IS

Kacmar, Charles J.

Topic Weight Topic Terms
0.593 job employees satisfaction work role turnover employee organizations organizational information ambiguity characteristics personnel stress professionals
0.198 model research data results study using theoretical influence findings theory support implications test collected tested
0.105 offshore offshoring client projects locations organizational vendor extra cultural problems services home sites two-stage arrangements

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Ahuja, Manju K. 1 Chudoba, Katherine M. 1 George, Joey F. 1 McKnight, D. Harrison 1
autonomy 1 fairness 1 IT personnel 1 organizational commitment 1
road warrior 1 Turnover 1 turnover intention 1 work–family conflict 1
work overload 1 work exhaustion 1

Articles (1)

IT ROAD WARRIORS: BALANCING WORK--FAMILY CONFLICT, JOB AUTONOMY, AND WORK OVERLOAD TO MITIGATE TURNOVER INTENTIONS. (MIS Quarterly, 2007)
Authors: Abstract:
    This study examines the antecedents of turnover intention among information technology road warriors. Road warriors are IT professionals who spend most of their workweek away from home at a client site. Building on Moore's (2000) work on turnover intention, this article develops and tests a model that is context-specific to the road warrior situation. The model highlights the effects of work--family conflict and job autonomy, factors especially applicable to the road warrior's circumstances. Data were gathered from a company in the computer and software services industry. This study provides empirical evidence for the effects of work--family conflict, perceived work overload, fairness of rewards, and job autonomy on organizational commitment and work exhaustion for road warriors. The results suggest that work--family conflict is a key source of stress among IT road warriors because they have to juggle family and job duties as they work at distant client sites during the week. These findings suggest that the context of the IT worker matters to turnover intention, and that models that are adaptive to the work context will more effectively predict and explain turnover intention.