Design Blueprint for Stress-Sensitive Adaptive Enterprise Systems.

Marc T. P. Adam, Henner Gimpel, Alexander Maedche, René Riedl

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)277-291
Number of pages15
JournalBusiness & Information Systems Engineering
Volume59
Issue number4
DOIs
Publication statusPublished - 1 Aug 2017

Keywords

  • Adaptive automation
  • Affective computing
  • Biofeedback
  • Design science research
  • Enterprise systems
  • NeuroIS
  • Stress
  • Technostress

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