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Assessing Intentional Resume Deception: Development and Nomological Network of a Resume Fraud Measure

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Abstract

Resume fraud is pervasive and has detrimental consequences, but researchers lack a way to study it. We develop and validate a measure for empirically investigating resume misrepresentations purposely designed to mislead recruiters. In study 1, an initial set of items designed to measure three theorized resume fraud dimensions (fabrication, embellishment, omission) are rated for content validity. In study 2, job seekers complete the measure and its factor structure is evaluated. In study 3, another sample of job seekers is surveyed to verify the measure’s factor structure and to provide evidence regarding construct validity. In study 4, working adults who recently conducted a job search are surveyed to determine which individuals are more likely to commit resume fraud and whether resume fraud relates to critical work behaviors. We confirm the three-factor structure of our measure and offer evidence of construct validity by showing that socially desirable responding, Machiavellianism, moral identity, conscientiousness, emotional stability, and agreeableness are related to resume fraud. Additionally, we find that resume fraud predicts reduced job performance and increased workplace deviance beyond deceptive interviewing behavior. Resume fraud is rarely studied despite the negative impact it can have on job-related outcomes. Researchers can use this measure to explore further the antecedents and outcomes of resume fraud and to advise recruiters on how to minimize it. We develop a measure focusing on intentional resume misrepresentations designed to deceive recruiters. This is one of the first studies to examine the antecedents and outcomes of resume fraud.

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Notes

  1. Although recommended by factor analysis experts (e.g., MacCallum et al., 1999; Velicer & Fava, 1998), we note that our strict item inclusion criteria might have led to some construct deficiency in exchange for desired internal consistency and parsimony. As a result, we reexamined the items from study 2 using less stringent standards (.50 for communalities and .70 for factor loadings) and found that the revised standards added 9 items (3 fabrication and 6 embellishment) to our original 11 (see Appendix for the additional items). Thus, we retained the full set of study 2 items in study 3 to test both models.

  2. We combined the fabrication and embellishment items into a general measure of resume fraud in this study because our model did not predict any differential effects across these two dimensions.

  3. As indicated in footnote 1, we also included the nine items retained when using less stringent item inclusion criteria for comparison purposes to the original version.

  4. The fit indices for the longer version from study 2 approached acceptable levels (χ2 = 360.02 (167), χ2/df = 2.16, CFI = .94, TLI = .92, RMSEA = .08) but were inferior to indices for the original version (χ2 = 79.18 (41), χ2/df = 1.93, CFI = .98, TLI = .97, RMSEA = .07). Given these results, we believe the original version is superior, but recognize the longer version may still be a viable option. We retested our hypotheses and all the conclusions remained the same using the longer version. We continue with the original version because of its superior fit to the data, but in the Appendix, we italicize the additional items so that researchers can use whichever version best suits their needs.

  5. Although not shown in Table 6, further analyses indicated that IFB did not explain significant incremental variance in any work behavior beyond resume fraud. Furthermore, all resume fraud dimensions that were significant remained significant when controlling for individual differences including SDR, Machiavellianism, moral identity, conscientiousness, emotional stability, and agreeableness. These results are available from the first author on request.

  6. Study 3: measured cause model: χ2 = 757.33 (491), χ2/df = 1.54, CFI = .91, TLI = .89, RMSEA = .06 and original model: χ2 = 357.64 (174), χ2/df = 2.06, CFI = .93, TLI = .92, RMSEA = .08; χ2difference = 919.84, dfdifference = 437, p < .001. Study 4: measured cause model: χ2 = 2157.39 (856), χ2/df = 2.52, CFI = .86, TLI = .84, RMSEA = .08 and original model: χ2 = 1237.55 (419), χ2/df = 2.95, CFI = .90, TLI = .89, RMSEA = .09; χ2difference = 399.69, dfdifference = 317, p < .01.

References

  • Abrams, R. (2014). Walmart vice president forced out for lying about degree. New York Times, 163, p. B3.

  • Alge, B. J., Anthony, E. L., Rees, J., & Kannan, K. (2010). Controlling A, while hoping for B: Deviance deterrence and public versus private deviance. In L. L. Neider & C. Schriesheim (Eds.), The ‘dark’ side of management (pp. 115–141). Charlotte: Information Age Publishing.

    Google Scholar 

  • Amare, N., & Manning, A. (2009). Writing for the robot: How employer search tools have influenced résumé rhetoric and ethics. Business Communication Quarterly, 72, 35–60.

    Article  Google Scholar 

  • Anastasi, A. (1982). Psychological testing (5th ed.). New York: Macmillan.

    Google Scholar 

  • Anderson, J. C., & Gerbing, D. W. (1991). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411–423.

    Article  Google Scholar 

  • Anonymous. (2012). Resume fraud still major problem HR needs to address. HR Focus, 89, 13–15.

    Google Scholar 

  • Aquino, K., & Reed, A. (2002). The self-importance of moral identity. Journal of Personality and Social Psychology, 83, 1423–1440.

    Article  Google Scholar 

  • Babcock, P. (2003). Spotting lies. HR Magazine, 48(10), 46–52.

  • Bachler, C. J. (1995). Resume fraud: Lies, omissions and exaggerations. The Personnel Journal, 74, 50–60.

    Google Scholar 

  • Bennett, R. J., & Robinson, S. L. (2000). The development of a measure of workplace deviance. Journal of Applied Psychology, 85, 349–360.

    Article  Google Scholar 

  • Berry, C. M., Carpenter, N. C., & Barratt, C. L. (2012). Do other-reports of counterproductive work behavior provide an incremental contribution over self-reports? A meta-analytic comparison. Journal of Applied Psychology, 97, 613–636.

    Article  Google Scholar 

  • Berry, C. M., Sackett, P. R., & Wiemann, S. (2007). A review of recent developments in integrity test research. Personnel Psychology, 60, 271–301.

    Article  Google Scholar 

  • Bible, J. D. (2012). Lies and damned lies: Some legal implications of resume fraud and advice for preventing it. Employee Relations Law Journal, 38, 22–47.

    Google Scholar 

  • Bishop, J. D. (2006). Moral intuitions versus game theory: A response to Marcoux on resume embellishing. Journal of Business Ethics, 67, 181–189.

    Article  Google Scholar 

  • Broussard, R. D., & Brannen, D. E. (1986). Credential distortions: Personnel practitioners give their views. Personnel Administrator, 31, 129–146.

    PubMed  Google Scholar 

  • Brown, B. S., & McInerney, M. (2008). Changes in academic dishonesty among business students in the United States, 1999–2006. International Journal of Management, 25, 621–632.

    Google Scholar 

  • Callahan, D. (2004). The cheating culture. Orlando: Harcourt, Inc..

    Google Scholar 

  • Campbell, D., & Fiske, D. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81–105.

    Article  Google Scholar 

  • Carpenter, N. C., Berry, C. M., & Houston, L. (2014). A meta-analytic comparison of self-reported and other-reported organizational citizenship behavior. Journal of Organizational Behavior, 35, 547–574.

    Article  Google Scholar 

  • Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1, 245–276.

    Article  Google Scholar 

  • Christie, R., & Geis, F. (1970). Studies in Machiavellianism. New York: Academic.

    Google Scholar 

  • Conway, J. M., & Huffcutt, A. I. (2003). A review and evaluation of exploratory factor analysis practices in organizational research. Organizational Research Methods, 6, 147–168.

    Article  Google Scholar 

  • Conway, J. M., & Lance, C. E. (2010). What reviewers should expect from authors regarding common method bias in organizational research. Journal of Business and Psychology, 25, 325–334.

    Article  Google Scholar 

  • DePaulo, B. M., Kashy, D. A., Kirkendol, S. E., Wyer, M. M., & Epstein, J. A. (1996). Lying in everyday life. Journal of Personality & Social Psychology, 70, 979–995.

    Article  Google Scholar 

  • Dineen, B. R., Duffy, M. K., Henle, C. A., & Lee, K. (2017). Green by comparison: Deviant and normative transmutations of job search envy in a temporal context. Academy of Management Journal, 60, 295–320.

    Article  Google Scholar 

  • Donnellan, M. B., Oswald, F. L., Baird, B. M., & Lucas, R. E. (2006). The mini-IPIP scales: Tiny-yet-effective measures of the Big Five factors of personality. Psychological Assessment, 18, 192–203.

    Article  Google Scholar 

  • Elkman, P. (2009). Telling lies: Clues to deceit in the marketplace, politics, and marriage. New York: W. W. Norton & Company.

    Google Scholar 

  • Fan, J., Gao, D., Carroll, S. A., Lopez, F. J., Tian, T., & Meng, H. (2012). Testing the efficacy of a new procedure for reducing faking on personality tests within selection contexts. Journal of Applied Psychology, 97, 866–880.

    Article  Google Scholar 

  • Girden, E. R. (1991). ANOVA: Repeated measures. Newbury Park: Sage.

    Google Scholar 

  • Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale: Lawrence Erlbaum.

    Google Scholar 

  • Guillory, J., & Hancock, J. T. (2012). The effect of Linkedin on deception in resumes. Cyberpsychology, Behavior, and Social Networking, 15, 135–140.

    Article  Google Scholar 

  • Guion, R. M. (1997). Content validity. In L. H. Peters, C. R. Greer, & S. A. Youngblood (Eds.), The Blackwell encyclopedia dictionary of human resource management (pp. 58–59). Cambridge: Blackwell.

    Google Scholar 

  • Henle, C. A., Dineen, B. R., & Duffy, M. K. (2014). Deception by job applicants: Development of a resume fraud measure. Poster presented at the annual meeting of the Society for Industrial & Organizational Psychology, Honolulu, HA.

  • Henle, C. A., & Gross, M. A. (2013). Born to be deviant? An examination of the relationship between workplace deviance and employee personality. In S. M. Elias (Ed.), Deviant and criminal behavior in the workplace (pp. 50–76). New York: New York University Press.

    Chapter  Google Scholar 

  • Hilbert, G. A. (1985). Involvement of nursing students in unethical classroom and clinical behaviors. Journal of Professional Nursing, 1, 230–234.

    Article  Google Scholar 

  • Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1, 104–121.

    Article  Google Scholar 

  • Hinkin, T. R., & Tracey, J. B. (1999). An analysis of variance approach to content validation. Organizational Research Methods, 2, 175–186.

    Article  Google Scholar 

  • Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179–185.

    Article  Google Scholar 

  • Jöreskog, K. G. (1999). How large can a standardized coefficient be? Retrieved from http://www.ssicentral.com/lisrel/techdocs/HowLargeCanaStandardizedCoefficientbe.pdf.

  • Kim, B. H. (2011). Deception and applicant faking: Putting the pieces together. In G. P. Hodgkinson & J. K. Ford (Eds.), International review of industrial and organizational psychology (Vol. 26, pp. 239–292). Chichester: Wiley.

    Google Scholar 

  • Kish-Gephart, J. J., Harrison, D. A., & Treviño, L. (2010). Bad apples, bad cases, and bad barrels: Meta-analytic evidence about sources of unethical decisions at work. Journal of Applied Psychology, 95, 1–31.

    Article  Google Scholar 

  • Kluemper, D. H., McLarty, B. D., & Bing, M. N. (2015). Acquaintance ratings of the Big Five personality traits: Incremental validity beyond and interactive effect with self-reports in the prediction of workplace deviance. Journal of Applied Psychology, 100, 237–248.

    Article  Google Scholar 

  • Lennon, R. T. (1956). Assumptions underlying the use of content validity. Educational and Psychological Measurement, 16, 294–304.

    Article  Google Scholar 

  • Levashina, J., & Campion, M. A. (2007). Measuring faking in the employment interview: Development and validation of an interview faking behavior scale. Journal of Applied Psychology, 92, 1638–1656.

    Article  Google Scholar 

  • Levashina, J., Morgeson, F. P., & Campion, M. A. (2012). Tell me some more: Exploring how verbal ability and item verifiability influence responses to biodata questions in a high-stakes selection context. Personnel Psychology, 65, 359–383.

    Article  Google Scholar 

  • Lewicki, R. J. (1983). Lying and deception: A behavioral model. In M. H. Bazerman & R. J. Lewicki (Eds.), Negotiating in organizations (pp. 68–90). Beverly Hills: Sage.

    Google Scholar 

  • Lucas, G. M., & Friedrich, J. (2005). Individual differences in workplace deviance and integrity as predictors of academic dishonesty. Ethics & Behavior, 15, 15–35.

    Article  Google Scholar 

  • Lussier, R. N., & Hendon, J. R. (2016). Human resource management (2nd ed.). Thousand Oaks: Sage.

    Google Scholar 

  • MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4, 84–99.

    Article  Google Scholar 

  • Macur, J. (2014). Preaching accountability, but harboring a lie. New York Times, 163, p. 2.

  • McGarvey, R. (1993). Resume fraud. Training, 30, 10–14.

    Google Scholar 

  • Meng, X., Rosenthal, R., & Rubin, D. B. (1992). Comparing correlated correlation coefficients. Psychological Bulletin, 111, 172–175.

    Article  Google Scholar 

  • Moore, C., Detert, J. R., Treviño, L. K., Baker, V. L., & Mayer, D. M. (2012). Why employees do bad things: Moral disengagement and unethical organizational behavior. Personnel Psychology, 65, 1–48.

    Article  Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

    Google Scholar 

  • O’Boyle Jr., E. H., Forsyth, D. R., Banks, G. C., & McDaniel, M. A. (2012). A meta-analysis of the dark triad and work behavior: A social exchange perspective. Journal of Applied Psychology, 97, 557–579.

    Article  Google Scholar 

  • O’Connell, M. S., Kung, M., & Tristan, E. (2011). Beyond impression management: Evaluating three measures of response distortion and their relationship to job performance. International Journal of Selection and Assessment, 19, 340–351.

    Article  Google Scholar 

  • Oh, I., Charlier, S. D., Mount, M. K., & Berry, C. M. (2014). The two faces of high self-monitors: Chameleonic moderating effects of self-monitoring on the relationships between personality traits and counterproductive work behaviors. Journal of Organizational Behavior, 35, 92–111.

    Article  Google Scholar 

  • Ones, D. S., & Viswesvaran, C. (1998). The effects of social desirability and faking on personality and integrity assessment for personnel selection. Human Performance, 11, 245–269.

    Article  Google Scholar 

  • Paulhus, D. L. (1984). Two-component models of socially desirable responding. Journal of Personality and Social Psychology, 46, 598–609.

    Article  Google Scholar 

  • Peterson, M. H., Griffith, R. L., Isaacson, J. A., O’Connell, M. S., & Mangos, P. M. (2011). Applicant faking, social desirability, and the prediction of counterproductive work behaviors. Human Performance, 24, 270–290.

    Article  Google Scholar 

  • Reynolds, W. M. (1982). Development of reliable and valid short forms of the Marlowe-Crowne Social Desirability Scale. Journal of Clinical Psychology, 38, 119–125.

    Article  Google Scholar 

  • Rosse, J. G., Stecher, M. D., Miller, J. L., & Levin, R. A. (1998). The impact of response distortion on preemployment personality testing and hiring decisions. Journal of Applied Psychology, 83, 634–644.

    Article  Google Scholar 

  • Sackett, P. R., & Wanek, J. E. (1996). New developments in the use of measures of honesty, integrity, conscientiousness, dependability, trustworthiness, and reliability for personnel selection. Personnel Psychology, 49, 787–829.

    Article  Google Scholar 

  • Schriesheim, C. A., Powers, K. J., Scandura, T. A., Gardiner, C. C., & Lankau, M. J. (1993). Improving construct measurement in management research: Comments and a quantitative approach for assessing the theoretical content adequacy of paper-and-pencil survey-type instruments. Journal of Management, 19, 385–417.

    Article  Google Scholar 

  • Simmering, M. J., Fuller, C. M., Richardson, H. A., Ocal, Y., & Atinc, G. M. (2015). Marker variable choice, reporting, and interpretation in the detection of common method variance: A review and demonstration. Organizational Research Methods, 18, 473–511.

    Article  Google Scholar 

  • Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245–251.

    Article  Google Scholar 

  • Tepper, B. J., & Henle, C. A. (2011). A case for recognizing distinctions among constructs that capture interpersonal mistreatment in work organizations. Journal of Organizational Behavior, 32, 487–498.

    Article  Google Scholar 

  • Todd, D. M. (2012).Workzone: Inquiries on rise amid resume fraud. Pittsburgh Post Gazette. Retrieved from http://www.post-gazette.com/business/dateline/2012/08/12/Workzone-Inquiries-on-rise-amid-resume-fraud/stories/201208120234.

  • Valentine, S., & Fleischman, G. (2003). The impact of self-esteem, Machiavellianism, and social capital on attorneys’ traditional gender outlook. Journal of Business Ethics, 43, 323–335.

    Article  Google Scholar 

  • Velicer, W. F., Eaton, C. A., & Fava, J. L. (2000). Construct explication through factor or component analysis: A review and evaluation of alternative procedures for determining the number of factors or components. In R. D. Goffin & E. Helmes (Eds.), Problems and solutions in human assessment: Honoring Douglas N. Jackson at seventy (pp. 41–71). Norwell: Kluwer Academic.

    Chapter  Google Scholar 

  • Velicer, W. F., & Fava, J. L. (1998). Effects of variable and subject sampling on factor pattern recovery. Psychological Methods, 3, 231–251.

    Article  Google Scholar 

  • Williams, L. J., & Anderson, S. E. (1991). Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of Management, 17, 601–617.

    Article  Google Scholar 

  • Williams, L. J., & McGonagle, A. K. (2016). Four research designs and a comprehensive analysis strategy for investigating common method variance with self-report measures using latent variables. Journal of Business and Psychology, 31, 339–359.

    Article  Google Scholar 

  • Wood, J., Schmidtke, J., & Decker, D. (2007). Lying on job applications: The effects of job relevance, commission, and human resource management experience. Journal of Business & Psychology, 22, 1–9.

    Article  Google Scholar 

  • Yao, G., Wu, C., & Yang, C. (2008). Examining the content validity of the WHOQOL-BREF from respondents’ perspective by quantitative methods. Social Indicators Research, 85, 483–498.

    Article  Google Scholar 

  • Zerbe, W. J., & Paulhus, D. L. (1987). Socially desirable responding in organizational behavior: A reconception. Academy of Management Review, 12, 250–264.

    Article  Google Scholar 

  • Zwick, W. R., & Velicer, W. F. (1986). Factors influencing five rules for determining the number of components to retain. Psychological Bulletin, 99, 432–442.

    Article  Google Scholar 

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Acknowledgements

We thank Dan Ganster and Ray Hogler for their helpful comments on an earlier version of this paper, Jacquelyn Thompson for her editorial assistance, and Victoria Mattingly for her help with data collection.

Funding

A grant from the SHRM Foundation provided funding for this project.

Author information

Authors and Affiliations

  1. Department of Management, Colorado State University, 224 Rockwell Hall, Fort Collins, CO, 80523, USA

    Christine A. Henle

  2. Krannert School of Management, Purdue University, 4037 Rawls Hall, West Lafayette, IN, 47907, USA

    Brian R. Dineen

  3. Carlson School of Management, University of Minnesota, 3-292 CSOM, 19th Avenue South, Minneapolis, MN, 55455, USA

    Michelle K. Duffy

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  1. Christine A. Henle
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Correspondence to Christine A. Henle.

Appendix

Appendix

Resume Fraud Items

Recent reports have documented the prevalence of inaccurate information on resumes. For example, job seekers might list a college degree they never earned, leave off a job from which they were fired, exaggerate the importance of their job duties, or make up dates of employment to hide gaps. Keeping in mind that all of your responses are anonymous, in your most recent or current job search, to what degree did you intentionally do the following to increase your chances of receiving an interview? Please respond using the below response scale. Although some questions may seem repetitive, please answer as best as you can.

1

2

3

4

5

6

7

Not at all

To hardly any extent

To a little extent

To a moderate extent

To a considerable extent

To a very great extent

Completely

  1. Regarding your resume, during your current or most recent job search, rate the extent to which you have intentionally:
  2. Fabrication
  3. FAB1: Included information that is no longer true
  4. FAB2: Invented accomplishments that did not really occur
  5. FAB3: Provided incorrect information
  6. FAB4: Claimed to have skills that you do not have
  7. FAB5: Misrepresented the description of an event
  8. FAB6: Listed knowledge or skills you do not possess
  9. FAB7: Invented some work situations or accomplishments that did not really occur
  10. FAB8: Made up information regarding the quality or quantity of your performance
  11. FAB9: Made up information related to your past or current employment
  12. FAB10: Claimed work experience that you do not actually have
  13. FAB11: Made claims that were false
  14. FAB12: Invented degrees you do not have
  15. FAB13: Included information that is fabricated
  16. FAB14: Made up information regarding your involvement in job-related or extracurricular activities
  17. FAB15: Made up information related to your academic record
  18. FAB16: Provided information about references that is not true
  19. FAB17: Made up information on your resume
  20. Embellishment
  21. EMB1: Inflated the importance of activities or awards
  22. EMB2: Distorted your qualifications to match qualifications required for the job
  23. EMB3: Overstated your involvement in activities
  24. EMB4: Exaggerated the impact of your performance in your past jobs or your current one
  25. EMB5: Overstated information related to your academic record
  26. EMB6: Provided an enhanced picture of your past or current record
  27. EMB7: Made exaggerated claims
  28. EMB8: Overstated information
  29. EMB9: “Padded” your resume
  30. EMB10: Included information that is not exactly true
  31. EMB11: Stretched the truth regarding information on your resume
  32. EMB12: Exaggerated your responsibilities on previous jobs or your current one
  33. EMB13: Embellished information
  34. EMB14: Tried to make yourself appear as an ideal candidate when you were not
  35. EMB15: Made the information on your resume sound better than it really is
  36. EMB16: Included things that were exaggerated
  37. EMB17: Described team accomplishments as primarily your own
  38. Omission
  39. OMI1: Failed to mention relevant things from your past or current record
  40. OMI2: Omitted information about your involvement in certain job-related or extracurricular activities
  41. OMI3: Deleted information in order to help your chances of getting an interview
  42. OMI4: Omitted important information about past or current job responsibilities
  43. OMI5: Omitted information that doesn’t portray you in a favorable manner
  44. OMI6: Suppressed information that may not look favorable
  45. OMI7: Left relevant information off
  46. OMI8: Failed to include information that is less than positive
  47. OMI9: Kept information vague so it could not be easily verified
  48. OMI10: Omitted pertinent details about your past or current record
  49. OMI11: Omitted relevant information related to your academic record
  50. OMI12: Left information off that might hurt your chances of getting a job
  51. OMI13: Tried to suppress your connection to negative events in your work history
  52. Note. Items in bold are those included in the final versions of the scales. Items in italics could be added in longer versions of the scales.

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Henle, C.A., Dineen, B.R. & Duffy, M.K. Assessing Intentional Resume Deception: Development and Nomological Network of a Resume Fraud Measure. J Bus Psychol 34, 87–106 (2019). https://doi.org/10.1007/s10869-017-9527-4

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