A Habit Strength-Based Explanation for Auditors’ Use of Simple Cognitive Processes for Complex Tasks

Sarah BonnerUniversity of Southern California

Kathryn KadousEmory University

Tracie MajorsUniversity of Southern California

May 15, 2020

We thank Leo Barcellos, Lori Bhaskar, Scott Emett, Cassandra Estep, Lisa Gaynor, Emily Griffith, Ryan Guggenmos, Bright Hong, Justin Leiby, Eldar Maksymov, Chris Nolder, Mark Peecher, Truman Rowley, Adam Vitalis, Chris Wolfe, Wendy Wood, and workshop participants at Arizona State University, Texas A&M University, and the Texas Audit Symposium for helpful feedback. We thank Erik Fujinami, Bright Hong, JungKoo Kang, Andrew Kim, Sharon Kim, Suteera Pongtepupathum, Taylor Reis, Michael Rezzo, Stacey Ritter, Meredith Schultz, and Fiona Wang for helpful feedback on the instrument. We also thank Nathaniel Young for the photographs used in the instruments, and Bright Hong, Ryan Kalaf, Molly Starobin, Genna Young, and Dana Zadeh for other research assistance. We also thank the four senior auditors with whom we conducted extensive interviews for giving their time. This study was supported by a Center for Audit Quality Research Advisory Board grant. We thank Margot Cella and Lauren Tuite of the CAQ for facilitating access to participants, members of the Research Advisory Board, especially John DeMelis, for helpful input, and participants for giving their time.

The views expressed in this article and its content are those of the authors alone and not those of the Center for Audit Quality.

A Habit Strength-Based Explanation for Auditors’ Use of Simple Cognitive Processes for Complex Tasks

We experimentally examine whether audit seniors’ use of simple cognitive processes for a complex task is affected by the strength of habits to use these processes that they developed as staff auditors. A habit is a mental association between a behavior and a specific context. We propose that, for seniors with stronger simple process habits, the typical audit room context automatically and unconsciously activates the simple processes, impeding selection of task-appropriate processes. Consistent with this, in the typical context, seniors with stronger habits identify fewer issues with a complex estimate than seniors with weaker habits. Further, seniors with stronger habits perform better in an alternative context that does not activate the simple processes, while those with weaker habits do not. Additional analyses validate the habit strength measure, including identifying determinants, which is valuable because preventing formation of strong simple process habits may be more feasible than changing established habits.

JEL codes: G10, M40, M41, M42, D80, D91

Keywords: habits, cognitive processing, accounting estimates, audit quality, goodwill impairment, fair value

I. INTRODUCTION

Complex accounting estimates, including goodwill and valuation allowances, are

susceptible to misstatement due to management bias, implying that effective auditing is critical

for financial reporting quality (Bratten et al. 2013; Griffith, Hammersley, and Kadous 2015;

Cannon and Bedard 2017). However, inspection reports cite continued deficiencies in audits of

complex estimates, particularly in evaluations of underlying assumptions (IFIAR 2017; IFIAR

2019). These reports and a growing body of research (Kadous and Zhou 2019; Griffith 2018;

Joe, Wu, and Zimmerman 2017; Griffith, Hammersley, Kadous, and Young 2015; Austin,

Hammersley, and Ricci 2019) suggest that deficiencies in this area are caused by auditors’ use of

simple cognitive processes, such as superficial processing, which impairs their ability to identify

issues with assumptions. Yet, we know little about why this is the case. We examine whether the

extent to which seniors use simple cognitive processes when auditing a complex estimate is

affected by the strength of habits to use these processes that they developed as staff auditors.

A habit is an association in memory between a behavior and a stable context (generally

one’s surroundings, including other people) in which that behavior is enacted; the association

develops as the behavior is repeated in that context with experienced rewards (Wood and Rünger

2016; Mazar and Wood 2018). For example, moviegoers can develop habits to eat popcorn by

frequently attending movies in a theater and repeatedly eating and enjoying popcorn while there

(Neal, Wood, Wu, and Kurlander 2011). Likewise, we posit that staff auditors can develop habits

to use simple cognitive processes in the audit room context in which they typically work (a

conference room at a client site housing multiple team members).1 This context is fairly stable

over time and across clients. Many staff likely repeat the simple processes when performing 1 We define simple cognitive processes as follows. Superficial processing is focusing on obvious, surface features (Craik and Lockhart 1972); confirmatory processing is searching for and interpreting evidence consistent with expectations or desired outcomes (Kunda 1990; Nickerson 1998); and piecemeal processing is evaluating cues one or a few at a time, then concluding and moving on (Anderson 1981).

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simple tasks because they are sufficiently effective and particularly efficient for these tasks.

Also, some staff may feel rewarded for using the processes, such as by experiencing positive

reinforcement from superiors for efficiency (Nelson and Proell 2018). These characteristics of

the environment staff face are thus conducive to the formation of habits to use simple processes.

Habits resist extinction (Wood and Neal 2016; Verplanken, Roy, and Whitmarsh 2018),

such that we expect staff, when promoted to senior, will “carry forward” their habits. However,

we expect these habits will vary in strength, based on the extent that seniors, as staff, repeatedly

used the simple processes and felt rewarded for doing so. Stronger habits imply stronger context-

behavior associations in memory such that, when people with strong habits experience the

context, it is likely they will automatically respond with the behavior even if it is undesirable for

the current task (Wood and Rünger 2016). For example, people who have a strong “eat popcorn

at the movies” habit eat the same amount of stale as fresh popcorn when in a theater context,

despite indicating they dislike the stale popcorn (Neal et al. 2011). Similarly, we expect that

seniors with strong simple process habits will use the simple processes when auditing an estimate

in the typical audit room context, despite their inappropriateness for the task. Thus, we predict

that seniors with stronger simple process habits will be less effective at identifying issues with

the assumptions underlying an estimate than will seniors with weaker habits in this context.

Altering context cues prevents the automatic activation of habitual responses, allowing

people instead to act with intention (Wood, Tam, and Witt 2005). For example, moviegoers with

strong popcorn-eating habits react positively to a meeting room context: they eat significantly

less stale than fresh popcorn here because they can allow the tastiness of the popcorn to guide

their behavior. We likewise expect that seniors with stronger simple process habits will be more

likely to use the complex processes that are appropriate for the estimates task in the alternative

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context and, therefore, identify more issues with assumptions. In contrast, people with weak

habits are less likely to have their habits activated by the context in which they were formed, so

are less likely to respond positively to an alternative context. For example, moviegoers with

weak popcorn-eating habits eat significantly less stale than fresh popcorn in both a theater and a

meeting room (Neal et al. 2011). In our setting, seniors with weaker habits may be processing

intentionally, in which case context should have no effect. However, auditors face conditions that

are conducive to habit formation, such that these seniors may be processing habitually, but with

complex processes instead. If so, they may perform worse in the alternative context when their

habits are not activated and they must regroup (Wood 2019). Together, these expectations imply

an interaction between simple process habit strength and context, which is our second prediction.

We test our predictions in a 2 x 2 between-participants experiment with 128 experienced

audit seniors from two large audit firms. Participants evaluate assumptions underlying a fair

value estimate in a goodwill impairment case. The case contains embedded issues reflective of

management bias, the identification of which is impeded by use of simple cognitive processes.

Thus, our dependent measure is the number of issues auditors identify.

We measure our first independent variable, simple process habit strength, using reaction

times: how fast auditors, after being primed with a photograph of the typical context, complete

word fragments related to the simple processes relative to control fragments. This implicit

measure directly captures habit strength (Rebar, Gardner, Rhodes, and Verplanken 2018), here

the strength of the typical audit room context-simple processes association in memory, and has

been used in prior studies of habits (e.g., Danner, Aarts, and de Vries 2008; Adriaanse et al.

2011; Neal, Wood, Labrecque, and Lally 2012; Hargadon 2017). We use a median split to

classify auditors as having stronger or weaker habits.

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Consistent with psychology research (e.g., Neal et al. 2012), we manipulate context to

test our hypotheses about habit strength. We randomly assign auditors to imagine working in the

typical or an alternative context when working on the estimates task. Participants in the typical

context view a photograph of a typical audit room. This context is designed to activate, with

differential probability depending on strength, auditors’ simple process habits. Those in the

alternative context view the same audit room, but with key cues altered; to the extent auditors’

habits were formed only in the typical context, the alternative context should not activate them.

Results support our predictions. In the typical context, seniors who have stronger simple

process habits identify fewer issues than weaker habits seniors. This effect is not reduced as

auditors have more experience. We also find an interaction between habit strength and context.

Seniors with stronger habits identify more issues in the alternative versus typical context. Seniors

with weaker habits identify marginally fewer issues in the alternative context. Additional

analyses suggest that at least some of these auditors have complex process habits.

The observed interaction between context and habit strength is consistent with theory and

supports that habit strength drives our results. However, we strengthen this inference. First, we

analyze theoretical determinants of habit strength. We find that the extent to which seniors, as

staff, repeated behaviors reflecting the simple processes and felt rewarded for doing so predict

habit strength. Further, completion of simple (versus complex) tasks, as staff, led to repetition of

simple processes, but less so for auditors with high effectiveness preferences. Second, we show

that stronger simple process habits auditors who likely also developed their habits in the

alternative context are not influenced by context because their strong simple process habits are

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activated here as well. Third, we show that stronger simple process habits auditors who inhibit

the habitual response by exerting self-discipline are not influenced by the alternative context.2

Our findings contribute to the auditing literature and practice. Habits are a form of Type 1

processing (Evans and Stanovich 2013) that, while garnering significant interest in psychology

(Verplanken 2018), have not yet been examined in auditing. Type 1 processes likely are

generally influential for auditor judgments because auditors face a number of depleting factors,

such as stress, fatigue, and cognitive load, that lead to reliance on these processes (e.g., Potthoff

et al. 2018). Moreover, the audit environment, with its stable context and repetition of tasks, is

conducive to habit formation. Thus, habits may be a particularly important Type 1 process in

auditing. While researchers have speculated that features of the environment such as the

piecemeal, checklist-like nature of audit programs could encourage simple processing (Griffith et

al. 2015a; Griffith et al. 2015b), our study provides evidence that seniors’ strong simple process

habits that develop as a result of factors that vary when they are staff, including exposure to

simple tasks, experienced rewards for using simple processes, and effectiveness preferences, may

be a fundamental cause of this behavior. Importantly, while these habits likely were adaptive for

these seniors as staff, they become problematic after promotion because seniors continue to work

in the same context as they did when staff, but their tasks become more complex.

Indeed, firms are realizing the importance of habits, but they generally focus on personal

health habits (PwC 2020). We believe the habit construct can be extended to audit tasks.

Conceiving of habits as an underlying cause of behavior illuminates why deficiencies in audits of

estimates and other complex accounts may persist. Habits are “hardwired” in memory and, when

strong, resist interventions such as informational appeals, education, and instructions

2 We also conduct tests that rule out the possibility that differences across contexts that could affect auditors’ issue identification (e.g., perceived stress) can explain our findings.

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(Verplanken and Wood 2016; Lally and Gardner 2013). This implies that interventions such as

revisions to audit standards or increased training are unlikely to change the behavior of seniors

with strong simple process habits. Psychology theory suggests that getting these auditors to use

complex processes requires changing context, or helping them inhibit habitual processing, both

of which present challenges. Successful context change requires identifying which auditors

would benefit and which would not. Inhibiting effects of strong habits requires self-discipline

and is especially challenging in depleting environments (Itzchakov, Uziel, and Wood 2018). A

third possibility involves helping these seniors develop new, complex process habits that would

replace the old ones. However, strong (old) habits are difficult to extinguish; in support, we find

that the negative effect of strong simple process habits is not diminished by experience.

In light of these challenges, firms likely would benefit most from preventing staff from

developing simple process habits in the first place. Our analysis of determinants offers concrete

ideas. Firms could reduce staff’s time spent on simple tasks by encouraging seniors to involve

staff in complex tasks. Firms could prime professional identity, as we show that auditors with

high identity are less apt to use simple processes. Finally, firms could reduce staff’s repetition of

simple processes by leading them to instead use complex processes. This could be accomplished

through seniors’ coaching approaches, or through technology such as visualization. While some

inefficiency may result, using complex processes for simple tasks could lead to engagement-

level benefits such as incidental detection of fraud in low-risk areas and earlier and/or faster

development of complex process habits in individual auditors. The latter would be beneficial not

only for auditing complex estimates but for other complex tasks such as auditing revenues.

The rest of the paper is organized as follows. Section 2 provides theory and hypotheses.

Sections 3 and 4 describe the design and results of the experiment. Section 5 concludes.

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II. BACKGROUND AND HYPOTHESIS DEVELOPMENT

In this section, we first develop theory that simple cognitive processes (superficial,

confirmatory, and piecemeal processing) allow for effective and efficient completion of the

simple tasks that staff frequently perform. Drawing from psychology theory on habits, we then

argue that repetition of the processes in the typical audit room context with rewards can lead staff

to develop habits of varying strength to use the processes. For seniors carrying forward stronger

(versus weaker) simple process habits, the typical context is more likely to activate use of those

processes, irrespective of task demands. Consequently, we predict that simple process habit

strength will negatively affect seniors’ performance of these tasks.

Simple Tasks Performed by Staff Auditors and Cognitive Processes

Staff auditors frequently perform tasks that are relatively simple (e.g., Power 2003;

Westermann et al. 2015; Westermann et al. 2019).3 We define simple tasks as those that involve

unambiguous information cues and only a few cues to process, individually, at a time (Bonner

1994). For example, vouching prices from sales invoices to a price list is simple because it

involves prices that are quantified and objective. Further, because vouching consists of a series

of “micro-tasks” in that the auditor vouches prices for one invoice at a time, there are only a few

cues to process per audited “item” (Bonner 1994). Finally, staff can process each cue (price)

individually because the necessary integration to project the likely misstatement in sales typically

is performed later by software or a senior. We propose, therefore, that staff performing simple

tasks will use simple cognitive processes, specifically superficial, confirmatory, and piecemeal

processing, because these processes are appropriate for these tasks. They lead to sufficiently

effective performance and are far more efficient than complex processes (deep, nonconfirmatory,

3 Seniors in our study reported spending a median of 70 percent of their time as staff working on simple tasks. An informal survey of ten current staff auditors indicates they spend a median of 80 percent of time on simple tasks.

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and integrative processing) and, as argued below, we expect staff receive positive reinforcement

for exhibiting this tradeoff between efficiency and effectiveness when performing simple tasks.

Psychology research defines superficial processing as focusing on obvious, surface

features of information cues, and deep processing as analyzing their meaning and implications

(Craik and Lockhart 1972; Craik 2002). Superficial processing is sufficient for effective

performance of simple audit tasks given their unambiguous cues. For example, when vouching

sales prices, auditors only need to glance at the price list to see if invoice prices are correct.

While deeper processing, such as thinking about whether prices make sense under current

economic conditions, also would lead to effective performance in this task, it is unnecessary to

achieve the objective of testing the accuracy assertion for sales. Consequently, deeper processing

during this simple task would lead to inefficiency.

Confirmatory processing is searching for evidence supporting, and/or interpreting

evidence to be consistent with, what one expects or desires to see; nonconfirmatory processing

entails searching for and accurately interpreting contradictory information (e.g., Kunda 1990).

Confirmatory processing also is sufficient for effective performance of simple audit tasks

because of their unambiguous cues. For the vouching task, identifying incorrect prices requires

only noting mismatches between invoices and the price list. Searching for contradictory evidence

is not required because the evidence needed for drawing conclusions appears as part of the task;

also, there is no interpretation needed to identify mismatches. While nonconfirmatory processing

(e.g., scrutinizing each invoice with a price mismatch to ensure that there are no errors or fraud

in other terms) also would lead to effective performance, again, it is unnecessary and inefficient.

Finally, piecemeal processing involves bringing one or a few cues into working memory,

evaluating them, then “closing them out” by removing them from memory, while integrative

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processing involves considering the implications of cues jointly, which necessitates returning to

earlier cues for re-processing each time a new cue is introduced (e.g., Anderson 1981).

Piecemeal processing is sufficient for effective performance of simple audit tasks, at least the

“micro-task” part that is performed by staff. For the vouching task, staff compare the prices for

one invoice to the price list, record any mismatches, and move to the next invoice knowing that

information integration will be done later. Although integrative processing also could lead to

effective performance, it is unnecessary and inefficient as integration would occur (again) later.

To summarize, superficial, confirmatory, and piecemeal processing are sufficiently

effective and particularly efficient for the simple tasks that staff perform frequently. Thus, we

posit that staff, on average, repeat these processes, but that they do so to varying degrees

depending on factors such as their exposure to simple tasks. In turn, repetition of behavior in a

stable context with experienced rewards leads to habit formation (e.g., Mazar and Wood 2018).

Simple Cognitive Processes as Habits

A habit is a mental association between a behavior (e.g., eating popcorn) and a stable

context in which that behavior is enacted (e.g., movie theater), with “context” referring to one’s

surroundings, including physical surroundings and people (Wood and Rünger 2016).4 Here, the

behaviors are the simple processes, and the context is a conference room at a client site in which

a team of auditors typically works. Audit staff and seniors work in a stable context as they tend

to be assigned to the same clients over time; moreover, features of the typical context are fairly

consistent across clients.5 Hence, auditors face conditions highly conducive to habit formation.

4Associations between items, e.g., the concepts “birthday” and “cake,” are developed in memory as those items are experienced together (Collins and Loftus 1975; McNamara 1992). Habits, even physical ones like running, are represented in memory as links between context and behavior (Wood and Rünger 2016; Neal et al. 2012). While psychology tends to examine physical habits, a few studies explore mental habits (e.g., Verplanken et al. 2007).5 Following prior research (e.g., Hargadon 2017), we interviewed four audit seniors to establish key elements of the typical audit room context. There was clear agreement on these elements: a conference table and chairs, multiple laptops, a printer, office supplies, snacks, coffee cups, and water bottles. We then staged the photograph of the typical audit room context to include these elements, similar to psychology research using a single, typical theater to

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Initially, a given behavior may occur in response to a goal, the achievement of which is

rewarded. For example, at first, a person may eat popcorn at a movie theater because it tastes

good. Indeed, research shows that experiencing rewards strengthens habits (Gardner and Lally

2013). Similarly, at first, staff likely use simple processes to perform simple tasks in an audit

room because they feel rewarded (e.g., by positive reinforcement from a superior for efficiency).

Over time, however, with rewarded repetition in a stable context, behaviors can become more

strongly linked to the context than to the initial goal (or task demands). Thus, behavioral control

shifts to context, such that a behavior is automatically and unconsciously activated by the context

rather than by task demands and the related anticipation of rewards (Wood and Neal 2007; Wood

2017; Verplanken 2018).6 For example, moviegoers who repeatedly enjoy popcorn can develop

an “eat popcorn at the movies” habit, such that elements of the theater context (e.g., theater seats)

activate the behavior to eat popcorn, rather than the desirability of the popcorn itself (Wood,

Quinn, and Kashy 2002; Wood 2017). Likewise, we expect that staff who repeatedly use simple

processes in the typical audit room context can develop “simple process habits,” such that

elements of this context (e.g., a conference table) activate their cognitive processing, rather than

the appropriateness of the processes for the demands of the particular task they are performing.

Habit strength is the strength of the association between the context and behavior in

memory. As with other associations in memory, habit strength increases with the frequency of

rewarded co-occurrence of two items (Deese 1960). Thus, people form strong popcorn-eating

habits with extensive experience eating and enjoying popcorn while watching movies in a

study popcorn-eating habits. Auditors in our experiment indicated spending a median of 70 percent of their time in a room like the staged room. 6 Habits can be formed quickly (Gardner and Lally 2018). For example, participants’ median days (repetitions) for exercise habit formation range from 66-154 (Lally, van Jaarsveld, Potts, and Wardle 2010; Fournier et al. 2017). Likewise, audit staff have the potential to reach 150 repetitions of simple processing in less than four months based on conservative assumptions of two simple tasks per day and a five-day workweek.

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theater. We expect that staff likewise can form strong simple process habits with extensive

rewarded repetition of simple processes while working in the typical audit room context.

As we note above, the simple processes are effective and highly efficient for the simple

tasks staff tend to perform, and so, on average, likely are repeated and rewarded. That is, most

audit teams face time and deadline pressures (e.g., Bobek, Daugherty, Radtke 2012; Brown,

Gissel, Neely 2016; Westermann et al. 2019). To manage such pressures, superiors tend to

reduce budgeted audit hours where possible, which likely is easiest in the lower risk areas where

staff tend to work (e.g., Houston 1999; Bierstaker and Wright 2001, 2005). Staff will thus use the

simple processes for simple tasks to manage to their superiors’ preferences (e.g., Bagley 2010),

receiving positive reinforcement for so doing (e.g., Nelson and Proell 2018). Importantly,

however, repetition and rewards will vary across individuals, creating variation in habit strength.

Repetition of the processes will vary based on factors such as how frequently staff perform

simple tasks. Staff also will vary in how much they feel rewarded. For example, staff with a high

need for approval (Kelley 1994; Malone and Roberts 1996) may more highly value praise.

When the context is experienced, habit strength determines the probability that habitual

behaviors are automatically and unconsciously activated in memory, then enacted, irrespective

of current goals or task demands (e.g., Wood and Rünger 2016). Because habits are resistant to

extinction (e.g., Wood and Neal 2016; Verplanken et al. 2018), we expect that staff will carry

forward their simple process habits when promoted to senior. Seniors who developed stronger

habits will be more likely to use the simple processes when in the typical audit room. This is

problematic because most auditors stay in this context as they move from staff to senior, but task

demands change. Thus, to the extent the processes that are activated by context are inappropriate

for the task at hand, seniors’ effectiveness will suffer.

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Effect of Simple Process Habit Strength on Evaluation of Assumptions in Typical Context

Indeed, prior research supports that auditing complex estimates is a task that cannot be

completed effectively with simple processing (Kadous and Zhou 2019; Griffith 2018; Joe et al.

2017; Griffith et al. 2015b; Austin et al. 2019). This task is complex in that it involves

ambiguous cues, such as predictions and qualitative information, that require interpretation and

scrutiny to detect potential management bias. It also contains cues that have implications for

other cues, including those that support one assumption but contradict others (Griffith et al.

2015a, 2015b; Kadous and Zhou 2019). Thus, superficial and piecemeal processing could cause

auditors to miss evidence indicative of problems. Confirmatory processing could lead auditors to

fail to identify contradictory evidence or to “explain it away.”

We predict that the likelihood of the simple processes being activated automatically by

the typical audit room context, even though the task requires complex processes, increases with

habit strength. As a result, we predict that seniors with stronger habits will be less effective at

auditing an estimate than seniors with weaker habits in the typical context. Consistent with

stronger habits causing behavior inconsistent with intention, Neal et al. (2011) find that people

with strong popcorn-eating habits eat as much stale as fresh popcorn when in a movie theater

despite indicating dislike of the former. This occurs because, while people can in theory inhibit a

strongly habitual response and choose a different action, doing so requires a great deal of self-

discipline (e.g., Wood 2017). Further, alternative actions are less accessible for people with

strong habits (e.g., Lally and Gardner 2013). Thus, while seniors with strong habits may

understand conceptually that simple processes are inappropriate for the complex tasks they

perform, we predict they are likely to stick with the automatically triggered simple processes.

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By contrast, the typical context is less likely to activate the simple processes for weaker

habits auditors. Even if activated, these auditors can inhibit their habits and access the alternative

complex processes with greater ease, relative to auditors with stronger simple process habits.

Thus, we predict that auditors with weaker simple process habits will perform better than

auditors with stronger habits. As mentioned earlier, we capture the use of simple processes using

the issues auditors identify with the assumptions underlying an estimate. Stated formally:

H1: In the typical audit room context, auditors with stronger simple process habits will identify fewer issues in assumptions than those with weaker simple process habits.

Context as a Moderator of Habit Strength

Psychology research has shown that altering context cues can jar people out of engaging

in strongly habitual behaviors (e.g., Wood and Neal 2009). Since the context in which the habit

was developed is no longer available to activate the response (e.g., Verplanken et al. 2018),

people are left to more thoughtfully consider which action is most appropriate (Wood 2019). For

example, Neal et al. (2011) show that people with strong habits to eat popcorn at a movie theater

respond positively to being placed in an alternative context (watching a video in a meeting

room); they eat less stale popcorn than fresh popcorn. In fact, they eat no more stale popcorn

than do people with weak habits in the alternative context. Likewise, we predict that seniors with

stronger habits will be more effective at auditing a complex estimate in an alternative context.

Their simple process habits will not be activated and we expect that, freed up to consider which

processes are appropriate, they will use the complex processes needed for the task.

While we predict that auditors with stronger habits will respond positively to a different

context, we expect those with weaker habits are less likely to do so. One possibility is that these

auditors are processing intentionally, which implies little reaction to context. This possibility is

consistent with how persons with weaker habits for a behavior generally are characterized in

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psychology studies on habits. For example, participants with weaker popcorn-eating habits, who

eat less stale than fresh popcorn in both the typical and alternative contexts, are characterized as

intentionally deciding how much popcorn to eat based on tastiness (Neal et al. 2011).

However, the audit environment is more complex than those previously studied. First, it

is depleting (e.g., Hurley 2015). Intentional decision-making requires executive control, such that

auditors engaging in intentional cognitive processing on their tasks would be “constantly in the

throes of heavy mental lifting” (Wood 2019, 9). Thus, while people with weak popcorn-eating

habits can intentionally choose whether or not to eat popcorn on the occasion they see a movie in

a theater, depleted auditors may not be able to make intentional choices each time they engage in

cognitive processing. Second, in psychology studies, there generally is no single behavior that is

the obvious “opposite” of the studied behavior and that occurs as a consequence of having a

weaker habit for the studied behavior. For example, people with weak popcorn-eating habits may

not go to the theater frequently or, instead, may go frequently but eat nothing. In contrast,

auditors must perform audit tasks and must use cognitive processing to do so. Consequently,

there is an obvious “opposite” to using simple cognitive processes: using complex processes.

Taken together, these arguments suggest that seniors carrying forward weaker simple process

habits may process habitually, but may instead have habits for complex processes.

To summarize, we predict that auditors with stronger simple process habits will respond

positively to context. However, we predict that auditors with weaker simple process habits will

be less likely to respond positively to context. If they are processing intentionally, they should be

relatively unaffected. Alternatively, if they are using complex process habits, those habits will

not be automatically activated by the alternative context; thus, they must regroup and start afresh,

which could negatively affect their performance (Wood 2019). For example, people with healthy

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eating habits who experience a context change make less healthy food choices in the new context

(Lin, Wood, and Monterosso 2016). Collectively, our predictions for the effects of context on

seniors with stronger and weaker simple process habits imply the following hypothesis:

H2: Auditors with stronger simple process habits will identify more issues in assumptions in the alternative audit room context than in the typical audit room context, while auditors with weaker simple process habits will not.

III. METHOD

Participants

Participants are 128 experienced senior auditors (mean experience of 40.3 months) from

two large audit firms.7 Study administration was facilitated by the Center for Audit Quality, with

participants completing the study during firm training sessions.8 The estimates task requires

participants to evaluate management’s assumptions related to a goodwill impairment test.

Seniors typically perform this task in practice (Griffith et al. 2015a).

Design and Procedures

Our study employs a 2 x 2 between-participants design. We measure simple process habit

strength and use a median split to classify participants as having either stronger or weaker simple

process habits. We manipulate context by randomly assigning auditors either to the typical audit

room or an alternative audit room that eliminates many cues from the typical room. Following

psychology research (e.g., Neal et al. 2011; Neal et al. 2012), we manipulate context not to

examine its effects per se but to validate the habit strength construct by showing differential

context effects when simple process habits are activated (in the typical context) versus not (in the

alternative context). Observing theory-consistent effects of context will support the predictive

validity of our habit strength measure (see Rebar et al. 2018).

7 Institutional review board approval was obtained. 8 Firm has a significant main effect on the dependent variable, but does not interact with our independent variables. Results of hypothesis tests including firm as a covariate remain significant at the same critical levels as reported.

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The study proceeds as follows. Participants first view a photograph of either the typical

or alternative context and write a paragraph to reinforce the manipulation. They then complete

the estimates task, which includes listing issues of concern regarding the assumptions. Next, they

answer post-experimental questions. Finally, all participants view a photo of the typical context

when completing the habit strength measure. We use this context when measuring habit strength

because, as mentioned earlier, this is the context in which staff spend most of their time and,

thus, are likely to develop habits. Use of the typical context for both the manipulation (to activate

habits with differential probability based on strength) and during measurement of habit strength

is consistent with prior research (e.g., Neal et al. 2011; Neal et al. 2012).

Simple Process Habit Strength

We measure simple process habit strength using a reaction-time measure. Implicit

measures are advantageous for capturing the strength of mental associations between items, such

as “birthday” and “cake” (De Houwer, Teige-Mocigemba, Spruyt, and Moors 2009). That is, the

strength of a link in memory affects not only the probability, but also the speed, of activation of

the second item when the first item is activated. Because habits are defined as associations in

memory between a context and a behavior, a reaction time measure directly captures habit

strength (Labrecque and Wood 2015; Mazar and Wood 2018; Rebar et al. 2018). While other

measures such as frequency of past behavior in a stable context (Mazar and Wood 2018) capture

individual determinants of habit strength, the reaction-time measure captures the resulting

association in memory, which incorporates all determinants, including experienced rewards. Yet

other measures capture outcomes of habit strength, such as the extent to which a behavior feels

automatic (Verplanken and Orbell 2003). Our reaction-time measure captures automaticity using

speed, but also overcomes limitations with outcome-based measures. For example, automaticity

16

can resist conscious reflection (e.g., Hagger et al. 2015; Gardner 2015; Rebar et al. 2018).9 More

fundamentally, we do not measure habit strength using outcomes because they can reflect other

processes; that is, they do not capture the context-dependency of habits.

Our habit strength measure assesses the speed of auditors’ recognition of words reflective

of the simple processes after experiencing the context in which we expect most have developed

their processing habits (i.e., the typical audit room). This general context-behavior reaction time

approach has been used in other psychology studies. For example, Neal et al. (2012) assess the

speed of participants’ recognition of words reflecting running after viewing words reflecting the

typical context in which they run (e.g., “gym”). Adriaanse et al. (2011) assess the speed of

participants’ recognition of words reflecting habitual snacks after being primed with “home” and

of habitual drinks after being primed with “bar.” Similar implicit measures have been used to

capture habits for transportation (Danner et al. 2008) and hand hygiene (Hargadon 2017).

We implement our measurement procedures as follows. Near the end of the study, we

prime (i.e., activate in memory, see, e.g., Doyen, Klein, Simons, and Cleerman 2014) the typical

context by having all auditors complete a one-minute “spot the difference” exercise involving

two photographs: the typical room and the same room with five small differences created using

Photoshop.10 We then collect reaction times by having auditors complete word fragments that are

reflective of the simple processes while the typical context remains activated (the photograph of

9 This is not to say that psychology research has not successfully used self-reports of automaticity, including for the cognitive habits of negative self-thinking (Verplanken et al. 2007; Verplanken and Tangelder 2011) and worrying (Verplanken and Fisher 2014). However, the measures would be difficult here – it seems unlikely that seniors would report that the simple processes feel automatic on their current tasks due to social desirability concerns; implicit measures are recommended when social desirability is a concern (Verplanken and Orbell 2003; Gardner and Tang 2014). Also, while people are able to report on the automaticity of habits such as worrying (i.e., that they do so “unintentionally”), it seems likely auditors would not have similar metacognitive access to the nature of their cognitive processes. However, future research could use these scales to measure other types of auditor habits that do not introduce these challenges, such as habits related to behaviors that are socially desirable. 10 We measure habit strength after manipulating context to prevent hypothesis guessing. We do not expect the earlier manipulation to affect the habit strength measure because we take this measure after auditors’ memory for context-related behaviors in the estimates task has been cleared by answering post-experimental questions. Consistent with this, context condition is not associated with measured habit strength (two-tailed p = 0.562).

17

the typical room remains displayed). We instruct auditors to type the entire word represented by

each fragment as quickly as possible (see Figure 1, Panel A for instructions), tracking completion

time in milliseconds.11 The simple process words (e.g., scan, glance) are shown in Figure 1,

Panel B, and were chosen based on the previously mentioned interviews with four seniors.

Auditors for whom the simple processes are strongly habitual (assuming those habits were

developed in the typical context) should, ceteris paribus, more quickly complete the related word

fragments. However, because reaction times also can be affected by idiosyncratic factors such as

typing or reading speed, we subtract reaction times to non-audit control words (as in Neal et al.

2012). The control words (e.g., bark; see Panel B) are roughly matched to the simple process

words on syllables and length.12 We classify auditors with faster (slower) completion times

relative to the median as having stronger (weaker) simple process habits.

Audit Room Context

Our second independent variable is audit room context. We manipulate context by asking

auditors to imagine they are at a client site when viewing a picture of either a typical audit room

or an alternative room that removes many elements of the former context (see Panels A and B of

Figure 2). Use of a photo to manipulate context is consistent with psychology research (e.g.,

Neal et al. 2012; Weinstein, Przybylski, and Ryan 2009). As discussed earlier, the typical room

contains common elements auditors encounter (e.g., chairs and equipment for multiple team

members). The alternative room omits several cues while maintaining a realistic working

environment (see Panel B).13 We staged the two audit rooms in a conference room of a

11 We observe skewness for some fragments’ reaction times; thus, we transform each reaction time by taking the reciprocal (see Whelan 2008).12 Reaction times for the simple process word fragments load on one factor (eigenvalue = 5.01) and have a Cronbach’s alpha of 0.89, consistent with them reliably capturing the single construct of simple process habit strength. Reaction times for the control words load on two factors. Multi-dimensionality is to be expected as these words are not thematically related. 13 We asked participants the extent to which they imagined themselves in the room and found doing so natural. We confirm that there is no difference in these responses across contexts (smallest two-tailed p = 0.467). Also, lower

18

participating firm’s office, and a research assistant photographed the rooms. After viewing the

pictures, auditors in the typical (alternative) context condition are given the instructions shown in

Panel C (D) of Figure 2. They are asked to “describe what you have imagined in 5-7 sentences,”

to activate the context in memory and enable spreading activation to related concepts (here,

cognitive processes) and also to make them feel like they are in the room (MacInnis and Price

1987). The probability with which simple process habits are activated when completing the

estimates task should (should not) vary with habit strength in the typical (alternative) context.

Task, Dependent Variables, and Other Measures

Estimates Task

The task requires that auditors evaluate management’s assumptions underlying an

estimate of goodwill as part of the client’s step-one analysis of an impairment test and is adapted

from Kadous and Zhou (2019). The task includes background information, analysis, and

evidence related to management’s assumptions. The client uses a discounted cash flow model to

estimate the fair value of the reporting unit, which indicates that it passes the impairment test.

The task includes sections for three key assumptions: five-year projections of revenue, operating

expenses, and capital expenditures. We embed seven issues that, as in the real-world task, are

less likely to be identified if auditors use simple cognitive processes (see the Appendix).

Dependent Variable and Other Measures

Because our focus is on how habit strength affects cognitive processing in the estimates

task, our dependent variable is the number of embedded issues a participant identifies (Issues

Identified). We ask participants to “list any specific concerns” they have about the estimate based

responses may reflect participants finding the context quite unrealistic or having another idiosyncratic reaction. We confirm that our results replicate when excluding participants responding below the midpoint on these questions.

19

on their evaluation.14 Auditors also complete a number of other post-experimental questions to

capture determinants of habit strength, potential moderators, and potential noise variables.

IV. RESULTS

Tests of Hypotheses

Values for Issues Identified range from zero to six of the seven embedded issues.

Descriptive statistics are tabulated in Table 1, Panel A. We test hypotheses using an Analysis of

Variance (ANOVA) model with Issues Identified as the dependent variable and independent

variables indicating whether the participant’s Simple Process Habit Strength is stronger or

weaker and whether the assigned Context is typical or alternative (see Panel B).15

H1 predicts that, within the typical context, auditors with stronger simple process habits

will identify fewer issues than auditors with weaker habits. Simple effects analyses are displayed

in Panel C of Table 1. In support of H1, there is a negative effect of Simple Process Habit

Strength on Issues Identified (one-tailed p = 0.014) in the typical context. In this context, seniors

with stronger habits identify fewer issues than those with weaker habits (means = 1.09 vs. 1.91).

Consistent with research indicating that strong habits are particularly “hard to break” (Wood and

Neal 2016), an additional analysis (untabulated) reveals that months of experience does not

reduce the habit strength effect (p > 0.500). Thus, while, experience could in theory reduce the

negative effects of habits (e.g., through knowledge acquisition), our findings suggest otherwise.

H2 predicts that auditors with stronger habits will identify more issues when in the

alternative versus typical context, while auditors with weaker habits are less likely to be

positively influenced by context. In support of H2, the interaction between Simple Process Habit 14 An author and a doctoral student, both with auditing experience and blind to experimental condition, independently coded participants’ listings for the presence of each embedded issue and reconciled any differences. Raw agreement was 98% and Cohen’s Kappa is 0.92, which is significantly greater than chance (p < 0.001). We use the reconciled coding for our dependent variable.15 The data meet the ANOVA assumptions. However, because our dependent variable involves count data, we verify that our results hold using a negative binomial regression model.

20

Strength and Context is significant (two-tailed p = 0.011) (see Panel B).16 As shown in Panel C,

among auditors classified as having high Simple Process Habit Strength, there is a positive

simple effect of Context on Issues Identified (one-tailed p = 0.024) (means = 1.09 and 1.83 for

the typical and alternative contexts, respectively). Performance of stronger simple process habits

auditors in the alternative context is indistinguishable from that of auditors with weaker simple

process habits in the typical context (untabulated, two-tailed p = 0.868). Turning to auditors with

weaker habits, we observe a marginally significant negative simple effect of Context (two-tailed

p = 0.096) (means = 1.91 vs. 1.28), which may suggest their use of complex process habits.17

Additional Analyses

In this section, we first provide further evidence about the validity of our habit strength

measure (as suggested by Rebar et al. 2018). Following, we explore implications of our finding

that weaker habits auditors identify marginally fewer issues in the alternative context. Finally,

we present robustness tests to show that effects of context are not driven by features of the

typical vs. alternative context per se, but are best explained by theory on habits.18

Validation of Habit Strength Measure

16 We also examine auditors’ Reasonableness Assessments (likelihood that the fair value is reasonable on a scale from 0-10) and Actions (no current action vs. immediate action) in (untabulated) structural equations models. Model results show that our independent variables affect Issues Identified, which then affects Reasonableness Assessment (i.e., more issues lead to a lower reasonableness assessment), which then negatively affects Action. 17 With the continuous Simple Process Habit Strength measure, there is a significant Context x Simple Process Habit Strength interaction (two-tailed p = 0.022). The Johnson-Neyman technique identifies two statistically significant inflection points. The negative effect of Context observed for weaker habits auditors in tests of H2 is significant for Simple Process Habit Strength scores ranging from the minimum of -0.033 to -0.008. The effect of Context is insignificant until a Simple Process Habit Strength score of 0.039, at which point the observed positive effect of Context for stronger habits auditors becomes significant, and then strengthens, persisting to the maximum of 0.089. This supports the theoretical prediction and demonstrates that our interaction is not dependent on the median split.18 We conduct other robustness tests. First, results for hypotheses tests are significant at the same critical levels if we drop or reclassify the participant with the median measure of habit strength and drop the five participants closest to the median. Second, results for tests of hypotheses are robust to dropping an outlier who identified 6 of the 7 issues (that falls about three standard deviations above the mean performance); the only exception is that the directionally negative simple effect of Context for weaker habits auditors drops in significance (two-tailed p = 0.180). Third, substituting auditors’ self-reported comfort with goodwill and number of goodwill audits for Simple Process Habit Strength in the primary ANOVA does not yield a significant interaction with Context (both p > 0.500), which is important given both measures are correlated with Simple Process Habit Strength (both two-tailed p < 0.050).

21

Determinants of simple process habit strength. Our theory proposes that auditors build

simple process habits as staff, but these habits vary in strength. We use a structural equations

model to examine determinants of habit strength (see Figure 3). Theory predicts that habit

strength increases as a function of repetition of behaviors and rewards felt from such repetition in

a stable context (Mazar and Wood 2018). We measure Simple Process Repetition with four

questions capturing seniors’ use of approaches to simple tasks, as staff, that reflect use of the

simple processes on a scale from 1 “Never Used This Approach” to 9 “Always Used This

Approach”.19 These questions are akin to those used in psychology research to capture habit

strength using frequency of repetition of past behavior (e.g., Danner et al. 2008; Neal et al. 2011;

Neal et al. 2012).20 We measure auditors’ tendency to seek their team’s approval as a proxy for

Rewards. Staff valuing approval more would likely feel more rewarded by positive

reinforcement from superiors for use of the simple processes. We elicit agreement (ranging from

1 “Strongly Disagree” to 7 “Strongly Agree”) that, as staff making day-to-day decisions on their

engagements, they generally chose the option they thought their audit team would approve of.

We also measure antecedents of Simple Process Repetition. These include auditors’

exposure to simple tasks as staff, which creates opportunities for using the simple processes, and

19 The questions were: (1) “When checking invoice terms, searched to see that there was evidence that agreed to what I was looking for (e.g., if I was looking for a dollar amount of ‘38,’ looked on the invoice to see if there was a ‘38’ anywhere)” (2) “When reviewing terms of a transaction or item, closely examined the details (e.g., checked additional details outside of just the key terms)” (reverse-scored) (3) “When evaluating the findings of audit procedures, considered results from each procedure separately (i.e., did not think about connections among results)” and (4) “When performing an audit procedure, considered how my findings within this procedure related to each other (e.g., if there were issues with multiple invoices in the sample, I thought about whether the same problem could be causing the issues)” (reverse-scored). Two additional questions (seeking a reasonable explanation for exceptions and quickly moving through work) did not load on the latent factor, and are not included. 20 If a given behavior occurs across a variety of contexts, psychologists tend to assess context stability (the extent to which the behavior occurs in the same context) and combine it with a measure of repetition. However, if the behavior is assumed to occur in a particular context, psychologists tend to use the frequency measure in isolation conditioned on the assumed context. For example, researchers elicit participants’ frequency of eating popcorn when they go to the movie theater (Neal et al. 2011). We use the latter approach, given the stability of the typical audit room for most auditors. Supporting this idea, time spent working in the typical context is not a predictor of Simple Process Habit Strength (p > 0.500). Model results are robust to including this path. Moreover, the relation between repetition and habit strength can be non-linear (Lally et al. 2010); model results also are robust to applying a natural log transformation to the questions capturing repetition of behaviors.

22

personal effectiveness preferences, which could lead staff to use complex processes even for

simple tasks. We measure Simple Task Exposure as the percentage of time that auditors report

having worked on simple versus complex audit tasks as staff. We measure professional identity

as a proxy for Effectiveness Preference. Prior research finds that stronger professional identity

predicts a focus on audit effectiveness (Bamber and Iyer 2007; Bauer 2015), consistent with

effective audit task performance being an integral part of the self-concept (Britt 1999, 2005).

Standard measures support a good model fit (χ2(22) = 24.57, p = 0.318; CFI = 1.00;

RMSEA = 0.03). The four indicators of Simple Process Repetition discussed above load on one

latent factor (largest one-tailed p = 0.047). As expected, Simple Process Repetition positively

affects Simple Process Habit Strength (one-tailed p = 0.029), as does Rewards (one-tailed p =

0.003). Turning to antecedents of Simple Process Repetition, as expected, there is a positive

effect of Simple Task Exposure (one-tailed p = 0.027); completing more simple tasks leads to

greater repetition of simple processes.21 However, this effect is moderated by a negative Simple

Task Exposure X Effectiveness Preference interaction (one-tailed p = 0.033), indicating that this

relationship is less pronounced for auditors with higher effectiveness preferences. That these

theoretical determinants predict our habit strength measure validates the measure. The findings

also reinforce a key benefit of our measure of habit strength: the memory association reflects

effects of frequency of repetition of behavior and experienced rewards.

Moderation of context effects for strong habits auditors who also develop habits in

the alternative context. Because the audit environment provides ample opportunities for

rewarded repetition of behaviors for habit development, we assume that auditors develop habits

in the typical context. However, some may also develop habits in our alternative context if they

spend enough time working in that context. While a change in context can prevent habits from

21 This finding also supports our assumption that simple processes are adaptive for simple tasks.

23

being activated, this is only true if the person has not also developed habits in the alternative

context (Verplanken et al. 2018). Thus, if auditors with stronger simple process habits also have

developed their habits in the alternative context, the alternative context is unlikely to improve

performance. In that case, the alternative context will activate the simple processes just as the

typical context does. Table 2, Panel A reports results of a regression (in the full sample) with

Context, Simple Process Habit Strength, and Alternative Context Experience as independent

variables, and Issues Identified as the dependent variable. We measure Alternative Context

Experience using auditors’ time spent working in contexts like our alternative context. The three-

way interaction is significant (two-tailed p = 0.048), and we explore the results for weaker habits

auditors in a subsequent section. Consistent with theory, regression estimates (see Panel B)

reveal a positive effect of Context for stronger habits auditors with low and medium Alternative

Context Experience (largest one-tailed p = 0.049). However, this effect is insignificant at high

Alternative Context Experience (one-tailed p = 0.432), consistent with the idea that auditors with

stronger simple process habits who also developed their habits in the alternative context have the

simple processes activated in both contexts.

Moderation of context effects for stronger habits auditors who exert self-discipline.

Because inhibiting strong habits is effortful (Wood 2016, 2017), we assume that auditors with

stronger habits use the automatically activated simple processes unless the alternative context

prevents their activation. However, if auditors with stronger simple process habits effortfully

inhibit the simple processes with self-discipline, the alternative context will have less

opportunity to improve performance. Table 3, Panel A reports results of a regression (in the full

sample) with Context, Simple Process Habit Strength, and Self-Discipline as independent

variables, and Issues Identified as the dependent variable. Self-Discipline is auditors’ agreement

24

on a 7-point scale that they exerted self-discipline while working on the estimates task.22 Among

auditors with stronger habits, a regression reveals the expected Context X Self-Discipline

interaction (two-tailed p = 0.045; Panel B). Consistent with theory, estimates from the regression

(Panel C) reveal a positive effect of Context for stronger habits auditors exerting low and

medium Self-Discipline (largest one-tailed p = 0.018). However, there is an insignificant effect at

high Self-Discipline (one-tailed p = 0.497), consistent with the idea that auditors with stronger

habits who effortfully inhibit their habits have less need for the alternative context.

Exploring the Nature of Processing Among Weaker Habits Auditors

In the development of H2, we considered the possibility that at least some auditors with

weaker simple process habits may have complex process habits. We consider this possibility

further in this section. First, our analysis of determinants of simple process habits (see Figure 3)

supports that at least some staff had opportunities to develop complex process habits. To the

extent that complex processes are the opposite of the four simple process indicators that we

measured, this analysis indicates the following. Seniors who, as staff, engaged in more repetition

of complex processes developed weaker simple process habits.23 This finding suggests that

seniors could have developed complex process habits as staff due to performing more complex

tasks. The related finding that staff with high effectiveness preferences tended to use complex

processes even on simple tasks implies that these staff felt rewarded from repeating the complex

processes. Next, we examine whether our findings suggest these seniors are using complex

process habits (versus intentional processing) on the estimates task.

22 The three-way interaction does not reach significance (two-tailed p = 0.170). This is not unexpected: exerting self-discipline is less relevant for auditors with weaker simple process habits because they are less likely to have the simple processes activated. Consistent with this idea, weaker habits auditors exert less self-discipline than stronger habits auditors (one-tailed p = 0.044). We report the full-sample regression for completeness. 23 See footnote 19 for the questions. The opposites are closely examining details, thinking about connections across procedures, considering how findings relate within a procedure, and not simply searching for confirming evidence.

25

If weaker habits auditors are using complex process habits, we expect them to perform

well in the typical context because their complex process habits are activated and are effective

for the task. However, we expect they may have difficulty in the alternative context because

these habits are not activated and they may need to regroup unless, as discussed earlier, they

have formed habits in both contexts. Consistent with our expectations, estimates from a

regression model (Table 2, Panel C) show that the effect of Context is significant and negative

for weaker habits auditors with low and medium Alternative Context Experience (two-tailed p’s

of 0.017 and 0.067), consistent with complex process habits not being activated in the alternative

context. The insignificant effect at high Alternative Context Experience (p > 0.500) is consistent

with these auditors having complex process habits activated in both contexts. Overall, the

findings support complex process habits being at play, especially considering that intentional

processing would lead to similar performance across contexts and irrespective of experience in

the alternative context. However, future research is needed to more directly study such habits.

Robustness Checks for Differences Across the Typical and Alternative Contexts

In this section we present analyses supporting that the observed effects of context are not

driven by differing features of the typical vs. alternative context per se. Table 4, Panel A reports

auditors’ thoughts about the context, coded from the paragraphs they wrote during the

manipulation. Chi-square analyses (see Panel B) indicate that six thoughts differ across

contexts.24 Auditors in the typical (vs. alternative) context are more likely to think about:

24 Two coders assessed the paragraphs for whether the auditor showed evidence in support of the thought (e.g., “I am supervising my staff”), showed evidence contradicting the thought (e.g., I am not supervising my staff”), or did not mention the thought. Coders also coded thoughts about the client coming in and being in a staff role; the former did not differ by context, and no auditors mentioned the latter. The task was completed by two separate sets of coders. Cohen’s Kappa for each pair was 0.46 and 0.88, which are both significantly greater than chance (p < 0.001). Coding differences were reconciled. We also asked the auditors directly about six inferences experienced from their assigned context: feeling cramped, multi-tasking, feeling stressed, interruptions, busy season, and the client coming in. All except the client coming in differ across context (all p < 0.001). We performed the three robustness tests described in the following paragraph for these inferences and confirm that they do not drive reported results.

26

coaching or supervising staff, feeling stressed (i.e., due to clutter or being cramped),

interruptions, time pressure, busy season, and a personal recollection (e.g., from their audit

experience). For the last two thoughts, only six and seven auditors showed evidence of them. For

these two, we reperform hypotheses tests within two subsamples that exclude these six and seven

auditors, respectively. Results are significant at the same critical levels, except that the decline in

performance for weaker habits auditors falls below significance; however, additional analysis

reveals a significant decline for those with less Alternative Context Experience.

We examine the robustness of our results to the other four thoughts in three ways. First,

we include them as covariates in the ANOVAs used to test hypotheses; results are significant at

the same critical levels, except that the decline for weaker habits auditors is significant only for

those with less Alternative Context Experience. Second, in lieu of using Context as an

independent variable, we use the context-related thoughts. These thoughts do not interact with

Simple Process Habit Strength in the form of our observed interaction. Third, assuming the

thoughts invoke the simple processes, to explain our interaction, stronger habits auditors would

need to show fewer of the thoughts in the alternative (vs. typical) context, while weaker habits

auditors would not. ANOVAs using Simple Process Habit Strength and Context and their

interaction, with the thoughts as dependent variables, show only a main effect of Context.

V. DISCUSSION AND CONCLUSIONS

This paper examines simple process habit strength as a potential reason why some audit

seniors use simple processes on complex tasks, including audits of estimates, despite that those

processes are inappropriate for such tasks. Using a reaction-time measure of habit strength and

manipulating imagined context, we show that, in the typical audit room context, seniors with

stronger simple process habits identify fewer issues in a complex estimate than do seniors with

27

weaker habits. Moreover, seniors with stronger habits who are placed in an alternative context

identify more issues, while auditors with weaker habits identify marginally fewer issues in that

context. The observed interaction is consistent with theory and supports that habit strength is the

causal construct. However, we strengthen this inference by reporting evidence of theory-

consistent determinants of habit strength and moderators of context effects. Finally, we provide

evidence that auditors with weaker simple process habits may be using complex process habits.

Prior research and PCAOB inspection reports have attributed difficulties in audits of

complex accounts to auditors’ use of simple processes. Our study provides evidence that the

strength of simple process habits may be a root cause. Habits are “hardwired” links between the

context and processes in auditors’ memory. Because the context in which seniors work does not

change, seniors with strong simple process habits may use the simple processes for complex

tasks in spite of firm training and decision aids, changes in professional standards, and recurring

audit deficiencies. For example, the requirement in both judgment frameworks and the standard

on auditing estimates (PCAOB 2019) to search for contradictory evidence likely would be

ineffective for seniors with strong habits; although they likely would comply, their habits may

lead them to find ways to explain away such information (e.g., Verplanken 2018). Instead,

psychology theory suggests that, to be effective, interventions must either alter context or be

targeted toward breaking or overcoming the habits. These strategies present difficulties, such that

firms may find preventing strong simple process habits from forming among staff to be more

promising. Alternatively, a more proactive approach could be helping staff develop complex

process habits. Accounting firms are discovering the power of building positive habits for their

employees’ health and well-being (PwC 2020). They may be able to use similar approaches to

build cognitive processing habits among staff that will be appropriate when they are promoted

28

and performing senior-level tasks. Cultivating complex process habits could be highly beneficial:

if seniors have carried forward complex process habits, this would free up bandwidth for using

intentional processes on other, new tasks, such as coaching and reviewing.

Our analysis of determinants suggests that staff may use more complex processes when

performing more complex tasks, such that “pushing down” more complex tasks could be

beneficial. Firms could further leverage the habits literature for additional insight into how they

can facilitate formation of complex process habits. For example, firms could speed up formation

of complex process habits by innovating ways for staff to find repetition of those processes

enjoyable and rewarding (e.g., Gardner and Lally 2013). They could reduce frictions that make

complex processing difficult to prevent backsliding (Lally and Gardner 2013), perhaps by

encouraging complex tasks to be performed when there are few distractions. Finally, firms can

vividly highlight valued outcomes of using effective processing on complex tasks to build

satisfaction and encourage repetition of complex processes (Lally and Gardner 2013). Complex

processes also could be made more rewarding through thoughtful design of firm technology such

as apps (Carden and Wood 2018), and by making staff feel that they have autonomy and self-

direction in choosing processes (Lally and Gardner 2013).

Finally, firms may be able to facilitate auditors’ recognition of simple versus complex

tasks and the appropriate processes for each. With this approach, auditors could build memory

associations between type of task and processes, such that task instead of context would activate

processing. Research with tax professionals indicates that at least some appear to distinguish

between simple and complex tasks and use the appropriate cognitive processing (Magro 1999,

2005). However, future research is needed to determine how this can best be accomplished.

29

Our study contributes to the auditing literature by demonstrating the importance of habit

strength to auditor performance of a critical task. Our work also may contribute to the literature

on auditor skepticism (see Nelson 2009; Nolder and Kadous 2018) by providing an alternative

view that problems attributed to lack of skepticism also could arise from habits. Also, while we

focus on audits of complex estimates, we expect that simple process habits impair auditor

performance of other audit tasks that require complex processing as well. Our work also provides

a methodology for measuring cognitive processing habits. Given the ubiquitous nature of habits,

we expect researchers in auditing and other areas of accounting could adapt and use our measure.

Our study has limitations that offer ideas for future research. Our findings suggest that

some seniors with weaker simple process habits may have complex process habits, but this

conclusion relies on the assumption that complex processes are the alternative to simple

processes. Future research can examine complex process habits directly. Future research also can

examine whether seniors develop habits for other behaviors, such as reviewing staff’s work,

habits that also could mitigate the negative effects of depletion (Mullis and Hatfield 2018).

30

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FIGURE 1 Simple Process Habit Strength Measure

Panel A:

Instructions: On the following screens, you will see a series of word fragments. The number of blanks indicates the number of missing letters.

For example, if there is one blank visible, this means there is one letter missing. As another example, if there are three blanks visible, this means there are three letters missing.

Please type the word (the entire word, not just the missing letters) as quickly as possible and then hit the arrow to continue to the next word fragment. As an example to get you started, view the two word fragments below: 

WO __ D

__ __ AGMEN __

As soon as you figure out the word, you would type the word in the textbox below the word fragment. For example, once you realized the first word was “WORD,” you would type “WORD” in the textbox. As another example, once you realized the second word was "FRAGMENT," you would type "FRAGMENT" in the textbox.  Please remember to type in the word and hit the arrow button as quickly as possible. Please click the arrow below to begin.

Panel B:

CONTROL WORD FRAGMENTS STAFF PROCESS WORD FRAGMENTS B __ RK (BARK) __ HOC __ __ ATE (CHOCOLATE) FANC __ (FANCY ) MAGAZ __ __ ES (MAGAZINES) MA __ SHMA __ __ OW (MARSHMALLOW) PAINT __ __ USH (PAINTBRUSH) __ __ TERMELON (WATERMELON)

CHE __ __ LIST (CHECKLIST) GLAN __ E (GLANCE) INSPE __ __ (INSPECT) PROC __ __ D (PROCEED) __ __ ASONABLE (REASONABLE) SC __ N (SCAN) __ KIM (SKIM) SPREA __ __ __ EET (SPREADSHEET) VE __ __ FY (VERIFY)

Panel A displays the instructions that participants read prior to completing the word fragments. Panel B displays the word fragments that we use to measure Simple Process Habit Strength. We calculate the average of each auditor’s completion times for the simple process fragments minus the average of each auditor’s completion times for the control, baseline (i.e., non-audit related) word fragments. We transform each reaction time by taking the reciprocal, which is a transformation commonly used in psychology studies using reaction-time measures to adjust for skewness (see Whelan 2008). We then classify auditors with completion times faster (slower) than the median as having stronger (weaker) simple process habits.

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FIGURE 2 Audit Room Context Manipulation

Panel A: Typical Audit Room Context

Panel B: Alternative Audit Room Context

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Panel C: Instructions Read by Participants in the Typical Audit Room Context:

Please imagine that you are working in this audit room today. You are working in here all day, and your intern and three staff are also all here today. Look around and take in the room. Imagine how the day would progress as you are

working in this room.

For example: o Imagine yourself sitting in the chair (yours is the gray one to the far right) and your

staff and intern sitting in the other chairs.o Imagine yourself using your laptop and other tools/supplies as you are doing your

audit work.o Imagine what might be happening throughout the day as you do your work in this

room.

Please describe what you have imagined in 5-7 sentences in the box below.

Panel D: Instructions Read by Participants in the Alternative Audit Room Context:

Please imagine that you are working in this audit room today. You are working by yourself in here all day, as your intern and three staff are all at a full

day training in the local office today. Look around and take in the room. Imagine how the day would progress as you are

working in this room.

For example: o Imagine yourself sitting in the chair.o Imagine yourself using your laptop and other tools/supplies as you are doing your

audit work.o Imagine what might be happening throughout the day as you do your work in this

room.

Please describe what you have imagined in 5-7 sentences in the box below.

Figure 2 provides details of the manipulation of (imagined) context. Auditors assigned to the typical (alternative) audit room context view the picture of the audit room in Panel A (Panel B), and read the instructions displayed in Panel C (and Panel D). After reading through the instructions, auditors then write a paragraph imagining themselves working in the context in the picture.

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FIGURE 3 Determinants of Simple Process Habit Strength

The above structural equations model examines determinants of auditors’ simple process habit strength. The chi-squared test for this model reveals good fit (χ2

(22) = 24.57, p = 0.318), as do other standard measures (CFI = 1.00; RMSEA = 0.03). Figure 2 defines Simple Process Habit Strength. We measure Simple Task Exposure using auditors’ self-reported percentage of time (spent as a staff working on audit procedures) that they worked on simple (versus complex) audit procedures (from 0 to 100 percent, in increments of 10). We measure Effectiveness Preference using the professional identity measure from Bauer (2015). We measure Simple Process Repetition with four questions that elicit the extent to which (when the seniors were staff and performing simple tasks), they used approaches that are indicative of the simple processes (on a scale from 1 “Never Used This Approach” to 9 “Always Used This Approach.”). Simple Process Indicator 1 is “When reviewing terms of a transaction or item, closely examined the details (e.g., checked additional details outside of just the key terms” (reverse-scored). Simple Process Indicator 2 is “When performing an audit procedure, considered how my findings within this procedure related to each other (e.g., if there were issues with multiple invoices in the sample, I thought about whether the same problem could be causing the issues)” (reverse-scored). Simple Process Indicator 3 is “When checking invoice terms, searched to see that there was evidence that agreed to what I was looking for (e.g., if I was looking for a dollar amount of ‘38,’ looked on the invoice to see if there was a ‘38’ anywhere.” Simple Process Indicator 4 is “When evaluating the findings of audit procedures, considered results from each procedure separately (i.e., did not think about connections among results).” We measure Rewards using auditors’ agreement (on a scale from 1 “Strongly Disagree” to 7 “Strongly Agree”) that, when staff, and making day-to-day decisions on their engagements, they generally chose the option that they thought their audit team members would approve of. P-values are one-tailed for directional predictions.

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Simple Task Exposure

Effectiveness Preference

Simple Task Exposure X

Effectiveness Preference

Simple Process Repetition

Simple Process Indicator 1

Simple Process Indicator 2

Simple Process Indicator 3

Simple Process Indicator 4

ß = + 0.05 p = 0.027

ß = + 0.60 p = 0.035

ß = - 0.01 p = 0.033ß = + 0.96

p = 0.040

ß = + 1.03 p = 0.029

ß = + 1.49 p = 0.047

Fixed at 1

Simple Process Habit Strength

ß = + 0.17 p = 0.029

Rewards

ß = + 0.09 p = 0.003

TABLE 1: Auditor Performance (Issues Identified) by Simple Process Habit Strength and Context

Panel A: Descriptive Statistics Simple Process Habit Strength

ContextStronger Simple Process Habits

Weaker Simple Process Habits

Typical Audit Room 1.09(1.19) n=34

1.91(1.84)n=32

Alternative Audit Room 1.83(1.58)n=30

1.28(1.30)n=32

Panel B: Analysis of Variance for Issues Identified

df SS MS F-statistic p-valueSimple Process Habit Strength 1 0.57 0.57 0.25 0.615 Context 1 0.12 0.12 0.05 0.820Simple Process Strength X Context 1 14.99 14.99 6.73 0.011

Error 124 276.09 2.23

Panel C: Simple Effects Comparisons df t-statistic p-value

Context for Stronger Simple Process Habits Auditors 124 1.99 0.024*Context for Weaker Simple Process Habits Auditors 124 -1.68 0.096Simple Process Habit Strength in the Typical Context 124 -2.23 0.014*Simple Process Habit Strength in the Alternative Context 124 1.46 0.148

We conduct an ANOVA to test our hypotheses. Independent variables are defined in the notes to Figures 1 and 2. The dependent variable is Issues Identified, which is the total number of issues, out of seven embedded issues, that the auditor identifies in the goodwill impairment case. Descriptive statistics are reported in Panel A. Panel C reports our test of H1, that is, the simple effect of Simple Process Habit Strength on Issues Identified, considering the typical audit room context. Panel B and Panel C report our test of H2, including the interaction between Simple

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Process Habit Strength and Context on Issues Identified, as well as the effect of Context for auditors with stronger and weaker simple process habits. P-values with * are one-tailed, and all other p-values are two-tailed.

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TABLE 2: Performance (Issues Identified) for Auditors by Context, Simple Process Habit Strength, and Experience Working in the Alternative Context

Panel A: Regression Model (Full Sample) df Coeff. Std. Error t-statistic p-value

Intercept 119 2.31 0.42 5.56 <0.001Context 119 -1.39 0.57 -2.42 0.017Simple Process Habit Strength 119 -1.25 0.59 -2.10 0.038Alternative Context Experience 119 -0.01 0.01 -1.17 0.243Context X Simple Process Habit Strength 119 2.65 0.83 3.19 0.002Context X Alternative Context Experience 119 0.02 0.01 1.70 0.093Simple Process Habit Strength X Alternative Context Experience

119 0.01 0.01 0.82 0.416

Context X Simple Process Habit Strength X Alternative Context Experience

119 -0.04 0.02 -2.00 0.048

Panel B: Simple Effects Estimates for Auditors with Stronger Simple Process Habits df Coeff. Std. Error t-statistic p-value

Context for Low Alternative Context Experience Auditors

119 1.17 0.54 2.15 0.017*

Context for Medium Alternative Context Experience Auditors

119 0.64 0.38 1.67 0.049*

Context for High Alternative Context Experience Auditors

119 0.11 0.62 0.17 0.432*

Panel C: Simple Effects Estimates for Auditors with Weaker Simple Process Habits df Coeff. Std. Error t-statistic p-value

Context for Low Alternative Context Experience Auditors

119 -1.28 0.53 -2.43 0.017

Context for Medium Alternative Context Experience Auditors

119 -0.70 0.38 -1.85 0.067

Context for High Alternative Context Experience Auditors

119 -0.11 0.49 -0.23 0.819

We conduct a regression model to examine effects of Context, Simple Process Habit Strength, and Alternative Context Experience (and their interactions) on Issues Identified. Simple Process Habit Strength is defined in the notes to Figure 1. Context is defined in the notes to Figure 2. Alternative Context Experience is measured as auditors’ self-reported indication of the amount of time they spend working in contexts like our alternative context. Issues Identified is defined in the notes to Table 1. The results of the regression model are reported in Panel A. Estimates from the model for the effect of Context at low (one standard deviation below the mean), medium (the mean), and high (one standard deviation above the mean) levels of experience working in the alternative context are reported in Panel B (for auditors with stronger simple process habits) and in Panel C (for auditors with weaker simple process habits). P-values with * are one-tailed, and all other p-values are two-tailed.

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TABLE 3: Performance (Issues Identified) for Auditors by Context, Simple Process Habit Strength, and Self-Discipline While Working on the Estimates Task

Panel A: Regression Model (Full Sample) df Coeff. Std. Error t-statistic p-value

Intercept 120 1.77 0.91 1.96 0.053Context 120 -0.50 1.21 -0.41 0.679Simple Process Habit Strength 120 -2.24 1.30 -1.72 0.088Self-Discipline 120 0.03 0.19 0.16 0.875Context X Simple Process Habit Strength 120 4.11 2.01 2.04 0.043Context X Self-Discipline 120 -0.03 0.25 -0.11 0.915Simple Process Habit Strength X Self-Discipline

120 0.29 0.26 1.11 0.268

Context X Simple Process Habit Strength X Self-Discipline

120 -0.55 0.40 -1.38 0.170

Panel B: Regression Model (with Stronger Simple Process Habits Auditors) df Coeff. Std. Error t-statistic p-value

Intercept 60 -0.47 0.85 -0.55 0.583Context 60 3.61 1.46 2.47 0.016Self-Discipline 60 0.32 0.17 1.91 0.061Context X Self-Discipline 60 -0.58 0.28 -2.05 0.045

Panel C: Simple Effects Estimates for Stronger Simple Process Habits Auditors

df Coeff. Std. Error t-statistic p-valueContext for Low Self-Discipline Auditors 60 1.47 0.51 2.90 0.003*Context for Medium Self-Discipline Auditors 60 0.74 0.34 2.15 0.018*Context for High Self-Discipline Auditors 60 0.00 0.48 0.01 0.497*

We conduct a regression model to examine effects of Context, Simple Process Habit Strength, and Self-Discipline (and their interactions) on Issues Identified. Simple Process Habit Strength is defined in the notes to Figure 1. Context is defined in the notes to Figure 2. Self-Discipline is measured as auditors’ agreement on a 7 point scale that they exerted self-discipline while working on the goodwill task. Issues Identified is defined in the notes to Table 1. The results of the regression model are reported in Panel A. Panel B reports results from running the regression within strong simple process habits auditors. Panel C reports estimates from the model for the effect of Context at low (one standard deviation below the mean), medium (the mean), and high (one standard deviation above the mean) levels of Self-Discipline. P-values with * are one-tailed, and all other p-values are two-tailed.

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TABLE 4: Thoughts Reported by Auditors in Written Paragraphs (by Context)

Panel A: Descriptive Statistics – Frequencies (Percentages)

Mentioned the Presence of the Inference

Mentioned the Absence of the Inference

No Mention of the Inference

Inference Typical Context

Alternative Context

Typical Context

Alternative Context

Typical Context

Alternative Context

Coaching or Supervising of Staff

31(47.0%)

10(16.1%)

0(0.0%)

13(21.0%)

35(53.0%)

39(62.9%)

Stress (i.e., due to clutter, cramped)

35(53.0%)

4(6.5%)

1(1.5%)

9(14.5%)

30(45.5%)

49(79.0%)

Interruptions 33(50.0%)

2(3.2%)

5(7.6%)

33(53.2%)

28(42.4%)

27(43.6%)

Busy Season 6(9.1%)

0(0.0%)

0(0.0%)

0(0.0%)

60(90.9%)

62(100.0%)

Contact from the Client

16(24.2%)

21(33.9%)

0(0.0%)

0(0.0%)

50(75.8%)

41(66.1%)

Time Pressure 4(6.1%)

1(1.6%)

2(3.0%)

14(22.6%)

60(90.9%)

47(75.8%)

Personal Recollection

6(9.1%)

1(1.6%)

N/A N/A 60(90.9%)

61(98.4%)

Panel B: Chi-Square Test for Differences Across Context Conditions

Inference Chi-Square Test ResultCoaching or Supervising of Staff χ2

(2) = 23.87, p < 0.001

Stress (i.e., due to clutter, cramped) χ2(2) = 35.52, p < 0.001

Interruptions χ2(2) = 48.03, p < 0.001

Busy Season χ2(1) = 5.91, p = 0.015

Contact from the Client χ2(1) = 1.44, p = 0.230

Time Pressure χ2(2) = 12.27, p = 0.002

Personal Recollection χ2(1) = 3.46, p = 0.063

The above table displays our analysis of thoughts auditors had in their written paragraphs by Context condition. Panel A displays frequencies and percentages (coded from auditors’ written paragraphs during the manipulation of context, i.e., in which they imagined themselves working in the particular context). Panel B displays results of a chi-squared test for differences in frequencies across Context conditions.

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APPENDIX – EMBEDDED ISSUES IN GOODWILL IMPAIRMENT CASE

Assumption Description of the issue

Revenue projections The company consistently over-projected growth in the past, which casts doubt on the accuracy of the current projections

Revenue projections The projected revenue growth of Product C is not guaranteed due to uncertainties (a new competing product, delays in production, and/or reliance on synergies with existing product lines)

Revenue projections There is an outlier in the benchmarking analysis for the projected revenue growth rate, so while the client’s rate is below the peer average, it would not be if this outlier were excluded

Revenue projections Projected revenue growth is inconsistent with the overall market/economy/industry outlook

Operating expense projections The company plans to increase sales staff by 10 percent in the next three years, resulting in a significant increase in employment expense. This is not factored into the client’s operating expense assumption

Capital expenditures projections

The company is building a new $14 million office building, which is not included in the capital expenditures forecast.

Capital expenditures projections

The company’s forecasted capital expenditures exhibit slower growth than industry analysts’ projections.

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