Journal Articles

The Effects of IT-Enabled Supply Chain Process Change on Job and Process Outcomes: A Longitudinal Investigation

2013, Journal of Operations Management

Hillol Bala


Prior research on information technology (IT)-enabled supply chain management (SCM) has primarily focused on macro-level issues (e.g., IT capabilities related to SCM, and SCM design and optimization) and outcomes (e.g., firm performance). There has been limited research that focuses on micro-level outcomes related to employees who actually execute SCM processes in organizations. These employee-level outcomes are important because successful implementation of SCM systems and processes hinges on SCM employees’ support and commitment. I develop and test a model positing that SCM employees’ perceptions of changes in their work process characteristics, i.e., process complexity and process rigidity, following a new SCM system implementation will influence their job outcomes, i.e., job performance, job satisfaction, job anxiety, and job security, and their perceptions of process outcomes, i.e., process performance and relationship quality. The model incorporates a holistic appraisal of the extent of change— change radicalness—as a mechanism between work process characteristics and outcomes. The model is supported in three studies conducted in the context of three different SCM system implementations (N = 278, 282, and 304, respectively). In particular, I found that individuals perceived a significant change in their work process characteristics following an SCM system implementation, and changes in work process characteristics had a significant impact on job and process outcomes. These findings contribute to the information systems and operations management literatures and their intersections by offering insights on challenges related to IT-enabled SCM innovation implementation in organizations.


Bala, H. (2013), “The Effects of IT-Enabled Supply Chain Process Change on Job and Process Outcomes: A Longitudinal Investigation,” Journal of Operations Management, 31(6), pp. 450-473.