The reason for carrying out this work is to identify the problem of credit sales fraud with our principal focus falling on Milwaukee Marriot Downtown. The primary objectives of this chapter are to come up with a descriptive survey method to collect data from business enterprises in Milwaukee Marriot Downtown regarding the issue of credit sales fraud, describe the sample selection, explain the procedures utilized in designing data collection instruments, and lastly identifying the statistical methods for analyzing the collected data. For this research, the best descriptive research method to use to gather information is the questionnaires. The polls will help in tabling down both open and closed questions to enable the respondents who for this case are a sampled group of Milwaukee Marriot Downtown cashiers to give their views regarding credit fraud as it affects their business.
Research Methodology
A proposed descriptive research methodology is in the form of a survey administered on the Milwaukee Marriot Downtown, which is one of the prestigious hotels in Wisconsin. The term "survey" applies to a research methodology purposed to collect data from a particular population, or just a sample from the population and utilizes questionnaires or interviews as the principal survey instruments. Most researchers use surveys to collect data from various individuals inquiring them to offer their personal views about certain phenomena, their household views or even the opinion of the larger institution. Sample surveys are fundamental tools applicable when collecting information and analyzing the information gathered from different individuals (McLeod, 2014). The sample surveys method is acceptable in research as a tool for performing and applying research methodologies.
Researchers worldwide are familiar with the use of surveys to study issues or trends of different projects. Marketing researchers usually utilize surveys to carry out their research on customer tastes and preferences and the shopping behaviours. Such studies normally consist of standardized methodologies used to collect information by conducting an examination of the systematically targeted samples. In rare cases, social scientists make conclusions before they disaggregate down the sample population findings to subgroups. For instance, the Gallop polls, a project in America examined issues disaggregated by factors such as gender, education, ethnicity, and different regions of the state.
Why the use of Questionnaires?
There are distinct benefits in utilizing questionnaires other than the interview methodology. Firstly, the surveys are less expensive than the personal interviews which are also more time consuming. Moreover, the polls are easy to administer. Nevertheless, the questionnaires offer more confidentiality to the interviewee than personal interviews. Personal interviews typically deal with open-ended questionnaires which are sometimes tough for the respondent to answer. On the other hand, the polls provide more systematic questions that the interviewee can quickly answer. Mailed surveys are efficient when information required should be brief and less costly to the researcher.
Researchers often view questionnaires as a written form of interviews. The researchers carry out inquiries face to face, through email, or telephones. Data collection via surveys is fast and efficient since the researcher administering the questionnaires does not need to be present physically when the interviewee responds to the questions (McLeod, 2014). Often, questionnaires utilize both open and closed queries to gather data. Hence, it is possible to collect both qualitative and quantitative data through the use of surveys. Closed questions enable the respondent to provide the answer that only fits specific categories that the researcher decided in advance. These data that fits into categories is simple data. In closed questions, the researchers limit the group of responses to as few as just two for instance yes, no, male or female. The limits can also include a list of alternatives from which the respondent ought to choose. The defendant's responses should contribute to valid information readily convertible to quantitative data, for example, the total number of yes and no answers.
Closed questions in questionnaires also make available ordinal data which researchers can use to make rankings. This data usually comprises of a rating scale used to value the strengths of attitudes and emotions like, strongly agree/agree/disagree. The closed questions have several advantages. Firstly, the closed questions are economical since they can provide numerous amounts of data at considerably low costs. Secondly, the researchers can obtain data very quickly through closed questions since the respondent usually ticks a box to represent his or her response. Hence, the researcher can get large sample sizes that represent the entire population in a generalized form. Nevertheless, the closed questions are standardized since all the respondents respond to same matters in a similar order. Therefore, it is easy to replicate a questionnaire to check for its reliability. Open questions enable respondents to think and table down their responses in the form of their words. Moreover, the open-ended questions allow the respondent to give detailed answers without limiting them as it is the case in closed questions.
If the researcher requires more detailed replies from the respondents, the closed questions are the preferred form of issues to include in a questionnaire (McLeod, 2014). The open questions can help in getting responses from the staff members of the restaurant regarding their opinions on the credit card security measures at this moment not restricting them to specific answers from which to pick. Besides, the open questions are relevant when the researcher wishes to collect qualitative data since the respondents can elaborate on their responses. Hence, the researcher can comprehend why the defendant chose to give the answer. However, the analysis of open questions is more complicated than the closed questions since in the case of open-ended questions the researcher has to read through the complete answers before categorizing them.
Sample
Stratified random sampling is appropriate to enable the researcher to gain proportionate and meaningful similarities and differences among the selected subgroups among the population (Solanki & Singh, 2015). The sampling theory argues that stratified random sampling is sufficient because the calculated mean of the stratified samples is closer to the average obtained from the entire population. Stratified sampling typically reflects the features of the total population. The sample used for this study focuses on a selected group of the Milwaukee Marriot Downtown cashiers to address the perceptions of the whole restaurant regarding credit sales fraud. Through the administration of well-structured questionnaires, the researcher is bound to gather as much information as possible regarding the credit card operations of the restaurant and their credit card security methods.
Data to be collected
The majority of survey questions are of simple form. Questionnaires provide the respondent with questions structured in such a way that the defendant picks an answer from pre-set conditions. Nominal data comprises of variables that have a variety of options to choose from (Timpany, 2012). Nominal data collection involves both open-ended and closed questions. For example, in our sample survey, the questionnaire should have the section where the sampled cashiers fill in their views regarding various fraud issues. For example, the researcher should collect data about the payment method that the restaurant uses and in this case, they have like three options to choose from for example PayPal, Debit cards or credit cards. Normally the options should be in the form of radio buttons and checkboxes. Also, the questionnaire should provide text boxes for the cashiers to give their responses other than the ones provided. Moreover, the survey ought to query about the type of systems that the restaurant uses, for example, POS, CRM, Online booking. In this case, the respondent can choose from the two or provide a different system in a text box, not in the options given. Also, the questionnaire should provide multiple response questions where the cashiers can pick multiple answers among the options provided.
Besides, the researcher ought to include the issue of the preferred mode of payment for fast foods in the restaurant and for this case two radio buttons are available to choose from that is, cash or credit. Moreover, the questionnaire should comprise of open-ended questions such as the reported cases of fraud in the restaurant. In the response, the respondent is not limited to the amount of information he or she should provide. Nevertheless, information regarding how fast the restaurant responds to cases of credit card fraud is relevant. In the response, the sampled respondents should base his or her answer on whether the restaurant responds within 24 hours or later than 24 hours as provided in the options from which to choose. Also, the questionnaire should comprise of a question inquiring the measures taken by the restaurant to enable they educate the customers on the safety of their credit card information and transactions. The questionnaire should also provide an open-ended question for the respondents to fill any cases of fraud they face other than the ones addressed through the questionnaire (McLeod, 2014).
Analyzing the Collected Data
After the collection of the required data by the researcher, several techniques are relevant to analyze the data gathered from the responses. In this case, data and predictive analysis are suitable since through analysis of data collected from the replies; the researchers can predict future trends and behaviours. Firstly, in data analysis, the nominal data undergoes data analysis using percentages and models to identify the typical responses. Secondly, the findings made after data analysis of the analytical data are taken to the next stage of predictive analysis. The predictive analysis focuses on information extraction from data for use in making predictions and reactions (Jackson, 2009). In this case, the nominal data gathered through the questionnaire is critical in helping to make conclusions regarding current the credit sales fraud issue affecting the hospitality industry, the security measures utilized by most restaurants and the recommended steps to enhance more credit card security.
Through predictive analysis of both quantitative and statistical data obtained from questionnaire responses, the researchers can predict future trends in credit sales fraud and possible measures applicable in future to deal with the same. The concept of predict analysis narrows down to studying the relationship between explanatory and predicted variables from previous occurrences and utilizing them to make predictions about unknown outcomes. The quality of predictive analysis often relies on the data analysis level and the quality of the assumptions made. The use of questionnaires as descriptive survey method enables the researcher to focus on the emotions, experiences and study the responses. Moreover, during the tabling down of the questions, the researcher can direct the data collection and analysis process as he or she plans (Jackson, 2009). Nevertheless, the researcher can collect the required information with well-planned questions at hand. Through a proper arrangement of research questions, the researcher can receive large amounts of information.
References
Jackson, S.L. (2009). Research Methods and Statistics: A Critical Thinking Approach 3rd edition. Belmont, CA: Wadsworth.
McLeod, S. A. (2014). Questionnaires. Retrieved from www.simplypsychology.org/questionnaires.html
Solanki, R., & Singh, H. (2015). Efficient classes of estimators in stratified random sampling. Statistical Papers, 56(1), 83-103. doi:10.1007/s00362-013-0567-1
Timpany, G. (2012). Data Types: Using Nominal Data in Survey Research. inQuisium BLOG. Retrieved 24 July 2016, from http://survey.cvent.com/blog/customer-insights-2/data-types-using-nominal-data-in-survey-research
