Likert scale frequency options trading


It can be said that two respondents with scale positions 1 and 2 are as far apart as two respondents with scale positions 4 and 5, but not that a person with score 10 feels twice as strongly as one with score 5. Temperature is interval scaled, being measured either in Centigrade or Fahrenheit. Interval scales may be either numeric or semantic.

Study the examples below in figure 3. Circle the appropriate score on each line Succulence 5 4 3 2 1 Fresh tasting 5 4 3 2 1 Free of skin blemish 5 4 3 2 1 Good value 5 4 3 2 1 Attractively packaged 5 4 3 2 1 a Please indicate your views on Balkan Olives by ticking the appropriate responses below: Excellent Very Good Good Fair Poor Succulent Freshness Freedom from skin blemish Value for money Attractiveness of packaging b Most of the common statistical methods of analysis require only interval scales in order that they might be used.

These are not recounted here because they are so common and can be found in virtually all basic texts on statistics. Ratio scales The highest level of measurement is a ratio scale. This has the properties of an interval scale together with a fixed origin or zero point. Examples of variables which are ratio scaled include weights, lengths and times.

Ratio scales permit the researcher to compare both differences in scores and the relative magnitude of scores. For instance the difference between 5 and 10 minutes is the same as that between 10 and 15 minutes, and 10 minutes is twice as long as 5 minutes. Given that sociological and management research seldom aspires beyond the interval level of measurement, it is not proposed that particular attention be given to this level of analysis.

Suffice it to say that virtually all statistical operations can be performed on ratio scales. Measurement scales The various types of scales used in marketing research fall into two broad categories: In comparative scaling, the respondent is asked to compare one brand or product against another. With noncomparative scaling respondents need only evaluate a single product or brand. Noncomparative scaling is frequently referred to as monadic scaling and this is the more widely used type of scale in commercial marketing research studies.

Comparative scales Paired comparison 2: It is sometimes the case that marketing researchers wish to find out which are the most important factors in determining the demand for a product. Conversely they may wish to know which are the most important factors acting to prevent the widespread adoption of a product.

Take, for example, the very poor farmer response to the first design of an animal-drawn mould board plough. A combination of exploratory research and shrewd observation suggested that the following factors played a role in the shaping of the attitudes of those farmers who feel negatively towards the design: Suppose the organisation responsible wants to know which factors is foremost in the farmer's mind.

It may well be the case that if those factors that are most important to the farmer than the others, being of a relatively minor nature, will cease to prevent widespread adoption. The alternatives are to abandon the product's re-development or to completely re-design it which is not only expensive and time-consuming, but may well be subject to a new set of objections. The process of rank ordering the objections from most to least important is best approached through the questioning technique known as 'paired comparison'.

Each of the objections is paired by the researcher so that with 5 factors, as in this example, there are 10 pairs- In 'paired comparisons' every factor has to be paired with every other factor in turn.

However, only one pair is ever put to the farmer at any one time. The question might be put as follows: Which of the following was the more important in making you decide not to buy the plough? The question is repeated with a second set of factors and the appropriate box ticked again. This process continues until all possible combinations are exhausted, in this case 10 pairs.

It is good practice to mix the pairs of factors so that there is no systematic bias. The researcher should try to ensure that any particular factor is sometimes the first of the pair to be mentioned and sometimes the second. The researcher would never, for example, take the first factor on this occasion 'Does not ridge' and systematically compare it to each of the others in succession.

That is likely to cause systematic bias. Below labels have been given to the factors so that the worked example will be easier to understand.

The letters A - E have been allocated as follows: The data is then arranged into a matrix. Assume that farmers have been interviewed and their responses are arranged in the grid below. Further assume that the matrix is so arranged that we read from top to side. This means, for example, that out of farmers said the fact that the plough was too expensive was a greater deterrent than the fact that it was not capable of ridging.

Similarly, farmers said that the plough's inability to inter-crop was more important than the inability to ridge when deciding not to buy the plough. It can be seen that it is more important for designers to concentrate on improving transportability and, if possible, to give it an inter-cropping capability rather than focusing on its ridging capabilities remember that the example is entirely hypothetical. One major advantage to this type of questioning is that whilst it is possible to obtain a measure of the order of importance of five or more factors from the respondent, he is never asked to think about more than two factors at any one time.

This is especially useful when dealing with illiterate farmers. Having said that, the researcher has to be careful not to present too many pairs of factors to the farmer during the interview. For ten factors, brands or product attributes this would give 45 pairs. Clearly the farmer should not be asked to subject himself to having the same question put to him 45 times.

For practical purposes, six factors is possibly the limit, giving 15 pairs. It should be clear from the procedures described in these notes that the paired comparison scale gives ordinal data. Dollar Metric Comparisons 3: This type of scale is an extension of the paired comparison method in that it requires respondents to indicate both their preference and how much they are willing to pay for their preference.

This scaling technique gives the marketing researcher an interval - scaled measurement. An example is given in figure 3. How much more, in cents, would you be prepared to pay for your preferred fish? A common problem with launching new products is one of reaching a decision as to what options, and how many options one offers. Whilst a company may be anxious to meet the needs of as many market segments as possible, it has to ensure that the segment is large enough to enable him to make a profit.

It is always easier to add products to the product line but much more difficult to decide which models should be deleted. One technique for evaluating the options which are likely to prove successful is the unity-sum-gain approach. The procedure is to begin with a list of features which might possibly be offered as 'options' on the product, and alongside each you list its retail cost. A third column is constructed and this forms an index of the relative prices of each of the items.

The table below will help clarify the procedure. The important thing is that he should have considerably less hypothetical money to spend than the total value of the alternative product features. In this way the farmer is encouraged to reveal his preferences by allowing researchers to observe how he trades one additional benefit off against another.

For example, would he prefer a side rake attachment on a 3 metre head rather than have a transporter trolley on either a standard or 2.

The farmer has to be told that any unspent money cannot be retained by him so he should seek the best value-for-money he can get. In cases where the researcher believes that mentioning specific prices might introduce some form of bias into the results, then the index can be used instead. Survey respondents might then be given a maximum of 60 points and then, as before, are asked how they would spend these 60 points.

In this crude example the index numbers are not too easy to work with for most respondents, so one would round them as has been done in the adjusted column. It is the relative and not the absolute value of the items which is important so the precision of the rounding need not overly concern us. The design of the final market version of the product can then reflect the farmers' needs and preferences.

Practitioners treat data gathered by this method as ordinal. Noncomparative scales Continuous rating scales: The respondents are asked to give a rating by placing a mark at the appropriate position on a continuous line.

The scale can be written on card and shown to the respondent during the interview. Two versions of a continuous rating scale are depicted in figure 3. Whichever of these forms of the continuous scale is used, the results are normally analysed as interval scaled. The line marked scale is typically used to measure perceived similarity differences between products, brands or other objects. Consider the products below which can be used when frying food.

In the case of each pair, indicate how similar or different they are in the flavour which they impart to the food. Temperature is interval scaled, being measured either in Centigrade or Fahrenheit. Interval scales may be either numeric or semantic. Study the examples below in figure 3. Circle the appropriate score on each line Succulence 5 4 3 2 1 Fresh tasting 5 4 3 2 1 Free of skin blemish 5 4 3 2 1 Good value 5 4 3 2 1 Attractively packaged 5 4 3 2 1 a Please indicate your views on Balkan Olives by ticking the appropriate responses below: Excellent Very Good Good Fair Poor Succulent Freshness Freedom from skin blemish Value for money Attractiveness of packaging b Most of the common statistical methods of analysis require only interval scales in order that they might be used.

These are not recounted here because they are so common and can be found in virtually all basic texts on statistics. Ratio scales The highest level of measurement is a ratio scale. This has the properties of an interval scale together with a fixed origin or zero point. Examples of variables which are ratio scaled include weights, lengths and times.

Ratio scales permit the researcher to compare both differences in scores and the relative magnitude of scores. For instance the difference between 5 and 10 minutes is the same as that between 10 and 15 minutes, and 10 minutes is twice as long as 5 minutes. Given that sociological and management research seldom aspires beyond the interval level of measurement, it is not proposed that particular attention be given to this level of analysis.

Suffice it to say that virtually all statistical operations can be performed on ratio scales. Measurement scales The various types of scales used in marketing research fall into two broad categories: In comparative scaling, the respondent is asked to compare one brand or product against another. With noncomparative scaling respondents need only evaluate a single product or brand. Noncomparative scaling is frequently referred to as monadic scaling and this is the more widely used type of scale in commercial marketing research studies.

Comparative scales Paired comparison 2: It is sometimes the case that marketing researchers wish to find out which are the most important factors in determining the demand for a product. Conversely they may wish to know which are the most important factors acting to prevent the widespread adoption of a product. Take, for example, the very poor farmer response to the first design of an animal-drawn mould board plough.

A combination of exploratory research and shrewd observation suggested that the following factors played a role in the shaping of the attitudes of those farmers who feel negatively towards the design: Suppose the organisation responsible wants to know which factors is foremost in the farmer's mind.

It may well be the case that if those factors that are most important to the farmer than the others, being of a relatively minor nature, will cease to prevent widespread adoption. The alternatives are to abandon the product's re-development or to completely re-design it which is not only expensive and time-consuming, but may well be subject to a new set of objections.

The process of rank ordering the objections from most to least important is best approached through the questioning technique known as 'paired comparison'. Each of the objections is paired by the researcher so that with 5 factors, as in this example, there are 10 pairs- In 'paired comparisons' every factor has to be paired with every other factor in turn. However, only one pair is ever put to the farmer at any one time.

The question might be put as follows: Which of the following was the more important in making you decide not to buy the plough? The question is repeated with a second set of factors and the appropriate box ticked again. This process continues until all possible combinations are exhausted, in this case 10 pairs. It is good practice to mix the pairs of factors so that there is no systematic bias.

The researcher should try to ensure that any particular factor is sometimes the first of the pair to be mentioned and sometimes the second. The researcher would never, for example, take the first factor on this occasion 'Does not ridge' and systematically compare it to each of the others in succession.

That is likely to cause systematic bias. Below labels have been given to the factors so that the worked example will be easier to understand. The letters A - E have been allocated as follows: The data is then arranged into a matrix. Assume that farmers have been interviewed and their responses are arranged in the grid below.

Further assume that the matrix is so arranged that we read from top to side. This means, for example, that out of farmers said the fact that the plough was too expensive was a greater deterrent than the fact that it was not capable of ridging. Similarly, farmers said that the plough's inability to inter-crop was more important than the inability to ridge when deciding not to buy the plough.

It can be seen that it is more important for designers to concentrate on improving transportability and, if possible, to give it an inter-cropping capability rather than focusing on its ridging capabilities remember that the example is entirely hypothetical.

One major advantage to this type of questioning is that whilst it is possible to obtain a measure of the order of importance of five or more factors from the respondent, he is never asked to think about more than two factors at any one time.

This is especially useful when dealing with illiterate farmers. Having said that, the researcher has to be careful not to present too many pairs of factors to the farmer during the interview. For ten factors, brands or product attributes this would give 45 pairs. Clearly the farmer should not be asked to subject himself to having the same question put to him 45 times. For practical purposes, six factors is possibly the limit, giving 15 pairs. It should be clear from the procedures described in these notes that the paired comparison scale gives ordinal data.

Dollar Metric Comparisons 3: This type of scale is an extension of the paired comparison method in that it requires respondents to indicate both their preference and how much they are willing to pay for their preference. This scaling technique gives the marketing researcher an interval - scaled measurement. An example is given in figure 3. How much more, in cents, would you be prepared to pay for your preferred fish? A common problem with launching new products is one of reaching a decision as to what options, and how many options one offers.

Whilst a company may be anxious to meet the needs of as many market segments as possible, it has to ensure that the segment is large enough to enable him to make a profit. It is always easier to add products to the product line but much more difficult to decide which models should be deleted. One technique for evaluating the options which are likely to prove successful is the unity-sum-gain approach. The procedure is to begin with a list of features which might possibly be offered as 'options' on the product, and alongside each you list its retail cost.

A third column is constructed and this forms an index of the relative prices of each of the items. The table below will help clarify the procedure. The important thing is that he should have considerably less hypothetical money to spend than the total value of the alternative product features. In this way the farmer is encouraged to reveal his preferences by allowing researchers to observe how he trades one additional benefit off against another.

For example, would he prefer a side rake attachment on a 3 metre head rather than have a transporter trolley on either a standard or 2. The farmer has to be told that any unspent money cannot be retained by him so he should seek the best value-for-money he can get.

In cases where the researcher believes that mentioning specific prices might introduce some form of bias into the results, then the index can be used instead. Survey respondents might then be given a maximum of 60 points and then, as before, are asked how they would spend these 60 points.

In this crude example the index numbers are not too easy to work with for most respondents, so one would round them as has been done in the adjusted column. It is the relative and not the absolute value of the items which is important so the precision of the rounding need not overly concern us.

The design of the final market version of the product can then reflect the farmers' needs and preferences. Practitioners treat data gathered by this method as ordinal. Noncomparative scales Continuous rating scales: The respondents are asked to give a rating by placing a mark at the appropriate position on a continuous line. The scale can be written on card and shown to the respondent during the interview. Two versions of a continuous rating scale are depicted in figure 3.

Whichever of these forms of the continuous scale is used, the results are normally analysed as interval scaled. The line marked scale is typically used to measure perceived similarity differences between products, brands or other objects.

Consider the products below which can be used when frying food. In the case of each pair, indicate how similar or different they are in the flavour which they impart to the food. The line marking scale is a continuous scale.