Technological Change and Employee Motivation in a Telecom Operations Team

Technological Change and Employee Motivation in a Telecom Operations Team by Samuel Ogbonnaya Ude MAPD, Dallas Baptist University, 2008 BSc, University of Nigeria, 1989 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University June 2015 Abstract Some managers view innovative product development and convenient service delivery as necessary to business survival. However, unmotivated employees might negate any gains from the use of innovation. The purpose of this correlational study, grounded in diffusion of innovation theory, was to assess the relationship between creativity and support for innovation, resistance to change, and organizational commitment and employee motivation. A random sample of 81 information technology (IT) professionals from telecom service centers completed an online survey. Simultaneous multiple linear regression was the statistical technique used to analyze these data. The results indicated a poor model with low R to significantly predicted employee motivation, F (3, 78) = 5.481, p < . 002, R = . 174. In the final model, support for creativity and innovation were significant contributors to employees’ motivation. Resistance to change was not a significant predictor to employees’ motivation. Although the p-value was significant, the R was low and indicated a poor model fit. Future researchers might consider incorporating additional variables to make the model more useful. The implications for positive social change include the potential to enhance telecom managers’ understanding of the factors that affect employee motivation; however, managers should consider incorporating additional variables specific to the work environment. Ultimately, a manager’s ability to motivate workers is vital for implementing change, particularly when the introduction of technological innovation frequently occurs within an industry.Some managers view innovative product development and convenient service delivery as necessary to business survival. However, unmotivated employees might negate any gains from the use of innovation. The purpose of this correlational study, grounded in diffusion of innovation theory, was to assess the relationship between creativity and support for innovation, resistance to change, and organizational commitment and employee motivation. A random sample of 81 information technology (IT) professionals from telecom service centers completed an online survey. Simultaneous multiple linear regression was the statistical technique used to analyze these data. The results indicated a poor model with low R to significantly predicted employee motivation, F (3, 78) = 5.481, p < . 002, R = . 174. In the final model, support for creativity and innovation were significant contributors to employees’ motivation. Resistance to change was not a significant predictor to employees’ motivation. Although the p-value was significant, the R was low and indicated a poor model fit. Future researchers might consider incorporating additional variables to make the model more useful. The implications for positive social change include the potential to enhance telecom managers’ understanding of the factors that affect employee motivation; however, managers should consider incorporating additional variables specific to the work environment. Ultimately, a manager’s ability to motivate workers is vital for implementing change, particularly when the introduction of technological innovation frequently occurs within an industry. Technological Change and Employee Motivation in a Telecom Operations Team by Samuel Ogbonnaya Ude MAPD, Dallas Baptist University, 2008 BSc, University of Nigeria, 1989 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Business Administration Walden University June 2015 Dedication The providences and goodwill humbled me throughout this doctoral journey. I dedicate this work to Our Father and God Almighty for keeping me safe and sound throughout my quest for this higher degree. I also dedicate this work to my father, Elder S.K. Ude (deceased) and my uncle, Dr. M.S.C. Nwariaku (deceased) for their unassuming worldviews that shaped me as a person. My loving mother, Edna Ude, whose prayers and love were fundamental to my successes; I dedicate this dissertation to God and my supportive family. Acknowledgments Through my journey of seeking a higher degree, several people picked me up, dusted me off, and righted my path when I gave up all hope of continuing with this doctoral program; because of your persistence, this was possible. Rosy, my beautiful wife and number one cheerleader, thanks for sacrificing a lot for me. I want to acknowledge your love, patience, and support to get me across this finish line, thank you for everything. Sam Obi Ude (Jr) my son, thanks for being supportive throughout this quest. To my siblings, Emmanuel, Charles, Francis, Ezinne, and Nma, I am grateful for your love, prayers, and support. I want to thank my in-laws; Mrs. Helen Lee Martin and Mr. Lonnie Martin; I applaud you for your encouragement, support, and understanding. My enduring thanks to close relatives and friends like Mr. and Mrs. Emma Onyemaechi, Mr. and Mrs. Eke Agbai Eke, Uba Mary Rufus, Julius Nnandilobi, Jean Carter, Ivory Ude, Brandon Martin, and Dr. Marie Bakari, for her inspiration and sisterly love. This dream would not have come true without the outstanding work and dedication of my committee chairperson; special thanks to Dr. Ify Diala, whose guidance, persistence, and rigid instructions for execution of high quality work became the greatest achievement of my lifetime. Thanks for being so magnanimously supportive, helpful, and understanding. Thank you, Dr. Maurice Dawson and Dr. Christos Makrigeorgis, for your unrelenting advice that shaped the outcome of this study. Finally, I acknowledge Dr. Reggie Taylor for his uncanny ability to simplify quantitative techniques; I owe you a debt of gratitude for opening my mind and scope of understanding to statistical techniques.