Abstract
We examine the impact of activated (salient) versus non-activated ethical norms on the aggressiveness of accounting decisions, in the presence of self-interest favoring aggressiveness. Using a case in which the accounting rules are ambiguous, we ask professional accountants to make an accounting decision as though they were in their own organization; we measure the ethical norms of their organization at the end of the experiment. Based on the focus theory of normative conduct, we argue that the general ethical norms of the participants’ organizations are activated when the decision structure is such that the participant receives a recommendation from a subordinate, whereas those norms are not activated when the participant is making the decision alone. We find that higher ethical norms decrease aggressiveness when the decision maker receives a recommendation, whereas higher ethical norms have no impact on aggressiveness when the decision maker makes the decision alone. Our results demonstrate that general ethical norms, known to impact decisions having clear ethical content, can also curb accounting aggressiveness when these norms are activated. Furthermore, firm practices such as decision structure can activate norms. These findings are of interest to practitioners and regulators who seek to temper aggressive accounting.
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Organizational and decision-making% structures can have a significant influence on decisions and has been examined in prior research. For example, Hannan et al. (2010) examine the impact of flattened organizational structures and norm enforcement on budgeting effectiveness.
There is an exception. The assertion that norms are not likely to influence behavior unless they are activated is consistent with the model of social norm activation postulated by Bicchieri (2006) that have been used by prior accounting literature (e.g., Davidson and Stevens 2013 and Hobson et al. 2011).
We can find only one theory that appears to ignore, or at least downplay, the importance of norm activation: the Theory of Reasoned Action in which norms are one of the antecedents individuals consider before taking action (Fishbein and Ajzen 1975).
Even though this case has been used in prior research (for example, Kadous et al. 2003), we piloted our version with four professors who teach financial accounting. Like the audit firm members who co-created the case with Johnstone et al. (2002), the financial accounting professors suggested there was no right or wrong answer.
While some may argue this design creates a potential for reverse causality, we control for this possibility. We ask participants many questions in between the accounting decision and the ethical norms questions, and the ethical norms questions are generic and not specifically about aggressive or conservative reporting. Finally, reverse causality would argue for only a main effect of norms, which is inconsistent with our results which suggest an interaction effect between norms and subordinate recommendations. In other words, if participants’ perceived ethical norms in their organizations are a function of their accounting decision in the study, we should only observe lower aggressiveness associated with higher ethical norms. Instead, we observe lower aggressiveness associated with higher ethical norms only when participants receive a recommendation but the opposite pattern of higher aggressiveness associated with higher ethical norms when participants did not receive any recommendation, indicating that a less (more) aggressive accounting decision did not always cause participants to correspondingly report a higher (lower) ethical norm.
We also administer a fourth condition which is also not expected to activate ethical norms, one in which participants are asked to assume the role of an assistant controller making a recommendation to his/her supervisor (RECtoSup, n = 23). This additional control condition is discussed in the Additional Analysis sub-section.
For the CPA Canada sample (n = 109), we sent a follow-up reminder in December 2013. Early respondents (n = 32) completed the study in September 2013 whereas follow-up respondents (n = 77) completed the study between December 2013 to February 2014. There are no distribution differences across the early and late respondents with respect to gender (χ2 < 0.01, two-tailed p = 0.925), level of position in their organization (χ2 = 2.53, two-tailed p = 0.470), whether a respondent had a professional accounting designation (χ2 = 1.02, two-tailed p = 0.312), the type of organization the respondent worked in (χ2 = 4.16, two-tailed p = 0.656), whether the company is headquartered in Canada (χ2 = 0.311, two-tailed p = 0.577), whether the company is headquartered in the U.S. (χ2 = 0.659, two-tailed p = 0.417), the country in which the respondent’s division is located (χ2 = 0.382, two-tailed p = 0.537), the industry of the respondent’s company (χ2 = 11.79, two-tailed p = 0.380), age (F = 2.13, two-tailed p = 0.148), years of work experience (F = 1.83, two-tailed p = 0.180), or years with their organization (F = 0.53, two-tailed p = 0.467).
Excluding the four participants from the purchased database and the four participants recruited from LinkedIn invitations did not change the inferences from our results.
The Amazon Turk (MTurk) participants are recruited on TurkPrime (Litman et al. 2017).
Considering only the participants in the three conditions ***in our hypotheses, the three samples did not differ in terms of gender distribution (χ2 = 3.56, two-tailed p = 0.468). There are differences in distribution of position held in the company, with a higher percentage of participants in middle management positions in the CPA Canada sample (41%) and the MTurk sample (45%), but a higher percentage in staff level positions (64%) in the Prolific sample (χ2 = 52.19, two-tailed p < 0.001). A majority of participants had a professional accounting designation in the CPA Canada sample (95%) and the MTurk sample (61%), but a majority of participants did not have a professional accounting designation in the Prolific source (82%) (χ2 = 69.53, two-tailed p < 0.001). In all three samples, the largest percentage of participants work in private companies rather than public companies or government/non-profit (χ2 = 8.72, two-tailed p = 0.069). As expected, majority of the participants work in companies that are headquartered in Canada in the CPA Canada sample (85%) (χ2 = 91.05, two-tailed p < 0.001), whereas majority of participants work in companies headquartered in the U.S. in the Prolific (84%) and the Turk Prime (97%) samples (χ2 = 87.97, two-tailed p < 0.001). Similarly, majority of participants work in a division headquartered in Canada (95%) in the CPA Canada sample, but a majority of participants work in a division headquartered in the U.S. in the Prolific sample (84%) and the MTurk sample (100%) (χ2 = 118.03, two-tailed p < 0.001). There are also differences in the distribution of industry across the three samples (χ2 = 48.06, two-tailed p = 0.001), with a highest percentage in manufacturing (18%) in the CPA Canada sample, a highest percentage in services (29%) in the Prolific sample, and a highest percentage in finance/insurance (39%) in the MTurk sample. Participants were also on average older and had more years of work experience in the CPA Canada sample (mean age = 42.89, mean years of work experience = 20.24) than in the Prolific sample (mean age = 29.27, mean years of work experience = 8.24) or the MTurk sample (mean age = 36.91, mean years of work experience = 15.09) (F = 23.62, two-tailed p < 0.001 for age; F = 17.09, two-tailed p < 0.001 for years of work experience). Participants had on average more years with their current company in the CPA Canada sample (mean years = 7.52) and the MTurk sample (mean years = 6.82) than in the Prolific sample (mean years = 2.71) (F = 11.62, two-tailed p < 0.001).
The Institute of Chartered Accountants of England and Wales (ICAEW 2011) has expressed concern over whether rewarding finance staff based on the financial performance of companies jeopardizes objectivity and leads to unethical behavior, lending credence to the importance of examining this feature in decision making.
We label the straight line method as aggressive and the usage rate method as conservative based on the impact on the current year’s net income. That is, the straight line (usage rate) method results in the highest (lowest) income for the current year. While the effects of aggressive (conservative) reporting this year may result in an offset the following year, we argue that individuals tend not to think in such rational terms. Not only is the ultimate future net income after taking into account the offset not known at the decision point in the case, but the heavily researched notion of time discounting finds that individuals have the tendency to attach greater value to immediate outcomes than delayed outcomes (Trope and Liberman 2012).
Social identity with the participant’s company and the participant’s profession is the mean response to five questions (Mael and Tetrick 1992): When someone criticizes this company (my profession), it feels like a personal insult; I am very interested in what others think about this company (my profession); When I talk about this company (my profession), I usually say “we” rather than “they”; This company’s (my profession’s) successes are my successes; When someone praises this company (my profession), it feels like a personal compliment (Cronbach alpha for social identity with company = 0.876, Cronbach alpha for social identity with profession = 0.914).
We conduct a similar ordered logistic regression to test H1 using the organizational ethical norms variable (OEthics) and the divisional ethical norms variable (DEthics) in place of our final ethical norms variable. The interaction terms AggREC*OEthics (Estimate = − 0.62, t = − 1.77, one-tailed p = 0.040) and AggREC*DEthics (Estimate = − 0.72, t = − 1.83, one-tailed p = 0.035) in the second set of ordered logistic regression are negative and significant. Overall, the results are consistent whether we use the composite final ethical norms variable or the organizational norms variable and the divisional ethical norms variable.
We conduct similar ordered logistic regressions to test H2 using the organizational ethical norms variable (OEthics) and the divisional ethical norms variable (DEthics) in place of our final ethical norms variable. In the first set of ordered logistic regression, the main effect ConsREC is negative and marginally significant (Estimate = − 0.60, t = − 1.45, one-tailed p = 0.074). In the second set of ordered logistic regression, the interaction term ConsREC*OEthics (Estimate = -0.45, t = − 1.21, one-tailed p = 0.115) is negative but not significant, and the interaction term ConsREC*DEthics (Estimate = − 0.77, t = − 1.88, one-tailed p = 0.031) is negative and significant. Overall, the results are consistent whether we use the composite final ethical norms variable or the organizational norms variable and the divisional ethical norms variable.
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Acknowledgements
We are grateful to Carol Raven, CPA Canada, for her help recruiting participants and to Weiming Liu and Greg Richins for their research assistance. We thank Karla Johnstone, Jean Bedard, and Stanley Biggs for sharing their research instrument with us. Comments on earlier versions of this paper from Kendall Bowlin, Joe Brazel, David Cooper, Jeremy Griffin, Karim Jamal, Steven Kachelmeier, Heather Pesch, Steve Salterio, Douglas Stevens, and workshop participants at the University of Alberta, University of Mississippi, North Carolina State University, Queen’s University, and the 22nd Symposium on Audit Research at University of Illinois at Urbana-Champaign are appreciated. Pam is grateful for the continuing financial support of Smith School of Business. Finally, we thank the section editor, Charles Cho, and two anonymous reviewers for their helpful insights.
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Kelly, K., Murphy, P.R. Reducing Accounting Aggressiveness with General Ethical Norms and Decision Structure. J Bus Ethics 170, 97–113 (2021). https://doi.org/10.1007/s10551-019-04290-w
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DOI: https://doi.org/10.1007/s10551-019-04290-w