Chapter 12 Discussion Questions Terms In Review 1
Chapter 12 Discussion Questionsterms In Review1discuss The Relative Me
Discuss the relative merits and problems of the following research measurement scales: 1. Rating and ranking scales. 2. Likert and differential scales. 3. Unidimensional and multidimensional scales.
Imagine you work at Menu Foods just before a significant pet food recall. You plan a research study and want to include questions measuring consumer confidence in your company's recovery. Develop a scale for each of these types to assess that confidence: 1. Constant-sum scale. 2. Likert-type summated scale. 3. Semantic differential scale. 4. Stapel scale. 5. Forced ranking scale.
In an employee satisfaction survey, you assess 'job involvement' with two kinds of scales: 1. A graphic rating scale. 2. A multiple rating list. Which scale would you recommend, and why?
You have results from a preference test of four soft drinks from 200 people. The preferences are as follows: Koak (50 people preferred Zip), Zip (150 preferred Pabze), Pabze (45 preferred Mr. Peepers), Mr. Peepers (50 preferred Koak). How do these brands rank overall? Create an interval scale for these four brands based on the data.
Identify issues in scale response term choices using these examples: 1. Yes—Depends—No. 2. Excellent—Good—Fair—Poor. 3. Excellent—Good—Average—Fair—Poor. 4. Strongly Approve—Approve—Uncertain—Disapprove—Strongly Disapprove.
When developing a consumer perception survey of four bicycle brands, determine the appropriate measurement questions, scales, data levels, and quantitative analysis methods for these tasks: 1. Overall assessment of all brands. 2. Comparison across dimensions: styling, durability, gear quality, brand image.
Evaluate a Likert-scale assessing attitudes towards an educational program, with responses from Strongly Agree to Strongly Disagree. How can these responses be used, and what purposes serve each use?
Discuss the importance of the survey introduction for the Albany Outpatient Laser Clinic and design a question to gauge pre-surgery patient attitudes affecting recovery and satisfaction.
Sample Paper For Above instruction
The evaluation of measurement scales and survey design is fundamental to obtaining valid and reliable data in marketing research. This paper discusses various measurement scales, their strengths and limitations, and provides practical examples to illustrate their application in real-world scenarios.
Advantages and Problems of Scales
Rating and ranking scales are commonly used in surveys to quantify consumer preferences (Churchill & Iacobucci, 2009). Rating scales allow respondents to express the intensity of their opinions on a continuum, providing nuanced data (DeVellis, 2016). Ranking scales force respondents to prioritize options, which can reveal relative preferences but may introduce bias or difficulty when many options are involved (Malhotra & Birks, 2007).
Likert scales are popular for measuring attitudes because they facilitate easy aggregation of responses—usually by summation (Kozak & Karpova, 2013). Differential scales, such as semantic differential scales, capture the connotations associated with a concept, offering depth in perceptual data collection (Osgood, Suci, & Tannenbaum, 1957). However, unidimensional scales assess only a single attribute, while multidimensional scales offer a comprehensive view, capturing multiple aspects simultaneously, but they complicate analysis (Hair et al., 2010).
Application to Consumer Confidence
To measure consumer confidence in Menu Foods' recovery efforts, scales must accurately quantify perceptions. A constant-sum scale requires respondents to divide a fixed amount among various attributes, which helps in understanding priority perceptions (Pruyn & Van Riel, 2004). A Likert-type summated scale aggregates individual item responses to produce an overall confidence score (Likert, 1932). Semantic differential scales assess feelings about recovery efforts by rating endpoints on bipolar adjectives (Osgood et al., 1957). Stapel scales, which are unipolar and numeric, can quickly gauge attitudes, while forced ranking compels respondents to compare recovery aspects directly.
Measuring Job Involvement
For employee job involvement, choosing the appropriate scale depends on the desired data level and analysis method. A graphic rating scale can capture intensity but may suffer from central tendency bias (Cohen, 1980). A multiple rating list allows for more detailed preferences or perceptions across different facets. Given the qualitative nature of job involvement, a multi-item scale with Likert responses may offer better reliability and validity by capturing various dimensions (Nunnally & Bernstein, 1994).
Preference Test Interpretation
In the soft drink preference test, Zip emerges as the most preferred brand, followed by Koak, Pabze, and Mr. Peepers, based on the number of preferences received. An interval scale, constructed with Cook and Campbell's (1979) method, could assign numerical values corresponding to preference strength, enabling quantification of the differences among brands.
Response Term Issues
Common problems with response terms include ambiguity and imbalance. For example, 'Yes—Depends—No' may be unclear, as 'Depends' lacks specificity. Likert response options such as 'Excellent—Good—Average—Fair—Poor' are generally consistent but can suffer from central tendency bias unless carefully designed (Carifio & Perla, 2008). Ensuring balanced and clearly defined response options enhances data quality.
Evaluating Bicycle Brands
Developing measurement questions for comparing bicycle brands involves selecting proper scales aligned with data levels. For overall assessment, an interval or ratio scale provides detailed quantitative data, while dimensions like styling or durability can be evaluated through ordinal ratings or Likert scales. Techniques like Analysis of Variance (ANOVA) can analyze differences across brands when data are interval or ratio (Field, 2013).
Attitudinal Survey Analysis
The Likert scale responses can be interpreted in multiple ways. They can be summed to generate an overall attitude score or analyzed individually to assess specific aspects of program perception. Both methods aid in interpreting attitudes, informing program improvements.
Survey Introduction and Question Design
The introduction for the Albany Outpatient Laser Clinic survey should establish trust and clarify purpose, e.g., "Your feedback helps us improve patient care." A pre-surgery attitude question could be: "On a scale from 1 to 10, how confident are you in the effectiveness of the laser treatment?" This quantifies patient expectations influencing recovery (Fink, 2015).
Conclusion
Overall, thoughtful choice of measurement scales and careful survey design are essential for collecting meaningful data. Combining qualitative and quantitative techniques enables researchers to capture complex consumer and employee perceptions, leading to better strategic decisions.
References
- Churchill, G. A., & Iacobucci, D. (2009). Marketing research: Methodological foundations. Cengage Learning.
- Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation: Design & analysis issues for field settings. Houghton Mifflin.
- DeVellis, R. F. (2016). Scale development: Theory and applications. Sage Publications.
- Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
- Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Pearson.
- Kozak, M., & Karpova, E. (2013). Measuring attitudes with Likert scales. Journal of Business Research, 66(7), 878-884.
- Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 1-55.
- Malhotra, N. K., & Birks, D. F. (2007). Marketing research: An applied approach. Pearson Education.
- Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. McGraw-Hill.
- Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning. University of Illinois Press.
- Pruyn, A., & Van Riel, A. C. R. (2004). Understanding the impact of different types of frontline employees’ customer orientation on customer satisfaction and loyalty. Journal of Retailing, 80(4), 273-283.
In conclusion, selecting appropriate measurement scales and carefully designing survey questions are critical to capturing accurate data that reflect true consumer and employee perceptions. Employing a combination of qualitative and quantitative methods enhances the richness of insights gathered, ultimately supporting better decision-making in marketing and organizational strategies.