefits.
Rather, the explanation may be that the panel itself is aging and as farmers get older they may become more resistant to change. Certainly as people get older their needs and attitudes are subject to change.
In these circumstances the data drawn from the panel is a function of the maturation of the panel rather than the experimental variables i. Whilst it is not always possible to adjust the experimental design so as to eliminate each of these potential threats to the validity of results, it is always possible to measure their impact upon results. The chief device for doing so is to include a 'control group'. Instrumentation: From time to time, measurement instruments have to be recalibrated or their readings become suspect.nenontuge.tk
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Although marketing research does make use of a wide range of mechanical, electrical and electronic instruments in experiments that clearly require periodic readjustment, e. Questionnaires may contain standardised questions with the challenge to consistency coming from the interpretation of the meaning of the question. Consider the apparently straight-forward question, "How big is your farm? The variation is due to farmers' interpretation of what the researcher really wants to know.
Some farmers will include only the land area that they had under crop in the year of the survey whilst others will include both productive and nonproductive land. In other instances, farmers may understand the question to mean the area of land they actually own. Another aspect is that of consistency in the conduct of interviews. There can be variation in the data collected during an experiment if either different interviewers are used to collect data after the experiment from those who conducted interviews before the experiment; or interviewers change the way questions are put to participants as they become more familiar with the content of the questionnaire.
Mortality: Over time there is a danger that some participants will drop out of an experiment. This can happen when people literally die or decide withdraw from an experimental group for one reason or another. This obviously changes the composition of the experimental group. Where the effects of a marketing variable are being studied by comparing data drawn either from two groups that have been matched to ensure that their composition is identical or the same group at different points in time then mortality can confound the results.
Sampling bias: Sampling bias occurs when the method of assigning participants to experimental groups results in groups whose behaviour cannot be compared to one another because they differ in some important respect s. Consider the task of evaluating the implementation of new weighing and grading practices within a municipal grain market. It could be that it is easier for larger grain traders to adopt the new practices since they are better able to afford the grading and weighing equipment required. If during a field experiment conducted to study the rate of adoption two groups are established with a view to comparing the rate of adoption within them and one of those groups is predominantly comprised of larger or smaller traders then this is likely to distort the results.
External validity Interactive effects of testing: The design of the experiment itself may give rise to measurement variations between the "before" and "after" phases of the research. Consider a test of consumer acceptance involving two exotic rice varieties being evaluated as possible replacements for a popular indigenous variety which is suffering from a disease and is therefore in short supply. The experimental design involves leaving a trial pack of rice A with a sample of households and returning a few weeks later to interview members of the household about rice A and to deliver a second trial pack containing rice B.
A third visit is subsequently made during which household members are asked questions about rice B. Respondents' assessment of rice B is not made under the same conditions as their assessment of rice A.
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When trying rice A the respondents are likely to have made comparisons, perhaps only subconsciously, with existing rice varieties that they already use. However, when evaluating rice B the respondents will also be making comparisons with rice A. This problem can be overcome, to some extent, by splitting the sample so that half are given the trial varieties in the order rice A then rice B; the remaining half are given the two varieties in the reverse order of rice B then rice A.
A more difficult problem to overcome is that whatever the sequence of presentation, by the time household members are asked about the second trial variety, they have become more 'experienced' interviewees and respond differently simply because they feel they better understand what the interviewer wants and how to answer the questions. By the same measure, the interviewer becomes more experienced the second time around, having become more familiar with the product, the interviewing process, and the questionnaire or interview schedule , and may pose the questions in a different way.
As a result, the interviewer may elicit different information on the third call from that which was obtained on the second visit. Interactive effects of sampling bias: It can happen that participants are assigned to an experimental group without due concern for possible bias and this then interacts with the experimental treatment producing a spurious outcome.
Such an interactive sampling bias would result from unknowingly assigning heavy users of a particular product category to one experimental group and using favourable responses to a new formulation within the category as the basis for projecting national demand. Contrived situations: Any laboratory experiment is, by definition, unlike the real world. On occasion this leads to experimental results which are not replicated in the real world. An outstanding example of this set of circumstances is that of Coca Cola's infamous blind taste panels. Coca Cola was concerned at the creeping increases in market share of Coke's main competitor Pepsi.
Coca Cola decided to conduct sensory analysis tests where participants were asked to score two colas on taste preference. The participants were given the colas in unmarked cups i. On balance, the preference was of Pepsi's slightly sweeter cola. Coca Cola reacted in a way seldom seen anywhere in the world. The brand leader was removed from the market and a new, slightly sweeter formulation was launched under the Coca Cola brand name. It was to prove a costly mistake. Coca Cola were inundated by calls from consumers who were irate over the company's tampering with a product that has almost become a national institution.
Most Americans have grown up with Coca Cola and could not accept that it could be changed. The company was forced to reintroduce the original formulation under the title of Coke Classic. Coca Cola's taste panels were conducted in an artificial environment in which such variables as the brand name, the packaging and all the associations which go along with these were not allowed to operate. The research focused only on the taste characteristics of the product and a particular result was obtained.
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However, in the real world people consume Coca Cola for many reasons, many of them having little to do with the taste. Experimental designs The process of experimentation is one of subjecting participants e. This is a common approach in advertising research where a sample of target customers are interviewed following exposure to an advertisement and their recall of the product, brand, or sales features is measured.
The amount of information recalled by the sample is taken as an indication of the effectiveness of the advertisement.
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For example, marketing extension personnel might have completed a trial campaign to persuade small-scale poultry producers, in a localised area, to make use of better quality feeds in order to improve the marketability and price of the end product. The decision to extend the campaign to other districts will depend on the results of this trial. After-only measures are taken, following the campaign, by checking poultry feed sales with merchants operating within the area.
Suppose a rise in sales of good quality poultry feed mixes occurs four weeks after the campaign ends. It would be dangerous to assume that this sales increase is wholly due to the work of the marketing extension officers. A large part of the increase may be due to other factors such as promotional activity on the part of feed manufacturers and merchants who took advantage of the campaign, of which they were forewarned, and timed their marketing programme to coincide with the extension campaign.
Some experimental research on labor market discrimination takes place in the lab. But far more of it is done in the field, which makes this particular area of experimental research unique relative to the explosion of experimental economic research more generally.
This paper surveys the full range of experimental literature on labor market discrimination, places it in the context of the broader research literature on labor market discrimination, discusses the experimental literature from many different perspectives empirical, theoretical, and policy , and reviews both what this literature has taught us thus far, and what remains to be done.
Published: David Neumark, Development of the American Economy. Economic Fluctuations and Growth. Deductive approach is mainly used for experiments research in order to test hypotheses.
Specifically, experiment researches involve manipulation with an independent variable in order to assess its impacts on dependent variables. Changes in price levels on volume of sales can be mentioned as a basic example for experiment. In this specific example, price can be specified as independent variable, whereas sales would be dependent variable.
Experimental Methods in Business Research - Durham University
The nature of relationships between two variables in causal experimental researches may be divided into three categories: symmetrical, reciprocal and asymmetrical. However, in symmetrical relationship change in one variable is not caused by change in another variable. In other words, symmetrical relationships of two individual variables usually would be the cause of another factor. For example, decrease in the levels of consumption of luxury products and decrease on the levels of consumer trust on financial institutions may occur at the same time as a result of a third factor — increasing level of uncertainty of perspectives of national economy.
For example, impacted by a marketing message a consumer purchases a car from a particular brand for the first time. Consequently, the consumer becomes loyal to the brand considering more purchases from the same brand in the future.