Reference no: EM131869497

Ashia Rallings, CEO of Medical Transport Group

Introduction

The purpose of this memo is to restate the original research problem, build upon methods of data collection, identify any challenges to those methods, and to detail the statistical methods used to evaluate the validity of that data.

Most importantly, this study will address the problem of increased costs associated with operating a fleet of medical supply trucks.This study will assess the various options available for reducing the cost associated with fleet operations for Medical Transport Group.

Methods of Data Collection Used

To begin, a questionnaire willbe administered to leading organizationswithin thetransportation industry. The questionnaire will ask questions concerning cost-saving business practices.

For example, a question may ask whether Medical Transport Group'scompetitors manage their fleets using an in-house fleet manager-which would be coded as 1; an outsourced company-coded as 2);or a combination of both of the two strategies-coded as 3). This data is considered "nominal data"; because it composed of variables that cannot be ordered by rank (Greener, 2008).

Next, the questionnaire will include a series of "yes/no" questions about existing business practices. For example, a question may ask, "Does your organization use telemetric guidance in your route planning?" or "Are your fleet vehicles considered ‘green' by EPA standards?" This data kind is considered dichotomous variables; because it is composed of two opposite variables (Greener, 2008). A "yes" would be coded as "yes 1" and a "no would be coded as "no 2".

Challenges to Data Collection

Interestingly, the most significant challenge to data collection is that in the spirit of competition, the other transportation organizationsmay not accurately describe their business practices. A strategy for overcoming this obstacle, may be to perform a literature review using industry trade publications to determine what the trending best practices are within the industry.

Statistical Methods to Validate Research

Coded responses from the questionnaire willbe documented into a codebook and entered into an Excel spreadsheet for statistical analysis.

Next, the datawill be organized into frequency tables, bar charts, and as measures of central tendency. The frequency tables will display a list of responses from the questionnaire and nominal data will be displayed using bar charts (Greener, 2008).

Once long-term trends are gleaned from the data, a bivariate analysis can be performed to evaluate relationships between the variables.

Based on the nominal data and the dichotomous data collected by the questionnaire, meta-analysis and Cramer's V can be performed to show strength of relationship between the nominal variables. Additionally, phi analysis can be performed to describe the relationship between the "yes/no" dichotomous data responses given in the questionnaire (Greener, 2008).

References

Greener, S. (2008).Business Research Methods. Venture Publishing ApS.