Abstract
Stress is a major problem in the human society, impairing the well-being, health, performance, and productivity of many people worldwide. Most notably, people increasingly experience stress during human-computer interactions because of the ubiquity of and permanent connection to information and communication technologies. This phenomenon is referred to as technostress. Enterprise systems, designed to improve the productivity of organizations, frequently contribute to this technostress and thereby counteract their objective. Based on theoretical foundations and input from exploratory interviews and focus group discussions, the paper presents a design blueprint for stress-sensitive adaptive enterprise systems (SSAESes). A major characteristic of SSAESes is that bio-signals (e.g., heart rate or skin conductance) are integrated as real-time stress measures, with the goal that systems automatically adapt to the users’ stress levels, thereby improving human-computer interactions. Various design interventions on the individual, technological, and organizational levels promise to directly affect stressors or moderate the impact of stressors on important negative effects (e.g., health or performance). However, designing and deploying SSAESes pose significant challenges with respect to technical feasibility, social and ethical acceptability, as well as adoption and use. Considering these challenges, the paper proposes a 4-stage step-by-step implementation approach. With this Research Note on technostress in organizations, the authors seek to stimulate the discussion about a timely and important phenomenon, particularly from a design science research perspective.
Similar content being viewed by others
References
Ahmed MU, Begum S, Funk P, Xiong N, von Scheele B (2011) A multi-module case-based biofeedback system for stress treatment. Artif Intell Med 51(2):107–115
Arnetz BB (1996) Techno-stress: a prospective psychophysiological study of the impact of a controlled stress-reduction program in advanced telecommunication systems design work. J Occup Environ Med 38(1):53–65
Arnetz BB, Berg M (1996) Melatonin and adrenocorticotropic hormone levels in video display unit workers during work and leisure. J Occup Environ Med 38(11):1108–1110
Arnetz BB, Wiholm C (1997) Technological stress: psychophysiological symptoms in modern offices. J Psychosom Res 43(1):35–42
Astor PJ, Adam MTP, Jerčić P, Schaaff K, Weinhardt C (2014) Integrating biosignals into information systems: a NeuroIS tool for improving emotion regulation. J Manag Inf Syst 30(3):247–278
Ayyagari R, Grover V, Purvis R (2011) Technostress: technological antecedents and implications. MIS Q 35(4):831–858
Bakker AB, Demerouti E, Euwema MC (2005) Job resources buffer the impact of job demands on burnout. J Occup Health Psychol 10(2):170–180
Barley SR, Meyerson DE, Grodal S (2011) E-mail as a source and symbol of stress. Organ Sci 22(4):887–906
BBC News Technology (2012) Volkswagen turns off Blackberry email after work hours. http://www.bbc.com/news/technology-16314901. Accessed 28 Mar 2016
Bostock S, Hamer M, Wawrzyniak AJ, Mitchell ES, Steptoe A (2011) Positive emotional style and subjective, cardiovascular, and cortisol responses to acute laboratory stress. Psychoneuroendocrinology 36(8):1175–1183
Bostrom RP, Gupta S, Thomas D (2009) A meta-theory for understanding information systems within sociotechnical systems. J Manag Inf Syst 26(1):17–48
Boucsein W (2009) Forty years of research on system response times: what did we learn from it. In: Schlick CM (ed) Methods and tools of industrial engineering and ergonomics. Springer, Berlin, pp 575–593
Boucsein W, Thum M (1997) Design of work/rest schedules for computer work based on psychophysiological recovery measures. Int J Ind Ergon 20(1):51–57
Brod C (1984) Technostress: the human cost of the computer revolution. Addison-Wesley, Reading
Buettner R, Daxenberger B, Eckhardt A, Maier C (2013) Cognitive workload induced by information systems: introducing an objective way of measuring based on pupillary diameter responses. In: Proceedings of SIGHCI 2013, Paper 20
De Kloet RE, Joels M, Holsboer F (2005) Stress and the brain: from adaptation to disease. Nat Rev Neurosci 6(6):463–475
Denson TF, Spanovic M, Miller N (2009) Cognitive appraisals and emotions predict cortisol and immune responses: a meta-analysis of acute laboratory social stressors and emotion inductions. Psychol Bull 135(6):823–853
Dickerson SS, Kemeny ME (2004) Acute stressors and cortisol responses: a theoretical integration and synthesis of laboratory research. Psychol Bull 130(3):355–391
Djajadiningrat T, Geurts L, Munniksma PR, Christiaansen G, de Bont J (2009) Rationalizer: an emotion mirror for online traders. In: Proceedings of the International Workshop on Design and Semantics of Form and Movement, pp 39–48
Easterby-Smith M, Thorpe R, Lowe A (2002) Management research: an introduction, 2nd edn. Sage, London
Edwards JR (1998) Cybernetic theory of stress, coping, and well-being. In: Cooper CL (ed) Theories of organizational stress. Oxford University Press, Oxford, pp 122–152
Emurian HH (1993) Cardiovascular and electromyograph effects of low and high density work on an interactive information system. Comput Hum Behav 9:353–370
Fairclough SH (2014) Physiological data should remain confidential. Nature 505:263
Fischer T, Riedl R (2015) Theorizing technostress in organizations: a cybernetic approach. In: Proceedings of the 12th International Conference on Wirtschaftsinformatik, Osnabrück, pp 1453–1467
Friend KE (1982) Stress and performance: effects of subjective work load and time urgency. Pers Psychol 35(3):623–633
Gimpel H, Adam MTP, Teubner T (2013a) Emotion regulation in management: harnessing the potential of NeuroIS tools. In: Proceedings of ECIS 2013, Paper 3
Gimpel H, Nißen M, Görlitz R (2013b) Quantifying the quantified self: a study on the motivation of patients to track their own health. In: Proceedings of ICIS 2013
Glaser BG, Strauss AL (1967) The discovery of grounded theory: strategies for qualitative research. Aldine de Gruyter, New York
Gregor S (2009) Building theory in the sciences of the artificial. In: Proceedings of the 9th Design Science Research in Information Systems and Technology (DESRIST), Article 4
Gregor S, Hevner AR (2013) Positioning and presenting design science research for maximum impact. MIS Q 37(2):337–355
Gregory RW, Muntermann J (2011) Theorizing in design science research: inductive versus deductive approaches. In: Proceedings of ICIS 2011, Paper 2
Gurrin C, Smeaton AF, Doherty AR (2014) Lifelogging: personal big data. Found Trends Inf Retr 8(1):1–107
Hakanen JJ, Bakker AB, Schaufeli WB (2006) Burnout and work engagement among teachers. J Sch Psychol 43(6):495–513
Hancock PA, Szalma JL (2007) Stress and neuroergonomics. In: Parasuraman R, Rizzo M (eds) Neuroergonomics: the brain at work. Oxford University Press, New York, pp 195–206
Hancock PA, Warm JS (1989) A dynamic model of stress and sustained attention. Hum Factors 31(5):519–537
Hazlett RL, Benedek J (2007) Measuring emotional valence to understand the user’s experience of software. Int J Hum Comput Stud 65(4):306–314
Hevner AR, March ST, Park J, Ram S (2004) Design science in information systems research. MIS Q 28(1):75–105
Hjortskov N, Rissén D, Blangsted AK, Fallentin N, Lundberg U, Søgaard K (2004) The effect of mental stress on heart rate variability and blood pressure during computer work. Eur J Appl Physiol 92(1–2):84–89
Hudiburg RA, Necessary JR (1996) Coping with computer stress. J Educ Comput Res 15(2):113–124
Johannsson G, Aronsson G (1984) Stress reactions in computerized administrative work. J Organ Behav 5(3):159–181
Kaufman BE (1999) Emotional arousal as a source of bounded rationality. J Econ Behav Organ 38(2):135–144
Knight WEJ, Rickard NS (2001) Relaxing music prevents stress-induced increases in subjective anxiety, systolic blood pressure, and heart rate in healthy males and females. J Music Ther 38(4):254–272
Korunka C, Huemer KH, Litschauer B, Karetta B, Kafka-Lützow A (1996) Working with new technologies: hormone excretion as an indicator for sustained arousal. A pilot study. Biol Psychol 42(3):439–452
Lauterbach J, Kahrau F, Mueller B, Maedche A (2013) Reconceptualizing enterprise systems. In: OASIS Workshop 2013, Milan, IFIP WG 8.2
Lazarus R (1991) Psychological stress in the workplace. J Soc Behav Pers 6(7):1–13
Lazarus RS, Folkman S (1984) Stress, appraisal, and coping. Springer, New York
Léger PM, David FD, Perret J, Dunaway MM (2010) Psychophysiological measures of cognitive absorption. In: Proceedings of SIGHCI 2010, Paper 9
Maier C, Laumer S, Eckhardt A, Weitzel T (2015a) Giving too much social support: social overload on social networking sites. Eur J Inf Syst 24(5):447–464
Maier C, Laumer S, Eckhardt A (2015b) Information technology as daily stressor: pinning down the causes of burnout. J Bus Econ 85(4):349–387
Maier C, Laumer S, Weinert C, Weitzel T (2015c) The effects of technostress and switching stress on discontinued use of social networking services: a study of Facebook use. Inf Syst J 25(3):275–308
Majchrzak A, Rice RE, Malhotra A, King N, Ba S (2000) Technology adaptation: the case of a computer-supported inter-organizational virtual team. MIS Q 24(4):569–600
McEwen BS (2006) Protective and damaging effects of stress mediators: central role of the brain. Dialogues Clin Neurosci 8(4):367–381
Ortiz de Guinea A, Webster J (2013) An investigation of information systems use patterns: technological events as triggers, the effects of time, and consequences for performance. MIS Q 37(4):1165–1188
Partala T, Surakka V (2003) Pupil size variation as an indication of affective processing. Int J Hum Comput Stud 59(1–2):185–198
Peffers K, Tuunanen T, Rothenberger M, Chatterjee S (2007) A design science research methodology for information systems research. J Manag Inf Syst 24(3):45–77
Pelletier CL (2004) The effect of music on decreasing arousal due to stress: a meta-analysis. J Music Ther 41(3):192–214
Picard RW (1997) Affective Computing. MIT Press, Cambridge
Podsakoff NP, LePine JA, 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
Ragu-Nathan TS, Tarafdar M, Ragu-Nathan BS, Tu Q (2008) The consequences of technostress for end users in organizations: conceptual development and empirical validation. Inf Syst Res 19(4):417–433
Riedl R (2013) On the biology of technostress: literature review and research agenda. Data Base Adv Inf Syst 44(1):18–55
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
Riedl R, Kindermann H, Auinger A, Javor A (2013) Computer breakdown as a stress factor during task completion under time pressure: identifying gender differences based on skin conductance. Adv Hum Comput Interact: 1–8 (Article ID 420169)
Riedl R, Davis FD, Hevner AR (2014) Towards a NeuroIS research methodology: intensifying the discussion on methods, tools, and measurement. J Assoc Inf Syst 15(10):Article 4
Rizzo JR, House RJ, Lirtzman SI (1970) Role conflict and ambiguity in complex organizations. Adm Sci Q 15(2):150–163
Salanova M, Llorens S, Cifre E (2013) The dark side of technologies: technostress among users of information and communication technologies. Int J Psychol 48:422–436
Schaaff K, Degen R, Adler N, Adam MTP (2012) Measuring affect using a standard mouse device. Biomed Eng 57(Suppl. 1):761–764
Seddon BPB, Calvert C (2010) A multi-project model of key factors affecting organizational benefits from enterprise systems. MIS Q 34(2):305–328
Sein MK, Henfridsson O, Purao S, Rossi M, Lindgren R (2011) Action design research. MIS Q 35(1):37–56
Strong D, Volkoff O (2010) Understanding organization-enterprise system fit: a path to theorizing the information technology artifact. MIS Q 34(4):731–756
Tams S, Grover V, Thatcher J (2014a) Modern information technology in an old workforce: toward a strategic research agenda. J Strateg Inf Syst 23(4):284–304
Tams S, Hill K, Ortiz de Guinea A, Thatcher J, Grover V (2014b) NeuroIS—alternative or complement to existing methods? Illustrating the holistic effects of neuroscience and self-reported data in the context of technostress research. J Assoc Inf Syst 15(10):Article 1
Tarafdar M, Tu Q, Ragu-Nathan BS, Ragu-Nathan TS (2007) The impact of technostress on role stress and productivity. J Manag Inf Syst 24(1):301–318
Tarafdar M, Tu Q, Ragu-Nathan TS (2010) Impact of technostress on end-user satisfaction and performance. J Manag Inf Syst 27(3):303–334
Tarafdar M, Tu Q, Ragu-Nathan TS, Ragu-Nathan BS (2011) Crossing to the dark side: examining creators, outcomes, and inhibitors of technostress. Commun ACM 54(9):113–120
Tarafdar M, Gupta A, Turel O (2013) The dark side of information technology use. Inf Syst J 23(3):269–275
Tarafdar M, Pullins EB, Ragu-Nathan TS (2015) Technostress: negative effect on performance and possible mitigations. Inf Syst J 25(2):103–132
Trimmel M, Meixner-Pendleton M, Haring S (2003) Stress response caused by system response time when searching for information on the Internet. Hum Factors 45(4):615–621
Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Q 27(3):425–478
vom Brocke J, Riedl R, Léger PM (2013) Application strategies for neuroscience in information systems design science research. J Comput Inf Syst 53(3):1–13
Wastell D, Cooper C (1996) Stress and technological innovation: a comparative study of design practices and implementation strategies. Eur J Work Organ Psychol 5:377–397
Watson HJ (2009) Business intelligence: past, present, and future. In: Proceedings of AMCIS 2009, Paper 153
Weil MM, Rosen LD (1997) Technostress: coping with technology @work @home @play. Wiley, New York
Wolff HG (1953) Stress and disease. Thomas, Springfield
Yerkes RM, Dodson JD (1908) The relation of strength of stimulus to rapidity of habit-formation. J Comp Neurol Psychol 18(5):459–482
Zhai J, Barreto A (2006) Stress recognition using non-invasive technology. In: Proceedings of FLAIRS 2006, pp 395–400
Zhai J, Barreto A, Chin C, Li C (2005) User stress detection in human-computer interactions. Biomed Sci Instrum 41(2):277–286
Author information
Authors and Affiliations
Corresponding author
Additional information
Accepted after three revisions by Prof. Dr. Karagiannis.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Adam, M.T.P., Gimpel, H., Maedche, A. et al. Design Blueprint for Stress-Sensitive Adaptive Enterprise Systems. Bus Inf Syst Eng 59, 277–291 (2017). https://doi.org/10.1007/s12599-016-0451-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12599-016-0451-3