Evaluating Key Predictors of Employee Response to Change in the Pharmaceutical Industry

Evaluating Key Predictors of Employee Response to Change in the Pharmaceutical Industry by Otis Steve Johnson MPA, New York University, 2004 BS, Hunter College of the City University of New York, 2000 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Management Walden University February 2016 Abstract This study addressed the factors that predict employee response to large-scale change in the United States pharmaceutical industry. When poorly executed, major organizational changes such as mergers and acquisitions are often disruptive and costly to organizations and demoralizing to employees. Although employee responses to change have been studied in several industries, employee responses during change execution in theThis study addressed the factors that predict employee response to large-scale change in the United States pharmaceutical industry. When poorly executed, major organizational changes such as mergers and acquisitions are often disruptive and costly to organizations and demoralizing to employees. Although employee responses to change have been studied in several industries, employee responses during change execution in the pharmaceutical industry have not been subject to study. The purpose of this correlational study was to reduce the knowledge gap related to organizational change in the pharmaceutical industry by evaluating key predictors of employee response to large-scale change. The theoretical framework consisted of transformational leadership, stakeholder, and change management theories. The research questions focused on 4 key predictors (initial change reaction, change communication, involvement in change development, and perceived change success) and their effect on 2 primary dependent variables: reaction to change (RC) and support of change (SC). Ninety-eight participants completed the survey and multiple regression was used to measure associations between predictor variables and dependent variables. The 4 independent variables in the aggregate predicted RC and the championing subscale of SC. Individually, none of the independent variables predicted RC, SC, or any of the SC subscales. The study contributes to positive social change by providing leadership with information in guiding creation of a supportive work environment during organizational change and to inspire employees developing medical innovations to fulfill global health needs, while creating skilled jobs and generating profit. Evaluating Key Predictors of Employee Response to Change in the Pharmaceutical Industry by Otis Steve Johnson MPA, New York University, 2004 BS, Hunter College of the City University of New York, 2000 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Management Walden University February 2016 Dedication I dedicate this dissertation to my children, Brianna and Ryan. I hope it inspires them to excel in everything they do. I also dedicate it to my parents, Vernon and Pearline, who made sure I got a good elementary and high school education, despite their limited financial means while raising a large family. I would also like to thank my brothers and sisters because they did not complain when our parents were spending all that they had to ensure I got a good education. To my loving wife, supportive friends, coworkers, instructors, and family, this is for you as well. Acknowledgments I want to thank Dr. Branford McAllister, my dissertation committee chair, for his sound advice and mentoring in quantitative research methods. Dr. McAllister was especially supportive in helping me navigate the various requirements and processes that must be followed. I especially appreciate his knowledge of what is mandatory and his help in negotiating some of the smaller aspects of the process that did not add much value to the quality of my research. In addition to his review activities, Dr. Walter McCollum provided specific suggestions regarding sampling approach that saved me time and frustration, and I would like to say thanks for his practical advice. I would also like to thank Dr. James Stewart, my former chair, and Dr. Nikunja Swain for all the helpful review feedback.