User Resistance Behaviors and Management Strategies in IT-Enabled Change

User Resistance Behaviors and Management Strategies in IT-Enabled Change

Tim Klaus, J. Ellis Blanton, Stephen C. Wingreen
Copyright: © 2015 |Pages: 20
DOI: 10.4018/joeuc.2015010103
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Information Technology (IT) is often used in organizations as a tool to enable change. However, as organizations switch to different vendors, upgrade their systems, or implement new systems, widespread user resistance is often encountered. Resistant behaviors often occur in these large-scale system implementations because the implementation transforms the jobs of employees and mandates system use. In order to understand resistant behaviors better as well as management strategies to minimize these behaviors, this study uses a focus group and qualitative semi-structured interviews. Based on the data collection, this study first creates a resistant behavior framework and a management strategy framework using a data-driven approach. The findings from the user resistance behaviors are classified into four categories. Also, eight preferred management strategies are identified by users, which are grouped into three categories. Then, the Framework-based Theory of User Resistance is proposed, which examines the causes and moderating forces that affect resistant behaviors. The practical implications of these frameworks also are described.
Article Preview
Top

Introduction

Change is a neutral idea which can both positively and negatively affect situations. Strategic decision makers always hope that change will be beneficial to the organization. However, to many employees, a change that benefits an organization often is perceived in a negative manner as it affects an individual’s job and life. This can be due to the change forced upon an employee who is lacking organizational power to protest (i.e., Doolin, 2004; Keen, 1981), the added complexity and workload of learning new skills (Alvarez, 2008), and many other reasons (Hirschheim & Newman, 1988). Thus organizational change often encounters resistant behaviors from individual employees who do not perceive that the benefits of the change outweigh the problems.

To facilitate large-scale organizational change today, managers often use IT. IT-enabled change is when organizational change is facilitated through the use of information technology, such as when processes are reengineered for the purposes of implementing ERP, CRM, and other large systems. These systems are organized around the principles of improved control, standardization, and routinization which make them attractive to top management (Burns, Jung, & Hoffman, 2009). However, organizations that implement a new large-scale system, upgrade their system, or switch to a different system often encounter widespread user resistance.

User resistance has been said to be “at the root of many enterprise software project failures” (Hill, March 26, 2003, p. 1) and it has been found to lead to low return on investment (Maurer, 2002). User resistance is not necessarily a negative characteristic of implementations as it can bring forth problematic issues that need to be addressed by management (Fiorelli & Margolis, 1993). However, whether or not a particular instance of user resistance is negative, it must be better understood by management in order to take action that provides a solution for the issues causing the resistance behaviors.

There are several studies that discuss user resistance behaviors. Shang & Su (2004) identifies three categories of resistance (Non-destructive, Proactively-destructive, and Passively-destructive). Lapointe and Rivard (2005) perhaps has the most extensive discussion on user resistance behaviors, yet the behaviors are conceptualized on only one dimension, ranging from adoption to aggressive resistance (Adoption, Neutrality, Apathy, Passive resistance, Active resistance, and Aggressive resistance). It does not address the issue of a resister with behaviors from multiple categories, nor examine the variations within each category, such as how evident behaviors are to others. An improved conceptualization of user resistance behaviors should lead to a better understanding of user resistance, which is important for managers implementing change.

This study attempts to further understand user resistance behaviors by addressing the following research question:

  • 1.

    How does user resistance manifest itself in a large-scale system implementation?

Through developing and integrating appropriate interventions for the system implementation plan, management strategies are often implemented to resolve the issues causing the user resistance behaviors. Despite many management strategies suggested in a wide range of articles, few studies examine the effect of management strategies on minimizing user resistance. Furthermore, studies looking at management strategies generally do not use a data-driven approach from the perspective of users to determine what management strategies are preferred. This study, however, a data-driven approach, seeking to find themes and categorizing based on what emerges from the qualitative data analysis rather than approaching the data with pre-set ideas and hypotheses (Namey, Guest, Thairu, & Johnson, 2008). Kotter and Schlesinger (1979) discusses management strategies that address resistance to change overall, but does not address the complexities of IT-enabled organizational change.

Therefore, from the perspective of users, the second research question seeks the desired management strategies which users think will minimize the user resistance behaviors that were exhibited:

Complete Article List

Search this Journal:
Reset
Volume 36: 1 Issue (2024)
Volume 35: 3 Issues (2023)
Volume 34: 10 Issues (2022)
Volume 33: 6 Issues (2021)
Volume 32: 4 Issues (2020)
Volume 31: 4 Issues (2019)
Volume 30: 4 Issues (2018)
Volume 29: 4 Issues (2017)
Volume 28: 4 Issues (2016)
Volume 27: 4 Issues (2015)
Volume 26: 4 Issues (2014)
Volume 25: 4 Issues (2013)
Volume 24: 4 Issues (2012)
Volume 23: 4 Issues (2011)
Volume 22: 4 Issues (2010)
Volume 21: 4 Issues (2009)
Volume 20: 4 Issues (2008)
Volume 19: 4 Issues (2007)
Volume 18: 4 Issues (2006)
Volume 17: 4 Issues (2005)
Volume 16: 4 Issues (2004)
Volume 15: 4 Issues (2003)
Volume 14: 4 Issues (2002)
Volume 13: 4 Issues (2001)
Volume 12: 4 Issues (2000)
Volume 11: 4 Issues (1999)
Volume 10: 4 Issues (1998)
Volume 9: 4 Issues (1997)
Volume 8: 4 Issues (1996)
Volume 7: 4 Issues (1995)
Volume 6: 4 Issues (1994)
Volume 5: 4 Issues (1993)
Volume 4: 4 Issues (1992)
Volume 3: 4 Issues (1991)
Volume 2: 4 Issues (1990)
Volume 1: 3 Issues (1989)
View Complete Journal Contents Listing