Data Collection Method One of the methods that will be chosen to collect data for the research project will be the use of a case study. Participants will be carefully selected from organizations in the retail sector. The organizations that will be selected will provide a well-diversified portfolio of both small and large sizes and across multiple product and service offering areas. The aim is to provide a broadened basis of opinion that could potentially allow the study to be expanded towards a broader applicability model for the findings. Once the organizations are established, participants from these organizations will be carefully chosen through a series of interviews to determine their level of trustworthiness and contribution to the study. Each candidate will have three interviews with three different interviewers. Interviewers will ask candidates open-ended questions that will test their trustworthiness and credibility in the study. Interviewers will have a predetermined set of questions that will be asked of the interviewee. Each session will last fifteen to twenty minutes. Once all interviews are completed, the interviewers will discuss the results of each interview with the candidate to choose the best choices. A total of twenty participants will be chosen to be part of the case study and at the end of the process they will be provided with $100 as a gesture of appreciation for their time. Participants will go through a series of three sessions, each lasting one to two hours. Each participant will sign a consent form to ensure compliance with legal protocol. The interviewer will ask open-ended questions so that the participant can provide honest and detailed data analysis software... middle of paper...: an invitation to understanding, detail, intentionality and thoughtfulness. Journal of Family Theory & Review, 4(2), 122-137.Nunan, D. & DiDomenico, M. L. (2013). Market research and big data ethics. International Journal of Market Research, 55(4), 2-13.Padgett, D. K. (2004). The experience of qualitative research. (1st ed.). Belmont, CA: Brooks/Cole Cengage Learning.Silva, J.A., Faria, E.R., Barros, R.C., Hruschka, E.R., De Carvalho, A.P., & Gama, J. (2013). Dataflow clustering: A survey. ACM Computing Surveys, 46(1), 13-13:31. doi:10.1145/2522968.2522981Sweeney, A., Greenwood, K. E., Williams, S., Wykes, T., Rose, D. S. (2013). Listening to the voices of service user researchers in collaborative qualitative data analysis: The case of multiple coding. Health Expectations, 16(4), 89-99. doi:10.1111/j.1369-7625.2012.00810.x