European Journal of Information Systems

, Volume 26, Issue 5, pp 451–468 | Cite as

Service robots in hospitals: new perspectives on niche evolution and technology affordances

  • Tobias Mettler
  • Michaela Sprenger
  • Robert Winter
Empirical Research


Changing demands in society and the limited capabilities of health systems have paved the way for robots to move out of industrial contexts and enter more human-centered environments such as health care. We explore the shared beliefs and concerns of health workers on the introduction of autonomously operating service robots in hospitals or professional care facilities. By means of Q-methodology, a mixed research approach specifically designed for studying subjective thought patterns, we identify five potential end-user niches, each of which perceives different affordances and outcomes from using service robots in their working environment. Our findings allow for better understanding resistance and susceptibility of different users in a hospital and encourage managerial awareness of varying demands, needs, and surrounding conditions that a service robot must contend with. We also discuss general insights into presenting the Q-methodology results and how an affordance-based view could inform the adoption, appropriation, and adaptation of emerging technologies.


health information technology IT affordance materiality mixed methods niche evolution Q-methodology service robots 



The authors wish to thank the editors and reviewers of this paper for their insightful comments that have greatly improved its content and presentation. They also want to extend their gratitude to the Swiss Academy of Engineering Sciences and the Swiss Informatics Society for their financial support.


  1. Ahn HS, Kuo I-H, Datta C, Stafford R, Kerse N, Peri K, Broadbent E and Macdonald BA (2014) Design of a kiosk type healthcare robot system for older people in private and public places. In Simulation, modeling, and programming for autonomous robots (Brugali D, Broenink JF, Kroeger T and Macdonald BA, Eds), pp 578–589, Springer, Cham.Google Scholar
  2. Al-Natour S and Benbasat I (2009) The adoption and use of IT artifacts: a new interaction-centric model for the study of user-artifact relationships. Journal of the Association for Information Systems 10(9), 661–685.Google Scholar
  3. Alves-Oliveira P, Petisca S, Correia F, Maia N and Paiva A (2015) Social robots for older adults: framework of activities for aging in place with robots. In Social robotics (Tapus A, André E, Martin J-C, Ferland F and Ammi M, Eds), pp 11–20, Springer, Cham.Google Scholar
  4. Baker R, Wildman J, Mason H and Donaldson C (2014) Q-ing for health—a new approach to eliciting the public’s views on health care resource allocation. Health Economics 23(3), 283–297.CrossRefGoogle Scholar
  5. Barentsen K and Trettvik J (2002) An activitiy theory approach to affordance. Proceedings of the 2nd Nordic Conference on Human-Computer Interaction, Aarhus, Denmark, pp 51–60.Google Scholar
  6. Barrett M, Oborn E, Orlikowski WJ and Yates J (2012) Reconfiguring boundary relations: robotic innovations in pharmacy work. Organization Science 23(5), 1448–1466.CrossRefGoogle Scholar
  7. Battilana J, Leca B and Boxenbaum E (2009) How actors change institutions: towards a theory of institutional entrepreneurship. The Academy of Management Annals 3(1), 65–107.CrossRefGoogle Scholar
  8. Bepko JR RJ, Moore JR and Coleman JR (2009) Implementation of a pharmacy automation system (robotics) to ensure medication safety at Norwalk hospital. Quality Management in Healthcare 18(2), 103–114.Google Scholar
  9. Berlinger NT (2006) Robotic surgery—squeezing into tight places. New England Journal of Medicine 354(20), 2099–2101.CrossRefGoogle Scholar
  10. Bertelsen OW (2006) Tertiary artifacts at the interface. In Aesthetic computing (Fishwick PA, Ed), pp 357–368, MIT Press, Cambridge, MA.Google Scholar
  11. Best ML, Smyth TN, Etherton J and Wornyo E (2010) Uses of mobile phones in post-conflict Liberia. Information Technologies and International Development 6(2), 91–108.Google Scholar
  12. Bhattacherjee A and Hikmet N (2007) Physicians’ resistance toward healthcare information technology: a theoretical model and empirical test. European Journal of Information Systems Journal 16(6), 725–737.CrossRefGoogle Scholar
  13. Bodner J, Wykypiel H, Wetscher G and Schmid T (2004) First experiences with the da Vinci operating robot in thoracic surgery. European Journal of Cardio-theracic Surgery 25(5), 844–851.CrossRefGoogle Scholar
  14. Bouchard T (1976) Field research methods: interviewing, questionnaires, participant observation, systematic observation, unobtrusive measures. In Handbook of industrial and organisational psychology (Dunnette M, Ed), pp 363–413, Rand NcNally, Chicago.Google Scholar
  15. Bouwman H, Bejar A and Nikou S (2012) Mobile services put in context: a Q-sort analysis. Telematics and Informatics 29(1), 66–81.CrossRefGoogle Scholar
  16. Broadbent E, Stafford R and Macdonald B (2009) Acceptance of healthcare robots for the older population: review and future directions. International Journal of Social Robotics 1(4), 319–330.CrossRefGoogle Scholar
  17. Brown SR (1993) A primer on Q methodology. Operant Subjectivity 16(3/4), 91–138.Google Scholar
  18. Bygstad B, Munkvold BE and Volkoff O (2016) Identifying generative mechanisms through affordances: a framework for critical realist data analysis. Journal of Information Technology 31(1), 83–96.CrossRefGoogle Scholar
  19. Cepolina FE and Muscolo GG (2014) Design of a robot for hygienization of walls in hospital environments. Proceedings of the 41st International Symposium on Robotics, Munich, Germany, pp 1–7.Google Scholar
  20. Chamero A (2011) Radical embodied cognitive science. MIT Press, Cambridge, MA.Google Scholar
  21. Cooper RB and Zmud RW (1990) Information technology implementation research: a technological diffusion approach. Management Science 36(2), 123–139.CrossRefGoogle Scholar
  22. Costall A (1997) The meaning of things. Social Analysis: The International Journal of Social and Cultural Practice 41(1), 76–85.Google Scholar
  23. Creed Wed, DeJordy R and Lok J (2010) Being the change: resolving institutional contradiction through identity work. Academy of Management Journal 53(6), 1336–1364.CrossRefGoogle Scholar
  24. Davern M, Shaft T and Te’eni D (2012) Cognition matters: enduring questions in cognitive is research. Journal of the Association for Information Systems 13(4), 273–314.Google Scholar
  25. Deery J (1997) Courier robot keeps hospital staff ‘on the job. Journal For Healthcare Quality: Official Publication of the National Association for Healthcare Quality 19(1), 22–23.CrossRefGoogle Scholar
  26. Demir R (2015) Strategic activity as bundled affordances. British Journal of Management 26(S1), S125–S141.CrossRefGoogle Scholar
  27. Dennis KE (1988) Q-methodology: new perspectives on estimating reliability and validity. In Measurement of nursing outcomes (Strickland OL and Waltz CF, Eds), pp 409–419, Springer, New York.Google Scholar
  28. Diprose JP, Plimmer B, Macdonald BA and Hosking JG (2012) How people naturally describe robot behaviour. Proceedings of the Australasian Conference on Robotics and Automation, Wellington, New Zealand, pp. 1–9.Google Scholar
  29. Donner J (2004) Microentrepreneurs and mobiles: an exploration of the uses of mobile phones by small business owners in Rwanda. The Massachusetts Institute of Technology Information Technologies and International Development 2(1), 1–21.CrossRefGoogle Scholar
  30. Doolin B (2004) Power and resistance in the implementation of a medical management information system. Information Systems Journal 14(4), 343–362.CrossRefGoogle Scholar
  31. Faraj S. and Azad B (2012) The materiality of technology: an affordance perspective. In Materiality and Organizing: Social Interaction in a Technological World (Leonardi PM, Nardi BA and Kallinikos J, Eds), pp 237–258, Oxford University Press, Oxford.Google Scholar
  32. Forbes (2014) Top 20 technologies that will change our lives: next up – Digital medicine.
  33. Garmann-Johnsen NF, Mettler T and Sprenger M (2014) Service robotics in healthcare: A perspective for information systems researchers? In: Proceedings of the 35th International Conference on Information Systems, Auckland, New Zealand, pp 1–12.Google Scholar
  34. Gibson JJ (1979) The ecological approach to visual perception. Houghton Mifflin, Boston.Google Scholar
  35. Goh JM, Gao G and Agarwal R (2011) Evolving work routines: adaptive routinization of information technology in healthcare. Information Systems Research 22(3), 565–585.CrossRefGoogle Scholar
  36. Guest G, Bunce A and Johnson L (2006) How many interviews are enough?: an experiment with data saturation and variability. Field Methods 18(1), 59–82.CrossRefGoogle Scholar
  37. Hafermalz E, Hovorka DS and Riemer K (2015) Shared secret places: social media and affordances. Proceedings of the 26th Australasian Conference on Information Systems, Adelaide, Australia, pp 1–11.Google Scholar
  38. Hagele M (2016) Robots conquer the world [turning point]. IEEE Robotics and Automation Magazine 23(1), 120–118.CrossRefGoogle Scholar
  39. Haidegger T, Barreto M, Gonçalves P, Habibe M, Ragavanf SKV, Li H, Vaccarella A, Perrone R and Prestes E (2013) Applied ontologies and standards for service robots. Robotics and Autonomous Systems 61(11), 1215–1223.CrossRefGoogle Scholar
  40. Hedberg A and Morosi M (2015) Keeping health high on the eu agenda: Role for economic governance?, European Policy Centre, Brussels, Belgium.Google Scholar
  41. Idc (2015) Annual IT spending by western european healthcare providers to reach $14.6 billion by 2018. IDC, London.Google Scholar
  42. Iivari J, Isomäki H and Pekkola S (2010) The user – the great unknown of systems development: reasons, forms, challenges, experiences and intellectual contributions of user involvement. Information Systems Journal 20(2), 109–117.CrossRefGoogle Scholar
  43. International Federation of Robotics (2016) Definition of service robots.
  44. International Standardization Organization (2016) Robots and robotic devices – vocabulary.
  45. Jayawardena C, Kuo IH, Broadbent E and Macdonald BA (2014) Socially assistive robot healthbot: design, implementation, and field trials. IEEE Systems Journal 10(3), 1056–1067.CrossRefGoogle Scholar
  46. Joint Institute for Innovation Policy of the European Commission (2012) Investigating in research and innovation for grand challenges.
  47. Kane GC, Fichman RG, Gallaugher J and Glaser J (2009) Community relations 2.0. Harvard Business Review, 87 (11), 45–50.Google Scholar
  48. Kim H-W and Kankanhalli A (2009) Investigating user resistance to information systems implementation: a status quo bias perspective. MIS Quarterly 33(3), 567–582.Google Scholar
  49. Kirschling TE, Rough SS and Ludwig BC (2009) Determining the feasibility of robotic courier medication delivery in a hospital setting. American Journal of Health-System Pharmacy 66(19), 1754–1762.CrossRefGoogle Scholar
  50. Klaus T, Wingreen SC and Blanton JE (2010) Resistant groups in enterprise system implementations: A Q-methodology examination. Journal of Information Technology 25(1), 91–106.CrossRefGoogle Scholar
  51. Kuo IH, Rabindran JM, Broadbent Y, Lee YI, Kerse N, Stafford RMQ and Macdonald BA (2009) Age and gender factors in user acceptance of healthcare robots. Proceedings of the 18th IEEE International Symposium on Robot and Human Interactive Communication, Toyama, Japan, pp 214–219.Google Scholar
  52. Lanamäki A, Thapa D and Stendal K (2016) When is an affordance? Outlining four stances. Proceedings of the IFIP WG 8.2 Working Conference on Information Systems and Organizations, Dublin, Ireland, pp 125–139.Google Scholar
  53. Leonardi PM (2011) When flexible routines meet flexible technologies: affordance, constraint, and the imbrication of human and material agencies. MIS Quarterly 35(1), 147–176.Google Scholar
  54. Leonardi PM (2013) Theoretical foundations for the study of sociomateriality. Information and Organization 23(2), 59–76.CrossRefGoogle Scholar
  55. Li R, Wang S, Deng H, Wang R and Chang KC (2012) Towards social user profiling: unified and discriminative influence model for inferring home locations. Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Bejing, China, pp 1023–1031.Google Scholar
  56. Ljungblad S, Kotrbova J, Jacobsson M, Cramer H and Niechwiadowicz K (2012) Hospital robot at work: something alien or an intelligent colleague? Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work, Seattle, WA, pp 177–186.Google Scholar
  57. Magnani L (2008) Chances, affordances, niche construction. In Knowledge-based intelligent information and engineering systems (Lovrek I, Howlett RJ and Jain LC, Eds), pp 719–726, Springer, Berlin.Google Scholar
  58. Majchrzak A and Markus ML (2012) Technology affordances and constraints in management information systems. In Encyclopedia of Management Theory (Kessler E, Ed.), pp 832–836, Sage, London.Google Scholar
  59. McKeown B and Thomas D (1988) Q methodology. Sage Publications, Beverly Hills, CA.CrossRefGoogle Scholar
  60. Mesgari M and Okoli C (2015) Ecological approach to user sensemaking of technology. Proceedings of the 36th International Conference on Information Systems, Fort Worth, TX, pp 1–12.Google Scholar
  61. Mettler T and Raptis DA (2012) What constitutes the field of health information systems? Fostering a systematic framework and research agenda. Health Informatics Journal 18(2), 147–156.CrossRefGoogle Scholar
  62. Mirani R and Lederer AL (1998) An instrument for assessing the organizational benefits of is projects. Decision Sciences 29(4), 803–838.CrossRefGoogle Scholar
  63. Nejat G, Yiyuan S and Nies M (2009) Assistive robots in health care settings. Home Health Care Management and Practice 21(3), 177–187.CrossRefGoogle Scholar
  64. Nevo D and Wade MR (2007) How to avoid disappointment by design. Communications of the ACM 50(4), 43–48.CrossRefGoogle Scholar
  65. Norman DA (1990) The design of everyday things. Doubleday, New York, NY.Google Scholar
  66. O’leary K, Wobbrock JO and Riskin EA (2013) Q-methodology as a research and design tool for hci. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Paris, France, pp 1941–1950.Google Scholar
  67. Oborn E, Barrett M and Darzi A (2011) Robots and service innovation in health care. Journal of Health Services Research & Policy 16(1), 46–50.CrossRefGoogle Scholar
  68. Odling-Smee JJ (1988) The role of behavior in evolution. Cambridge University Press, Cambridge, UK.Google Scholar
  69. Orlikowski WJ and Iacono CS (2001) Research commentary: desperately seeking the “IT” in IT research – a call to theorizing the IT artifact. Information Systems Research 12(2), 121–134.CrossRefGoogle Scholar
  70. Oudshoorn N and Pinch T (2003) How users matter: The co-construction of users and technology (inside technology). MIT Press, Cambridge, MA.Google Scholar
  71. Ozkil AG, Fan Z, Dawids S, Aanes H, Kristensen JK and Christensen KH (2009) Service robots for hospitals: a case study of transportation tasks in a hospital. Proceedings of the IEEE International Conference on Automation and Logistics, Shenyang, China, pp 289–294.Google Scholar
  72. Patton MQ (2002) Qualitative research and evaluation methods. Sage Publications, Thousand Oaks, CA.Google Scholar
  73. Poulston A, Stevenson M and Bontcheva K (2016) User profiling with geo-located posts and demographic data. Proceedings of the 1st Workshop on Natural Language Processing and Computational Social Science, Austin, TX, pp 43–48.Google Scholar
  74. Pozzi G, Pigni F and Vitari C (2014) Affordance theory in the is discipline: a review and synthesis of the literature. Proceedings of the Twentieth Americas Conference on Information Systems, Savannah, GA, pp 1–12.Google Scholar
  75. Prestes E, Carbonera JL, Fiorini SR, Jorge VAM, Abel M, Madhavanb R, Locoro A, Goncalves P, Barreto ME, Habibg M, Chibani A, Gérard S, Amirat Y and Schlenoff C (2013) Towards a core ontology for robotics and automation. Robotics and Autonomous Systems 61, 1193–1204.CrossRefGoogle Scholar
  76. Rahim NZA, Lallmahomed MZI, Ibrahim R and Rahman AA (2011) A preliminary classification of usage measures in information system acceptance: a Q-sort approach. International Journal of Technology Diffusion 2(4), 25–47.CrossRefGoogle Scholar
  77. Riener R, Lunenburger L, Jezernik S, Anderschitz M, Colombo G and Dietz V (2005) Patient-cooperative strategies for robot-aided treadmill training: first experimental results. IEEE Transactions on Neural Systems and Rehabilitation Engineering 13(3), 380–394.CrossRefGoogle Scholar
  78. Sabherwal R, Jeyaraj A and Chowa C (2006) Information system success: individual and organizational determinants. Management Science 52(12), 1849–1864.CrossRefGoogle Scholar
  79. Seidel S, Recker J and Vom Brocke J (2013) Sensemaking and sustainable practicing: Functional affordances of information systems in green transformations. MIS Quarterly 37(4), 1275–1299.CrossRefGoogle Scholar
  80. Sergeeva A, Huysman M and Faraj S (2015) Transforming work practices of operating room teams: the case of the Da Vinci robot. Proceedings of the 36th Interational Conference on Information Systems, Fort Worth, USA, pp 1–10.Google Scholar
  81. Shotter J (1983) “Duality of structure” and “intentionality” in an ecological psychology. Journal for the Theory of Social Behavior 13(1), 19–44.CrossRefGoogle Scholar
  82. Stainton Rogers R (1995) Q methodology. In Rethinking methods in psychology (smith JA, Harré R and Van Langenhove L, Eds), Sage Publications, London.Google Scholar
  83. Stephenson W (1986) Protoconcursus: the concourse theory of communication: I. Operant Subjectivity 9(2), 37–58.Google Scholar
  84. Strauss AL and Corbin J (1998) Basics of qualitative research: Techniques and procedures for developing grounded theory. Sage, Newbury Park.Google Scholar
  85. Swiss Federal Statistical Office (2016) Hospital statistics. Swiss Federal Statistical Office, Neuchâtel, Switzerland.Google Scholar
  86. Takayama L, Ju W and Nass C (2008) Beyond dirty, dangerous and dull: what everyday people think robots should do. Proceedings of the 3rd ACM/IEEE International Conference on Human Robot Interaction, Amsterdam, The Netherlands, pp 25–32.Google Scholar
  87. Teddlie C and Yu F (2007) Mixed methods sampling: a typology with examples. Journal of Mixed Methods Research 1(1), 77–100.Google Scholar
  88. Te’eni, D (2016) Contextualization and problematization, gamification and affordance: a traveler’s reflections on EJIS. European Journal of Information Systems 25(6), 473–476.CrossRefGoogle Scholar
  89. The Wall Street Journal (2012) The robots are coming to hospitals.
  90. Thompson G (1966) The evaluation of public opinion. In Reader in public opinion and communication (Berelson B and Janowitz M, Eds), pp 7–12, Free Press, New York.Google Scholar
  91. Thrun S (2004) Toward a framework for human-robot interaction. Human-Computer Interaction 19(1), 9–24.CrossRefGoogle Scholar
  92. Treem JW and Leonardi PM (2013) Social media use in organizations: exploring the affordances of visibility, editability, persistence, and association. In Communication yearbook (SALMON CT, Ed), pp 143–189, Routledge, New York.Google Scholar
  93. Tsui KM, Desai M, Yanco HA and Uhlik C (2011) Exploring use cases for telepresence robots. In Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction, pp 11–18, Lausanne, Switzerland.Google Scholar
  94. Valenta AL and Wigger U (1997) Q-methodology: definition and application in health care informatics. Journal of the American Medical Informatics Association 4(6), 501–551.CrossRefGoogle Scholar
  95. Van Exel J and De Graaf G (2005) Q methodology: a sneak preview.
  96. Volkoff O and Strong DM (2013) Critical realism and affordances: theorizing it-associated organizational change processes. MIS Quarterly 37(3), 819–834.Google Scholar
  97. Wang C, Savkin AV, Clout R and Nguyen HT (2015) An intelligent robotic hospital bed for safe transportation of critical neurosurgery patients along crowded hospital corridors. IEEE Transactions on Neural Systems and Rehabilitation Engineering 23(5), 744–754.CrossRefGoogle Scholar
  98. Watts S and Stenner P (2012) Doing Q methodological researchtheory method and interpretation. Sage Publications, London.CrossRefGoogle Scholar
  99. Wingreen SC, Lerouge C and Blanton JE (2009) Structuring training for it professionals and the firm: an application of the q-methodology. International Journal of Global Management Studies 1(1), 53–67.Google Scholar
  100. Yoo Y, Lyytinen KJ, Boland RJ and Berente N (2010) The next wave of digital innovation: opportunities and challenges.

Copyright information

© The OR Society 2017

Authors and Affiliations

  1. 1.Swiss Graduate School of Public AdministrationUniversity of LausanneChavannes-près-RenensSwitzerland
  2. 2.Institute of Information ManagementUniversity of St. GallenSt. GallenSwitzerland

Personalised recommendations