Using Multi-Informant Designs to Address Key Informant and Common Method Bias

  • Christian Homburg
  • Martin Klarmann
  • Dirk Totzek


The important key informant and common method problems in survey research are taken up in this article. The authors focus on the question how researchers can rely on multiinformant designs in order to limit the threats of key informant and common method bias on the validity and reliability of survey research. In particular, they show how researchers can effectively design studies that employ multiple informants and how multi-informant data can be aggregated in order to obtain more accurate results than can be obtained with single informant studies.

Organizational Survey Research Survey Designs Common Method Bias Key Informant Bias 


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  1. [1]
    Bagozzi, R. P./Yi, Y. (1991): Multitrait-multimethod matrices in consumer research. Journal of Consumer Research, Vol. 17, 4, pp. 426–439.CrossRefGoogle Scholar
  2. [2]
    Baruch, Y./Holtom, B. C. (2008): Survey response rate levels and trends in organizational research. Human Relations, Vol. 61, 8, pp. 1139–1160.CrossRefGoogle Scholar
  3. [3]
    Baumgartner, H./Steenkamp, J.-B. (2001): Response styles in marketing research: a cross-national investigation. Journal of Marketing Research, Vol. 38, 2, pp. 143–156.CrossRefGoogle Scholar
  4. [4]
    Bazerman, M. H./Moore, D. A. (2009): Judgment in managerial decision making, 7th ed. Hoboken, NJ: Wiley.Google Scholar
  5. [5]
    Bliese, P. D. (1998): Group size, ICC values, and group-level correlations: a simulation. Organizational Research Methods, Vol. 1, 4, pp. 355–373.CrossRefGoogle Scholar
  6. [6]
    Bliese, P. D. (2000): Within-group agreement, non-independence, and reliability: implications for data aggregation and analysis. In: Klein, K. J., & Kozlowski, S. W. (eds.). Multilevel theory, research, and methods in organizations. San Francisco, CA: Jossey-Bass, pp. 349–381.Google Scholar
  7. [7]
    Brown, R. D./Hauenstein, N. M. A. (2005): Interrater agreement reconsidered: an alternative to the rwg indices. Organizational Research Methods, Vol. 8, 2, pp. 165–184.CrossRefGoogle Scholar
  8. [8]
    Campbell, D. T./Fiske, D. W. (1959): Convergent and discriminant validation by the multitraitmultimethod matrix. Psychological Bulletin, Vol. 56, 2, pp. 81–105.CrossRefGoogle Scholar
  9. [9]
    Chandon, P./Morwitz, V. G./Reinartz, W. J. (2005): Do intentions really predict behavior? Selfgenerated validity effects in survey research. Journal of Marketing, Vol. 69, April, pp. 1–14.CrossRefGoogle Scholar
  10. [10]
    Churchill, G. A. (1979): A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, Vol. 16, 1, pp. 64–73.CrossRefGoogle Scholar
  11. [11]
    Cohen, J. (1960): A coefficient of agreement for nominal scales. Educational and Psychological Measurement, Vol. 20, 1, pp. 37–46.CrossRefGoogle Scholar
  12. [12]
    Conant, J. S./Mokwa, M. P./Varadarajan, P. R. (1990): Strategic types, distinctive marketing competencies and organizational Performance: a multiple measures-based study. Strategic Management Journal, Vol. 11, 5, pp. 365–383.CrossRefGoogle Scholar
  13. [13]
    Cote, J. A./Buckley, M. R. (1987): Estimating trait, method, and error variance: generalizing across 70 construct validation studies. Journal of Marketing Research, Vol. 24, 3, pp. 315–318.CrossRefGoogle Scholar
  14. [14]
    Cote, J. A./Buckley, M. R. (1988): Measurement error and theory testing in consumer research: An illustration of the importance of construct validation. Journal of Consumer Research, Vol. 14, 1, pp. 579–582.Google Scholar
  15. [15]
    Crampton, S. M./Wagner, J. A. (1994): Percept-percept inflation in microorganizational research: an investigation of prevalence and effect. Journal of Applied Psychology, Vol. 79, 1, pp. 67–76.CrossRefGoogle Scholar
  16. [16]
    Dixon, M./Cunningham, G. B. (2006): Data aggregation in multilevel analysis: a review of conceptual and statistical issues. Measurement in Physical Education and Exercise Science, Vol. 10, 2, pp. 85–107.CrossRefGoogle Scholar
  17. [17]
    Doty, D. H./Glick, W. H. (1998): Common methods bias: Does common methods variance really bias results. Organizational Research Methods, Vol. 1, 4, pp. 374–406.CrossRefGoogle Scholar
  18. [18]
    Evans, M. G. (1985): A Monte Carlo study of the effects of correlated method variance in moderated multiple regression analysis. Organizational Behavior and Human Decision Processes, Vol. 36, 3, pp. 305–323.CrossRefGoogle Scholar
  19. [19]
    Feldman, J. M./Lynch, J. G. (1988): Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology, Vol. 73, 3, pp. 421–435.CrossRefGoogle Scholar
  20. [20]
    Glick, W. H. (1985): Conceptualizing and measuring organizational and psychological climate: pitfalls in multilevel research. Academy of Management Review, Vol. 10, 3, pp. 601–616.Google Scholar
  21. [21]
    Golden, B. R. (1992): The past is the past – Or is it? The use of retrospective accounts as indicators of past strategy. Academy of Management Journal, Vol. 35, 4, pp. 848–860.CrossRefGoogle Scholar
  22. [22]
    Goodman, L. A. (1961): Snowball sampling. The Annals of Mathematical Statistics, 32, pp. 148–170.CrossRefGoogle Scholar
  23. [23]
    Hambrick, D. C. (1981): Strategic awareness within top management teams. Strategic Management Journal, Vol. 2, 3, pp. 263–279.CrossRefGoogle Scholar
  24. [24]
    Harrison, D. A./McLaughlin, M. E./Coalter, T. M. (1996): Context, cognition, and common method variance: psychometric and verbal protocol evidence. Organizational Behavior and Human Decision Processes, Vol. 68, 3, pp. 246–261.CrossRefGoogle Scholar
  25. [25]
    Heck, R. H. (2001): Multilevel modeling with SEM. In: Marcoulides, G. A., & Schumacker, R. E. (eds.). New developments and techniques in Structural Equation Modeling. 2nd ed. Mahwah, NJ: Lawrence Erlbaum, pp. 89–128.Google Scholar
  26. [26]
    Homburg, Ch./Fürst, A. (2005): How organizational complaint handling drives customer loyalty: an analysis of the mechanistic and the organic Approach. Journal of Marketing, Vol. 69, 3, pp. 95–114.CrossRefGoogle Scholar
  27. [27]
    Homburg, Ch./Klarmann, M. (2009): Multi Informant-Designs in der empirischen betriebswirtschaftlichen Forschung, Die Betriebswirtschaft, Vol. 69, 2, pp. 147–171.Google Scholar
  28. [28]
    Homburg, Ch./Droll, M./Totzek, D: (2008): Customer prioritization: Does it pay off, and how should it be implemented? Journal of Marketing, Vol. 72, 5, pp. 110–130.CrossRefGoogle Scholar
  29. [29]
    James, L. R./Demaree, R. G./Wolf, G: (1984): Estimating within-group interrater reliability with and without response bias. Journal of Applied Psychology, Vol. 69, 1, pp. 85–98.Google Scholar
  30. [30]
    James, L. R./Demaree, R. G./Wolf, G. (1993): rwg: an assessment of within-group interrater agreement. Journal of Applied Psychology, Vol. 78, 2, pp. 306–309.CrossRefGoogle Scholar
  31. [31]
    Jarvis, C. B./MacKenzie, S. B./Podsakoff, P. M. (2003): A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, Vol. 30, September, pp. 199–218.CrossRefGoogle Scholar
  32. [32]
    John, G./Reve, T. (1982): The reliability and validity of key informant data from dyadic relationships in marketing channels. Journal of Marketing Research, Vol. 19, 4, pp. 517–524.CrossRefGoogle Scholar
  33. [33]
    Kenny, D. A./Kashy, D. A./Cook, W. L. (2006): Dyadic data analysis. New York: Guilford Press.Google Scholar
  34. [34]
    Kirca, A. H., Jayachandran, S./Bearden, W. O. (2005): Market orientation: a meta-analytic review and assessment of its antecedents and impact on performance. Journal of Marketing, Vol. 69, 2, pp. 24–41.CrossRefGoogle Scholar
  35. [35]
    Klarmann, M. (2008): Methodische Problemfelder der Erfolgsfaktorenforschung: Bestandsaufnahme und empirische Analysen, Wiesbaden: Gabler.Google Scholar
  36. [36]
    Klein, K. J./Bliese, P. D./Kozlowski, S. W./Dansereau, F./Gavin, M. B./Griffin, M. A./Hofmann, D. A./James, L. R./Yammarino, F. J./Bligh, M. C. (2000): Multilevel analysis techniques: commonalities, differences, and continuing questions. In: Klein, K. J., & Kozlowski, S. W. (eds.). Multilevel theory, research, and methods in organizations. San Francisco, CA: Jossey Bass, pp. 512–553.Google Scholar
  37. [37]
    Kozlowski, S. W./Hattrup, K. (1992): A disagreement about within-group agreement: disentangling issues of consistency versus consensus. Journal of Applied Psychology, Vol. 77, 2, pp. 161–167.CrossRefGoogle Scholar
  38. [38]
    Kumar, N./Stern, L. W./Anderson, J. C. (1993): Conducting interorganizational research using key informants. Academy of Management Journal, Vol. 36, 6, pp. 1633–1651.CrossRefGoogle Scholar
  39. [39]
    Lance, C. E./LaPointe, J. A./Fisicaro, S. A. (1994): Tests of three causal models of halo rater error. Organizational Behavior and Human Decision Processes, Vol. 57, 1, pp. 83–96.CrossRefGoogle Scholar
  40. [40]
    LeBreton, J. M./Senter, J. (2008): Answers to 20 questions about interrater reliability and interrater agreement. Organizational Research Methods, Vol. 11, 4, pp. 815–852.Google Scholar
  41. [41]
    LeBreton, J. M./James, L. R./Lindell, M. K. (2005): Recent issues regarding rWG, r*WG, rWG(J), and r*WG(J). Organizational Research Methods, Vol. 8, 1, pp. 128–138.CrossRefGoogle Scholar
  42. [42]
    Libby, R./Blashfield, R. K. (1978): Performance of a composite as a function of the number of judges. Organizational Behavior and Human Performance, Vol. 21, 2, pp. 121–129.CrossRefGoogle Scholar
  43. [43]
    Mezias, J. M./Starbuck, W. H. (2003): Studying the accuracy of managers’ perceptions: a research odyssey. British Journal of Management, Vol. 14, 1, pp. 3–17.Google Scholar
  44. [44]
    Miles, R. E./Snow, C. C. (1978): Organizational strategy, structure, and process. New York: McGraw-Hill.Google Scholar
  45. [45]
    Natter, M./Mild, A./Wagner, U./Taudes, A. (2008): Planning new tariffs at tele.ring: the application and impact of an integrated segmentation, targeting, and positioning tool. Marketing Science, Vol. 27, 4, pp. 600–609.CrossRefGoogle Scholar
  46. [46]
    Phillips, L. W. (1981): Assessing measurement error in key informant reports: a methodological note on organizational analysis in marketing. Journal of Marketing Research, Vol. 18, 4, pp. 395–415.CrossRefGoogle Scholar
  47. [47]
    Podsakoff, P. M./Organ, D. W. (1986): Self-reports in organizational research: problems and prospects. Journal of Management, Vol. 12, 4, pp. 531–544.CrossRefGoogle Scholar
  48. [48]
    Podsakoff, P. M./MacKenzie, S. B./Lee, J.-Y./Podsakoff, N. P. (2003): Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, Vol. 88, 5, pp. 879–903.CrossRefGoogle Scholar
  49. [49]
    Reinartz, W./Krafft, M./Hoyer, W. D. (2004): The customer relationship management process: measurement and impact on performance. Journal of Marketing Research, Vol. 41, 3, pp. 293–305.CrossRefGoogle Scholar
  50. [50]
    Rindfleisch, A./Malter, A. J./Ganesan, S./Moorman, C. (2008): Cross-sectional versus longitudinal survey research: concepts, findings, and guidelines. Journal of Marketing Research, Vol. 45, June, pp. 261–279.CrossRefGoogle Scholar
  51. [51]
    Sathe, V. (1978): Institutional versus questionnaire measures of organizational structure. Academy of Management Journal, Vol. 21, 2, pp. 227–238.CrossRefGoogle Scholar
  52. [52]
    Schmidt, F. L./Hunter, J. E. (1989): Interrater reliability coefficients cannot be computed when only one stimulus is rated. Journal of Applied Psychology, Vol. 74, 2, pp. 368–370.CrossRefGoogle Scholar
  53. [53]
    Shrout, P. E./Fleiss, J. L. (1979): Intraclass correlations: uses in assessing rater reliability. Psychological Bulletin, Vol. 86, 2, pp. 420–428.CrossRefGoogle Scholar
  54. [54]
    Starbuck, W. H./Mezias, J. M. (1996): Opening Pandora ’s Box: studying the accuracy of managers’ perceptions. Journal of Organizational Behavior, Vol. 17, 2, pp. 99–117.CrossRefGoogle Scholar
  55. [55]
    Tinsley, H. E. A./Weiss, D. J. (1975): Interrater reliability and agreement of subjective judgements. Journal of Counseling Psychology, Vol. 22, 4, pp. 358–374.CrossRefGoogle Scholar
  56. [56]
    Tversky, A./Kahneman, D. (1974): Judgment under uncertainty: heuristics and biases. Science, Vol. 185, September, pp. 1124–1131.CrossRefGoogle Scholar
  57. [57]
    Van Bruggen, G. H./Lilien, G. L./Kacker, M. (2002): Informants in organizational marketing research: why use multiple informants and how to aggregate responses. Journal of Marketing Research, Vol. 39, 4, pp. 469–478.Google Scholar
  58. [58]
    Vandenberg, R. J./Lance, C. E. (2000): A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research. Organizational Research Methods, Vol. 3, 1, pp. 4–70.CrossRefGoogle Scholar
  59. [59]
    Venkatraman, N./Ratmanujam, V. (1987): Measurement of business economic performance: an examination of method convergence. Journal of Management, Vol. 13, 1, pp. 109–122.CrossRefGoogle Scholar
  60. [60]
    Vosgerau, J./Anderson, E./Ross, W. T. (2008): Can inaccurate perceptions in business-to-business (b2b) relationships be beneficial? Marketing Science, Vol. 72, 2, pp. 205–224.Google Scholar
  61. [61]
    Wall, T. D./Michie, J./Patterson, M./Wood, S. J./Sheehan, M./Clegg, C. W./West, M. (2004): On the validity of subjective measures of company performance. Personnel Psychology, Vol. 57, 1, pp. 95–118.CrossRefGoogle Scholar
  62. [62]
    Wieseke, J. (2008): Mehrebenenmodelle. In: Herrmann, A., Homburg, Ch., & Klarmann, M. (eds.). Handbuch Marktforschung. 3rd ed. Wiesbaden: Gabler, pp. 499–519.Google Scholar
  63. [63]
    Williams, L. J./Brown, B. K. (1994): Method variance in organizational behavior and human resources research: effects on correlations, path coefficients, and hypothesis testing. Organizational Behavior and Human Decision Processes, Vol. 57, 2, pp. 185–209.CrossRefGoogle Scholar
  64. [64]
    Williams, L. J./Cote, J. A./Buckley, M. R. (1989): Lack of method variance in self-reported affect and perceptions at work: reality or artifact. Journal of Applied Psychology, Vol. 74, 3, pp. 462–468.CrossRefGoogle Scholar

Copyright information

© Gabler Verlag | Springer Fachmedien Wiesbaden 2012

Authors and Affiliations

  • Christian Homburg
    • 1
  • Martin Klarmann
    • 2
  • Dirk Totzek
    • 1
  1. 1.University of MannheimMannheimGermany
  2. 2.Karlsruhe Institute of Technology (KIT)KarlsruheGermany

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