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Kontextsensitive Assistenzsysteme und Überwachung am Arbeitsplatz: Ein meta-analytisches Review zur Auswirkung elektronischer Überwachung auf Beschäftigte

  • Nils Backhaus
Wissenschaftliche Beiträge

Zusammenfassung

Durch die Zunahme digitalisierter kontextsensitiver Arbeitssysteme besteht vermehrt auch die Möglichkeit, Arbeitsplätze und -tätigkeiten umfassend elektronisch zu überwachen. In diesem Review wird die Frage adressiert, wie sich eine potentielle Überwachung auf Beschäftigte auswirkt. Das Review umfasst 85 Studien zur Auswirkung auf die Outcome-Variablen Leistung, Stress, Belastung und Beanspruchung, Motivation, Zufriedenheit, Vertrauen, Commitment sowie positive und negative Verhaltensweisen und den affektiven Zustand von Beschäftigten. Die Studien werden sowohl qualitativ als auch meta-analytisch aufbereitet. Es zeigen sich heterogene Befunde auf die Leistung der Beschäftigten und überwiegend kleine nachteilige Effekte auf die Stresserleben, Beanspruchung, wahrgenommene Kontrolle, Zufriedenheit, Commitment und Affekt. Daran anknüpfend lässt sich nachzeichnen, dass die nachteiligen Auswirkungen von Überwachung durch eine bewusste Gestaltung und Implementierung der Systeme abgefedert werden können, z. B. durch die Vermeidung von Einzelüberwachung (Überwachungsebene), eine partizipative Einführung unter Beteiligung der Beschäftigten, eine sinnvolle Begründung und ein positives Feedback. Die meisten Studien im Review basieren jedoch auf korrelativen bzw. quasiexperimentellen Designs und erlauben daher nur Aussagen zu Gestaltungshinweisen bzw. -empfehlungen. Für ein gesichertes Gestaltungswissen sind Studien erforderlich, die längsschnittlich angelegt sind und systematische Interventionen, auch im Feld, umfassen.

Praktische Relevanz Durch die Digitalisierung der Arbeitswelt, insbesondere die Einführung vernetzter, intelligenter bzw. kontextsensitiver Systeme, entstehen neue Potentiale zur Überwachung der Beschäftigten. Dieser Aspekt wird bislang noch sehr selten bei der arbeitswissenschaftlichen Gestaltung und Bewertung von Assistenzsystemen berücksichtigt. Der Beitrag sensibilisiert für diese Thematik und verdeutlicht die möglichen Auswirkungen und Risiken von elektronischer Überwachung. Zur Vermeidung negativer Auswirkungen werden praxisnahe Gestaltungshinweise gegeben.

Schlüsselwörter

Elektronische Überwachung am Arbeitsplatz Kontextsensitive Assistenzsysteme Digitalisierung der Arbeitswelt Meta-Analyse/Review 

Context sensitive assistance and the effect of electronic monitoring at work: A meta-analytic review

Abstract

Context-sensitive work systems become more and more popular and may increase the potential for electronic monitoring at the workplace. A scoping review addresses the question how electronic monitoring affects employees. 85 studies are selected with the following outcome variables: performance, stress and strain, work motivation, work satisfaction, trust, commitment, as well as positive and negative behaviors, and the affective states of employees. The studies are summarized both qualitatively and meta-analytically. There are heterogeneous findings for employee’s performance and mostly small adverse effects on subjective stress, perceived control, satisfaction, commitment and affect. Adequate design and implementation of electronic monitoring can reduce the negative impact of electronic monitoring. The personal level of monitoring, participatory introduction, reasonable justification, and positive feedback through monitoring can reduce negative responses to electronic monitoring. However, most studies in the review are based on correlative and quasi-experimental research and therefore only offer design recommendations. For confirmed design knowledge, longitudinal studies and planned interventions (in the field) are required.

Practical Relevance Digitalised working environments, in particular the introduction of interconnected, intelligent, and context-sensitive systems, can lead to an increase of employee monitoring. This aspect is still very rarely taken into account in the design and evaluation of digital assistance systems. The contribution sensitizes to this topic and describes the effects and risks of electronic employee monitoring. In order to avoid negative effects, practical design guidelines are given.

Keywords

Electronic monitoring at the workplace Context sensitive assistance Digitization of work Meta-analytic review 

Notes

Förderung

Das Forschungs- und Entwicklungsprojekt „Arbeitsassistenzsystem für die Individualisierung von Arbeitsgestaltung und Methodentraining (AIM)“ wird mit Mitteln des Bundesministeriums für Bildung und Forschung (BMBF) im Programm „Innovationen für die Produktion, Dienstleistung und Arbeit von morgen“ gefördert (Förderkennzeichen 02L14A162) und vom Projektträger Karlsruhe (PTKA) betreut.

Literatur

  1. Aiello JR, Douthitt EA (2001) Social facilitation from Triplett to electronic performance monitoring. Group Dyn 5:163CrossRefGoogle Scholar
  2. Aiello JR, Kolb KJ (1995) Electronic performance monitoring and social context: impact on productivity and stress. J Appl Psychol 80:339–353CrossRefGoogle Scholar
  3. Aiello JR, Svec CM (1993) Computer monitoring of work performance: extending the social facilitation framework to electronic presence. J Appl Soc Psychol 23:537–548CrossRefGoogle Scholar
  4. Ajunwa I, Crawford K, Schultz J (2017) Limitless worker surveillance. Calif Law Rev 105:735–776Google Scholar
  5. Alder GS, Ambrose ML (2005a) An examination of the effect of computerized performance monitoring feedback on monitoring fairness, performance, and satisfaction. Organ Behav Hum Decis Process 97:161–177CrossRefGoogle Scholar
  6. Alder GS, Ambrose ML (2005b) Towards understanding fairness judgments associated with computer performance monitoring: an integration of the feedback, justice, and monitoring research. Hum Resour Manage Rev 15:43–67CrossRefGoogle Scholar
  7. Alder GS, Noel TW, Ambrose ML (2006) Clarifying the effects of internet monitoring on job attitudes: the mediating role of employee trust. Inf Manage 43:894–903CrossRefGoogle Scholar
  8. Alge BJ (2001) Effects of computer surveillance on perceptions of privacy and procedural justice. J Appl Psychol 86:797–804CrossRefGoogle Scholar
  9. Alge BJ, Hansen D (2014) Workplace monitoring and surveillance since “1984”: a review and agenda. In: Coovert MD, Thompson LF (Hrsg) The psychology of workplace technology. Taylor & Francis, New York, S 209–237Google Scholar
  10. Alge BJ, Ballinger GA, Green SG (2004) Remote control: predictors of electronic monitoring intensity and secrecy. Pers Psychol 57:377–410CrossRefGoogle Scholar
  11. Amick BC, Smith MJ (1992) Stress, computer-based work monitoring and measurement systems: a conceptual overview. Appl Ergon 23:6–16CrossRefGoogle Scholar
  12. Arnaud S, Chandon J‑L (2013) Will monitoring systems kill intrinsic motivation? An empirical study. Rev Gest Ressour Hum 90:35–53Google Scholar
  13. Ayyagari R, Grover V, Purvis R (2011) Technostress: technological antecedents and implications. MIS Q 35:831–858CrossRefGoogle Scholar
  14. Backhaus N (2018a) Review zur Wirkung elektronischer Überwachung am Arbeitsplatz und Gestaltung kontextsensitiver Assistenzsysteme (baua: Bericht). Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, Dortmund, Berlin, DresdenGoogle Scholar
  15. Backhaus N (2018b) Review zur Wirkung elektronischer Überwachung am Arbeitsplatz und Gestaltung kontextsensitiver Assistenzsysteme (Beitrag B.5.1). In: GfA (Hrsg) ARBEIT(s).WISSEN.SCHAF(f)T – Grundlage für Management & Kompetenzentwicklung. Gesellschaft für Arbeitswissenschaft, DortmundGoogle Scholar
  16. Ball K (2010) Workplace surveillance: an overview. Labor Hist 51:87–106CrossRefGoogle Scholar
  17. Bartels LK, Nordstrom CR (2012) Examining big brother’s purpose for using electronic performance monitoring. Perform Improv Q 25:65–77CrossRefGoogle Scholar
  18. BAuA (2014) Leitfaden für die Erarbeitung von Scoping Reviews. Bundesanstalt für Arbeitsschutz und Arbeitsmedizin, DortmundGoogle Scholar
  19. Baumann H, Maschke M (2016) Betriebsvereinbarungen 2015 – Verbreitung und Themen. WSI Mitt 67:223–232CrossRefGoogle Scholar
  20. Becker TE, Marique G (2014) Observer effects without demand characteristics: an inductive investigation of video monitoring and performance. J Bus Psychol 29:541–553CrossRefGoogle Scholar
  21. Bhave DP (2014) The invisible eye? Electronic performance monitoring and employee job performance. Pers Psychol 67:605–635Google Scholar
  22. BMAS (2017) Weißbuch Arbeiten 4.0. BMAS, BerlinGoogle Scholar
  23. Brewer N (1995) The effects of monitoring individual and group performance on the distribution of effort across tasks. J Appl Soc Psychol 25:760–777CrossRefGoogle Scholar
  24. Brewer N, Ridgway T (1998) Effects of supervisory monitoring on productivity and quality of performance. J Exp Psychol Appl 4:211CrossRefGoogle Scholar
  25. Callaghan G, Thompson P (2002) ‘We recruit attitude’: the selection and shaping of routine call centre labour. J Manag Stud 39:233–254CrossRefGoogle Scholar
  26. Caplan RD, Cobb S, French JRP (1975) Job demands and worker health; main effects and occupational differences. National Institute for Occupational Safety and Health, WashingtonCrossRefGoogle Scholar
  27. Carayon P (1993) Effect of electronic performance monitoring on job design and worker stress: review of the literature and conceptual model. Hum Factors 35:385–395CrossRefGoogle Scholar
  28. Carayon‐Sainfort P (1992) The use of computers in offices: impact on task characteristics and worker stress. Int J Hum Comput Interact 4:245–261CrossRefGoogle Scholar
  29. Carpenter D, McLeod A, Hicks C, Maasberg M (2016) Privacy and biometrics: an empirical examination of employee concerns. Inf Syst Front 20:91CrossRefGoogle Scholar
  30. Cascio WF, Montealegre R (2016) How technology is changing work and organizations. Annu Rev Organ Psychol Organ Behav 3:349–375CrossRefGoogle Scholar
  31. Castanheira F, Chambel MJ (2010) Reducing burnout in call centers through HR practices. Hum Resour Manage 49:1047–1065CrossRefGoogle Scholar
  32. Chalykoff J, Kochan TA (1989) Computer-aided monitoring: its influence on employee job satisfaction and turnover. Pers Psychol 42:807–834CrossRefGoogle Scholar
  33. Chang SE, Liu AY, Lin S (2015) Exploring privacy and trust for employee monitoring. Ind Manag Data Syst 115:88–106CrossRefGoogle Scholar
  34. Cohen J (1988) Statistical power analysis for the behavioral sciences, 2. Aufl. Lawrence Erlbaum, HillsdalezbMATHGoogle Scholar
  35. Däubler W (2015) Gläserne Belegschaften? Das Handbuch zum Arbeitnehmerdatenschutz, 6. Aufl. Bund-Verlag, Frankfurt a. M.Google Scholar
  36. Davidson R, Henderson R (2000) Electronic performance monitoring: a laboratory investigation of the influence of monitoring and difficulty on task performance, mood state, and self-reported stress levels. J Appl Soc Psychol 30:906–920CrossRefGoogle Scholar
  37. Day A, Paquet S, Scott N, Hambley L (2012) Perceived information and communication technology (ICT) demands on employee outcomes: the moderating effect of organizational ICT support. J Occup Health Psychol 17:473–491CrossRefGoogle Scholar
  38. Day A, Scott N, Kelloway EK (2010) Information and communication technology: implications for job stress and employee well-being. In: Perrewé PL, Ganster DC (Hrsg) New developments in theoretical and conceptual approaches to job stress, Bd. 8. Emerald Group Publishing, Bingley, S 317–350CrossRefGoogle Scholar
  39. Deery S, Iverson R, Walsh J (2002) Work relationships in telephone call centres: understanding emotional exhaustion and employee withdrawal. J Manag Stud 39:471–496CrossRefGoogle Scholar
  40. DGB-Index Gute Arbeit (2016) DGB-Index Gute Arbeit. Der Report 2016. Wie die Beschäftigten die Arbeitsbedingungen in Deutschland beurteilen. PrintNetwork, ASTOV Vertriebsgesellschaft, BerlinGoogle Scholar
  41. DiTecco D, Cwitco G, Arsenault A, André M (1992) Operator stress and monitoring practices. Appl Ergon 23:29–34CrossRefGoogle Scholar
  42. Douthitt EA, Aiello JR (2001) The role of participation and control in the effects of computer monitoring on fairness perceptions, task satisfaction, and performance. J Appl Psychol 86:867–874CrossRefGoogle Scholar
  43. Eurofound (2018) Employment and working conditions of selected types of platform work. Publication Office of the European Union, Luxemburg (Working Paper)Google Scholar
  44. Fenner DB, Lerch FJ, Kulik CT (1993) The impact of computerized performance monitoring and prior performance knowledge on performance evaluation. J Appl Soc Psychol 23:573–601CrossRefGoogle Scholar
  45. Ferguson GA (1959) Statistical analysis in psychology and education. McGraw-Hill, New YorkGoogle Scholar
  46. Fox S, Spector PE, Miles D (2001) Counterproductive Work Behavior (CWB) in response to job stressors and organizational justice: some mediator and moderator tests for autonomy and emotions. J Vocat Behav 59:291–309CrossRefGoogle Scholar
  47. Galletta D, Grant RA (1995) Silicon supervisors and stress: merging new evidence from the field. Account Manag Inf Technol 5:163–183Google Scholar
  48. Garcia-Ceja E, Osmani V, Mayora O (2016) Automatic stress detection in working environments from smartphones’ accelerometer data: a first step. IEEE J Biomed Health Inform 20:1053–1060CrossRefGoogle Scholar
  49. Gichuhi JK, Ngari JM, Senaji T (2016) Employees’ response to electronic monitoring: the relationship between CCTV surveillance and employees’ engagement. Int J Innov Res Dev 5:141–150Google Scholar
  50. Goomas DT, Ludwig TD (2009) Standardized goals and performance feedback aggregated beyond the work unit: optimizing the use of engineered labor standards and electronic performance monitoring. J Appl Soc Psychol 39:2425–2437CrossRefGoogle Scholar
  51. Grant RA, Higgins CA (1989) Monitoring service workers via computer: the effect on employees, productivity, and service. Natl Prod Rev 8:101–112CrossRefGoogle Scholar
  52. Grant RA, Higgins CA (1991a) Computerized performance monitors: factors affecting acceptance. IEEE Trans Eng Manag 38:306–315CrossRefGoogle Scholar
  53. Grant RA, Higgins CA (1991b) The impact of computerized performance monitoring on service work: testing a causal model. Inf Syst Res 2:116–142CrossRefGoogle Scholar
  54. Greenberg L, Barling J (1999) Predicting employee aggression against coworkers, subordinates and supervisors: the roles of person behaviors and perceived workplace factors. J Organ Behav 20:897–913CrossRefGoogle Scholar
  55. Griffith TL (1993) Monitoring and performance: a comparison of computer and supervisor monitoring. J Appl Soc Psychol 23:549–572CrossRefGoogle Scholar
  56. Hales TR, Sauter SL, Peterson MR, Fine LJ, Putz-Anderson V, Schleifer LR, Bernard BP et al (1994) Musculoskeletal disorders among visual display terminal users in a telecommunications company. Ergonomics 37:1603–1621CrossRefGoogle Scholar
  57. Hedges LV, Olkin I (1985) Statistical methods for meta-analysis. Academic Press, OrlandozbMATHGoogle Scholar
  58. Henderson R, Mahar D, Saliba A, Deane F, Napier R (1998) Electronic monitoring systems: an examination of physiological activity and task performance within a simulated keystroke security and electronic performance monitoring sytem. Int J Hum Comput Stud 48:143–157CrossRefGoogle Scholar
  59. Henle CA, Kohut G, Booth R (2009) Designing electronic use policies to enhance employee perceptions of fairness and to reduce cyberloafing: an empirical test of justice theory. Comput Hum Behav 25:902–910CrossRefGoogle Scholar
  60. Hilgendorf E, Seidel U (2016) Juristische Herausforderungen für digitale Wertschöpfung – strukturierte Lösungswege für KMU. VDI/VDE Innovation + Technik, BerlinGoogle Scholar
  61. Hirsch-Kreinsen H (2016) Zum Verhältnis von Arbeit und Technik bei Industrie 4.0. Polit Zeitgesch 66:10–16Google Scholar
  62. Holland PJ, Cooper B, Hecker R (2015) Electronic monitoring and surveillance in the workplace: the effects on trust in management, and the moderating role of occupational type. Pers Rev 44:161–175CrossRefGoogle Scholar
  63. Holman D (2002) Employee wellbeing in call centres. Hum Resour Manag J 12:35–50CrossRefGoogle Scholar
  64. Holman D, Chissick C, Totterdell P (2002) The effects of performance monitoring on emotional labor and well-being in call centers. Motiv Emot 26:57–81CrossRefGoogle Scholar
  65. Holthaus C, Park Y‑K, Stock-Homburg R (2015) People Analytics und Datenschutz – Ein Widerspruch? Datenschutz Datensicherh 39:676–681CrossRefGoogle Scholar
  66. Hovorka-Mead AD, Ross WH, Whipple T, Renchin MB (2002) Watching the detectives: seasonal student employee reactions to electronic monitoring with and without advance notification. Pers Psychol 55:329–362CrossRefGoogle Scholar
  67. Hugl U (2013) Workplace surveillance examining current instruments, limitations and legal background issues. Tour Manag Stud 9:58–63Google Scholar
  68. Huston TL, Galletta DF, Huston JL (1993) The effects of computer monitoring on employee performance and stress: results of two experimental studies. Proceedings of the 26th Hawaii International Conference on System Sciences, Bd. 4, S 568–574Google Scholar
  69. Introna LD (2000) Workplace surveillance, privacy and distributive justice. ACM SIGCAS Comput Soc 30:33–39CrossRefGoogle Scholar
  70. Jensen JM, Raver JL (2012) When self-management and surveillance collide. Group Organ Manag 37:308–346CrossRefGoogle Scholar
  71. Jeske D, Santuzzi A (2014) Part-time workers’ responses to electronic performance monitoring. Int J Work Cond 8:63–82Google Scholar
  72. Jeske D, Santuzzi AM (2015) Monitoring what and how: psychological implications of electronic performance monitoring. New Technol Work Employ 30:62–78CrossRefGoogle Scholar
  73. Kidwell RE Jr., Bennett N (1994) Employee reactions to electronic control systems. Group Organ Manag 19:203–218CrossRefGoogle Scholar
  74. Kolb KJ, Aiello JR (1996) The effects of electronic performance monitoring on stress: locus of control as a moderator variable. Comput Hum Behav 12:407–423CrossRefGoogle Scholar
  75. Kopp R, Sokoll K (2015) Wearables am Arbeitsplatz – Einfallstore für Alltagsüberwachung? Neue Z Arbeitsr 22:1352–1359Google Scholar
  76. Krause R (2017) Digitalisierung und Beschäftigtendatenschutz. Bundesministerium für Arbeit und Soziales, BerlinGoogle Scholar
  77. Larson JR, Callahan C (1990) Performance monitoring: how it affects work productivity. J Appl Psychol 75:530–538CrossRefGoogle Scholar
  78. Liao EY, Chun H (2016) Supervisor monitoring and subordinate innovation. J Organ Behav 37:168–192CrossRefGoogle Scholar
  79. Lim VKG (2002) The IT way of loafing on the job: cyberloafing, neutralizing and organizational justice. J Organ Behav 23:675–694CrossRefGoogle Scholar
  80. Lu JL (2005) Perceived job stress of women workers in diverse manufacturing industries. Hum Factors Ergon Manuf 15:275–291CrossRefGoogle Scholar
  81. Ludwig TD, Goomas DT (2009) Real-time performance monitoring, goal-setting, and feedback for forklift drivers in a distribution centre. J Occup Organ Psychol 82:391–403CrossRefGoogle Scholar
  82. Mallo J, Nordstrom CR, Bartels LK, Traxler A (2007) The effect of age and task difficulty. Perform Improv Q 20:49–63CrossRefGoogle Scholar
  83. Martin AJ, Wellen JM, Grimmer MR (2016) An eye on your work: how empowerment affects the relationship between electronic surveillance and counterproductive work behaviours. Int J Hum Resour Manag 27:2635–2651CrossRefGoogle Scholar
  84. McNall LA, Roch SG (2009) A social exchange model of employee reactions to electronic performance monitoring. Hum Perf 22:204–224CrossRefGoogle Scholar
  85. McNall LA, Stanton JM (2011) Private eyes are watching you: reactions to location sensing technologies. J Bus Psychol 26:299–309CrossRefGoogle Scholar
  86. Meyer JP, Allen NJ (1991) A three-component conceptualization of organizational commitment. Hum Resour Manage Rev 1:61–89CrossRefGoogle Scholar
  87. Möller J (2015) Verheißung oder Bedrohung? Die Arbeitsmarktwirkungen einer vierten industriellen Revolution (IAB-Discussion Paper): Institut für Arbeitsmarkt- und Berufsforschung (http://doku.iab.de/discussionpapers/2015/dp1815.pdf)Google Scholar
  88. Moorman RH, Wells DL (2003) Can electronic performance monitoring be fair? Exploring relationships among monitoring characteristics, perceived fairness, and job performance. J Leadersh Organ Stud 10:2–16CrossRefGoogle Scholar
  89. Moran S, Nishida T, Nakata K (2013) Perceptions of a wearable ubiquitous monitoring device. IEEE Technol Soc Mag 32:56–64CrossRefGoogle Scholar
  90. Nath ND, Akhavian R, Behzadan AH (2017) Ergonomic analysis of construction worker’s body postures using wearable mobile sensors. Appl Ergon 62:107–117CrossRefGoogle Scholar
  91. Nebeker DM, Tatum BC (1993) The effects of computer monitoring, standards, and rewards on work performance, job satisfaction, and stress. J Appl Soc Psychol 23:508–536CrossRefGoogle Scholar
  92. Nerdinger FW (2014) Arbeitsmotivation und Arbeitszufriedenheit. In: Nerdinger FW, Blickle G, Schaper N (Hrsg) Arbeits- und Organisationspsychologie. Springer, Berlin, Heidelberg, S 419–440Google Scholar
  93. Niehoff BP, Moorman RH (1993) Justice as a mediator of the relationship between methods of monitoring and organizational citizenship behavior. Acad Manage J 36:527–556Google Scholar
  94. Nield D (2014) In corporate wellness programs, wearables take a step forward. Fortune 15.04.2014Google Scholar
  95. O’Donnell AT, Jetten J, Ryan MK (2010) Watching over your own: how surveillance moderates the impact of shared identity on perceptions of leaders and follower behaviour. Eur J Soc Psychol 40:1046–1061CrossRefGoogle Scholar
  96. O’Donnell AT, Ryan MK, Jetten J (2013) The hidden costs of surveillance for performance and helping behaviour. Group Process Intergroup Relat 16:246–256CrossRefGoogle Scholar
  97. Oz E, Glass R, Behling R (1999) Electronic workplace monitoring: what employees think. Omega 27:167–177CrossRefGoogle Scholar
  98. Peterson RA, Brown SP (2005) On the use of beta coefficients in meta-analysis. J Appl Psychol 90:175–181CrossRefGoogle Scholar
  99. Podgórski D, Majchrzycka K, Dąbrowska A, Gralewicz G, Okrasa M (2017) Towards a conceptual framework of OSH risk management in smart working environments based on smart PPE, ambient intelligence and the Internet of Things technologies. Int J Occup Saf Ergon 23:1–20CrossRefGoogle Scholar
  100. Reichardt S (2016) Überwachungsgeschichte(n) – Facetten eines Forschungsfeldes. Gesch Ges 42:5–33CrossRefGoogle Scholar
  101. Rietzschel EF, Slijkhuis M, Van Yperen NW (2014) Close monitoring as a contextual stimulator: How need for structure affects the relation between close monitoring and work outcomes. Eur J Work Organ Psychol 23:394–404CrossRefGoogle Scholar
  102. Rogers KJS, Smith MJ, Sainfort PC (1990) Electronic performance monitoring, job design and psychological stress. Proc Hum Factors Ergon Soc Annu Meet 34:854–858CrossRefGoogle Scholar
  103. Rosenblat A, Kneese T, Boyd D (2014) Workplace surveillance. Data & Society working paper. Data & Society Research Institute, New York City (https://datasociety.net/pubs/fow/WorkplaceSurveillance.pdf)CrossRefGoogle Scholar
  104. Rosenthal R (1994) Parametric measures of effect size. In: Cooper H, Hedges LV (Hrsg) The handbook of research synthesis. SAGE, New York, S 231–244Google Scholar
  105. Roßnagel A, Jandt S, Marschall K (2017) Juristische Aspekte bei der Datenanalyse für Industrie 4.0. In: Vogel-Heuser B, Bauernhansl T, ten Hompel M (Hrsg) Handbuch Industrie 4.0 Bd.2: Automatisierung. Springer, Berlin, Heidelberg, S 491–522CrossRefGoogle Scholar
  106. Roßnagel A, Jandt S, Skistims H, Zirfas J (2012) Datenschutz bei Wearable Computing: Eine juristische Analyse am Beispiel von Schutzanzügen. Springer Vieweg, WiesbadenCrossRefGoogle Scholar
  107. Roth A, Siepmann D (2016) Industrie 4.0 – Ausblick. In: Roth A (Hrsg) Einführung und Umsetzung von Industrie 4.0: Grundlagen, Vorgehensmodell und Use Cases aus der Praxis. Springer, Berlin, Heidelberg, S 247–260CrossRefGoogle Scholar
  108. Rothe H‑J, Debitz U, Metz A‑M (2011) Arbeit in Call-Centern – Arbeit am virtuellen Fließband? In: Bamberg E, Ducki A, Metz A‑M (Hrsg) Gesundheitsförderung und Gesundheitsmanagement in der Arbeitswelt: Ein Handbuch. Hogrefe, Göttingen, S 633–652Google Scholar
  109. Sarpong S, Rees D (2014) Assessing the effects of ‘big brother’ in a workplace: the case of WAST. Eur Manag J 32:216–222CrossRefGoogle Scholar
  110. Scherer KR (2005) What are emotions? And how can they be measured? Soc Sci Inf (Paris) 44:695–729CrossRefGoogle Scholar
  111. Schleifer LM, Amick BC (1989) System response time and method of pay: stress effects in computer‐based tasks. Int J Hum Comput Interact 1:23–39CrossRefGoogle Scholar
  112. Schleifer LM, Galinsky TL, Pan CS (1996) Mood disturbances and musculoskeletal discomfort: effects of electronic performance monitoring under different levels of VDT data‐entry performance. Int J Hum Comput Interact 8:369–384CrossRefGoogle Scholar
  113. Schmidt FA (2016) Arbeitsmärkte in der Plattformökonomie – Zur Funktionsweise und den Herausforderungen von Crowdwork und Gigwork. Friedrich-Ebert-Stiftung, BonnGoogle Scholar
  114. Schoorman FD, Wood MM, Breuer C (2015) Would trust by any other name smell as sweet? Reflections on the meanings and uses of trust across disciplines and context. In: Bornstein BH, Tomkins AJ (Hrsg) Motivating cooperation and compliance with authority. Springer, Cham, S 13–35Google Scholar
  115. Schulz A, Schöllgen I (2017) Emotionsarbeit – Ein Review zu Gestaltungsaussagen. Z Arbeitswiss 71:26–38CrossRefGoogle Scholar
  116. Schwarzer G (2017) Package ‘meta’. https://cran.r-project.org/web/packages/meta/meta.pdf. Zugegriffen: 26. Sept. 2018 (Software)Google Scholar
  117. Schweizer G (2010) „Großer Lauschangriff“ im Call Center – auch ein Arbeitsschutzthema. Gute Arb 22:25–27Google Scholar
  118. Seppänen M, Pajarre E, Kuparinen P (2015) The effects of performance-monitoring technology on privacy and job autonomy. Int J Bus Inf Syst 20:139–156Google Scholar
  119. Sewell G (2012) Organization, employees and surveillance. In: Ball K, Haggerty KD, Lyon D (Hrsg) Routledge handbook of surveillance studies. Routledge, London, New York, S 303–312Google Scholar
  120. Sewell G, Barker JR (2006) Coercion versus care: using irony to make sense of organizational surveillance. Acad Manage Rev 31:934–961CrossRefGoogle Scholar
  121. Sewell G, Barker JR, Nyberg D (2012) Working under intensive surveillance: When does ‘measuring everything that moves’ become intolerable? Hum Relat 65:189–215CrossRefGoogle Scholar
  122. Shahri A, Hosseini M, Phalp K, Taylor J, Ali R (2014) Towards a code of ethics for gamification at enterprise. In: Frank U, Loucopoulos P, Pastor Ó, Petrounias I (Hrsg) The practice of enterprise modeling 7th IFIP WG 8.1 Working Conference, PoEM 2014, Manchester, November 12–13, 2014 Springer, Berlin, Heidelberg, S 235–245CrossRefGoogle Scholar
  123. Sharpe D (1997) Of apples and oranges, file drawers and garbage: why validity issues in meta-analysis will not go away. Clin Psychol Rev 17:881–901CrossRefGoogle Scholar
  124. Smith MJ, Carayon P (1995) New technology, automation, and work organization: stress problems and improved technology implementation strategies. Int J Hum Factors Manuf 5:99–116CrossRefGoogle Scholar
  125. Smith MJ, Carayon P, Sanders KJ, Lim SY, LeGrande D (1992) Employee stress and health complaints in jobs with and without electronic performance monitoring. Appl Ergon 23:17–27CrossRefGoogle Scholar
  126. Spector PE (1986) Perceived control by employees: a meta-analysis of studies concerning autonomy and participation at work. Hum Relat 39:1005–1016CrossRefGoogle Scholar
  127. Spitzmüller C, Stanton JM (2006) Examining employee compliance with organizational surveillance and monitoring. J Occup Organ Psychol 79:245–272CrossRefGoogle Scholar
  128. Spreitzer G, Cameron L, Garrett L (2017) Alternative work arrangements: two images of the new world of work. Annu Rev Organ Psychol Organ Behav 4:473–499CrossRefGoogle Scholar
  129. Sprigg CA, Jackson PR (2006) Call centers as lean service environments: job-related strain and the mediating role of work design. J Occup Health Psychol 11:197–212CrossRefGoogle Scholar
  130. Stanton JM (2000) Traditional and electronic monitoring from an organizational justice perspective. J Bus Psychol 15:129–147CrossRefGoogle Scholar
  131. Stanton JM, Barnes-Farrell JL (1996) Effects of electronic performance monitoring on personal control, task satisfaction, and task performance. J Appl Psychol 81:738CrossRefGoogle Scholar
  132. Stanton JM, Julian AL (2002) The impact of electronic monitoring on quality and quantity of performance. Comput Hum Behav 18:85–101CrossRefGoogle Scholar
  133. Stanton JM, Sarkar-Barney STM (2003) A detailed analysis of task performance with and without computer monitoring. Int J Hum Comput Interact 16:345–366CrossRefGoogle Scholar
  134. Stanton JM, Stam KR (2003) Information technology, privacy, and power within organizations: a view from boundary theory and social exchange perspectives. Surveill Soc 1:152–190CrossRefGoogle Scholar
  135. Stanton JM, Weiss EM (2000) Electronic monitoring in their own words: an exploratory study of employees’ experiences with new types of surveillance. Comput Hum Behav 16:423–440CrossRefGoogle Scholar
  136. Stieglitz S (2015) Gamification – Vorgehen und Anwendung. HMD 52:816–825CrossRefGoogle Scholar
  137. Teucke M, Werthmann D, Lewandowski M, Thoben K‑D (2017) Einsatz mobiler Computersysteme im Rahmen von Industrie 4.0 zur Bewältigung des demografischen Wandels. In: Vogel-Heuser B (Hrsg) Handbuch Industrie 4.0, Bd. 2. Springer, Berlin, Heidelberg, S 575–603CrossRefGoogle Scholar
  138. Varca PE (2006) Telephone surveillance in call centers: prescriptions for reducing strain. Manag Serv Qual 16:290–305CrossRefGoogle Scholar
  139. Visser WA, Rothmann S (2008) Exploring antecedents and consequences of burnout in a call centre: empirical research. SA J Ind Psychol 34:79–87CrossRefGoogle Scholar
  140. de Vries RE, van Gelder J‑L (2015) Explaining workplace delinquency: the role of honesty–humility, ethical culture, and employee surveillance. Pers Individ Dif 86:112–116CrossRefGoogle Scholar
  141. Watkins Allen M, Coopman SJ, Hart JL, Walker KL (2007) Workplace surveillance and managing privacy boundaries. Manag Commun Q 21:172–200CrossRefGoogle Scholar
  142. Watson AM, Foster Thompson L, Rudolph JV, Whelan TJ, Behrend TS, Gissel AL (2013) When big brother is watching: goal orientation shapes reactions to electronic monitoring during online training. J Appl Psychol 98:642–657CrossRefGoogle Scholar
  143. Wellen J, Martin A, Hanson D (2009) The impact of electronic surveillance and workplace empowerment on work attitudes and behaviour. In: Langford PH, Reynolds NJ, Kehoe JE (Hrsg) 8th Industrial and Organisational Psychology Conference. Australian Psychological Society, Sydney, S 145–149Google Scholar
  144. Wells DL, Moorman RH, Werner JM (2007) The impact of the perceived purpose of electronic performance monitoring on an array of attitudinal variables. Hum Resour Dev Q 18:121–138CrossRefGoogle Scholar
  145. Westin AF (1992) Two key factors that belong in a macroergonomic analysis of electronic monitoring: employee perceptions of fairness and the climate of organizational trust or distrust. Appl Ergon 23:35–42CrossRefGoogle Scholar
  146. Workman M (2009) A field study of corporate employee monitoring: attitudes, absenteeism, and the moderating influences of procedural justice perceptions. Inf Organ 19:218–232CrossRefGoogle Scholar
  147. Zimmermann K (2017) Digitalisierung der Produktion durch Industrie 4.0 und ihr Einfluss auf das Arbeiten von morgen. In: Spieß B, Fabisch N (Hrsg) CSR und neue Arbeitswelten: Perspektivwechsel in Zeiten von Nachhaltigkeit, Digitalisierung und Industrie 4.0. Springer, Berlin, Heidelberg, S 53–72Google Scholar
  148. Zweig D, Scott K (2007) When unfairness matters most: supervisory violations of electronic monitoring practices. Hum Resour Manag J 17:227–247CrossRefGoogle Scholar
  149. Zweig D, Webster J (2002) Where is the line between benign and invasive? An examination of psychological barriers to the acceptance of awareness monitoring systems. J Organ Behav 23:605–633CrossRefGoogle Scholar
  150. Zweig D, Webster J (2003) Personality as a moderator of monitoring acceptance. Comput Hum Behav 19:479–493CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature 2018

Authors and Affiliations

  1. 1.Bundesanstalt für Arbeitsschutz und Arbeitsmedizin (BAuA)DortmundDeutschland

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