Research Approaches in e-HRM: Categorisation and Analysis

  • Stefan Strohmeier
Part of the Progress in IS book series (PROIS)


Electronic Human Resource Management (e-HRM) is a new interdisciplinary field of research at the intersection of Human Resources (HR) and Information Systems (IS). Research in e-HRM is currently based on diverse research approaches from HR and IS, its “parent disciplines”, as well as other disciplines. The frequent implicitness and thus uncertainty of the used research approaches, however, is disadvantageous for future e-HRM research because it obstructs a conscious and instructed selection and adoption of research approaches as well as mutual understanding and cooperation between different research approaches. The current chapter thus aims to categorise (which approaches are available?) and analyse (which characteristics and potential do these approaches demonstrate?) e-HRM research approaches. To this end, a brief framework of conceptual criteria is derived that allows research approaches in e-HRM to be categorised and analysed. Based on this, a categorisation and analysis of four major approaches, i.e., critical research, interpretive research, post-positive research and design research, is offered, and the possibilities for adopting these approaches in e-HRM research are described.


e-HRM e-HRM research e-HRM methodology e-HRM paradigms Critical research Interpretive research (Post-) Positive research Design research 


  1. Anderson, V. (2004). Research approaches in human resource management. London: CIPD.Google Scholar
  2. Aier, S., & Fischer, C. (2011). Criteria of progress in information systems design theories. Information Systems and e-Business Management, 9, 133–172.CrossRefGoogle Scholar
  3. Alvesson, M. (2009). Critical perspectives on strategic HRM. In J. Storey, P. M. Wright, & D. Ulrich (Eds.), The routledge companion to strategic human resource management (pp. 52–62). Oxon: Routledge.Google Scholar
  4. Alvesson, M., & Deetz, S. (2000). Doing critical management research. London: Sage.Google Scholar
  5. Applegate, L. M. (1999). Rigor and relevance in MIS research—Introduction. MIS Quarterly, 23(1), 1–2.CrossRefGoogle Scholar
  6. Bailey, K. D. (1994). Typologies and taxonomies: An introduction to classification techniques. Thousand Oaks: Sage.Google Scholar
  7. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120.CrossRefGoogle Scholar
  8. Bondarouk, T, V. & Furtmueller, E., (2012) E-HRM research: Promises, hopes, facts and path forward, reviewing four decades of empirical evidence. In C. Tansley & H. Williams (eds.), Proceedings of the 4 th International e-HRM Conference: Innovation, Creativity and e-HRM (pp. 25–60), Nottingham Trent University.Google Scholar
  9. Bunge, M. (1959). Causality: The place of the causal principle in modern science. Cambridge Mass.: Harvard University Press.Google Scholar
  10. Bunge, M. (1967a). Scientific research I: The search for system. New York: Springer.Google Scholar
  11. Bunge, M. (1967b). Scientific research II: The search for truth. New York: Springer.CrossRefGoogle Scholar
  12. Burrell, G., & Morgan, G. (1979). Sociological paradigms and organizational analysis. London: Heinemann Books.Google Scholar
  13. Carlsson, S. A. (2010). Design science research in information systems: A critical realist approach. In A. R. Hevner & S. Chatterjee (Eds.), Design science research in information systems (pp. 209–233). New York: Springer.CrossRefGoogle Scholar
  14. Cecez-Kecmanovic, D. (2005). Basic assumptions of the critical research perspective in information systems. In D. Howcroft & E. M. Trauth (Eds.), Handbook of critical information systems research—Theory and application (pp. 19–46). Cheltenham: Edward Elgar.Google Scholar
  15. Cecez-Kecmanovic, D. (2011). Doing critical information systems research—Arguments for a critical research methodology. European Journal of Information Systems, 20, 440–445.CrossRefGoogle Scholar
  16. Chen, W., & Hirschheim, R. (2004). A paradigmatic and methodological examination of information systems research from 1991 to 2001. Information Systems Journal, 14(3), 197–235.CrossRefGoogle Scholar
  17. Cua, F. C., & Garret, T. C. (2009). Understanding epistemology and ontology in information systems research. In A. Cater-Steel & L. Al-Hakim (Eds.), Information systems research methods, epistemology and applications (pp. 35–57). Hershey: IGI Global.Google Scholar
  18. Dachler, H.-P., & Enderle, G. (1989). Epistemological and ethical considerations in implementing human resource management. Journal of Business Ethics, 8, 597–606.CrossRefGoogle Scholar
  19. Deetz, S. (1996). Describing differences in approaches to organization science: Rethinking Burrell and Morgan and their legacy. Organization Science, 7(2), 191–207.CrossRefGoogle Scholar
  20. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.Google Scholar
  21. Fischer, C., Winter, R., & Wortmann, F. (2010). Design theory. Business and Information Systems Engineering, 6, 387–390.CrossRefGoogle Scholar
  22. Goles, T., & Hirshheim, R. (2000). The paradigm is dead, the paradigm is dead…long live the paradigm: The legacy of Burrell and Morgan. International Journal of Management Science, 28(3), 249–268.Google Scholar
  23. Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association of Information Systems, 5(8), 312–335.Google Scholar
  24. Hayek, F. A. (1955). Degrees of explanation. British Journal for the Philosophy of Science, 6(23), 209–255.CrossRefGoogle Scholar
  25. Hevner, A. R., & Chatterjee, S. (2010). Design science research frameworks. In A. R. Hevner & S. Chatterjee (Eds.), Design science research in information systems (pp. 23–31). New York: Springer.CrossRefGoogle Scholar
  26. Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science in information systems research. MIS Quarterly, 28(1), 75–105.Google Scholar
  27. Iivari, J. (2007). A paradigmatic analysis of information systems as design science. Scandinavian Journal of Information Systems, 19(2), 39–64.Google Scholar
  28. Khazanchi, D. & Munkvold, B. E. (2002). On the rhetoric and relevance of IS research paradigms (pp. 1–10), Proceedings of the 36th Hawai Conference on Systems Sciences. Google Scholar
  29. Klein, H. K., & Myers, M. D. (1999). A set of principles for conducting and evaluating interpretive field studies in information systems. MIS Quarterly, 23(1), 67–93.CrossRefGoogle Scholar
  30. Kuechler, B., & Vaishnavi, J. (2008). On theory development in design science research: Anatomy of a research project. European Journal of Information Systems, 17, 489–504.CrossRefGoogle Scholar
  31. Kuhn, T. S. (1976). The structure of scientific revolutions (3rd ed.). Chicago: Chicago University Press.Google Scholar
  32. Lee, A. (1991). Integrating positivist and interpretivist approaches to organizational research. Organization Science, 2, 342–365.CrossRefGoogle Scholar
  33. March, S. T., & Smith, G. (1995). Design and natural science research on information technology. Decision Support Systems, 15(4), 251–266.CrossRefGoogle Scholar
  34. Mayrhofer, W. (2009). Groping in the dark? Recent contributions to progress in interpretative research—A review. German Journal of Human Resource Research, 23(2), 166–182.Google Scholar
  35. McKenna, S., Singh, P., & Richardson, J. (2008). A drunkards’ search: looking for ‘HRM’ in the wrong places. Management International Review, 48(1), 115–136.CrossRefGoogle Scholar
  36. McKenna, S., Richardson, J., & Manroop, L. (2011). Alternative paradigms to the study and practice of performance management and evaluation. Human Resource Management Review, 21(2), 148–157.CrossRefGoogle Scholar
  37. Myers, M. D., & Klein, H. K. (2011). A set of principles for conducting critical research in information systems. MIS Quarterly, 35(1), 17–36.Google Scholar
  38. Niehaves, B. (2007). On epistemological diversity in design science: New vistas for design-oriented IS research? (pp. 1–13) Proceedings of the 28 th International Conference on Information Systems, Montreal.Google Scholar
  39. Nienhüser, W. (2011). Empirical research on human resource management as production of ideology. Management Revue, 22(4), 367–393.Google Scholar
  40. Olivas-Luján, M. & Rosseau, D. M. (2010). Can the evidence-based movement help e-HRM to bridge the research-practice-gap? In S. Strohmeier & A. Diederichsen (eds.), Evidence-based e-HRM? On the Way to Rigorous and Relevant Research, Proceedings of the 3 rd European Academic Workshop on Electronic Human Resource Management (pp. 3–13), Bamberg.Google Scholar
  41. Orlikowski, W. J., & Baroudi, J. J. (1991). Studying information technology in organizations: research approaches and assumptions. Information Systems Research, 2(1), 1–28.Google Scholar
  42. Orwell, G. (1949). 1984, London: Penguin.Google Scholar
  43. Panayotopoulou, L., Galanaki, E., & Papalexandris, N. (2010). Adoption of electronic systems in hrm: Is national background of the firm relevant? New Technology, Work and Employment, 25(3), 253–269.CrossRefGoogle Scholar
  44. Parry, E. (2011). An examination of e-HRM as means to increase the value of the HR function. International Journal of Human Resource Management, 22(5), 1146–1162.CrossRefGoogle Scholar
  45. Paucar-Caceres, A., & Wright, G. (2011). Contemporary discourses in information systems research: Methodological inclusiveness in a sample of information systems journals. International Journal of Information Management, 31(6), 593–598.CrossRefGoogle Scholar
  46. Peffers, K., Tuunanen, T., Rothenberger, M., Chaterjee, S. (2007/2008). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45–77.Google Scholar
  47. Popper, K. R. (1963). Conjectures and refutations: The growth of scientific knowledge. New York: Harper and Row.Google Scholar
  48. Robey, D. (1996). Diversity in information systems research: Threat, promise, and responsibility. Information Systems Research, 7(4), 400–408.CrossRefGoogle Scholar
  49. Robey, D., & Markus, L. M. (1998). Rigor and relevance: Producing consumable research about information systems. Information Resources Management Journal, 11(1), 7–15.CrossRefGoogle Scholar
  50. Ruël, H. J. M., & Bondarouk, T. V. (2012). A cross-national perspective on the intersection between information technology and HRM. In C. Brewster & W. Mayrhofer (Eds.), Handbook on research on comparative human resource management (pp. 416–448). Cheltenham: Edward Elgar.Google Scholar
  51. Searle, R. H. (2006). New technology: The potential impact of surveillance techniques in recruitment practices. Personnel Review, 35(3), 336–351.CrossRefGoogle Scholar
  52. Stone, D. & Dulebohn, R. (2013). Emerging issues in theory and research of e-HRM. Human Resource Management Review 23(1), 1–5.Google Scholar
  53. Strohmeier, S. (2007). Research in e-HRM: Review and implications. Human Resource Management Review, 17(3), 19–37.CrossRefGoogle Scholar
  54. Strohmeier, S. (2009). Concepts of e-HRM consequences: A categorization, review, and suggestion. International Journal of Human Resource Management, 20(3), 528–543.CrossRefGoogle Scholar
  55. Strohmeier, S. (2012). Design research in e-HRM—An outline, example, and discussion. In C. Tansley & H. Williams (eds.), Proceedings of the Fourth International e-HRM Conference: Innovation, Creativity and e-HRM (pp. 374–400), Nottingham Trent University.Google Scholar
  56. Strohmeier, S., & Kabst, R. (2009). Organizational adoption of e-HRM. An empirical exploration of major adoption factors. Journal of Managerial Psychology, 24(6), 482–501.CrossRefGoogle Scholar
  57. Tansley, C., & Newell, S. (2007). A Knowledge-based view of agenda-formation in the development of human resource information systems. Management Learning, 38(1), 95–119.CrossRefGoogle Scholar
  58. van Aken, J. E. (2004). Management research based on the paradigm of design science: The quest for tested and grounded technological rules. Journal of Management Studies, 41(2), 219–241.CrossRefGoogle Scholar
  59. van Aken, J. E. (2005). Management research as a design science: Articulating the research products of mode 2 knowledge production in management. British Journal of Management, 16(1), 19–36.CrossRefGoogle Scholar
  60. Venable, J. (2006). The role of theory and theorising in design science research. First International Conference on Design Science Research in Information Systems and Technology (pp. 1–18), Claremont, California.Google Scholar
  61. Walls, J. G., Widmeyer, G. R., & El Sawy, O. A. (1992). Building an information systems design theory for vigilant EIS. Information Systems Research, 3(1), 36–59.CrossRefGoogle Scholar
  62. Walsham, G. (1995). Interpretive case studies in IS research: nature and method. European Journal of Information Systems, 4(2), 74–81.CrossRefGoogle Scholar
  63. Watson, T. J. (2004). HRM and critical social science analysis. Journal of Management Studies, 41(3), 447–467.CrossRefGoogle Scholar
  64. Williams, M. (2000). Interpretivism and generalization. Sociology, 34(2), 209–224.Google Scholar
  65. Winter, R. (2008). Design science research in Europe. European Journal of Information Systems, 17, 470–475.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Chair of Management Information SystemsSaarland UniversitySaarbrueckenGermany

Personalised recommendations