BRM 203 UNIT 3 Scaling & mesurement technique Dr Kanchan.pptx

STUDY MATERIAL FOR MANAGEMENT STUDENTS

1. BUSINESS RESEARCH METHODS UNIT 3 SCALING & MEASUREMENT TECHNIQUES Prof (Dr) KANCHAN KUMARI FACULTY OF MANAGEMENT AND INTERNATIONAL BUSINESS

2. Concept of Measurement Measurement is the process of recording observations collected as part of the research. Scaling, on the other hand, is the assignment of objects to numbers or semantics . These two words merged together refer to the relationship among the assigned objects and the recorded observations. Scaling methods are divided into two main categories, open questions and closed question . Scaling is the process of generating the continuum, a continuous sequence of values, upon which the measured objects are placed. An open question is one in which the respondent does not have to indicate a specific response.

3. Need of Measurement The goal of measurement is to get reliable data with which to answer research questions and assess theories of change . Inaccurate measurement can lead to unreliable data, from which it is difficult to draw valid conclusions. The purposes of measurement can be categorized as measurement being in the service of quality, monitoring, safety, making something fit (design, assembly), and problem solving . We should note that measurement sometimes serves multiple purposes.

4. Problems in measurement in management research Any measure is subject to some degree of imprecision or error which inversely affects reliability . For example, the greater is the degree of imprecision or error, the less accurate the result findings. The errors can be at random, which is less concerning, or systematic known as biases. Common issues in reliability include measurement errors like trait errors and method errors . Issues in validity are maturation, biases, and interaction effects. Four types of reliability are test/retest, alternate-forms, split-half, and interrater reliability. Measurement Error (also called Observational Error) is the difference between a measured quantity and its true value . It includes random error (naturally occurring errors that are to be expected with any experiment) and systematic error (caused by a mis-calibrated instrument that affects all measurements).

5. Problems in measurement in management research – Validity and Reliability Problem in Measurement in Management Research: Validity And Reliability. Problems in Measurement should be precise and unambiguous in an ideal research study. This objective, however, is often not met with in entirety. As such the researcher must be aware about the sources of error in measurement.

6. Levels of measurement – Statisticians often refer to the "levels of measurement" of a variable, a measure, or a scale to distinguish between measured variables that have different properties. There are four basic levels:

7. There are four basic levels of Measurement: Nominal- Gender is an example of a nominal variable because the categories (woman, man, transgender, non-binary, etc.) cannot be ordered from high to low. Olympic medals are an example of an ordinal variable because the categories (gold, silver, bronze) can be ordered from high to low Ordinal- Is age an ordinal variable? Depending on the question, age can be a nominal or ordinal variable . If the question is "How old are you?" it's a nominal variable. If the question is "What age range are you in?" it's an ordinal variable. Interval -An IQ (Intelligence Quotient) score from a standardized test of intelligences is a good example of an interval scale score. IQ scores are derived from a lengthy testing process that requires the participant to complete a number of cognitive tasks. Ratio- All quantitative data fall under the ratio level of measurement. For example, wages, stock price, sales value, age, height, weight, etc. are the real life variable of ratio level measurement. If we say the sales value is 0, then there is no sale

8. Attitude Scaling Techniques An attitude scale is a measurement tool used in psychology and social sciences to assess an individual's attitude toward a particular object, concept, or event . Attitudes refer to the positive or negative evaluations, feelings, or beliefs that individuals hold towards an object or issue. Structured methods including scales are presented as better able to objectively measure attitudes. Specific scaling techniques are outlined, such as graphic rating scales, semantic differential scales, rankings, and multiple item scales including Thurstone and Likert scales . Example: In such studies, attitudes are typically measured using two main types of scales: either Likert Scales, where there are five response categories ranging between two extreme positions, e.g. strongly agree and strongly disagree, or using semantic differential questions, which contain a set of opposites, e.g. easy

9. Concept of Scale Scales of measurement in research and statistics are the different ways in which variables are defined and grouped into different categories . Sometimes called the level of measurement, it describes the nature of the values assigned to the variables in a data set. a scale is a set of numbers that help to measure or quantify objects . A scale on the graph shows the way the numbers or pictures are used in data. Scaling is the branch of measurement that involves the construction of an instrument that associates qualitative constructs with quantitative metric units . Scaling evolved out of efforts in psychology and education to measure “unmeasurable” constructs like authoritarianism and self-esteem.

10. Rating Scales viz. Likert Scales The rating scale is a closed-ended survey question used to represent respondent feedback in a comparative form for specific particular features/products/services . It is one of the most established question types for online and offline surveys where survey respondents are expected to rate an attribute or feature. Likert scaling is a bipolar scaling method , measuring either positive or negative response to a statement. Sometimes an even-point scale is used, where the middle option of "neither agree nor disagree" is not available. This is sometimes called a "forced choice" method, since the neutral option is removed.

11. RATING SCALE

12. LIKERT SCALE

13. Semantic Differential Scales Semantic Differential Scale is a rating scale used to measure the attitudes and opinions of respondents toward an object, person, event, or idea . It uses a set of bipolar adjectives, such as "good-bad," "happy-sad," "strong-weak," etc., placed at opposite ends of a continuum. Example of a semantic differential question? Semantic differential scale questions ask respondents to mark their position on a scale between two opposite adjectives, such as "Good-Bad", "Hot-Cold", "Black-White.“ Use: In its most basic form, a semantic differential scale is a survey you use to conduct a psychological measurement. You can use the scale to understand your audience's approaches, attitudes, and perspectives . Researchers use the survey to allow respondents to express their judgment of a topic on a multi-point scale

14. Constant Sum Scales A constant sum scale is a type of question used in a market research survey in which respondents are required to divide a specific number of points or percents as part of a total sum . The allocation of points are divided to detail the variance and weight of each category Example: With constant sum, the question would be, “ On 100 points, score points on the factors that mean the most to you; be sure to divide your score so that the total adds to 100! ” and the responses you receive from a respondent would be: Price- 60. Location- 10. Ambiance- 5. Use: This is the simplest way to analyze the constant-sum scale data. All you have to do is divide the total number of points of an option by the number of respondents, and you have the mean score . This method provides a more nuanced understanding of how respondents rank the item

15. Ranking Scales A ranking scale forces respondents to rank a list of items with only one selection in each rank . Ranking scale questions often ask respondents to rank based on preference, but you can get creative with your ranking criteria . USE: A rating scale questions allows you to measure strength of response. A ranking scale question allows you to measure priority of options . Using the two in tandem can give you very powerful insights into consumer preferences . Example: Ranking scales are commonly used to identify customer preferences, prioritize product features, and understand the importance of different factors . Here are some examples of ranking scale questions: Please rank the following product features in order of importance. Rank the following brands in order of preference. Fig: Ranking scale questions for survey

16. Paired comparison & Forced Ranking Paired comparison Forced Ranking

17. Paired comparison & Forced Ranking Paired comparison The pairwise comparison method (sometimes called the 'paired comparison method') is a process for ranking or choosing from a group of alternatives by comparing them against each other in pairs , i.e. two alternatives at a time. Paired comparison is the process of comparing a set of options using head-to-head pairs to judge which one is the most preferred overall . Also known as “paired ranking”, it is a popular research method used for ranking people's preferences, informing strategic decisions, and conducting voting at scale. For example, in a paired comparison one compares three food products: (A) the usual freeze-dried form, (B) a new freeze-dried product, (C) the new product, not freeze-dried . Each of the three pairs are tested twice by 13 panellists in two different presentation orders, A–B, B–A, A–C, C–A, B–C, C–B. Forced Ranking Forced ranking is a workforce management tool that compares and ranks employees' performances relative to each other instead of against a pre-determined standard . There are no standards for measuring the performance of the employees, but the comparison is person-to-person. This method is also called as vitality curve. A forced distribution or ranking requires managers to put a designated percentage of staff within each category and this is designed to prevent managers from taking the 'easy option' by rating everyone in the middle (the central tendency bias). Example: Managers typically place a certain share of employees into each category. For example, 20% are rated top performers, 70% are satisfactory performers, and 10% are categorized as low performers .

18. THANK YOU Dr. KANCHAN KUMARI