Role of Human-Computer Interaction Factors as Moderators of Occupational Stress and Work Exhaustion

Software professionals perform boundary-spanning activities, and thus need strong interpersonal, technical, and organizational knowledge to be professionally competent. They have to perform in a demanding work environment characterized by strict deadlines, differing time zones, interdependency in teams, increased interaction with clients, and extended work hours. These characteristics lead to occupational stress and work exhaustion. Yet, the impact of stress is felt in different ways by different people, even if they perform the same functions. These differences in the perception of stress can be caused by varying confidence in their technical capabilities. People possess varying technical capabilities, based on their acquisition of technical skills, comfort level in using the technology, and intrinsic motivation. These attributes represent the human-computer interaction (HCI) personality of software professionals. This article examines whether these HCI factors moderate the relationship between occupational stress and work exhaustion. Data were collected from software professionals located in Chennai and Bangalore in India. The data revealed that HCI factors had a main effect but no significant moderating effects on work exhaustion. The control over the technology variable emerged as the key variable among the HCI factors that affected software professionals' ability to cope with stress and work exhaustion.

[1]  Jacob Cohen,et al.  Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .

[2]  J. Peiró,et al.  Self-efficacy specificity and burnout among information technology workers: An extension of the job demand-control model , 2002 .

[3]  KrasnerHerb,et al.  A field study of the software design process for large systems , 1988 .

[4]  Paul J. Sherman,et al.  Aircrews’ Evaluations of Flight Deck Automation Training and Use: Measuring and Ameliorating Threats to Safety , 1997 .

[5]  T. Kikuchi.  [Psychological stress]. , 2000, Nihon rinsho. Japanese journal of clinical medicine.

[6]  N. Bajpai,et al.  RAISING THE GLOBAL COMPETITIVENESS OF TAMIL NADU ' S INFORMATION TECHNOLOGY INDUSTRY , 1999 .

[7]  Joseph J. Martocchio,et al.  Effects of conceptions of ability on anxiety, self-efficacy, and learning in training. , 1994, The Journal of applied psychology.

[8]  Magid Igbaria,et al.  Determinants of MIS employees' turnover intentions: a structural equation model , 1992, CACM.

[9]  R. Lazarus.  Psychological stress and the coping process , 1970 .

[10]  Bill Curtis,et al.  A field study of the software design process for large systems , 1988, CACM.

[11]  Joseph J. Martocchio,et al.  Microcomputer playfulness: development of a measure with workplace implications , 1992 .

[12]  Magid Igbaria,et al.  The effects of self-efficacy on computer usage , 1995 .

[13]  Jacob Weisberg,et al.  Measuring Workers′ Burnout and Intention to Leave , 1994 .

[14]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[15]  Richard D. Johnson,et al.  The Multilevel and Multifaceted Character of Computer Self-Efficacy: Toward Clarification of the Construct and an Integrative Framework for Research , 1998, Inf. Syst. Res..

[16]  L. Cronbach,et al.  Aptitudes and instructional methods: A handbook for research on interactions , 1977 .

[17]  S. Jex,et al.  Efficacy beliefs as a moderator of the impact of work-related stressors: a multilevel study. , 1999, The Journal of applied psychology.

[18]  Jo Ellen Moore,et al.  Job attitudes and perceptions of exhausted IS/IT professionals: are we burning out valuable human resources? , 1998, SIGCPR '98.

[19]  Marilyn E. Gist,et al.  THE INFLUENCE OF TRAINING METHOD ON SELF‐EFFICACY AND IDEA GENERATION AMONG MANAGERS , 1989 .

[20]  Madeline Weiss,et al.  Effects of Work Stress and Social Support on Information Systems Managers , 1983, MIS Q..

[21]  Denise Potosky,et al.  A field study of computer efficacy beliefs as an outcome of training: the role of computer playfulness, computer knowledge, and performance during training , 2002, Comput. Hum. Behav..

[22]  Jo Ellen Moore,et al.  One Road to Turnover: An Examination of Work Exhaustion in Technology Professionals , 2000, MIS Q..

[23]  Joseph J. Martocchio,et al.  Five-factor model of personality and employee absence , 1997 .

[24]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[25]  Simon S. K. Lam,et al.  Collective efficacy versus self-efficacy in coping responses to stressors and control: a cross-cultural study. , 2000, The Journal of applied psychology.

[26]  Steve M. Jex,et al.  Efficacy beliefs and work stress: An exploratory study , 1992 .

[27]  Harry Rubin,et al.  Motivations and behaviors of software professionals , 1988, SIGCPR '88.

[28]  R. N. Anantharaman,et al.  Development of an instrument to measure stress among software professionals: factor analytic study , 2003, SIGMIS CPR '03.

[29]  Debra L. Nelson,et al.  Individual Adjustment to Information-Driven Technologies: A Critical Review , 1990, MIS Q..

[30]  VenkateshViswanath.  Determinants of Perceived Ease of Use , 2000 .

[31]  Deborah Compeau,et al.  Application of Social Cognitive Theory to Training for Computer Skills , 1995, Inf. Syst. Res..

[32]  J. Ellis Blanton,et al.  The professional development challenge for IT professionals , 2002, CACM.

[33]  Robert Karasek,et al.  Job decision latitude and mental strain: Implications for job redesign , 1979 .

[34]  Felix C. Brodbeck,et al.  Stressor-burnout relationship in software development teams , 1994 .

[35]  I. Ajzen.  The theory of planned behavior , 1991 .

[36]  Kathleen M. Carley.  Organizational Learning and Personnel Turnover , 1992 .

[37]  A. Saks,et al.  Moderating effects of self‐efficacy for the relationship between training method and anxiety and stress reactions of newcomers , 1994 .

[38]  Laura Hall,et al.  Computer self-efficacy, training effectiveness and user attitudes: An empirical study , 1999, Behav. Inf. Technol..

[39]  Deborah Compeau,et al.  Computer Self-Efficacy: Development of a Measure and Initial Test , 1995, MIS Q..

[40]  Viswanath Venkatesh,et al.  Role of Computer Self-Efficacy in Predicting User Acceptance and Use of Information Technology , 1996 .

[41]  R. Vallerand.  Deci and Ryan's self-determination theory: A view from the hierarchical model of intrinsic and extrinsic motivation. , 2000 .

[42]  Thomas Hill,et al.  Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. , 1987 .

[43]  Joseph J. Martocchio,et al.  EFFECTS OF FEEDBACK AND COGNITIVE PLAYFULNESS ON PERFORMANCE IN MICROCOMPUTER SOFTWARE TRAINING , 2006 .

[44]  Edward R. Kemery,et al.  On Using Regression Coefficients to Interpret Moderator Effects , 1990 .

[45]  Marisa Salanova,et al.  Computer training, frequency of usage and burnout: the moderating role of computer self-efficacy , 2000 .

[46]  Marilyn E. Gist,et al.  EFFECTS OF ALTERNATIVE TRAINING METHODS ON SELF-EFFICACY AND PERFORMANCE IN COMPUTER SOFTWARE TRAINING , 1989 .

[47]  Simon S. K. Lam,et al.  Improving group decisions by better pooling information: a comparative advantage of group decision support systems. , 2000, The Journal of applied psychology.