Scaling in research

Scaling in research

1. Objectives Introduction Measurement and Scaling Issues i n Attitud e Meas u rement Levels of Measurement Scales T yp e s o f Sc a lin g T ec h niqu e s # Comparative Scales # Non-comparative Scales Selection of an Appropriate Scaling Technique Conclusion K e y W o rds

2. Th e Meas u re m ent & Scaling T ec h niqu e help s us t o : explain the concepts of measurement and scaling, discuss four levels of measurement scales, classify and discuss different scaling techniques, and select an appropriate attitude measurement scale for our research problem.

3. As we discussed earlier, the data consists of quantitative variables, like price, income, sales etc., and qualitative var i ab l es l i k e k n owledg e , perf o rmance , characte r etc. The qualitative information must be converted into numerical form for further analysis. This is possible through measurement and scaling techniques. A common feature of survey based research is to have respondent’s feelings, attitudes, opinions, etc. in some measurable form.

4. Before we proceed further it will be worthwhile to understand the following two terms: (a) Measurement, and (b) Scaling. Measurement: Measurement is the process of observing and recor d ing th e o b servations tha t are collecte d as part o f research. The recording of the observations may be in terms of numbers or other symbols to characteristics of objects according to certain prescribed rules. The respondent’s, characteristics are feelings, attitudes, opinions etc. The most important aspect of measurement is the specification of rules for assigning numbers to characteristics. The rules for assigning numbers should be standardized and applied uniformly. This must not change over time or objects. Scaling: Scaling is the assignment of objects to numbers or semantics according to a rule. In scaling, the objects are text statements, usually statements of attitude, opinion, or feeling.

5. When a researcher is interested in measuring the attitudes, feelings or opinions of respondents he/she should be clear about the following: What is to be measured? Who is to be measured? The choices available in data collection techniques

6. The level of measurement refers to the relationship among the values that are assigned to the attributes, feelings or opinions for a variable. Typically, there are four levels of measurement scales or methods of assigning numbers: Nominal scale, Ordinal scale, Interval scale, and Ratio scale.

7. Nomi n al Sca l e is t h e crude st among all meas u rement scales but it is also the simplest scale. In this scale the different scores on a measurement simply indicate different categories. The nominal scale does not express any values or relationships between variables. The nominal scale is often referred to as a categorical scale. The assigned numbers have no arithmetic properties and act onl y as la b els. Th e onl y s t at i st i c a l op erat i o n t h at c an b e performed on nominal scales is a frequency count. We cannot determine an average except mode. For example : labeling men as ‘1’ and women as ‘2’ which is the most common way of labeling gender for data recording purpose does not mean women are ‘twice something or other’ than men. Nor it suggests that men are somehow ‘better’ than women.

8. Ordinal Scale involves the ranking of items along the continuum of the characteristic being scaled. In this scale, the items are classified according to whether they have more or less of a characteristic. The main characteristic of the ordinal scale is that the categ ories ha v e a log i ca l o r orde red relat i onsh i p. Th i s ty p e of scale permits the measurement of degrees of difference, (i.e. ‘more’ or ‘less’) but not the specific amount of differences (i.e. how much ‘more’ or ‘less’). This scale is very common in marketing, satisfaction and attitudinal research. Using ordinal scale data, we can perform statistical analysis like Median and Mode, but not the Mean. For example , a fast food home delivery shop may wish to ask its customers: How would you rate the service of our staff? ( 1) E x cellent • (2 ) V er y Goo d • ( 3) Goo d • (4 ) P oo r • (5 ) W or st •

9. Interval Scale is a scale in which the numbers are used to rank attributes such that numerically equal distances on the scale represent equal distance in the characteristic being measured. An interval scale contains all the information of an ordinal scale, but it also one allows to compare the difference/distance between attributes. Interval scales may be either in numeric or semantic formats. The interval scales allow the calculation of averages like Mean, Median and Mode and dispersion like Range and Standard Deviation. For example , the difference between ‘1’ and ‘2’ is equal to the difference between ‘3’ and ‘4’. Further, the difference between ‘2’ and ‘4’ is twice the difference between ‘1’ and ‘2’. Measuring temperature is an example of interval scale. But, we cannot say 40°C is twice as hot as 20°C.

10. Ratio Scale is the highest level of measurement scales. This has the properties of an interval scale together with a fixed (absolute) zero point. The absolute zero point allows us to construct a meaningful ratio. Ratio scales permit the researcher to compare both differences in scores and relative magnitude of scores. Examples of ratio scales include weights, lengths and times. For example , the number of customers of a bank’s ATM in the last three months is a ratio scale. This is because you can compare this with previous three months. For example , the difference between 10 and 15 minutes is the same as the difference between 25 and 30 minutes and 30 minutes is twice as long as 15 minutes

11. In comparative scaling, the respondent is asked to compare one object with another. The comparative scales can further be divided into the following four types of scaling techniques: Paire d C omparison Scale, R a n k Orde r Sca l e, Constant Sum Scale, and Q-sort Scale.

12. Paired Comparison Scale: This is a comparative scaling technique in which a respondent is presented with two objects at a time and as k ed t o sele c t on e objec t a c c o rd i n g t o so m e criterion . The data obtained are ordinal in nature. For example , there are four types of cold drinks - Coke, Pepsi, Sprite, and Limca. The respondents can prefer Pepsi to Coke or Coke to Sprite, etc.

13. Rank Order Scale : This is another type of comparative scaling technique in which respondents are presented with several items simultaneously and asked to rank them in the order of priori t y . Thi s is an ordi n al s c ale tha t d e s c ribes the favoured and unfavoured objects, but does not reveal the distance between the objects. Th e re s u l t ant data in ra n k order is ordi n al data. This yields better results when direct comparison are required between the given objects. The major disadvantage of this technique is that only ordinal data can be generated.

14. Constant Sum Scale : In this scale, the respondents are asked to allocate a constant sum of units such as points, rupees, or chips among a set of stimulus objects with respect to some criterion. For example, you may wish to determine how important the attributes of price, fragrance, packaging, cleaning power, and lather of a detergent are to consumers. Respondents might be asked to divide a constant sum to indicate the relative importance of the attributes. The advantage of this technique is saving time. However, main disadvantages are the respondents may allocate more or fewer points than those specified. The second problem is respondents might be confused.

15. Q-Sort Scale : This is a comparative scale that uses a rank order procedure to sort objects based on similarity with respect to some criterion. The important characteristic of this methodology is that it is more important to make comparisons among different responses of a respondent than the responses between different respondents. Therefore, it is a comparative method of scaling rather than an absolute rating scale. In this method the respondent is given statements in a large number for describing the characteristics of a product or a large number of brands of a product.

16. In non-comparative scaling respondents need only evaluate a single object. Their evaluation is independent of the other object which the researcher is studying. The non-comparative scaling techniques can be further divided into: Continuous Rating Scale, and Itemized Rating Scale.

17. Continuous Rating Scales : It is very simple and highly useful. In continuous rating scale, the respondent’s rate the objects by placing a mark at the appropriate position on a continuous line that runs from one extreme of the criterion variable to the other. Example : Question: How would you rate the TV advertisement as a guide for buying?

18. Itemized Rating Scales : Itemized rating scale is a scale having numbers or brief descriptions associated with each category. The categories are ordered in terms of scale position and the respondents are required to select one of the limited number of categories that best describes the product, brand, company, or product attribute being rated. Itemized rating scales are widely used in marketing research. Itemised rating scales is further divided into three parts, namely Likert scale, Semantic Differential Scale, and Stapel Scale.

19. Likert Scale : Likert, is extremely popular for measuring attitudes, because, the method is simple to administer. With the Likert scale, the respondents indicate their own attitudes by checking how strongly they agree or disagree with carefully worded statements that range from very positive to very negative towards the attitudinal object. Respondents generally choose from five alternatives (say strongly agree, agree, neither agree nor disagree, disagree, strongly disagree). A Likert scale may include a number of items or statements. Disadvantage of Likert Scale is that it takes longer time to complete than other itemised rating scales because respondents have to read each statement. Despite the above disadvantages, this scale has several advantages. It is easy to construct, administer and use.

20. Semantic Differential Scale : This is a seven point rating scale with end points associated with bipolar labels (such as good and bad, complex and simple) that have semantic meaning. It can be used to find whether a respondent has a positive or negative attitude towards an object. It has been widely used in comparing brands, products and company images. It has also been used to develop advertising and promotion strategies and in a new product development study.

21. Staple Scale : The Stapel scale was originally developed to measure the direction and intensity of an attitude simultaneously. Modern versions of the Stapel scale place a single adjective as a substitute for the Semantic differential when it is difficult to create pairs of bipolar adjectives. The modified Stapel scale places a single adjective in the centre of an even number of numerical Values.

22. A number of issues decide the choice of scaling technique. Some significant issues are: Problem Definition and Statistical Analysis, The Choice between Comparative and Non-comparative Scales, T y p e o f Cate g ory Label s , Number of Categories, Balanced versus Unbalanced Scale, and Forced versus Non-forced Categories

23. There are four levels of measurements: nominal, ordinal, interval, and ratio. The measurement scales, commonly used in marketing research, can be divided into two types; comparative and non-comparative scales. A number of scaling techniques are available for mea s ur e ment o f at t i t ude s . Ther e is n o unique way t ha t you can use to select a particular scaling technique for your research study.

24. Ranking Scales vs. Rating Scales Rating scales and ranking scales are important tools that, while seemingly similar, serve very different learning outcomes. Here is how they work, how they differ, and where they belong in your survey to get the best feedback from your consumers.

25. What is a Rating Scale? Rating scale questions are a variation of multiple choice. They ask the respondent to assign a value to a particular object or subject. Rating scales are close-ended questions that can help you gain quantitative data – information you can measure, hard facts. Rating scales allow you to collect data in a way that is easier to analyze and use.  A Rating scale question is one that seeks respondent feedback in a comparative form for specific features, products or service – “on a scale of 1 to 7 where one means ‘not at all likely’ and seven means ‘extremely likely,’ how likely are you to purchase the product in the next 3 months?"

26. What is a Ranking Scale? Ranking scales offer a different approach to gathering data—these questions ask respondents to compare items to one another , rather than rating them on a common scale. When trying to negotiate which items to remove from your dessert menu, for example, you might ask customers to rank the seven desserts you offer from their most favorite to least favorite, giving you insight into customer preferences.

27. Ranking vs Rating: Which is better?   Ranking and rating scales each have their advantages. They also both have a significant role in a survey. Neither question style can produce the best results on its own.   The most accurate surveys combine both styles of questions, along with open-ended questions. But getting the most out of your survey isn’t just about knowing which type of question to use. It also requires knowing when each style of question is appropriate.

28. Rating Pros and Cons Rating scales are one of the most commonly used survey questions, and for good reason; because rating questions are a variant of multiple-choice, they are often clearer and simpler for respondents to understand.  Rating scales are best to use when you want to measure the performance of something or someone. Questions can vary widely.  How likely are you to recommend our products to a friend or colleague?  Rate your level of satisfaction with our customer service.  To what degree did our onboarding process positively impact your success as an employee?

29. Ranking Pros and Cons The weakness of the ranking scale is also its strength: It forces consumers to place more importance on one item over another. There may be multiple items, however, that consumers value equally. Ranking does not disclose that information.  If you are trying to determine how certain products compare alongside one another, ranking is the perfect way to pose your question. Instead of only gauging the level of satisfaction a consumer has in a single item, ranking allows you to see the unique value of several different items together.