Case Study Analysis: Ohio Lottery Research Design

Question 1: Overall Research Design in the Ohio Lottery Case

According to Östlund et al. (2020), a mixed methods research design integrates qualitative and quantitative approaches to provide a comprehensive understanding of the research problem. The research design of the Ohio Lottery assumed a multi-phase structure, which integrated qualitative and quantitative approaches to yield an inclusive view of players and nonplayers. The qualitative MET, a method which disclosed the emotional and psychological drivers, was followed by a quantitative segmentation survey to corroborate the qualitative findings and further develop player classifications. This two-method approach let the Ohio Lottery get further insight into consumer behaviors and attitudes: Case Study Analysis: Ohio Lottery Research Design.

This research design had several advantages. The MET technique was effective in disclosing subconscious motivations—hard to capture with traditional survey methods—and thus particularly suited for understanding the emotional drivers of playing lotteries. Further, the integration of qualitative and quantitative phases ensured that the findings would be rich in detail yet generalizable across the target population, while iterative refinement of the survey instrument improved the relevance and reliability of the data collected.

Still, this had its negative sides to the design. MET required an intensive effort by participants in light of the 90 minutes needed to conduct each interview, considering the length of the quantitative survey, which is around 39 minutes, can also affect participation due to causing fatigue. Increasing phases and agencies also increased the cost of complexity for this research.

From a biblical perspective, Proverbs 16:33 states, “The lot is cast into the lap, but its every decision is from the Lord.” While the Ohio Lottery case study aims to understand the motivations behind lottery participation, it is important to acknowledge that ultimately, the outcome is in the hands of God.

Question 2: Evaluation of the MET Process

The MET, as explained in Exhibit OL-2, asked participants to bring in pictures that best relate to their feelings when engaging in playing the lottery. Coulter et al. (2001) describe the Metaphor Elicitation Technique (MET) as a method that uses visual imagery and metaphors to uncover consumers’ hidden thoughts and feelings about a topic. While using these images, the researchers explored, through a guided interview, its meaning and discovered both rational-emotional associations. Participants portrayed their perceptions by creating eye-catching collages.

The MET process had a number of strengths. Drawing as it did on metaphors and imagery, it tapped participants’ implicit beliefs and emotions to a depth and nuance that standard surveys usually do not achieve. The interactive nature of MET encouraged more elaborate and substantive responses from participants. Additionally, the inclusion of agency staff in the sessions allowed for immediate brainstorming and application of the insights.

Despite these strengths, the MET process was marked by some weaknesses. Image and collage preparation by a participant might induce some biased selections; not everybody might have equal motivation or creativity to conduct the process. Both visual images and stories are open to interpretation, and their detailed analyses would require high interview skills and experience. Only a limited sample size (N=25) was engaged in the research design, which required further follow-up studies for quantified generalizability.

Question 3: Measurement Scales of Sample Questions

The Ohio Lottery’s quantitative survey employed a variety of measurement scales, including Likert scales, as seen in Exhibit OL-3. Joshi et al. (2015) explain that Likert scales are commonly used in surveys to measure respondents’ attitudes, opinions, and perceptions by presenting a series of statements with a range of response options. Both of the scales used, “Lottery Importance Ratings” and “Lottery Attitudinal Ratings,” relied on 7-point scales to measure the perception of, or attitude the respondent had toward various lottery-play attributes.

The use of Likert scales offered several advantages. These scales allow participants to indicate a degree of their agreement or the level of importance of a certain statement, which helps in the segmentation and analysis of data. Ordinal scaling also allows for statistical assessment, including rating averages and tests of dispersion. Only two statements showed problems for the researchers concerning the questions related to the “Lottery Attitude” and “Lottery Importance.”

Participants had to answer abstract issues with these questions about the importance of dream schemes or issues of fairness—all by their nature subjective—and therefore subject to individual understanding. Emotional drivers need highly careful wording in order to be able to be unambiguous survey items. Moreover, variance might come because participants interpret this concept differently.

Question 4: Mapping Quantitative Instrument Content Using Exhibit 12-2

Taherdoost (2022) outlines the key components of a well-designed questionnaire, which include an introduction, instructions, demographic questions, target questions, and classification questions. Using the structure presented in Exhibit 12-2, a quantitative survey administered by the Ohio Lottery would have probably contained most of the elements described. The non-question items would have included an introduction and clear instructions to help participants know what the study was about and how to respond to the questions. Transitions between sections would have facilitated a smooth flow, holding the interest of the participant throughout the relatively long survey.

Demographic and contextual questions of an administrative nature were captured: participant ID, age, gender, income, and frequency of lottery play. Target questions probed specific subjects, including emotional drivers of play, attitudes toward winning, and perceptions of fairness. These questions were to answer the core objectives of the research in terms of what motivates or deters lottery participation. Classification questions further segmented the participants by their behaviors, motivations, and perceptions, thus helping to draw a fine segmentation basis for marketing and strategy development.

Question 5: Scoring Participant Alertness Questions

The survey included control questions to find out who was inattentive, for example, asking about scratch-off ticket denominations that do not exist. Berinsky et al. (2014) discuss the use of attention-check questions in surveys to identify inattentive respondents and improve data quality. This method had several advantages and disadvantages. The advantage of these questions is that they ensure higher quality in the data because they screen out those who are not attentive, hence reducing the possibility of incorrect or misleading data affecting the analysis. It also maintained the integrity of the segmentation process.

Indeed, this had some attendant possible disadvantages, as persons tagged as inattentive might resent their perceived scrutiny or offense. Overuse might simply bore or irritate attentive participants, thereby yielding response biases. Despite such questions being an excellent strategy in ensuring that the integrity of one’s data is sound, they should ideally be used in moderation and notice given to the subject lest adverse responses be elicited from the survey subjects.

Question 6: Evaluation of the MET Discussion Guide

The discussion guide for the MET, as set out in Exhibit OL-2, is an excellent tool with which to elicit in-depth and detailed responses. According to Secomb and Smith (2011), a well-designed discussion guide is crucial for conducting effective qualitative research interviews. The nature of the questions moves developmentally from rapport building to storytelling to collage creation, encouraging participants to delve incrementally deeper into their thoughts and feelings. Probing questions request elaboration, allowing meaningful data collection. What helped make it much better was that it facilitated an orderly and interesting flow of the discussions.

By asking participants to make collages, a creative outlet was provided, which enhanced the quality of, or put some breadth into, the data. However, the guide presented some challenges. Its long, complicated nature required skilled moderators, who would keep participants from tuning out to result in more pertinent and complete data. Furthermore, the subjective responses and visual nature of the outputs required expert in-depth analysis, which has risks of bias or inconsistency.

References

Berinsky, A. J., Margolis, M. F., & Sances, M. W. (2013). Separating the shirkers from the workers? Making sure respondents pay attention on self-administered surveys. American Journal of Political Science, 58(3), 739–753. https://doi.org/10.1111/ajps.12081

Coulter, R. A., Zaltman, G., & Coulter, K. S. (2001). Interpreting consumer perceptions of advertising: An application of the zaltman metaphor elicitation technique. Journal of Advertising, 30(4), 1–21. https://doi.org/10.1080/00913367.2001.10673648

Joshi, A., Kale, S., Chandel, S., & Pal, D. K. (2015). Likert scale: Explored and explained. British Journal of Applied Science & Technology, 7(4), 396–403. https://doi.org/10.9734/BJAST/2015/14975

Östlund, U., Kidd, L., Wengström, Y., & Rowa-Dewar, N. (2020). Combining qualitative and quantitative research within mixed method research designs: A methodological review. International Journal of Nursing Studies, 48(3), 369–383. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094322/

Secomb, J. M., & Smith, C. (2011). A mixed method pilot study: The researchers’ experiences. Contemporary Nurse, 39(1), 31–35. https://doi.org/10.5172/conu.2011.39.1.31

Taherdoost, H. (2022). Designing a questionnaire for a research paper: A comprehensive guide to design and develop an effective questionnaire. Asian Journal of Managerial Science, 11(1), 8–16. https://ajmsjournal.org/index.php/ajms/article/view/3087

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Please answer the following questions from the attached Case Study.

***Each question must be answered using only a peer-reviewed scholarly journal article.

1. Detail the overall research design in the Ohio Lottery case (See Exhibit OL1). What are the advantages and disadvantages of this design?
2. Evaluate the MET process (Exhibit OL-2). What are some of the strengths and weaknesses of the MET technique?
3. What measurement scales are used in the sample questions provided (Exhibit OL-3)? Why might the lottery attitude and lottery importance questions have presented the most challenge to the professional researchers?
4. Using text Exhibit 12-2, map out the likely quantitative instrument content.
5. The survey contained several questions that would alert the researchers that the participant was not taking the research process seriously (see case exhibit OL-3). Is this a good or a poor idea? Why?
6. Evaluate the MET discussion guide for the Ohio Lottery Research.
   

   Case Study Analysis: Ohio Lottery Research Design

The required textbook for this is:

• Schindler, P. S. (2022). Business research methods (14th ed.). McGraw-Hill.