Skip to main content
SpringerLink
Log in

Information technology as daily stressor: pinning down the causes of burnout

  • Original Paper
  • Published:
Journal of Business Economics Aims and scope Submit manuscript

Abstract

The research presented in this article aims to identify information technology-related stressors in daily work life that might contribute to burnout. We provide a detailed analysis of techno- and work-stressors, techno- and work-exhaustion, as well as the consequences of and interrelations among these perceptions. Techno-stressors and techno-exhaustion are theorized as antecedents of work-stressors, work-exhaustion, and work-related outcomes, such as job satisfaction, organizational commitment, and turnover intention. The proposed model assesses whether using information technology (IT) or other work-stressors cause exhaustion and consequently negative outcomes in terms of low job satisfaction, low organizational commitment, and high turnover intention. The results of an empirical study with 306 employees show that IT usage causes exhaustion because techno-stressors contribute to techno-exhaustion, which in turn influences work-exhaustion significantly. Our results also reveal that work-exhaustion negatively impacts job satisfaction, organizational commitment, and turnover intention, whereas techno-exhaustion only indirectly causes these psychological and behavioral responses through work-exhaustion. Finally, post hoc analyses identify that employees who use IT as a supporting tool for their daily work process (such as HR workers) report higher levels of techno-exhaustion than employees for whom IT is the core of their work (IT professionals, such as software developers).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Ahuja MK, Chudoba KM, Kacmar CJ, McKnight HD, George JF (2007) IT Road Warriors: Balancing work-family conflict, job autonomy, and work overload to mitigate turnover intentions. MIS Q 31(1):1–17

    Google Scholar 

  • Alge BJ (2001) Effects of computer surveillance on perceptions of privacy and procedural justice. J Appl Psychol 84(6):797–804

    Article  Google Scholar 

  • Alter S (2008) Defining information systems as work systems: implications for the IS field. Eur J Inf Syst 17(5):448–469

    Article  Google Scholar 

  • Alter S (2013) Work system theory: overview of core concepts, extensions, and challenges for the future. J Assoc Inf Syst 14(2):72–121

    Google Scholar 

  • Ayyagari R, Grover V, Purvis R (2011) Technostress: technological antecedents and implications. MIS Q 35(4):831–858

    Google Scholar 

  • Bagozzi RP (1979) The role of measurement in theory construction and hypothesis testing: toward a holistic model. In: Ferrell OC, Brown SW, Lamb CW (eds) Conceptual and theoretical developments in marketing. American Marketing Association, Chicago, pp 15–32

    Google Scholar 

  • Barley S, Meyerson D, Grodal S (2011) E-mail as a source and symbol of stress. Organ Sci 22(4):887–906

    Article  Google Scholar 

  • Baron RM, Kenny DA (1986) The moderator–mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51(6):1173–1182

    Article  Google Scholar 

  • Barrick MR, Zimmerman RD (2005) Reducing voluntary, avoidable turnover through selection. J Appl Psychol 90(1):159–166

    Article  Google Scholar 

  • Bartol KM (1983) Turnover among Dp personnel: a casual analysis. Commun ACM 26(10):807–811

    Article  Google Scholar 

  • Campell DT, Fiske DW (1959) Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull 56(2):81–105

    Article  Google Scholar 

  • Carmines EG, Zeller RA (2008) Reliability and validity assessment. Sage Publications, Newbury Park

    Google Scholar 

  • Chawla D, Sondhi N (2011) Assessing work-life balance among indian women professionals. Indian J Ind Relat 47(2):341–352

    Google Scholar 

  • Chin WW (1998) The partial least squares approach to structural equation modeling. In: Marcoulides GA (ed) Modern methods for business research. Erlbaum, Mahwah, pp 295–336

    Google Scholar 

  • Cohen J (1988) Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, Hillsdale

    Google Scholar 

  • de Croon E, Sluiter JK, Blonk RWB, Broersen J, Frings-Dresen M (2004) Stressful work, psychological job strain, and turnover: a 2-year prospective cohort study of truck drivers. J Appl Psychol 89(3):442–454

    Article  Google Scholar 

  • Eckhardt A, Maier C, Büttner R 2012 The influence of pressure to perform and experience on changing perceptions and user performance: a multi-method experimental analysis. Proceedings of the 33rd International Conference on information systems (ICIS), Orlando (FL)

  • Eckhardt A, Maier C, Hsieh JJ, Chuk T, Chan A, Hsiao J, Buettner R 2013 Objective measures of IS usage behavior under conditions of experience and pressure using eye fixation data. Proceedings of the 34th International Conference on information systems (ICIS), Milan

  • Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Article  Google Scholar 

  • Gallo A 2012 Stop email overload. http://blogs.hbr.org/hmu/2012/02/stop-email-overload-1.html

  • Hom PW, Katerberg RHC (1979) Comparative examination of three approaches to the prediction of turnover. J Appl Psychol 64(3):280–290

    Article  Google Scholar 

  • Hoppock R (1935) Job satisfaction. Harper, New York

    Google Scholar 

  • Hulland JS (1999) Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strateg Manag J 20(2):195–204

    Article  Google Scholar 

  • Joseph D, Kok-Yee N, Koh C, Soon A (2007) Turnover of information technology professionals: a narrative review, meta-analytic structural equation modeling, and model development. MIS Q 31(3):547–577

    Google Scholar 

  • Koeske GF, Koeske R (1993) A preliminary test of a stress–strain–outcome model for reconceptualizing the burnout phenomenon. J Soc Serv Resh 17(3–4):107–135

    Article  Google Scholar 

  • Kristensen TS, Borritz M, Villadsen E, Christensen KB (2005) The Copenhagen burnout inventory: a new tool for the assessment of burnout. Work Stress 19(3):192–207

    Article  Google Scholar 

  • Lacity M, Iyer V, Rudramuniyaiah S (2008) Turnover intentions of Indian IS professionals. Inf Syst Front 10(2):225–241

    Article  Google Scholar 

  • Laumer S, Beimborn D, Maier C, Weinert C (2013) Enterprise content management. Bus Inf Syst Eng 5(6):449–452

    Article  Google Scholar 

  • Lee TW, Mitchell TR, Holtom BC, McDaniel LS, Hill JW (1999) The unfolding model of voluntary turnover: a replication and extension. Acad Manag J 42(4):450–462

    Article  Google Scholar 

  • Leiter M, Schaufeli WB (1996) Consistency of the burnout construct across occupations. Anxiety Stress Coping Int J 9(3):229–243

    Article  Google Scholar 

  • Liang H, Saraf N, Hu Q, Xue Y (2007) Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Q 31(1):59–87

    Google Scholar 

  • Locke EA (1969) What is job satisfaction? Org Behav Human Perform 4(4):309–336

    Article  Google Scholar 

  • Maier C, Laumer S, Eckhardt A, Weitzel T 2012 online social networks as a source and symbol of stress: an empirical analysis. Proceedings of the 33rd International Conference on information systems (ICIS), Orlando (FL)

  • Maier C, Laumer S, Weitzel T 2013a Although i am stressed, i still use IT! Theorizing the decisive impact of strain and addiction of social network site users in post-acceptance theory. Proceedings of the 34th International Conference on information systems (ICIS), Milan (Italy)

  • Maier C, Laumer S, Eckhardt A, Weitzel T (2013b) Analyzing the impact of HRIS implementations on HR personnel’s job satisfaction and turnover intention. J Strat Inf Syst 22(3):193–207. doi:10.1016/j.jsis.2012.09.001

    Article  Google Scholar 

  • Maier C, Laumer S, Eckhardt A, Weitzel T (2014) Giving too much social support: social overload on social networking sites. Eur J Inf Syst. doi:10.1057/ejis.2014.3 (advance online publication 4 March 2014)

    Google Scholar 

  • Malhotra NK, Kim SS, Agarwal R (2004) Internet users’ information privacy concerns (IUIPC): the construct, the scale, and a causal model. Inf Syst Res 15(4):336–355

    Article  Google Scholar 

  • March J, Simon H (1958) Organizations. Wiley, New York

    Google Scholar 

  • Maslach C, Leiter M (2008) Early predictors of job burnout and engagement. J Appl Psychol 93(3):498–512

    Article  Google Scholar 

  • Maslach C, Schaufeli WB, Leiter MP (2001) Job burnout. Annu Rev Psychol 52(1):397–422

    Article  Google Scholar 

  • Middelton C, Cukier W (2006) Is mobile email functional or dysfunctional? Two perspectives on mobile email usage. Eur J Inf Syst 15(3):252–260

    Article  Google Scholar 

  • Mitchell TR, Holtom BC, Lee TW, Sablynski CJ, Erez M (2001) Why people stay: using job embeddedness to predict voluntary turnover. Acad Manag J 44(6):1102–1121

    Article  Google Scholar 

  • Moore JE (2000) One road to turnover. an examination of work exhaustion in technology professionals. MIS Q 24(1):141–168

    Article  Google Scholar 

  • Mourmant G, Gallivan MJ, Kalika M (2009) Another road to IT turnover: the entrepreneurial path. Eur J Inf Syst 18(5):498–521

    Article  Google Scholar 

  • Pawlowski SD, Kaganer EA, Cater JJ III (2007) Focusing the research agenda on burnout in IT: social representations of burnout in the profession. Eur J Inf Syst 16(5):612–627

    Article  Google Scholar 

  • Podsakoff PM, MacKenzie SB, Lee J-Y, Podsakoff NP (2003) Common method biases in behavioral research: a critical review and recommended remedies. J Appl Psychol 83(5):879–903

    Article  Google Scholar 

  • Podsakoff NP, LePine J, Lepine MA (2007) Differential challenge stressor-hindrance stressor relationships with job attitudes, turnover intentions, turnover, and withdrawal behavior: a meta-analysis. J Appl Psychol 92(2):438–454

    Article  Google Scholar 

  • Porter LW, Steers RM (1973) Organizational work and personal factors in employee turnover and absenteeism. Psychol Bull 80(2):151–176

    Article  Google Scholar 

  • Preacher KJ, Hayes AF (2004) SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav Res Methods, Instrum Comput 36(4):717–731

    Article  Google Scholar 

  • Ragu-Nathan TS, Tarafdar M, Ragu-Nathan BS, Qiang T (2008) The consequences of technostress for end users in organizations: conceptual development and empirical validation. Inf Syst Res 1(4):417–433

    Article  Google Scholar 

  • Riedl R, Kindermann H, Auinger A, Javor A (2012) Technostress from a neurobiological perspective: system breakdown increases the stress hormone cortisol in computer users. Bus Inf Syst Eng 4(2):61–69

    Article  Google Scholar 

  • Ringle CM, Wende S, Will A (2005) SmartPLS. University of Hamburg, Hamburg

    Google Scholar 

  • Rutner PS, Hardgrave BC, McKnight HD (2008) Emotional dissonance and the information technology professional. MIS Q 32(3):635–652

    Google Scholar 

  • Salanova M, Peiró JM, Schaufeli WB (2002) Self-efficacy specificity and burnout among information technology workers: an extension of the job demand-control model. Eur J Work Organ Psychol 11(1):1–25

    Article  Google Scholar 

  • Schaufeli WB, Leiter M, Kalimo R 1995 The general burnout inventory: a self-report questionnaire to assess burnout at the workplace. Proceedings of the work, stress and health ‘95: creating healthier workplaces, pp 10–23

  • Shirom A, Melamed S (2005) Does burnout affect physical health? A review of the evidence. In: Antoniou A-SG, Cooper CL (eds) Research companion to organizational health psychology. Edward Elgar, Cheltenham, pp 599–622

    Google Scholar 

  • Shrout PE, Bolger N (2002) Mediation in experimental and nonexperimental studies: new procedures and recommedations. Psychol Methods 7(4):422–445

    Article  Google Scholar 

  • Sicking M 2011 Burnout weiter auf dem Vormarsch. http://www.heise.de/resale/artikel/Burnout-weiter-auf-dem-Vormarsch-1230727.html

  • Der Spiegel (2011) Blackberry-pause: VW-Betriebsrat setzt E-Mail-Stopp nach Feierabend durch. http://www.spiegel.de/wirtschaft/service/blackberry-pause-vw-betriebsrat-setzt-e-mail-stopp-nach-feierabend-durch-a-805524.html

  • Süddeutsche Zeitung (2012) Von der Leyen will Arbeitnehmer vor Computerstress schützen. http://www.sueddeutsche.de/karriere/erreichbarkeit-bei-der-arbeit-von-der-leyen-will-arbeitnehmer-vor-computerstress-schuetzen-1.1380168. Accessed 16 November 2012

  • Tarafdar M, Tu Q, Ragu-Nathan TS (2010) Impact of technostress on end-user satisfaction and performance. J Manag Inf Systems 27(3):303–334

    Article  Google Scholar 

  • Tett RP, Meyer JP (1993) Job satisfaction, organizational commitment, turnover intention, and turnover: path analyses based on meta-analytic findings. Pers Psychol 46(2):259–293

    Article  Google Scholar 

  • Thatcher JB, Stepina LP, Boyle RJ (2002) Turnover of information technology workers: examining empirically the influence of attitudes, job characteristics, and external markets. J Manag Inf Syst 19(3):231–250

    Google Scholar 

  • Williams LJ, Edwards J, Vandenberg R (2003) Recent advances in causal modeling methods for organizational and management research. J Manag 29(6):903–936

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Lehrstuhl für Wirtschaftsinformatik, insb. Informationssysteme in Dienstleistungsbereichen, Centre of Human Resources Information Systems, Otto-Friedrich Universität Bamberg, An der Weberei 5, 96047, Bamberg, Germany

    Christian Maier & Sven Laumer

  2. Goethe-Universität Frankfurt am Main, Institut für Wirtschaftsinformatik, Centre of Human Resources Information Systems, Grüneburgplatz 1, 60323, Frankfurt am Main, Germany

    Andreas Eckhardt

Authors
  1. Christian Maier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sven Laumer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andreas Eckhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christian Maier.

Appendix

Appendix

See Tables 10, 11, 12, 13, 14, 15 and 16.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Maier, C., Laumer, S. & Eckhardt, A. Information technology as daily stressor: pinning down the causes of burnout. J Bus Econ 85, 349–387 (2015). https://doi.org/10.1007/s11573-014-0759-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11573-014-0759-8

Keywords

JEL Classification

Search

Navigation