Abstract:
Previous models of leadership have been based on an assumption of face-to-face contact between the leader and the follower. Increasingly, however, advanced information technology is being used by organizations to enable employees to work at a distance from their managers. This deployment of technology is occurring without knowledge of the full extent of its impact on human dynamics. There is little empirical data to identify and explain the factors that contribute to the increased complexity of the remote environment and the relationships and processes through which these factors influence individuals' performance and satisfaction. The current research investigated the relationship between the remote context, perceptions of leadership and individual outcomes. Four studies were conducted, beginning with semi-structured interviews with remotely managed individuals to identify elements in the remote environment that they considered important to outcomes. In the subsequent three studies, an instrument was developed to measure these elements and a model of remote leadership was formulated and tested. Unplanned communication, regularly scheduled communication, prior relationships with one's manager, and individual control beliefs were found to significantly predict perceptions of transformational leadership in the remotely managed group. These relationships differed in the proximally managed group. However, in both groups, perceived transformational leadership predicted job satisfaction, organizational commitment and perceived managerial trust in the individual. Together these studies demonstrated that context matters to a greater degree in the remote environment than in the proximal one, and the process through which this occurs is the perception of transformational leadership. Traditionally, leadership has been viewed as a predictor of outcomes, either directly or through mediational processes. These findings suggest that context rather than leadership style may be the logical starting point for leadership models in the remote environment.