Classification and Analysis of Management and Marketing Data

This work investigates effective methods of statistical analysis for strategic decision making in managerial and marketing applications. The motivation is to bridge the gap between statistics and marketing management by presenting statistical methods that are helpful in classifying segments. Three datasets are analyzed, and statistical methods are applied to solve management and marketing problems. The first portion investigates job seeking behaviors and aims to classify employees as either currently seeking a new position, passive, or not seeking a new position, without directly asking the employee. This provides management with a better understanding of the stability of the organization. The second portion examines leadership behaviors and provides a reliable self-assessment tool for understanding the underlying constructs of leadership behaviors. The third portion addresses resource allocation in a business franchise and differentiates between franchisees with the same level of tenure yet significantly different revenue results. The contribution is the development of a method to effectively allocate franchisor resources.

Dr. Tina M. Facca is an Assistant Professor of Marketing at John Carroll University, Ohio, USA. She earned her Ph.D. in Economics at Göttingen University, Germany. She holds an M.S. Statistics M.A.and a B.A.in Communication.