Error management culture

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Error management theory (EMT) is an extensive theory of perception and cognition biases created by David Buss and Martie Haselton. How humans think and make decisions using heuristics and biases may be embedded in the human brain. Error management training is a related area that uses this theory. The objective of it is to encourage trainees to make errors and encourage them in reflection to understand the causes of those errors and to identify suitable strategies to avoid making them in future.^[1]

An example of error management theory is the Ebbinghaus–Titchener circles that can illustrate, a person’s view of which of the (orange) centre circles is bigger is subjective, and can cause a misinterpretation of reality. That is to say, both circles are the same size but each person may interpret the information presented differently depending on which bias they rely on to make the decision.

Various biases in thinking and decision-making have been highlighted by Daniel Kahneman and have been shown to cause cognitive errors in psychological and economic decisions. Cognitive biases in error management theory refer to biases and heuristics that have survived evolutionary history, because they hold some benefits towards reproductive success. Based on Darwinian principles those that «out mate» others have a greater chance of successfully producing offspring. According to this theory, when there are differences in costs of errors made under conditions of uncertainty, selection favours «adaptive biases». Humans are animals, and evolution charts their passage from single celled organisms to the media and technology-consuming organisms of today. These adaption biases ensure that less costly survival or reproductive errors will be committed.

Error management theory asserts that evolved mind-reading agencies will be biased to produce more of one type of inferential error than another.^[2] These mind-reading biases have been further researched in terms of the mating world. Error management theory provides a clear explanation for the discovery that men have a tendency to perceive women as having greater sexual interest in them than is present, if they smile or touch them, and females have a tendency to underplay a man’s interest in them, even if it is quite strong. This is based on commitment scepticism. The theory has been much replicated,^{[failed verification]} but the authors are still^[when?] testing and refining it.^[3] Newer research indicates exceptions as well as gender differences may be significant to the effect, such as postmenopausal effects, the possible projection of sexual and commitment self-interest,^[4] and other differences including unrestricted sociosexuality.^[5]

Type errors[edit]

In the decision making process, when faced with uncertainty, a subject can make two possible errors: type I or type II.

A type I error is a false positive, thinking that an effect is there, when it is not. For example, acting on a fire alarm that turns out to be false. When someone infers sexual interest, where there is none, then a false-positive error has occurred.

A type II error is a false negative, not seeing an effect where one exists. Ignoring the fire alarm that turns out to be accurate, due to scepticism, illustrates this point. Falsely inferring a lack of intent about sexual interest means a false negative error has occurred.

Sexual overperception bias[edit]

Males[edit]

One of the aims of error management theory is to explain sexual overperception bias.^[6] Sexual overperception occurs when a type I error is committed by an individual. An individual committing this type error falsely concludes that someone else has a sexual interest in them.^[6] Research has shown that males are more likely than females to commit sexual overperception bias – men tend to overestimate women’s sexual interest while women tend to underestimate men’s.^[6] This is theorised to be likely due to the fact that the reproductive costs of sexual underperception are greater for men than the risk of making false positives.^[6] Men who perceive themselves as especially high in mate value are especially prone to experiencing this phenomenon. In addition, men who are also more inclined to pursue a short term mating strategy exhibit a more prominent case of sexual overperception bias.^[7]: 334

Manipulation[edit]

Differences in perceptions of sexual interest between men and women may be exploited by both genders. Men may present themselves as more emotionally invested in a woman than they actually are in order to gain sexual access to her; 71% of men report engaging in this form of manipulation and 97% of women report having experienced this form of manipulation.^[7] Women may present themselves as more sexually interested in a man than they actually are in order to fulfill other needs and wants.^[7] The manipulations create conflicts between men and women as to the status of their relationships. Women on the receiving end of emotional manipulation may complain that the relationship is moving too quickly while men on the receiving end of sexual manipulation may complain about «being led on».^[7]

Exceptions[edit]

The sister effect[edit]

The sister effect is an exception to male overperception bias. Haselton and Buss (2000) found that sexual overperception bias would not occur when the target the men had to perceive sexual intent from was their sister.^[8] They found that the men’s perception of their sister’s sexual intent was lower than their perception of sexual intent from other females. Haselton and Buss (2000) believed that this perception of female sexual interest was most accurate as it fell between women’s perception of women (high interest) and women’s perception of their own sexual interest (low interest).^[8] This could be a product of incest-avoidance mechanisms.^[7]

Sexual and commitment self-interest[edit]

Sexual underperception in males is also observed, in cases where men report low levels of their own sexual interest.^[6] A person’s own level of attraction, rather than their gender, may lead to over or under-perception.^[4] The exact mechanism for this is unclear but it is suggested that individuals may project their own level of sexual and commitment interestedness on to their interaction partner, whether they are in a relationship with them or they were strangers before the interaction.^[4]

«The Fox and the Grapes»[edit]

The Aesopian fable of The Fox and the Grapes gives another possible explanation as to why males fall victims of underperception. The fable concerns a fox that attempts to eat grapes, but fails to do so, as they are too high. The fox, being too proud to admit defeat, claims that the grapes are «sour» and thus inedible.^[4] In a similar fashion, males that expect a female to be uninterested may report less sexual interest, as an attempt at saving face.

Male insensitivity bias[edit]

A different explanation for the presence of both overperception and underperception in men is the male insensitivity bias. Evidence has shown that males lack perceptual sensitivity, so they are more likely to misperceive friendliness as sexual interest, but also more likely to misperceive sexual interest as friendliness, in comparison to females,^[9] something that explains the presence of both biases in males.

Sexual underperception bias[edit]

Females[edit]

Women also fall victim to misconceptions during male-female interactions. Haselton and Buss (2000) advocate that these errors primarily stem from women’s perceived desire for a committed relationship by a male counterpart.^[7] Women have evolved strategies to protect themselves from deception.^[10] One of these evolved strategies is to commit the Skeptical Commitment Bias.

Skeptical commitment bias[edit]

Women’s commitment skepticism arises from the high costs of falsely inferring a mate’s commitment to a relationship. It hypothesizes that women have adapted to be cognitively biased towards under perceiving male interest and commitment. This is due to the high cost of a false positive – a man not being committed and a woman accepting him – that could lead to raising a child without an investing mate, reputational damage and risk reducing chances of future courtship. The cost of a false negative – a man that is committed and a woman rejecting him – is far less costly to the female.
Women are limited to how many children they can have in a lifetime. However, men are not limited and can reproduce multiple times. Therefore, overperception costs are higher for females.^[11] This hypothesis is mentioned briefly by Buss (2012).^[7]

Females’ commitment skepticism is unique to humans. For other mammals, courtship rituals are not particularly varied and there is no guesswork or ambiguity involved. For instance, a long-tailed manakin bird has a mating dance that is instinctive and intricate and requires a young apprentice to perform as a duet to the female. If the dance is good enough the female will mate with the male, if the duet falls flat then she will not choose him to reproduce with. However, human courtship behaviour is more ambiguous and so requires these types of cognitive biases to avoid costly errors, in this case, sexual deception.^[6]

Exceptions[edit]

«Skeptical dad» and «Encouraging mum» hypothesis[edit]

Previously, commitment skepticism and overperception biases were thought of as sex specific. Women would underplay or fail to infer a psychological state that is there in order to prevent a false negative error. Men would over perceive female interest because the reproductive costs of sexual under perception are greater for men than women. Al-Shawaf (2016) stated that this is not what the core logic of the Error Management Theory (EMT) suggests. EMT states that the ancestral cost-benefit matrix of both false positive and false negative errors is what drives the cognitive biases and decision-making processes, not gender which is what it has been defined by.^[12]

Imagine a woman is assessing her potential mate’s commitment intent. The woman’s father also has a vested interest in whether she reproduces because he shares genes with her and thus, his reproductive interests extend to his daughter’s mate choice. The father also has to evaluate the costs and benefits of the two types of errors she could make when evaluating her mate’s commitment intent. If the chosen mate sexually deceives and then leaves her then the outcome is more costly for him than if his daughter is more cautious and underestimates intent. Thus, the father might take time before offering his parental seal of approval. The father shows the same skeptical commitment bias as his daughter, favouring the false negative error because it is less costly.

Taking the parental dynamic and switching it from father to mother, the same could be said for sexual overperception bias. A mother has an interest in who her son decides to mate with and therefore will favour the false positive error over false negative. If she fails to detect real interest in the woman, and thus, fails to share this female interest with her son, then it is more costly to her than if she falsely detects sexual interest from a woman towards her son and encourages him to pursue. If her son misses an opportunity, he has missed the chance to pass on his, and in doing so her own, genes. Therefore, the mother shows the same overperception bias as her son, favouring the false positive error because it is less costly.

It is not sex or gender that predicts what type of cognitive bias might be expressed but rather the potential costs to reproductive success.

Postmenopausal females[edit]

Contrasting the evidence for fertile females, skeptical commitment bias does not occur in postmenopausal women. Haselton and Buss (2000)^[8] found evidence for the perception biases studying young subjects; however, this was not representative of older females, who have passed through menopause. The reason for this disparity between pre- and postmenopausal females is that fertile females underestimate the intentions of males to invest in the relationship, in order to avoid the costs of pregnancy without support; however, postmenopausal women do not perceive such costs. Their inability to conceive means that there is no reason to underestimate a male’s intentions.

Alternative explanations[edit]

Some recent studies researching error management theory have found men and women’s perceptions of opposite gender sexual and commitment interest may be mitigated by other explanations.^[5]

Culture[edit]

With a universal proclivity, it would be possible to document the bias across cultures and «across different demographic groups, including among men varying in age, ethnicity, and education level» within cultures^[13] and in females based on their job status, health, levels of education and income equality.^[5] When investigated in Norway, one of the world’s most gender egalitarian societies,^[5] error management theory and its evolutionary explanation were supported. In addition, the pattern of misperception of men and women held up across demographic groups differing in relationship status (singles versus partnered participants).^[5]

Individual differences[edit]

Sexual over-perception relative to under-perception was reported more frequently among younger participants, among singles, and among participants with an unrestricted socio-sexual orientation.^[5] Endorsing and being more open to casual sex may have evoked more sexual interest from members of the opposite sex, leading to more frequent reports of sexual overperception.^[4] Socially unrestricted male and female high school students were found to report being more subject to sexual harassment as well as sexually harassing others.^[5] From this, it is possible that being subject to sexual over-perception may explain the link between socio-sexuality and being subject to sexual harassment.^[5]

Projection[edit]

As stated above what was reported about male sexual and commitment self-interest was also true of women. They self-reported levels of sexual interest and desire for commitment which also predicted their perceptions of their partners’ sexual interest and desire for commitment.^[14] This implies that instead of males and females falling victims of overperception and underperception respectively, both sexes project their own level of interest onto the individuals they are interacting with.^[15]

Reciprocity[edit]

Another explanation that removes overperception and underperception from the picture is how males and females reciprocate the perceived interest in one another. Evidence from speed dating shows that a partner’s level of attraction for an individual, influences the individual’s own interest in that particular partner.^[4] Unlike the «fox and the grapes» approach, which explains how underperception occurs in men as a means of face-saving, reciprocity reflects a real shift in the level of interest in a partner as a result of returning the perceived interest.

Other examples[edit]

Similar examples can also be seen in the judgment of whether a noise in the wild was a predator when it was more likely the wind—humans who assumed it was a predator were less likely to be attacked as prey over time than those who were skeptical. This is similar to the animistic fallacy.^{[clarification needed]}

Smoke detectors are designed with this theory in mind. Since the cost of a Type I error (false positive, e.g. a nuisance alarm) is much lower than the cost of a Type II error (false negative, e.g. an undetected fire that could burn a house down), the sensitivity threshold of a smoke detector is designed to error on the side of Type I errors. This explains why nuisance alarms are relatively common.^[16]

See also[edit]

• Reinforcement learning

Notes[edit]

Further reading[edit]

• Darwin, Charles (1871). The descent of man, and selection in relation to sex (2nd ed.). John Murray. ISBN 978-0-8014-2085-6.
• McKay, R.; Efferson, C. (2010). «The subtleties of error management» (PDF). Evolution & Human Behavior. 31 (5): 309–319. doi:10.1016/j.evolhumbehav.2010.04.005. Archived from the original on 2016-06-11.{{cite journal}}: CS1 maint: bot: original URL status unknown (link)
• Johnson, D. D. P.; Blumstein, D. T.; Fowler, J. H.; Haselton, M. G. (2013). «The evolution of error: error management, cognitive constraints, and adaptive decision-making biases». Trends in Ecology & Evolution. 28 (8): 474–481. doi:10.1016/j.tree.2013.05.014. PMID 23787087.

Introduction, Theory, and Hypotheses Development

Errors occur every day, and in every organization. For individuals and organizations alike, it is thus of interest to learn how to deal with errors in order to be successful. Error management can be described as a perspective that pledges for a “useful approach to errors with the goal of reducing future errors, of avoiding negative error consequences and of dealing quickly with error consequences once they occur” (Frese, 1995, p. 113). We consider errors as unintentional deviations from a goal, rule, or standard (Reason et al., 1990; Frese and Zapf, 1994; Hofmann and Frese, 2011; Frese and Keith, 2015). It has to be noted that the error itself may be disentangled from its consequences. Negative error consequences may ultimately include failure (Frese and Keith, 2015). In an organizational context, failure refers to the “termination of an initiative to create organizational value that has fallen short of its goals” (Shepherd et al., 2011, p. 1229). Further, errors can be distinguished from setbacks. In a work environment, setbacks can be described as “task-related disruptions and inhibitions” (Chong et al., 2020, p. 1409). In that sense, a setback shares a similarity with an inefficiency: Given an inefficiency, the goal is ultimately reached. However, the path to reach the goal is not optimal, as it requires more time and/or resources. On the contrary, setbacks require action from the employees: When confronted with setbacks, employees have to “appraise unforeseen problems, unlearn their existing automatic task scripts promptly, develop novel solutions, learn new ways of operations, and adapt to updated rules and advisories” (Chong et al., 2020, p. 1410).

Error management acknowledges that despite best efforts to prevent errors, it is impossible to avoid errors completely (Reason, 1997). This suggests that dealing with errors after they have occurred is necessary. Error management elaborates on the aforementioned idea that errors can be distinguished from their consequences. Thus, errors do not inevitably lead to negative consequences; it is possible to avoid or reduce negative consequences, and even positive consequences can occur. Such positive consequences may be learning from errors (e.g., Sitkin, 1992). What is more, more learning occurs from failure than from success (Shepherd et al., 2011). Studies on error management have mostly focused on effectiveness of error management training for individuals, for example when principles of error management were incorporated in software training (e.g., Keith and Frese, 2008), or on processes and effects of error management on the individual level (e.g., Frese et al., 1991; Dormann and Frese, 1994; Chillarege et al., 2003; Heimbeck et al., 2003; Keith and Frese, 2005; Keith, 2011; for a meta-analysis, see Keith and Frese, 2008).

On a team and organizational level, team and organizational members may share a view on errors (e.g., they may consider errors as learning opportunities) and may have common practices in regard to errors (e.g., to openly discuss an error with colleagues). The norms and practices constitute an organizational culture (House et al., 2004). Organizational culture consists of the following components: First, norms are behavioral prescriptions that organizational members agree on. Second, these organizational norms are internalized by organizational members. Third, the normative ideas are reinforced by organizational members independent of supervisors or outside interventions. Fourth, through practice, the norms produce ‘normative pressure’ to conform (House et al., 2004).

Error management culture¹ (van Dyck et al., 2005) denotes one form of organizational culture with regard to errors. Given an error management culture, team members expect errors to happen – therefore, they are more vigilant and are better in anticipating errors. This allows them to detect errors faster. As a rule of thumb, the faster errors are detected, the better the chances to minimize negative error consequences (Keith and Frese, 2011). In field studies, error management culture has been shown to benefit organizational outcomes such as profitability, innovativeness, and safety (e.g., van Dyck et al., 2005; Hofmann and Mark, 2006; Keith and Frese, 2011; Fischer et al., 2018). While field studies have the advantage of high ecological validity, the higher ecological validity comes at the expense of lower internal validity, as external influences can hardly be excluded. This may be problematic, as many factors may play an important role and influence organizational performance, for example the leadership of the company, the industry in which the company operates, as well as other cultural factors that go above and beyond the error management culture. In different terms: While the results of these studies are quite impressive, the question remains whether the effect of error management culture on performance unfolds directly, or whether other variables may explain or modify this effect.

Most of the (field) studies on error management culture studied the effects of error management culture on the aggregated, organizational level instead of the more fine-grained team level (e.g., van Dyck et al., 2005; Fischer et al., 2018). Another shortcoming of these field studies is that the question of how an error management culture can be induced remained unanswered.

Inducing culture is not a trivial issue. There are several components that can go wrong if one wants to develop a (organizational) culture in a team: First, people may not agree on a norm. Therefore, the concept of ‘culture (or climate) strength’ has become important in the organizational culture literature (Schneider et al., 2002). If only a few unit members take the norm for granted, we cannot consider it culture or climate. In fact, one key element of culture is that it is shared and accepted by most (if not all) members of the unit (team, organization, society; e.g., House et al., 2004). Low culture strength of error management culture would thus mean a disagreement on how to consider errors and deal with occurring errors. Even if the mean value of perceived error management culture may be high, a disagreement would mean that not all team members in fact feel they may openly admit errors, or voice ideas without having to fear punishment for errors. For error management culture to truly unfold, both the mean level and culture strength have to be high. (If the mean level was low and culture strength high, this would indicate a culture where errors are considered negatively and have to be prevented.) Second, there may be superficial adjustments to instructions by supervisors (or, in an experimental setting, to the experimental instructions); thus, a certain internalization of the norms needs to take place (Gal’perin, 1967). Superficial adjustments to instructions may look very similar to norms, but should not be confused with culture, because people may merely repeat instructions (e.g., in a manipulation check) and this conformity may just reflect the willingness to participate in a study or the willingness to superficially conform to the supervisor. Third, culture needs to change behavior in the organizational unit: The first and certainly important change in behavior is related to communication behavior in the organizational unit (we further develop this issue in the following paragraph). However, communication behavior is just one prerequisite of organizational culture. Fourth, the willingness to conform to a certain cultural norm may be influenced by (a) the time that one spends practicing the norms in an organizational unit, (b) the adequacy of the organizational norm to the tasks that need to be done, and (c) the convincingness and obvious importance of the organizational norm. These issues have the following implications: First, we need to experiment with various instructions and methods of presenting the norms. Second, we also need to experiment with various tasks to find out which ones can be used for certain normative systems. And third, experimental approaches have inherent weaknesses because the time spent practicing the norms is usually highly limited.

Particularly in newly formed teams, communication may be influenced by error management culture, which may ultimately increase performance. We believe that this relationship is particularly important for tasks that require creative problem solving for the following reasons: First, a high error management culture may create an environment where people do not fear blame or punishment for erroneous ideas. Due to the lack of fear of reprisal, team members may dare to articulate ideas they would have kept to themselves in an environment where errors are punished. Furthermore, an error management culture can also be beneficial for resolving misunderstandings, as team members of teams high in error management culture may be more likely to actively ask questions and reassure themselves. A high error management culture fosters an atmosphere where communication about errors, exploration and experimentation, and thus the introduction of new ideas, processes or procedures are encouraged (Keith and Frese, 2011). In such a high error management culture, more communication – both formal and informal – should take place. In teams with a high error management culture, team members are more willing to approach others and ask for help when they cannot correct an error by themselves. Open communication can foster quick error detection and error handling (van Dyck et al., 2005). Moreover, error communication represents the most important practice of error management culture (van Dyck et al., 2005). Error communication denotes the tendency to openly discuss errors with others, without the fear of being punished. It can be assumed that sharing potentially harmful information – i.e., that one has made an error – will be reciprocated by the fellow team members. The reciprocation serves two purposes: for one, it reinforces the error management culture, where errors can be shared openly. For another, when error communication is well received by team members, the reciprocation reinforces future error communication. An open discussion of errors may thus foster communication in general.

Second, communication can foster performance: When more ideas are expressed, the final solution may be improved: “effective group processes, particularly those related to communication, increase information and so are essential for high-performing development processes” (Brown and Eisenhardt, 1995, p. 368). Particularly for complex tasks, exchanging ideas and collectively verifying applicability to the problem, the integration of different viewpoints may foster an augmented and common comprehension of the task at hand. This common understanding, combined with the joint pooling of ideas, may enhance performance. For the context of aviation, Foushee (1984) argues that “the process of interaction is related to group performance” (p. 273). Interaction may be particularly important for group performance when tasks require a deeper understanding of the matter, and where the solution is not pre-defined as one clear statement. Such tasks require at least some amount of creativity (West, 2000).

Research on virtual teams supports the importance of communication on team success (e.g., Piccoli et al., 2004; Cramton and Webber, 2005; Horwitz et al., 2006; Marlow et al., 2017; Eisenberg et al., 2019). Moreover, virtual teams exchange information less effectively than traditional teams (Hightower et al., 1998). As traditional team members spend a lot of time in the office together, they have many opportunities for informal communication, for example when taking lunchbreaks together, and maybe even when they meet privately after work. For project teams, the situation may be quite different: many project teams are comprised only for the duration of one specific project. When team members expect no further cooperation and interaction after the completion of the project, motivation and possibilities for informal interaction may be lower than in “regular” work teams. This may be problematic, as “what appear to be merely ‘casual conversations around the water cooler’ often serve to informally exchange the kinds of information and experience that are critical to project coordination. …. [These informal communication channels] help to fill in the details of work, handle exceptions, correct mistakes and bad predictions, and over time mange the ripple effects of previous decisions and actions” (Herbsleb and Grinter, 1999, p. 86). Furthermore, “since designs never exhibit perfect modularity and are never error-free, process execution is rarely flawless, and the world is never completely predictable, informal communication will be essential to maintain project coordination” (Herbsleb and Grinter, 1999, p. 94).

The aim of the present studies is thus (a) to explore how error management culture can be induced, (b) to investigate whether we can replicate the beneficial effect of error management culture on performance found in field studies under standardized conditions, as well as (c) to gain insights into potential variables modifying or explaining this relationship. To address these issues, we conducted two studies with newly formed teams, in which we aim to explore the following research question and hypotheses:

Research Question 1: How can error management culture be induced? (Studies 1 and 2).

Hypothesis 1: Error management culture positively predicts performance. (Studies 1 and 2).

Hypothesis 2: Culture strength moderates the relationship between error management culture and performance. (Studies 1 and 2).

Hypothesis 3: Communication mediates the effect between error management culture and performance. (Study 2).

In both studies, we follow an experimental approach and shift the focus from the organizational to the team level. By grouping strangers into teams – newly forming teams of people who have not known each other before – we have the opportunity to attempt to experimentally induce an error management culture.

We use an abductive approach (e.g., Bamberger, 2019) for our experiments in this field. We do not suggest that we will manage to achieve all aspects of the complex concept of organizational culture within two experiments. Rather, we think that we should get closer to an idea of how to develop an organizational culture of a team.

In Study 1, which we conducted in a laboratory setting, we employed two rational problem solving tasks, for which the degree of correctness varies gradually and can be objectively quantified. Employing two tasks enabled us to explore the duration of potential effects of our manipulation. In Study 2, which we conducted online, we employed one task that requires creative problem solving. We adapted our manipulations from Study 1 to fit the different task and context, and we additionally created a second, “slimmed,” manipulation for error management culture. The design of Study 2 (see below) further allowed us to analyze the amount of communication between the team members. Both rational and creative problem solving are important to attain organizational performance, and are adequate variables to study team behavior in an experimental, yet realistic context (in fact, participants in Study 2 believed to be working on an actual task for an actual company).

The crucial test whether culture has actually unfolded (as opposed to a mere compliance with instructions) examines the culture strength. According to the literature, culture strength should moderate the effects of error management culture on performance (Schneider et al., 2002).

It is highly relevant to study error management culture in an experimental setting, thereby allowing standardization and exclusion of other variables rather than statistically controlling for them. On the team level, different processes may be related to error management culture than to error management on the individual level. Our research contributes to the existing literature in the following ways. First, from an empirical perspective, we attempt to experimentally induce error management culture and to investigate the beneficial effects of error management culture on performance. Second, from a theoretical perspective, by studying how an error management culture can be induced, we aim to shed light on questions regarding the drivers of change and innovation effects. Third, we are among the first ones to explicitly take culture strength into consideration when studying effects of error management culture. Fourth, as field studies have repeatedly demonstrated beneficial effects of error management culture on performance, from a practitioner perspective, the question of how to induce an error management culture is highly relevant.

In the following, we describe the studies we conducted in detail, discuss potential explanations for our results, and provide an outlook for future studies.

Study 1: Error Management Culture and Performance in Terms of Rational Problem Solving

Method

Sample

Participants were 136 students (N = 44 triads and 2 dyads) of a mid-sized German university. Mean age was 22.14 years (SD = 3.20) and 69.1% were female. Most of the participants (67.7%) worked at least part-time. Participants received either EUR 8 (approximately USD 9.50) or partial course credit as compensation.

Experimental Design and Procedure

We invited participants into the laboratory in sessions of three persons each to work on two team tasks, namely, the “NASA Moon Survival Problem” task (Hall and Watson, 1970) and its variation “Survival at Sea.” In both tasks, participants had to rank 15 items of equipment in terms of their importance for survival. The tasks (and similar variations of it) are commonly used to study team decision making processes (e.g., Wanous and Youtz, 1986). For both tasks, expert solutions represent the optimal ranking of the items.

We asked participants to individually complete questionnaires regarding demographics and their attitudes about errors. Then, we grouped individual participants from the same session into teams of three and randomly assigned teams to one of two experimental conditions (between-participants design with one factor: error framing condition): (1) Error management or (2) Error prevention. In the Error management condition, participants were encouraged to make errors while working on the team task and to learn from them. In the Error prevention condition, participants were instructed to avoid errors while working on the team task. We asked participants to write down the most important points of the manipulations, formulated as action principles (Glaub et al., 2014) on a flipchart. Furthermore, we aimed at fostering internalization (e.g., Gal’perin, 1967) of the manipulations by repeating them several times throughout the experiment. After receiving the manipulations and the instructions for the first task (i.e., the NASA Moon Survival Problem), participants were asked to discuss what they had read about errors. Participants then had 20 min to work on the first task. After 20 min, participants were provided with the expert solution for the first task, and asked to calculate the difference of their solution to the expert solution. Participants were informed that these differences were considered as errors. Subsequently, participants individually had to complete questionnaires regarding how they perceived the work environment in the team. After completion of the questionnaires for the first task (see “Measures” section for details), participants received the second task (i.e., Survival at Sea). Again, participants were asked to commonly find a solution, then were provided with the expert solution, and lastly asked to complete questionnaires on the work environment in the team (see “Measures” section for details). Finally, participants were thanked, debriefed and compensated.

Measures

Perceived Error Management Culture

We assessed perceived error management culture after each task with the 17-item Error Management Culture Questionnaire (van Dyck et al., 2005; α = 0.90 after Task 1 and α = 0.91 after Task 2), with slight modifications of item wordings to fit the team context. For example, the original item “After making a mistake, people try to analyze what caused it” was changed to “After making a mistake, people in this team tried to analyze what had caused it.” The Error Management Culture Questionnaire (van Dyck et al., 2005) is commonly used as a measure in organizations (Frese and Keith, 2015). It entails aspects of error competence, learning from errors, analyzing errors, and error communication. Participants responded on a five-point Likert scale. Individual responses were aggregated at the team level. To justify aggregation, we computed within-team agreement for each team using r_wg(j) (James et al., 1984, 1993), and reliability of responses among team members with intraclass correlation coefficients (ICC; Bliese, 2000). The mean values of r_wg(j) = 0.84, ICC(1) = 0.28 and ICC(2) = 0.53 [F(45,90) = 2.13, p < 0.01] for Task 1 and r_wg(j) = 0.89, ICC(1) = 0.24 and ICC(2) = 0.48 [F(45,88) = 1.94, p < 0.01] for Task 2 suggested appropriate levels of within-team agreement and reliability (Le Breton and Senter, 2008).

In order to avoid potential confusions with our experimental intervention and independent variable error management framing, we will refer to our measure of error management culture as perceived error management culture.

Team Performance

As a measure of team performance, for each task, we calculated the difference between the team’s solution and the expert solutions (ranging from 0 to 112). We inverted the variable, so that higher values indicate smaller deviations from the expert solution, and thus better performance. In the following, we will refer to this as closeness to the expert solution.

Moderator Variable: Culture Strength

As a measure for culture strength (Schneider et al., 2002), we used r_wg(j)-values of each team.

Control Variables

Task Familiarity. As task familiarity could influence performance in the task, we assessed task familiarity as a potential control variable. We asked participants whether they were familiar with the tasks, or had worked on the tasks before. A sample item is “Were you familiar with the ‘NASA Moon Survival Problem’ and the ‘Survival at Sea’ task?” Cronbach’s alpha was 0.79.

Familiarity With Team Members. As we recruited participants for Study 1 on campus, we considered the possibility that some participants may know one or both other team members. As we aimed to study how error management culture unfolds, and assumed that therefore, it was important to newly form teams, we decided to include familiarity with team members as control variable. We assessed if participants were familiar with their team members by asking “How well do you know the two other members of your group?” (from 1 = not at all to 5 = very well).

Results

Means, standard deviations, and intercorrelations of Study 1 variables are provided in Tables 1, 2.

To test whether we succeeded in inducing error management culture (Research Question 1) and if we can find the error management culture and performance link in teams (Hypothesis 1) for a rational problem solving task, we conducted mediation analyses (Preacher and Hayes, 2004), with error framing condition (i.e., Error Management or Error Prevention framing) as predictor variable, perceived error management culture as mediator, and performance (i.e., closeness to the expert solution) as criterion variable. We used 5,000 bootstrap samples and estimated 95% bootstrap confidence intervals (CIs). We included our control variables task familiarity and familiarity with team members in our analyses as covariates.

For the first task, we found that the error management culture manipulation led to a higher level of perceived error management culture for Task 1 than the error prevention culture manipulation, β = 1.28, p < 0.001. We did not find a relationship between perceived error management culture for Task 1 and performance, β = −0.18, p = 0.40. We did not find support for the indirect effect of error framing condition on team performance through perceived error management culture for Task 1, β = −0.23, CI [−0.83, 0.27] (see Table 3).

For the second task, we found that the error management culture manipulation led to a higher level of perceived error management culture for Task 2 than the error prevention culture manipulation, β = 0.84, p < 0.001. We did not find a relationship between perceived error management culture for Task 2 and performance, β = 0.11, p = 0.55. We did not find support for the indirect effect of error framing condition on team performance through perceived error management culture for Task 2, β = 0.09, CI [−0.23, 0.48] (see Table 3).

While we succeeded in inducing error management culture in terms of an effect of our manipulation on perceived error management culture, we were not able to find a direct effect of error management culture on performance. This is contradictory to our expectations based on findings in field studies (e.g., van Dyck et al., 2005; Fischer et al., 2018). One possibility why we did not find the expected effect is that maybe we did not succeed in actually manipulating error management culture after all. It is possible that the effects we found on perceived error management culture are rather an indicator of superficial compliance with the instructions than an actual change in culture.

In order to test this hypothesis (Hypothesis 2), we decided to take a closer look at culture strength (i.e., the agreement about the groups’ culture between team members; Schneider et al., 2002) regarding error management culture. In order to explore whether error management culture predicted performance in teams with a high culture strength, we tested whether culture strength moderates the relationship between perceived error management culture and performance (Hypothesis 2).

For Task 1, we conducted a moderation analysis using multiple linear regression, with perceived error management culture in Task 1 as predictor, culture strength in terms of r_wg(j) as moderator, and performance in Task 1 as criterion variable. We did not find a significant main effect of perceived error management culture (β = 0.24, p = 0.81), nor of culture strength (β = 0.60, p = 0.72). Further, we did not find a significant interaction effect of perceived error management culture and culture strength (β = −0.67, p = 0.77) (R² = 0.01; F = 0.16, p = 0.92).

Similarly, for Task 2, we conducted a moderation analysis using multiple linear regression, with perceived error management culture in Task 2 as predictor, culture strength in terms of r_wg(j) as moderator, and performance in Task 2 as criterion variable. We did not find a significant main effect of perceived error management culture (β = 0.87, p = 0.69), nor of culture strength (β = 0.41, p = 0.87). Further, we did not find a significant interaction effect of perceived error management culture and culture strength (β = −1.28, p = 0.74) (R² = 0.13; F = 2.01, p = 0.13). Thus, Hypothesis 2 is rejected (see Table 4).

Discussion

In Study 1, we were successful in manipulating error management culture in terms of an effect of our manipulation on perceived error management culture (Research Question 1). However, we could not find a beneficial effect of error management culture on performance in terms of rational problem solving (Hypothesis 1). Our additional analysis did not provide evidence for our speculation of a moderating effect of culture strength on the effect of perceived error management culture on performance. In concrete terms, we did not find evidence that perceived error management culture was beneficial for performance in teams with high culture strength, but not for teams with low culture strength.

We assumed that one of the reasons we did not find an effect of error management culture may lie in the type of tasks we had used – tasks that required rational problem solving. In order to effectively work on tasks that require rational problem solving, more analytic, convergent thinking may be required. Teams, particularly newly formed teams, that work on tasks that require rational problem solving may discuss in a focused, goal-oriented way (Guilford, 1957), and try to avoid errors whenever possible. On the contrary, in tasks that require creative problem solving, such as brainstorming, divergent thinking may be an effective strategy. For effectively conducting brainstorming tasks, it is particularly important that team members voice their ideas, without any limitations or barriers as to whether the idea may be implemented. Open communication is a vital part of error management culture. Therefore, we assumed that error management culture may be particularly beneficial for tasks that require creative problem solving, such as brainstorming. We aimed to address these possibilities in Study 2. As in Study 1, the pattern of results was the same for both tasks, for Study 2, we decided to employ only one task.

Study 2: Error Management Culture and Performance in Terms of Creative Problem Solving

We conducted Study 2 as an online experiment with newly formed teams. In Study 2, participants’ task was to create a marketing plan for a certain product (Hubner et al., 2020). While there are some factors that need to be considered when creating a marketing plan (such as who is the target group, how to advertise for the product, where to advertise, etc.), it is a task that requires a considerable amount of creativity. Similar to a brainstorming task, at first, one may collect ideas, and only in a second phase, the ideas are evaluated and selected, before agreeing on a common marketing plan.

We formed teams by grouping individual participants who had not known each other, and we attempted to manipulate error management culture. We had planned to comprise teams of three participants. However, as we had observed that some participants dropped out before the other two team members had shown up, we also used data of dyads, but included team size as control variable.

In Study 2, we employed the same manipulations as in Study 1 (after adapting them to fit the task and context). We additionally created a “slimmed” manipulation for error management culture. The main difference of both error management culture manipulations was that in the “slimmed” version, we did not ask participants to develop, formulate and note action principles for error management. Thereby, we aimed to address the issue that in the online environment, we were not able to control whether participants actually complied with our manipulation and did, in fact, formulate action principles. Different effects for both manipulations may thus suggest that participants in the “regular” error management condition actually complied with the manipulation and formulated action principles, and that these action principles were an important aspect of the manipulation.

Method

Sample

Participants were working adults from the United States recruited online using Amazon’s Mechanical Turk. Previous research has shown that data gathered from such environments is of acceptable quality (e.g., Buhrmester et al., 2011). We carefully followed specific suggestions that shall help to further enhance this quality: We used attention check items (e.g., “I receive my paycheck from goblins”; Meade and Craig, 2012), a manipulation check that measures understanding of instructions (see below) as a prerequisite to further participate in the experiment, as well as fair compensation (e.g., Aguinis and Lawal, 2012; Cheung et al., 2017). Additionally, in order to statistically control for potentially lower commitment to the participation in the study, we assessed and controlled for goal commitment (see below). The criteria for inclusion of respondents in the survey were age (>18 years) and place of residence (United States). Fourteen participants did not meet our criteria for inclusion and were excluded from further analyses. The final sample consisted of 309 participants (N_total = 128 teams, of which n_triads = 53 and n_dyads = 75). Mean age of participants was 35.81 years (SD = 11.53) and 43.9% were female². Participants’ average work-experience was 13.00 years (SD = 10.08) and 32.5% reported to hold a leadership position. Participants received USD 4.50 for participation (which corresponds to an hourly wage of approximately USD 9 and was thus in line with the United States federal minimum wage).

Experimental Design and Procedure

Participants were invited to work on a team task, namely, to develop a marketing plan for a newly developed product (Hubner et al., 2020). The product was fictitious, but as Hubner et al. (2020) demonstrated, participants deem it as realistic and often work enthusiastically on this task. The instructions explained that a start-up is currently working on the marketing concept of its most promising product, but is not sure how to advertise for it. Therefore, the start-up asks the “wisdom of the crowd” for help. Participants were explained that their task is embedded in a research project and that they also have to complete a questionnaire after working on the team task.

Participants were randomly assigned to one of three experimental conditions (between-participants design, one factor error framing condition with three levels): (1) a “slimmed” Error Management framing condition that did not foster internalization, (2) an Error Management framing condition similar to that of Study 1, and (3) an Error Prevention framing condition similar to that of Study 1. Participants who were grouped together received the same manipulation. In order to keep the manipulation realistic and in line with what is common in online environments such as Amazon’s Mechanical Turk, the manipulation was part of the written instructions that participants received for task completion. Our manipulations focused on how participants should deal with errors in the process of the team discussion. In the slimmed Error Management framing manipulation, we encouraged participants to make errors and to learn from them. In the Error Management framing condition similar to that of Study 1, we additionally aimed to foster internalization of the manipulations (e.g., Gal’perin, 1967). For this purpose, we asked participants to write down two error principles on a sheet of paper so they should be able to see them the entire time when working on the team task: “errors are positive” and “talk about errors openly in the team, as you can learn from them.” These principles should serve as guidelines to follow while working on the team task. In the Error Prevention framing condition similar to that of Study 1, participants were instructed to avoid errors. We also asked them to follow two error principles: “avoid errors as they only bother you and slow you down” and “make the marketing plan as perfect as possible” right from the start. We also asked participants to write down the error principles on a sheet of paper so they should be able to see them the entire time when working on the team task.

After reading the instructions, participants were asked to respond to questions assessing the understanding of the instructions. Participants who had received the same manipulation (i.e., either “slimmed” Error Management, Error Management or Error Prevention framing) and answered the questions correctly then arrived on a page containing a built-in chatroom. After the team members arrived on the page with the chatroom, the chat-function was automatically enabled. Participants could start to chat and generate ideas for a marketing plan. The teams had a maximum of 20 min time to complete the task. The chat window was programmed to close automatically 30 min after the first participant had logged in. Three minutes prior to that, participants were informed about the remaining time. After the chatroom closed, participants had to submit the team’s common final ideas on the next page. Subsequently, participants individually had to fill out questionnaires regarding how they perceived the work environment in the team (see “Measures” section for details). Finally, participants were thanked, debriefed and provided with a code for payment on Amazon’s Mechanical Turk.

Measures

Understanding of Instructions

After reading the instructions and before the dependent variable was assessed, participants responded to questions that probed whether participants had understood what the task was about and what the instructions had stated about errors. We asked participants three questions (“What does our most promising product do?,” “What task do you have to accomplish in this project?,” and “What was written in the text about making errors while working in a team?”) and they had to choose the correct answer out of four possibilities. A false answer led to an exclusion from the study, as it indicated that participants had not read the instructions carefully.

Error Management Culture

As in Study 1, we assessed error management culture with the 17-item Error Management Culture Questionnaire (van Dyck et al., 2005; α = 0.94), with slight modifications of item wordings to fit the team context. Participants responded on a five-point Likert scale. Individual responses were aggregated at the team level. To assess whether aggregation is justified, we computed within-team agreement for each team using r_wg(j) (James et al., 1984, 1993), and reliability of responses among team members with intraclass correlation coefficients (ICC; Bliese, 2000). The mean values of r_wg(j) = 0.83, ICC(1) = 0.15 and ICC(2) = 0.30 [F(127,177) = 1.43, p < 0.05] suggested low but still appropriate levels of within-team agreement and reliability (Le Breton and Senter, 2008), justifying aggregation.

Communication

We assumed that teams that communicated more with each other during the brainstorming task may produce more creative ideas. We thus observed the communication of the teams in terms of the number of words exchanged during the group discussion. We analyzed the chat protocols and counted the number of words that the participants exchanged while working on the task. As this is an objective measure, within-team consistency and agreement measures are not applicable.

Dependent Variables

We used two dependent variables as indicators of performance: the quality of the ideas for the marketing plan, and the quantity of the ideas the marketing plan consisted of. We operationalized quality of the ideas by assessing three characteristics of the marketing plans: originality, usefulness, and completeness (Dean et al., 2005). Dean et al. (2005) defined an idea as original when it “rare (…), ingenious, imaginative, or surprising” (p. 663). To assess usefulness, we oriented on Dean et al.’s (2005) definition of workability/feasibility: the idea has to be “easily implemented and does not violate known constraints” (Dean et al., 2005, p. 663). An idea can be considered as complete when it covers aspects such as “who, what, where, when, why, and how” (Dean et al., 2005, p. 663). Two independent raters who were blind to the conditions rated the marketing plans on originality, usefulness, and completeness (all ICCs > 0.70). Subsequently, originality, usefulness, and completeness (α = 0.87) were combined as a measure for the quality of the ideas for the marketing plan. We operationalized quantity of the ideas as the number of ideas submitted for the marketing plan. For this purpose, we counted the number of discrete ideas submitted by the teams.

Moderator Variable: Culture Strength

As in Study 1, we used r_wg(j)-values of each team as a measure for culture strength (Schneider et al., 2002).

Control Variables

Team Size. We controlled for team size because the amount of communication in the group may be higher in teams of three members than in teams of two members.

Task Familiarity. We included task familiarity as control variable, because both the quality and the quantity of ideas for the marketing plan may depend on how familiar participants are with similar tasks. We assessed task familiarity with the following three questions: “How familiar are you with creativity tasks, such as the task you were working on?”; “How familiar are you with creativity methods, such as brainstorming?”; “How experienced are you with marketing (from work, university, etc.)?” Participants responded on a five-point Likert scale. Cronbach’s alpha was 0.82.

Goal Commitment. Particularly for studies that are conducted online, the extent to which participants take the task seriously may influence the results. We therefore included goal commitment as control variable. We assessed goal commitment with three items of Hollenbeck et al.’s (1989) nine-item Goal Commitment scale. One sample item is “I was strongly committed to pursuing our goal of submitting a marketing plan.” Participants responded on a five-point Likert scale. Cronbach’s alpha was 0.72.

Results

Means, standard deviations, and correlations of Study 2 variables are provided in Tables 5, 6.

To test whether we succeeded in inducing error management culture (Research Question 1) and whether we could find an effect of perceived error management culture on performance (Hypothesis 1), we conducted mediation analyses (Preacher and Hayes, 2004; Hayes and Preacher, 2014) with error framing condition (i.e., Error Management vs. Error Prevention vs. “slimmed” Error Management framing) as predictor variable, perceived error management culture as mediator, and performance (in terms of quality and quantity) as criterion variables. As in Study 1, we used 5,000 bootstrap samples and estimated 95% bootstrap CIs, and we included team size, task familiarity, and goal commitment as covariates. For our multicategorical predictor variable (i.e., error framing condition), we created two dummy variables with indicator coding and the Error Prevention framing as reference category: D1 with codes of (0, 1, 0) for Error Prevention framing, Error Management framing, and “slimmed” Error Management framing, respectively, and D2 with codes of (0, 0, 1) for Error Prevention framing, Error Management framing, and “slimmed” Error Management framing, respectively.

We found that the Error Management framing manipulation led to a higher level of perceived error management culture than the Error Prevention framing manipulation, D1: β = 0.40, p < 0.05 (see Figure 1 path a₁). The “slimmed” Error Management framing manipulation did not lead to a higher level of perceived error management culture than the Error Prevention framing manipulation, D2: β = 0.00, p = 0.99 (see Figure 1 path a₂). As in Study 1, we could not find the relationship between perceived error management culture and performance, β = 0.17, p = 0.08 for quality of the ideas (see Figure 1 path b), and β = 0.15, p = 0.13 for quantity of the ideas (see Figure 1 path b). We did not find support for the indirect effect of the experimental manipulation on performance (neither in terms of quality nor quantity of the ideas) through perceived error management culture, neither for our first dummy variable (D1) “Error Prevention framing vs. Error Management framing,” β = 0.07, CI [−0.02, 0.21] for quality of the ideas, and β = 0.06, CI [−0.03, 0.17] for quantity of the ideas (see Figure 1), nor for our second dummy variable (D2) “Error Prevention framing vs. “slimmed” Error Management framing” β = 0.00, CI [−0.06, 0.09] for quality of the ideas, and β = 0.00, CI [−0.08, 0.07] for quantity of the ideas (see Table 7 and Figure 1).

To test whether culture strength moderated the relationship of error management culture and performance (Hypothesis 2), we conducted a moderation analysis using multiple linear regression, with perceived error management culture as predictor, culture strength in terms of r_wg(j) as moderator, and performance (both in terms of quality and quantity of the ideas) as criterion variable. For performance in terms of quality of the ideas, we did not find a significant main effect of perceived error management culture (β = 0.02, p = 0.92), nor of culture strength (β = −0.96, p = 0.26). Further, we did not find a significant interaction effect of perceived error management culture and culture strength (β = 0.26, p = 0.30) (R² = 0.06; F = 2.74, p = 0.05). For performance in terms of quantity of the ideas, we did not find a significant main effect of perceived error management culture (β = 0.32, p = 0.68), nor of culture strength (β = −1.63, p = 0.58). Further, we did not find a significant interaction effect of perceived error management culture and culture strength (β = 0.44, p = 0.61) (R² = 0.04; F = 1.88, p = 0.14) either. Thus, Hypothesis 2 is rejected (see Table 8).

To test whether perceived error management culture affected performance indirectly through communication (Hypothesis 3), we conducted serial mediation analyses (Preacher and Hayes, 2004; Hayes and Preacher, 2014) with error framing condition as predictor, perceived error management culture and communication as mediators, and performance (in terms of quality of the ideas or quantity of the ideas) as criterion variables. We used 5,000 bootstrap samples and estimated 95% bootstrap CIs. We found that the Error Management framing manipulation led to a higher level of perceived error management culture than the Error Prevention framing manipulation, D1: β = 0.40, p < 0.05 (see Figure 2 path a₁). The “slimmed” Error Management framing manipulation did not lead to a higher level of perceived error management culture than the Error Prevention framing manipulation, D2: β = 0.00, p = 0.99 (see Figure 2 path a₂). Furthermore, perceived error management culture positively predicted communication, β = 0.24, p < 0.01 (see Figure 2 path d), and communication positively predicted performance both in terms of quality of the ideas, β = 0.43, p < 0.001 (see Figure 2 path b), and quantity of the ideas, β = 0.45, p < 0.001 (see Figure 2 path b). The 95% bias corrected confidence interval for the indirect effect excluded zero, indicating a significant indirect relationship for our first dummy variable (D1) “Error Prevention framing vs. Error Management framing” with performance (both in terms of quality of the ideas and quantity of the ideas), β = 0.04, CI [0.00, 0.11] for quality of the ideas, and β = 0.04, CI [0.00, 0.11] for quantity of the ideas (see Figure 2). In other words, the results are consistent with the idea that perceived error management culture and communication mediate the relationship between error framing condition and performance. For our second dummy variable (D2), “Error Prevention framing vs. ‘slimmed’ Error Management framing,” we did not find an indirect relationship with performance (in terms of quality of the ideas or quantity of the ideas), β = 0.00, CI [−0.05, 0.04] for quality of the ideas, and β = 0.00, CI [−0.05, 0.05] for quantity of the ideas (see Table 9 and Figure 2).

Discussion

In sum, regarding Research Question 1, we succeeded in inducing error management culture in terms of an effect on perceived error management culture using the same type of manipulation as in Study 1, i.e., our manipulation containing action principles. Our “slimmed” manipulation (that did not ask participants to internalize action principles) was not successful.

In regard to Hypothesis 1, we were not able to find a direct, beneficial effect of error management culture on team performance. As in Study 1, culture strength did not moderate the relationship between error management culture and performance (Hypothesis 2). However, in regard to Hypothesis 3, we found an indirect, beneficial effect through communication in that our manipulation that included action principles fostered perceived error management culture, which increased communication, and communication fostered team performance.³

General Discussion

In the present paper, we investigated whether and how error management culture may be induced in newly formed teams, and if and how error management culture can be beneficial for performance, both in terms of rational and creative problem solving. We found that inducing error management culture is more difficult than expected. Our manipulation that included action principles that aimed to foster internalization was successful in terms of an effect on perceived error management culture. However, we did not find a direct effect of error management culture on performance, as it was previously found in field studies. This raises the question whether we actually succeeded in inducing error management culture, or whether our results rather reflect mere compliance with our instructions. In Study 2, where we included communication as a mediator, we found error management culture to be beneficial for performance indirectly via communication. In both samples, we further tested whether culture strength moderated the effect of error management culture on performance. We did not find the expected moderation effect. In the following, we will discuss our findings in greater detail, and suggest potential theoretical explanations.

Theoretical Contributions

Inducing an Error Management Culture

To the best of our knowledge, the present studies are among the first ones to investigate how an error management culture can be induced. In two studies, we used manipulations that included action principles (Glaub et al., 2014) in regard to dealing with errors – “error principles.” We had explicitly asked participants to write down these principles and follow them throughout working on the task(s). Additionally, we repeated our manipulations several times, and had a “reminder” of the principles visible at all times during the team discussion. By repetition of the main principles of our manipulations, we aimed to foster that participants internalize these principles (Gal’perin, 1967). As in Study 2, our manipulation that did not include these “error principles” was not successful, including such principles seems to be important when inducing error management culture.

It has to be noted that while we succeeded in terms of an effect of our manipulation on perceived error management culture, we did not find an effect (neither of our manipulation, nor of perceived error management culture) on performance. An explanation may either lie in the error management culture and performance relationship, or in the culture strength regarding error management culture. In the following, we discuss both possibilities in greater detail.

The Error Management Culture–Performance Relationship

Contrary to what we had expected based on the literature on error management culture in organizations (e.g., van Dyck et al., 2005; Fischer et al., 2018), we did not find a direct effect of error management culture on performance, neither in terms of rational, nor in terms of creative problem solving. One potential interpretation could be that error management culture is not beneficial for performance. This, however, would be contrary to findings in, for example, the aforementioned field studies. Additionally, experimental evidence on the individual level has repeatedly demonstrated a beneficial effect of error management training on performance (e.g., Keith and Frese, 2005). While we were able to successfully induce error management culture in terms of an effect on perceived error management culture in both studies, only in Study 2, where we included communication as mediating variable, we found that error management culture had an indirect effect on performance in terms of creative problem solving through increased communication among team members.

On the one hand, we were surprised that we did not find the direct effect of error management culture on performance that has been reported non-experimental field studies (e.g., van Dyck et al., 2005; Fischer et al., 2018). On the other hand, there is a major difference between the organizations studied in non-experimental field studies and the teams in our studies: In organizations, the organizational culture is most likely engrained and internalized by the members of the organization. The teams in our study were newly formed and comprised of strangers who had no prior interaction. Consequently, the teams did not have an already internalized culture, thus had to adopt a new culture. It is possible that in such situations where culture has to be newly formed and unfold, error management culture may take more time to fully unfold, or may not be strong enough to directly impact performance – communication may be the key driver.

Culture Strength

Our second potential explanation to why we did not find an effect of error management culture on performance lies in the culture strength, i.e., the agreement about the groups’ culture between team members (Schneider et al., 2002). We thus tested whether culture strength moderates the relationship between perceived error management culture and performance. We did not find culture strength to moderate the relationship of error management culture and performance. In other words, the relationship between perceived error management culture and performance did not depend on team members’ agreement about the group’s culture. This result reinforces our assumption that we did not actually succeed in inducing culture, and the effect of our manipulation on error management culture rather represents participants’ superficial compliance with our instructions. It has to be noted that when controlling for the (lack of) agreement, perceived error management culture was related to increased team performance.

Practical Contributions

An error management culture conveys a constructive view on errors as well as strategies for dealing with errors that have occurred. Negative error consequences, such as failure (Shepherd et al., 2011; Frese and Keith, 2015) shall be prevented, and positive consequences, such as learning from errors, shall be encouraged. Based on the previous findings that error management culture is beneficial for organizational performance, the question of how an error management culture can be induced is important for practitioners.

With our studies, we provide a starting point that outlines what interventions in change processes and mergers and acquisitions should consider and include. Our studies demonstrated that in order to induce error management culture, action principles in regard to errors shall be internalized, and thereby shape culture. These “error principles” may include rules how to deal with errors in the team or organization. For example, these “error principles” may explicitly encourage communicating an error that has occurred. By sharing the error with others – without having to fear blame or other negative consequences – other people may learn from the error. Furthermore, the error, once shared with others, may be used as a starting point to develop new, innovative ideas. Ultimately, this may enhance team or organizational performance.

Strengths, Limitations, and Future Research

One of the strengths of our studies is that we used different sources for all our variables. In both our studies, our independent variable was an aggregate measure of the respective team members. In Study 1, our dependent variables were objective measures. In Study 2, the dependent variables were assessed and counted by raters, and communication was objectively measured. Thereby, we were able to circumvent the common source bias, which is a problem in many studies.

Furthermore, replication is essential to reduce the likelihood of false-positive findings. In abductive research, (internal) replication is “a viable antidote to what Bliese and Wang (2020) term ‘origination bias,’ or in other words, ‘the practice of viewing findings from a single, original study as being almost sacred,’ even if these findings were exploratory in nature” (Bamberger, 2019, p. 104). In Study 2, we were able to replicate the findings regarding our manipulation containing action principles we obtained in Study 1. Moreover, we were able to extend our model by including communication as well as an indirect effect on performance.

Nonetheless, some questions remain to be answered. First, culture may unfold its beneficial effects over time. The present studies have largely neglected a temporal perspective on error management culture. In the present studies, newly formed teams worked together for 30 to 60 min. This may not be long enough for a (team) culture to establish, or to unfold effects on team performance. Particularly for newly formed teams, as was the case in the present studies, this time frame may not be long enough to establish shared practices (e.g., House et al., 2004). Future studies should observe teams over a longer period of time. For example, when conducting studies with university students, student teams could be observed throughout one semester. One possibility would be to form groups of first semester students, as most likely, first semester students do not know each other yet. With these newly formed teams, research could test different versions of error management instructions that may focus on different aspects of error management and error management culture (e.g., error detection, error handling, error communication). Students could be randomly assigned to either one of these classes, or a “control class” that does not make explicit statements about how errors should be dealt with. Over the course of an entire semester, it could be observed how an error management culture unfolds, and whether the performance of students in the “error management classes” was better in comparison to the control condition. As field studies have demonstrated beneficial effects of error management culture, error management training has been shown to be beneficial for performance, and the “control classes” represent more or less every “typical” class at university nowadays, institutional review boards should approve an application for such a study. If students would agree to provide their student registration number, such a design would even allow to study long-term effects on performance in terms of the grade point average. Taking the temporal perspective into consideration is a promising area for future research.

Moreover, we consider it possible that the group size in our studies is too small for a team culture to establish. All the teams in the studies reported in the present paper were either dyads or triads. We particularly aimed at recruiting more than two people (whenever possible), as we assumed team dynamics to unfold in teams with at least three members. One key element of error management culture is communication. Usually, this encompasses error communication. In Study 2, we have demonstrated that the mere quantity of communication was associated both with error management culture and with performance. Based on the tentative finding that communication may be an important variable for the error management culture and performance relationship, the size of the teams in our studies (two or three team members) may not have been adequate. In teams that are comprised of more members, there may be more chances and instances of communication. This increased (possibility for) communication may reinforce the error management culture. This may be a hint that an error management culture may unfold more easily in teams comprised of more team members. Future studies should thus attempt to recruit teams that are comprised of more members.

In that sense, the group size may also explain our somewhat surprising finding that culture strength did not moderate the relationship between error management culture and performance. It is possible that in within-group agreement might be more difficult to achieve in small groups as compared to medium-sized groups. We thus suggest that in future research with teams comprised of three or more members, the moderating role of culture strength should be further investigated.

We believe that even considering the limitation of the relatively small group size in our sample, the merit of our manuscript is to provide first ideas of how to induce an error management culture. Therefore, for this purpose, we believe that including dyads (while statistically controlling for the group size) is justified. Future studies should, if possible, use groups of three or even more members as level of analysis. Based on our experience, we suggest that for practical reasons, such experiments should be conducted in a laboratory setting (as opposed to online). The current Covid-19-crisis seriously limits researchers’ options for the moment being.

Furthermore, it remains to be tested whether our intervention can be successfully applied in organizational settings, where teams typically have already been formed. It seems plausible that interventions would have to be even stronger in order to “overrule” already established norms and practices regarding errors in such teams or organizations. Second, future research could explore how sustainable, i.e., long-lasting, the effects of such interventions are. Answering this question could be particularly important in view of change processes and mergers and acquisitions. For example, for how long should interventions regarding a cultural integration of the companies in a merger and acquisition be in effect? Many organizations would benefit from answers to such questions.

Admittedly, in hindsight, the tasks themselves may not have been optimal to study the phenomenon, because it may not have been obvious to the participants right away whether they had made an error, or what the error was (we further discuss this issue in the following paragraphs). In fact, this may be quite realistic, as many employees’ tasks may not provide immediate feedback. We regard the variety of tasks we employed as strength. In Study 1, we employed tasks that require rational problem solving, and where the degree of correctness of the teams’ solution can be judged objectively. In Study 2, participants worked on an actual task that requires creative problem solving: we had asked the teams to create a marketing plan for a given product. The task is a simulation of an actual work task. In fact, participants in Study 2 were online freelancers (“eLancers”), who believed to be working on an actual task for an actual company. This allowed us to combine advantages of an experimental setting, such as standardization, with advantages of field studies, such as task engagement. This contributes to a high applicability and generalizability of our results.

The task we used in Study 2 requires creativity, and may be quite similar to a brainstorming task. This procedure may raise the question of what actually constituted an error in the task. It is true that in the early stages of a brainstorming task, all ideas shall be voiced, regardless of whether they can be implemented or not. However, participants of Study 2 were not asked to provide as many creative ideas as possible; rather, they were asked to create a marketing plan for a (seemingly) real company and a (seemingly) real product. As such, ideas that were generated in an early phase of working on the task had then to be evaluated by the groups regarding their applicability in “real-life.” Admittedly, in the process of brainstorming, creative ideas that may not be applicable in real-life settings (which we would consider “erroneous”) may lead to good ideas that can be implemented. We do not consider this a contradiction to our concept of error management; Quite the opposite: embracing these “erroneous” ideas that the group rejects in the process of their discussion and acknowledging their potential may result in innovative yet applicable results.

On a similar notion, in Study 1, the errors the group made are represented by the deviations of their solution to the expert solution. The first stage of the task is to individually rank the items. In the following stage, the group discussion, team members often first analyze their individual rankings, and then “negotiate” a common solution. During this discussion, team members often explain their reasoning when ranking the items. Thereby, (individual) errors may become obvious and be discussed. For example, in the Landing on the Moon task, some participants correctly explained that matches do not work on the moon, as there is no oxygen that would light them up. In the Survival at Sea task, some participants realize that mosquito nets are not required on the ocean, as there are no mosquitos. During the group discussion, these insights may help overcoming individual errors when negotiating a common solution.

Research that has assessed innovator resilience potential (Todt et al., 2018), which includes “state-like qualities that are essential prerequisites for innovative functioning and coping with future setbacks (Todt et al., 2018, p. 522), demonstrated that effects are particularly strong after having experienced an innovation project termination before. For the context of our studies, one could conclude that the error management and performance relationship may be particularly strong when groups have experienced errors. While this idea definitely has its merits, we believe that there are several points that need to be considered: First, we agree that in order to observe specific behavior toward errors, errors actually need to take place. For example, in our first study, errors were operationalized as the deviations from the expert solutions to the Landing on the Moon and Survival at Sea task. As none of the groups were able to find the correct solution, we could say that they all made errors in the process of finding their solution. We are thus not able to directly compare groups that made no errors at all with groups that made errors. From a theoretical perspective, the concept of error management culture goes above and beyond behavioral reactions to errors (e.g., to discuss the error with a colleague); it can be described as a “mind-set” toward errors. The mind-set includes attitudes toward errors (e.g., to consider them as learning opportunities) or emotions toward errors (e.g., the absence of error strain). These do not require actual errors to happen.

As Study 2 was conducted online, we have little control over the situation in which participants took part in the study (for example, were participants distracted, etc.). Therefore, we took careful measures to enhance task engagement (fair compensation, attention checks, statistically controlling for goal commitment, using a real task). For studying a team concept, an online environment may be not be optimal, as team members do not even see each other – in the studies we had conducted, team members merely exchanged text messages. Again, as the pattern of results is similar to that of Study 1, the environment in which we conducted the study seems to have not affected our results.

Conclusion

A vast body of field studies has demonstrated the beneficial effect of error management culture on performance. In the present studies, we aimed at exploring the error management culture and performance relationship in an experimental setting. In two experiments with teams, we discovered that inducing an error management culture is more difficult than expected, and that the relationship is not as clear as expected. While we found a beneficial, yet indirect, effect via communication on performance in terms of creative problem solving, we were not able to find a direct effect on performance in terms of rational problem solving. One important question that remains unanswered is the temporal perspective. We encourage future research to further look into boundary conditions on the error management culture and performance relationship: employing different tasks may conclude in different results. Still, our studies are an important starting point in gaining a better understanding of the relationship between error management culture and performance.

Data Availability Statement

The datasets of the studies are available from the authors on reasonable request.

Ethics Statement

The studies involving human participants were reviewed and approved by Leuphana University of Lüneburg. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

All authors developed the theoretical ideas and study design. AK and DH collected the data, performed analyses, contributed to the method and results sections, and wrote the manuscript. NK and MF provided critical revisions.

Funding

This research was supported by grants from the German Research Foundation (Deutsche Forschungsgemeinschaft, Grant Numbers FR 638/38-1 and KE 1377/4-1). The publication of this manuscript has been funded by the Open-Access-Fund of the Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Footnotes

1. ^ We are aware of the debate going on whether the definition is of culture or of climate (e.g., Reichers and Schneider, 1990; Denison, 1996). We follow Fischer et al. (2018) and do not take part in this debate; rather, we keep the term error management culture that has been introduced by van Dyck et al. (2005).
2. ^ Calculations for the demographics is based on N = 303, as six participants did not respond to demographic questions.
3. ^ Note that the descriptive statistics provided in Table 6 reveal that while groups in the Error Management framing condition scored higher on perceived error management culture, groups in the “slimmed” Error Management framing condition scored higher on communication and quality and quantity of the ideas. (Note that these results are only a tentative description of the descriptive statistics).

References

Abstract

Purpose

Errors are inevitable, resulting from the human condition itself, system failures and the interaction of both. It is essential to know how to deal with their occurrence, managing them. However, the negative tone associated with them makes it difficult for most organizations to talk about mistakes clearly and transparently, for fear of being harmed, preventing their detection, treatment and recovery. Consequently, errors are not managed, remaining accumulated in the system, turning into successive failures. Organizations need to recognize the inevitability of errors, making the system robust, through leadership and an organizational culture of error management. This study aims to understand the role of these influencing variables in an error management approach.

Design/methodology/approach

In this paper methodology of a quantitative nature based on a questionnaire survey that analyses error management, leadership and the organizational culture of error management of 380 workers in Portuguese companies.

Findings

The results demonstrate that leadership directly influences error management and indirectly through the organizational culture of error management, giving this last variable a mediating role.

Originality/value

The study covers companies from different sectors of activity on a topic that is little explored in Portugal, but part of the daily life of organizations, which should deserve greater attention from directors and managers, as they assume a privileged position to promote and develop error management mechanisms. Error management must be the daily work of leaders. This study contributes to theoretical knowledge and business practice on error management.

Keywords

• Error management
• Leadership
• Organizational culture error management

Citation

Oliveira, M.F., Santos, E. and Ratten, V. (2022), «Strategic perspective of error management the role of leadership and an error management culture: a mediation model», Journal of Economics, Finance and Administrative Science, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JEFAS-01-2022-0028

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Margarida Freitas Oliveira, Eulália Santos and Vanessa Ratten

License

Published in Journal of Economics, Finance and Administrative Science. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode.

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1. Introduction

Errors are an inevitable part of all human activity and are prevalent in complex environments such as organizations, being impossible to eliminate them (Ramanujam and Goodman, 2003; Zhao and Olivera, 2006). Organizations have invested a lot in error prevention, implementing increasingly simpler systems and processes, easy to operate and maintain and ideally error-proof. However, these investments brought a reduction in errors in operations, but they also showed their limitations and the impossibility of eliminating all the errors that occur that can lead to negative results and too disturbing outcomes (Parry et al., 2015).

The most common is that organizations depend only on error prevention as a way to avoid them, focussing on the idea that errors must be eliminated before they occur, trying to eradicate its presence through mechanisms (e.g. system engineering, human factors, security systems, among others), aimed at reducing the occurrence. However, the exclusive emphasis on error prevention has its limits, especially in the long term, in that it simply reduces the possibility of learning from them, and minimizes the possibility that some errors can result in long-term positive consequences (van Dyck et al., 2005).

Error prevention is likely to lead to a culture of blame and punishment for the presence of errors, creating a strong tension caused by errors and, consequently generating harmful work behaviours of covering up errors, becoming a norm or rule. People, when working in error punishing cultures, develop a tendency to ignore and cover-up mistakes because the threats they face if they disclose them do not outweigh the benefits (Zhao and Olivera, 2006; Dimitrova et al., 2017). Therefore, a pure and simple error prevention approach cannot adequately deal with the fact that errors are unavoidable. A second “line of defence” is needed by organizations – error management – an active approach to errors designed to control and reduce the negative consequences of errors, preventing recurrence (Guchait et al., 2018) and increasing positive effects such as learning, creativity and innovation (Frese and Keith, 2015; Wang et al., 2018; Dahlin et al., 2018) and decreased turnover (Jung and Yoon, 2017). It is here that this study gains a strong justification, highlighting the importance of an error management approach in organizations, contributing to the knowledge and understanding of facilitating variables. Organizations that only emphasize the prevention of errors, do not accept errors and this has been a stance taken by a large number of companies, which shows failures and poor management (Love and Smith, 2016). Since errors are unpredictable, error prevention must be complemented by error management strategies (van Dyck et al., 2005; Deng et al., 2022; Matthews et al., 2022). The purpose of this article is to understand the role of leadership and an organizational culture of error management in the effective use of an error management strategy in organizations, whose literature theoretically recognizes its importance, with the need for more empirical studies remaining (Gelfand et al., 2011; van Dyck et al., 2005; Cannon and Edmondson, 2005). Therefore, it is intended to answer the following research question: what is the role of leadership and an organizational culture of error management in an error management strategy in organizations? There are no known studies dealing with the influence of both variables in an approach to error management in an organizational environment, encompassing various sectors of activity, namely in Portugal. This study contributes to filling this gap in a topic so relevant to leaders and managers.

To that end, this article, after this introduction, presents a literature review on the strategic perspective of error management, the role of leadership and an organizational culture of error management as facilitating variables for error management. Then, the methodology is presented. In the results section, a statistical analysis is carried out, and in the discussion section the analysis is complemented by discussing the results taking into account the explained literature review, and the implications and suggestions for future investigations are presented. Finally, the conclusions are presented.

2. The strategic perspective of error management

Managing errors effectively is crucial to the success of any business (Guchait et al., 2016; Deng et al., 2022). By the way, the relationship between error management and organizational performance is well evidenced in the literature (van Dyck et al., 2005; Gelfand et al., 2011; Swanson and Hsu, 2011; Oliveira et al., 2020).

Error management accepts errors as an intrinsic part of organizational life and is concerned with dissociating errors from their consequences (van Dyck et al., 2005). Its focus is on the effective way to deal with errors after they occur, to minimize their negative consequences, such as scheduling delays, quality and production problems, and even low employee performance, among others (Homsma et al., 2009; Swanson and Hsu, 2011), maximizing positive consequences such as learning, creativity and innovation (Frese and Keith, 2015; Wang et al., 2018; Dahlin et al., 2018), that positively contributes to organizational success in today’s competitive and global market (Hernández and Galvis, 2021). Therefore, error management must be seen as a value creation process from the strategic point of view and organizational development that managers must adopt in conducting their companies; the faster they do it, the faster companies will produce better results (Oliveira et al., 2020).

In organizations committed to managing errors, the main objective is not to prevent isolated errors, whether human or technological, but to make the system as robust as possible, to manage the errors that will undoubtedly happen. For this, it is essential to provide the necessary resources that make the system resilient, such as the existence of an organizational culture where communication and learning about errors are encouraged (Cusin and Goujon-Belghit, 2019). An effective error management climate promotes open communication and error sharing (Cigularov et al., 2010; Koc, 2013) and encourages individuals to treat mistakes as normal, rather than something they can be blamed for (Gold et al., 2013). It also encourages employees to report their mistakes (Gronewold et al., 2013) and helps to quickly detect and handle errors (Frese and Keith, 2015).

Managing errors is, therefore, recognizing the inevitability of errors and adopting an organizational focus in their management, admitting greater tolerance to errors, enabling an understanding of their nature and the mechanisms behind them, improving detection of them and reducing the probability of them being repeated. It is a process comprising three main steps: error detection, explanation, handling and recovery. Error detection is essential for reducing negative results and error recovery. Once an error has been detected, it is important to explain why it occurred. Once an error is detected, it is important to recognize and explain what happened and why. Error explanation represents the second step of the error handling process (Kanse et al., 2005) and it is important for learning from mistakes and for facilitating the final step, treatment and recovery, which may involve modifying an existing plan or developing a new one, to compensate for the error. Error handling or recovery aims to make it easier and faster to recover the state of the system when an error has been made (Keith and Frese, 2008).

In short, error management is a process that is concerned with increasing the speed at which errors are signalled and detected, to ensure that learning occurs (van Dyck et al., 2005). Error management is possible through fast detection and damage control. Once an error is detected, it is necessary to act quickly and have the actions properly defined to manage it. As it is not possible to eradicate errors, a systemic focus on error management in organizations is important.

2.1 Error management facilitators

Error management is a difficult and complex process, particularly in today’s dynamic organizational environment (Bauer and Mulder, 2013; Reason, 2000). Error management is influenced by several individual factors and the culture of organizations (Deng et al., 2022; Matthews et al., 2022). Thus, from the outset, an error management strategy will be facilitated, if it exists: (1) A general expectation that errors will occur; if individuals assume that errors do occur and this is accepted and natural thinking, then error management is facilitated because individuals are prepared to see errors when they do occur. If people do not recognize the possibility of errors occurring, then little effort will be made to identify whether an error has occurred (Hofmann and Frese, 2011). (2) A positive and constructive view of mistakes; if there is a positive and constructive view of errors, accepting that they can be valuable for learning and to stimulate greater attention and adaptability to new situations, and if this is an organization’s belief and value, then error management is facilitated because individuals in organizations are better equipped to detect and handle errors. An organization that promotes awareness of the occurrence of errors produces a high level of communication about errors, makes its members willing to learn from errors individually, makes them aware of possible error situations and appropriate reactions to them. On the contrary, if people are guilty, punished or if there are other negative reactions to the errors, it is likely that the error communication will be reduced, as in these cases, the most likely response to an error is not to report it, but to try to find other culprits (Cigularov et al., 2010; Koc, 2013; Gold et al., 2013; Gronewold et al., 2013). As a result, the opportunities for detecting, learning and preventing the same error from being repeated in the future are reduced. The degree to which individuals have a positive and constructive view of mistakes makes them, in the organization; admit the mistakes they make, allowing them to be treated in search of their current or future benefits. These individual behaviours are also used to assess organizational culture (Akgün et al., 2021) they portray an organizational culture that reveals some tolerance to error, that is, to make the system as tolerant as possible to error, insofar as its consequences are minimized. (3) Transparency of the organization’s systems structures; the greater the degree of transparency of the organization’s systems structures, the easier the error management becomes, that is, the more people know the situations in which they work and obtain feedback, the better understanding they have of the organization and, consequently, the more effectively will be able to handle errors. Thus, error management can be facilitated by the clarity of systems. (4) Organizational hierarchies. In organizational contexts, there is additional complexity due to hierarchies. All organizations are made up of people and depend on other organizations to get the resources they need. Likewise, all organizations at the various hierarchical levels that comprise them have leaders with the responsibility to help them achieve their goals. Leaders play an important role as they have a responsibility to monitor the progress of individuals and teams towards goals and provide the necessary feedback for error detection and management (Salas et al., 2004).

The literature suggests that monitoring mutual performance is critical to reducing errors that can be catastrophic (Salas et al., 2004; Wilson et al., 2005) and those leaders can play an important role in significantly improving the process error management.

Given the above, it appears that for a strategic approach to error management, it is important to take into account, in addition to individual perceptions, the influences of the social context (of the system), that is, it is deduced that either the culture organizational, or leadership, can assume a marked relevance in the error management process in organizations, since leaders in companies influence behaviours (of their employees or teams) and cultural support models (Avolio and Gardner, 2005; Block, 2003; Schein, 2004; Bass and Avolio, 1994), for the implementation of processes that lead to the achievement of results.

3. The role of organizational culture in error management

The literature shows that all organizations have a culture that establishes a set of norms and values, as well as practices and procedures, which lead to behaviours shared by its members (Schein, 2004; House et al., 2004; Panda, 2022). Organizational culture is the sum of all shared and correct certainties that a group has or will possess (learning) throughout its history. It is the set of implicit assumptions shared and taken as true by a group, which determine how that group perceives, thinks and reacts to its various environments (Schein, 2004). In this way, organizational culture can be conceived as a set of values and practices defined and developed by the organization, based on which a system of beliefs, norms and expectations that shape the thinking and behaviour of individuals is socially constructed. It allows, therefore, to create a feeling of harmony in the members of an organization, as they all feel that they have the same generic set of values, sharing clear ideas about what behaviours are acceptable or unacceptable in the context of their company. It is, therefore, a set of characteristics that individualizes each organization and makes it unique compared to any other, and may vary substantially depending on the sector of activity, region, country or business strategy. The different aspects of the culture of organizations, due to their differences in values, beliefs, norms and strategic guidelines, can have different and significant implications in the error management process (Gelfand et al., 2011; Göktürk et al., 2017), insofar as this is an organizational process that does not try to end errors, but rather to deal with errors and their consequences after they occur, ensuring that errors are quickly reported and detected, that negative consequences are effectively minimized and treated, and that learning, creativity and innovation occur (van Dyck et al., 2005; Frese and Keith, 2015; Wang et al., 2018; Dahlin et al., 2018).

According to van Dyck et al. (2005), organizations, more implicitly or explicitly, develop a culture of dealing with errors and this culture is different from organization to organization. Consequently, organizations develop a particular form of error culture – “error management culture” – a concept that applies to the idea of managing errors at the level of a unit (e.g. organization). The same authors argue that a strong organizational culture at the level of norms and common practices of communication about errors, detection, analysis and rapid correction of errors is essential to reduce negative consequences and promote positive consequences of errors. They suggest that organizations should promote and develop a culture of error management as a performance-boosting measure. In their study, they validated that a positive error management culture is related to success, leading to beneficial organizational results, such as performance and innovation. Too Rochlin (1999) states that there must be an organizational focus (shared) that does not blame the error so that it can be reported. An organizational culture of error management is compatible with a general awareness of errors, that is, assuming the inevitability of errors (Ramanujam and Goodman, 2003), which increases the probability of detecting errors and prepares the organization for their treatment. As such, an organizational culture that is aware of errors supports error handling. For this purpose, an environment of safety and reliability in the interaction between the parties, (actions of individual workers) based on the social structure, beliefs, rituals and myths of the entire organization, is required (Cusin and Goujon-Belghit, 2019).

Edmondson (2004) and Rochlin (1999) argue that there is a cultural dimension to how organizations deal with mistakes. In this sense, an error management culture can be of central importance for companies considering following an error management strategy (Wang et al., 2018, 2020; Deng et al., 2022; Panda, 2022).

Thus, analysing the influence of the organization’s culture, that is, the behaviours, attitudes and beliefs of its members regarding the way they deal with day-to-day errors in the performance of their functions, as the objective of this empirical study, assumes that is extremely important for error management, so the following research hypothesis is formulated:

H1.

An organizational culture of error management positively influences error management.

4. The role of leadership in error management

The new theories of leadership that have been developed in recent years play an important role in understanding how leaders motivate to perform better. However, surprisingly little attention has been paid to error management in organizations. Several authors have drawn attention to the need to review contemporary theories of leadership, so that they address error management and its practices, such as detecting, treating, sharing and learning from mistakes (Judge et al., 2008; Bass and Avolio, 1994). In general, existing theories and research highlight those organizational contexts are characterized by hierarchical levels, where leaders assume particular importance, being key players and the main actors who, through their actions, decisions and provision of feedback, can encourage members of their teams to adopt productive attitudes and behaviours in the face of error (Cannon and Edmondson, 2005; Salas et al., 2004). They may frame mistakes as learning opportunities rather than something to hide or punish (Rodriguez and Griffin, 2009; Nielsen et al., 2013; Deng et al., 2022; Dimitrova et al., 2017).

According to Edmondson (2004), error detection rates are strongly and positively associated with high levels of “leader coach”, which suggests that certain leaders establish a climate of openness that facilitates reporting and discussing errors. Too authentic leadership, in the study by Farnese et al. (2019), was positively related to reducing the existence of errors, promoting a work environment oriented toward error management and learning (Nielsen et al., 2013; Farnese et al., 2019).

In addition to shaping learning, leaders need to train their subordinates to a constructive view of mistakes and a general expectation that mistakes will occur, so that they recognize them and focus efforts to detect them. Leadership is a relationship founded on credibility and trust. Without these two factors, people do not take risks and, without taking risks, there is no change or evolution and companies perish (Kouzes and Posner, 2003). So, a fundamental requirement for error management is that organizations have leaders who accept errors as an intrinsic characteristic of the organization, which although not desirable, can appear at any time, and despite having negative consequences, it can also produce positive results.

Error management converges to situate leaders as central figures, who through their actions and attitudes can reverse, or at least reduce, the negativity conveyed by errors (Maurer et al., 2017; Farnese et al., 2019). Leaders are, thus, in a favourable position for the dissemination of error management because, in the first place, it is the leaders who must favour and facilitate processes of quick and open error communication along with the various hierarchical levels of organizations. Second, to effectively address errors, leaders must be close to the source of error, which requires them to set clear objectives and incorporate a strong and compelling vision of error responses in them. If leaders act in this way at the hierarchical level of organizations, the error management process will be facilitated and significantly improved. Based on the explained arguments a second research hypothesis is stated:

H2.

Leadership positively influences error management.

5. Organizational culture of error management versus leadership

From the foregoing analysis, it can be deduced that there is an interrelationship between organizational culture and leadership. According to Schein (2004), culture and leadership are two sides of the same coin, as leaders create cultures when they create groups and organizations. Leadership can influence the nature of organizational culture is a well-known assumption and evidenced in the literature (Avolio and Gardner, 2005; Block, 2003). Leaders in organizations become key elements for the dissemination/modification of culture, being the transmitting and stimulating centre of values, attitudes, beliefs and other elements that define the organization’s culture. It is the leaders who create mechanisms for the development of the culture and the characteristics and qualities of that culture are operationalized and taught by them to their followers (Block, 2003; Bass and Avolio, 1994). Consequently, it is up to the organization’s leadership to perceive the dysfunctional elements of the organization’s culture and manage the shift to a culture prepared for the general expectation that mistakes will inevitably occur and to build a positive view of them. In organizations, beliefs about mistakes need to be not only captured in formal and documented organizational policies (e.g. vision) but also reflected in the daily activities and procedures whose role of the leader is fundamental for the purpose.

Cannon and Edmondson (2005), found a positive relationship between leadership and orientation towards learning through mistakes and, as a result, left open the importance of attesting to the role of team leaders in a clear alignment of developing constructive beliefs and behaviours about the error.

Given the arguments explained, leaders can take a catalytic role and implement practices and procedures for an error management approach. It is expected that it is the leaders who indoctrinate and do, make act and change behaviours and attitudes leading to error management in organizations. Due to the background of the literature, research hypothesis three is formulated:

H3.

Leadership positively influences an organizational culture of error management.

6. Methodology

6.1 Conceptual framework

Figure 1, shows the conceptual model, being considered a mediation model, where the independent variable (Leadership) causes the mediating variable (Organizational culture of error management) and this one, for its instead, conveys the effect of an independent variable on the dependent one (Error management).

6.2 Research design

6.2.1 Type of investigation

The present study is non-experimental, cross-sectional and quantitative. The study was carried out in the form of a questionnaire survey to assess the perspective of respondents regarding their attitude and behaviour towards practices and procedures that promote error management.

6.2.2 Population and sample

The target population of this study are Portuguese over 18 years old who are working in Portuguese companies in different sectors of activity. After eliminating some incomplete questionnaires, the sample consisted of 380.

6.2.3 Sampling technique

The convenience sampling technique was used which is non-probabilistic workers were selected because they have characteristics that are consistent with the objectives of the investigation. With this sampling technique, respondents are chosen according to a certain criterion of convenience, for example, their immediate availability and knowledge of the subject under study, as well as the associated low cost. In this way, the inclusion of employees from companies from the various activity sectors under study, with characteristics such as functions, level of academic qualifications and knowledge of the organization in terms of organizational culture and leadership to ensure obtaining the set of information that would allow the achievement of the study objectives.

6.2.4 Instruments

The questionnaire comprises four parts. The first part assesses leadership, the second analyses the organizational culture of error management, the third analyses error management and the fourth part characterizes the respondents in terms of socio-demographic and professional data (gender, age, educational qualifications, seniority, hierarchical position, sectors of activity and size of the organization).

To assess error management, 7 items (Table 1) were used, leadership was measured using 9 items (Table 2) and the organizational culture of error management was assessed using 7 items (Table 3), from the study by Oliveira et al. (2020). To measure the items under study, a 5-point Likert frequency scale was used (1- Never to 5- Always).

6.2.5 Data collection and ethical procedures

The data collection process was carried out using Google Forms, which supported the creation of the questionnaire. Data collection took place between April and June 2019, covering 64 Portuguese companies from eight sectors of activity. The companies that agreed to participate in the study sent an email to their workers, which stated the objectives of the study, and it was also ensured that the filling in of the questionnaires would be anonymous and confidential, as well as the processing of data, to preserve the identity of each respondent.

6.3 Analytical procedure/technics

After data collection, a database was built using the IBM Statistical Package for Social Sciences Statistics 26 software, and to carry out the characterization of the sample and the descriptive analysis of the variables, descriptive statistics were used. According to Kline (2016), we also analysed the existence of missing cases, outliers and the sensitivity of the items (asymmetry coefficients (|Sk| ≤ 3) and flatness (|Ku| ≤ 7)).

To analyse the causal relationships between the variables, the analysis of structural equations was applied. This technique consists of analysing two models: the measurement model and the structural model (Marôco, 2014). To analyse the measurement model, we started by applying an exploratory factor analysis (EFA) using the principal components method to extract the factors and the Kaiser criterion to measure the minimum number of factors to retain (eigenvalues greater than 1). To verify the adequacy of the application of EFA to the sample, we use the index of Kaiser-Meyer-Olkin (KMO >0.7 reveals the acceptable suitability of the sample) and the test (p < 0.05) of sphericity of Bartlett (Hair et al., 2014).

In the confirmatory factor analysis (CFA), the adequacy of the structure that emerged from the EFA was tested. To this end, the maximum likelihood estimation method (implemented in the AMOS (Analysis of a Moment Structures) software) was used and the following goodness-of-fit indices were used: the ratio of the Chi-square statistics to the degrees of freedom (χ²/df) less than 3 (Kline, 2016), goodness of fit index (GFI) and comparative fit index (CFI) superior than 0.90 are indicators of a good fit (Hair et al., 2014), root mean square error of approximation (RMSEA) is considered good in the range [0.05, 0.08] (Arbuckle, 2014).

The reliability of the variables under study was assessed using Cronbach’s alpha and composite reliability, according to Hair et al. (2014), these indicators are considered adequate if they present values greater than 0.7. When analysing convergent validity, the average variance extracted (AVE), must have values greater than 0.5 and when analysing discriminant validity, the square of the correlation between the variables must be lower than the value of AVE (Hair et al., 2014).

In the structural model, causal relationships are analysed, that is, the hypotheses under study are tested and the percentage of variance explained by the dependent variables in the structure model is analysed using the coefficient of determination (R²). The significance of the direct, indirect and total effects of the mediation model was evaluated with the test of Sobel (Marôco, 2014).

7. Results

7.1 Sample characterization

The sample is composed of 380 individuals, the majority being men (71.3%, n = 271) and 54.5% (n = 207) of the respondents are 40 years old or younger. With regard to education, most have higher education qualifications (53.5%, n = 203). In terms of seniority in the organization, most individuals have worked in the organization for more than 5 years (82.3%, n = 313). Regarding the hierarchical position within the organization, the majority of respondents (77.1%, n = 291) occupy the position of middle managers/technical staff, 18.7% (n = 71) occupy management positions and 4.2% (n = 16) occupy administrator/manager positions. Regarding company size, it appears 48.2% (n = 183) of individuals perform functions in large companies, 26.3% (n = 100) in medium-sized companies, 16.3% (n = 62) in companies small scale and 9.2% (n = 35) in micro-enterprises.

Finally, with regard to activity sectors, 54.5% (n = 207) of respondents belong to the construction area, 16.6% (n = 63) to the automotive area, 12.6% (n = 48) to the services area, 7.1% (n = 27) to the hotel and tourism area, 4.2% (n = 16) to the industry area, 2.4% (n = 9) to the environment and energy area, 1.8% (n = 7) to the communication area and 0.8% (n = 3) to the real estate area.

7.2 Descriptive analysis of constructs

Table 1 shows that individuals tend to manage errors in organizations (the mean frequency values of all items have values well above the midpoint 3, on a scale from 1 to 5), although there are negatively skewed distributions for all items, which means that there are still some individuals with low-frequency levels. Thus, it is noteworthy that when individuals make a mistake, they seek to correct it immediately (M = 4.69, Standard deviation (SD) = 0.59), try to avoid mistakes that will occur in their work (M = 4.47, SD = 0.73), and when they perform the functions in their work, they constantly seek to detect the mistakes they make (M = 4.38, SD = 0.74).

About leadership (Table 2), individuals attribute a higher frequency level to the item “when I make a mistake I reveal it to my boss, as I am completely open to talk to him about the mistakes” (M = 4.43, SD = 0.77) and lower to the item “my boss recognizes the errors” (M = 3.35, SD = 0.89).

Table 3 shows that there is a general concern to correct errors (M = 3.68, SD = 0.98), to detect errors that occur (M = 3.56, SD = 0.96) and to learn about the mistakes made (M = 3.52, SD = 1.08).

7.3 Measurement model

The KMO measure and Bartlett sphericity test revealed good adequacy of the sample for each of the variables under study, after eliminating the items EM1, EM4, EM5, L1, L2 and L8, for presenting values in the communalities below 0.5 (Error management: χ2(6) = 444.34, p < 0.001, KMO = 0.78; Leadership: χ2(15) = 1453.64, p < 0.001, KMO = 0.90; Error management organizational culture: χ2(21) = 1384.94, p < 0.001, KMO = 0.91). The EFA showed that the three variables under study have a one-dimensional structure. Then, the CFA after the elimination of item C6 (the residue of item C6 had a strong correlation with the residue of item L9), the adjustment indices of the model revealed a good fit quality (χ² = 277.477, df = 97, χ²/df = 2.861, GFI = 0.917, CFI = 0.948, RMSEA = 0.070) according to Arbuckle (2014), Hair et al. (2014) and Kline (2016). Table 4 show that the loadings vary from 0.655 to 0.853 (λ ≥ 0.5) and individual reliabilities vary from 0.429 to 0.728 (R² ≥ 0.25). Cronbach’s alpha and composite reliability values are greater than 0.79, which is considered acceptable (Hair et al., 2014). The AVE values of the leadership and organizational culture of error management constructs are greater than 0.5 and the error management construct presents a value that is within the acceptability limit, which is an indicator of adequate convergent validity (Hair et al., 2014).

The correlations between the three constructs are positive and significant (Table 5), with the highest correlation between the leadership and the organizational culture of error management constructs (r = 0.74). The AVE values of the constructs are greater than the square of the correlation between the constructs, so there is evidence of discriminant validity (Hair et al., 2014).

7.4 Structural model

Leadership and the error management organizational culture explain 39% of the variability of error management and leadership explains 55% of the variability of the error management organizational culture. The empirical results (Table 6) show that the organizational culture of error management positively and significantly influences error management (β = 0.27, p < 0.01), which empirically supports hypothesis 1.

Regarding hypothesis 2, this is empirically supported, as leadership positively and significantly influences error management (β = 0.39, p < 0.001).

There is sufficient statistical evidence to affirm that leadership positively and significantly influences the organizational culture of error management (β = 0.74, p < 0.001), which empirically supports hypothesis 3.

Leadership had a total effect of 0.593 on error management, with a direct effect of 0.390 and an indirect effect, mediated by the organizational culture of error management, of 0.203. The indirect effect, mediated by the organizational culture of error management, corresponds to 34.23% of the total effect of leadership on error management. Through the application of the Sobel test, it was concluded that the mediation effect of the organizational culture of error management related to the effect of leadership on error management is statistically significant (Z = 3.029, p < 0.01). Thus, it is concluded that although leadership directly influences error management, leadership also indirectly influences error management, through the organizational culture of error management, whereby the organizational culture of error management assumes the role of mediating variable.

8. Discussion

The foregoing results allow us to state that both the organizational culture of error management and leadership influence how errors are managed in organizations. Culture takes on a deep meaning for error management in organizations (Reason, 2000) and can act as an influencing variable (van Dyck et al., 2005). Different aspects of organizational culture can have significant implications for the error management process (Gelfand et al., 2011; Göktürk et al., 2017; Wang et al., 2020; Panda, 2022; Deng et al., 2022; Matthews et al., 2022). Thus, an error management approach will be easier if there is a strong organizational culture with practices, procedures, norms and values conducive to error management. Allied to culture, the greater the focus of leaders on the dissemination of behaviours, among their subordinates, leading to error management, the more effective error management will be. This result corroborates the fact that leaders are the fundamental actors in organizations who, through their actions, decisions and provision of feedback, can encourage their team members to adopt productive attitudes and behaviours in the face of error (Cannon and Edmondson, 2005; Salas et al., 2004; Maurer et al., 2017; Farnese et al., 2019). They may frame mistakes as learning opportunities rather than something to hide or punish (Rodriguez and Griffin, 2009; Deng et al., 2022; Nielsen et al., 2013; Dimitrova et al., 2017).

There is enough statistical evidence to affirm that leadership positively and significantly influences the organizational culture of error management. These results corroborate the literature, whose leaders play an important role in the creation and development of culture, occupying a privileged position in organizations to promote and increase mechanisms and behaviours conducive to error management (Avolio and Gardner, 2005; Block, 2003; Bass and Avolio, 1994; Schein, 2004). The results of this investigation clearly show that error management should be a daily work of leaders. Leadership is the most significant variable for the model, causing greater variability in error management, which is why it is fundamental. This is an important contribution of this study that corroborates the attention of several authors in the literature (Judge et al., 2008; Bass and Avolio, 1994) to the need to review contemporary theories of leadership, so that they address error management and their practices, such as detecting, processing, sharing and learning from errors. It is important to emphasize that, in the face of constant change processes, which are imposed on organizations in a global market, where errors are inevitable, an error management approach at the corporate level must be considered and faced as a value creation process from a strategic and organizational development point of view. This is an objective practical implication of this study.

Given the above, the aim is to have contributed to boosting future research in this field, especially in the Portuguese business context, since, so far, empirical studies involving the variables proposed here and the relationships established between them are unknown, which confers some peculiarity to this study. This study contributes to theoretical knowledge of error management and business practice on strategic error management, as a management tool for leaders and managers.

The need for future studies is justified for the expansion of knowledge and improvement in this field of study; namely, it would be interesting to know the type of organizational culture most suited to an error management approach. Study the various styles of leadership, to verify which one is best suited to an error management approach, allowing for a direct relationship to be established between the leadership style and the way to manage errors. In this line of thought, a comparison between several countries with similar organizational cultures will bring much knowledge to research in this area.

Since the phenomenon of errors may not be immediate, a longitudinal study aiming to investigate the relationships in a temporal sequence between the organizational culture variables of error management, leadership and error management may be useful to understand and assess change and the development of the phenomenon under analysis.

9. Conclusion

The objective of this investigation was to understand the role of leadership and an organizational culture of error management, in the use of an error management strategy in organizations, in the Portuguese business context. For this purpose, a cross-sectional, quantitative study was carried out, covering several companies from various sectors of activity, allowing the assessment of the representative perspective of 380 respondents regarding their attitude and behaviour towards the practices and procedures that promote error management.

The empirical results show that leadership directly influences error management and indirectly through the organizational culture of error management, giving this last variable a mediating role, thus confirming the study hypotheses formulated.

These results are interesting because they allow shedding new light on the practice of a strategic error management approach in organizations, providing details of the influences of the variables under study. In addition to theoretical contributions, the data obtained make clear practical contributions to the management of organizations: the more focused leaders are on developing common practices, standards and procedures for error management, the stronger the organizational culture of error management. Error management assumes an essential dimension in the leader’s role. Error management must be part of the leader’s functions, as with other skills classically assigned to leaders.

Figures

Figure 1

Conceptual model

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Corresponding author

Received 9 March 2016; accepted 25 April 2016; published 28 April 2016

1. The Origin and Development of Error Management Climate

In organizations, errors may always exist. For example, it cannot finish the task before deadline, forgetting to send a message in time, hiring the wrong person, and so on. For a long time, people think that making mistakes are very bad things; it will bring serious loss to the organization; in the organization, people should try to avoid the occurrence of errors, and do a good job in the prevention of errors. However, enterprise practice proves that due to the information acquisition for people to making decision is limited; the error cannot completely prevent ( Zhao, 2006 ). Wherever it may produce, so researchers become to treat the error more scientifically (Dyck, 2005), shift attention to how to reduce the harm as much as possible after the error occurred, and ultimately learn from errors, and promote the organizational goals on. Frese et al. (1991) proposed the concept of error management, different from error prevention; error management is to provide a learning opportunity for the organization members, so that they know how to adjust and change their behavior. The difference between error prevention and error management is: error prevention produces before the error occurred, and is to try to reduce the number of errors; error management occurs after the error, treats error as the cause and tries to control the false negative effects ( Keith & Frese, 2005 ). Currently most enterprises will adopt error prevention measures, however, error prevention can only achieve the purpose of control error, pure error prevention cannot teach people how to deal with errors and learn from the mistake of strategy ( Huber, 1991 ). In contrast, error management teaches people how to learn from mistakes. Error is not good in itself, but when it happens, it will be very useful for the organization to learn from the mistakes and improve the work flow. Error management can guarantee that the error is found and reported in the first time, while eliminate the negative impact caused by the error and learn from it, which is needed by the modern enterprise especially Internet company’s management.

2. The Definition of the Concept of Error Management Climate

2.1. Distinguish of Error Related Concepts

Error management climate is part of positive organizational culture, and error is defined as the accident deviation behavior from goals or expectations. Keith & Frese (2011) distinguished several relative concepts: firstly, the distinction between errors and violation is that errors refer to unintentional deviation from the original plans, objectives, rules or standards, probably (but not necessarily) will have negative consequences, such as damage, stress, and depression; and the violation refers to intentionally deviate from the rules or standards in order to achieve a certain purpose. Secondly, the difference between mistakes and failures: failure is a negative result, it may be caused by errors, but not all the mistakes will lead to failure. If the error can be found timely and correctly, it may not lead to failure. Thirdly, the difference between mistakes and low performance: errors and low performance may lead to the same results such as cannot complete the task in time, and the difference between the two is that errors will make people have a feeling: I can do better. Dyck (2005) defined the error management: error management does not mean to eliminate all errors, but to go after the error handling and its consequences. The error management can also be applied to the organization level, namely error management culture. Organizational error management culture refers to the organization and organizational procedures, error related practices and attitudes, and is the way the method of error handling. The latest research of error management culture covers into a more comprehensive concept of error management climate. Cigularov, Chen, & Rosecrance (2010) considered that error management climate (EMC) refers to a kind of organization atmosphere, which promoted “error communicating and sharing, helping each other in the error environment, the exploration and analysis of the error, reducing negative influence and recovering quickly from the mistakes in” after an error occurred.

2.2. Distinguish of Error Management Climate Related Concepts

Error management culture refers to organizational procedures, error related practices and attitudes, and the method of error handling of organizations. Error management culture emphasizes a set of guidelines, value conception system that is shared in the organization, which is outward and visible; and error management climate contains not only outward and visible the value concept system, but also an internalized atmosphere. Error prevention appears before the error occurred, and is possible to eliminate the error; error management is in order to curb the negative influence, to promote the positive effects of false error.

3. Error Management Mechanism

The main purpose of error management is handling errors quickly and efficiently, reducing the loss and harm caused by the error, learning from mistakes and the possible future error prevention. The study found that error management mechanism lies in the following three points: 1) timely monitoring, in-depth analysis and open communication after error occurred; 2) effectively handling errors and negative consequences; 3) looking for the opportunity to reverse from the mistakes and find valuable information to learn ( Cigularov, Chen, & Rosecrance, 2010 ).

4. The Structure and Measurement of Error Management Climate

Based on the reviews of the literature, the dimensions of error management climate are summarized as below. Study on error management climate dimensions of foreign scholars are mainly in the following aspects: Frese et al. (1991) found that the error can be divided into two dimensions: emotional mood and action dimensions. Emotional dimension contains the risk of error, error prediction, error pressure and error concealment; action dimension contains error learning, error thinking, error competence and error pressure; Rybowiak et al. (1999) studied individual orientation for error, and formed the individual orientation error attitude questionnaire which contains eight dimensions: error ability, error learning, error communication, error thinking, risk undertaking, error prediction, error competence and error pressure; Dyck (2005) divided error management culture into two dimensions: error management culture and error avoidance culture. Error management culture includes four dimensions: error mastery, error communication, error undertaking and error antipathy. Gold et al. (2013) proposed error management climate blame orientation and error management climate open orientation: blame orientation does not allow employees to make an error, and open orientation will treat error as a normal thing, allowing the employees to make mistakes. Based on Van Dack et al. (2005) theory, the error management climate has been verified by Chinese scholars such as Tsai (2009) . He considered that error management climate included four dimensions: error control, error communication, error bear and error antipathy.

5. The Relevant Empirical Study of Error Management Climate

The empirical research on error management climate can be divided into two aspects: the influence factors and the effect of the results ( Yin, 2012 ). Firstly, research shows that transformational leaders are good at promoting staff to explore, trial and error, and so that have positive effects on error management climate; the laissez-faire leadership always disregard organization’s objectives, ignores employees’ ask, and is not conducive to the construction of organizational error management climate. Research on performance appraisal orientation and error management climate indicates that performance appraisal target to evaluate the alignment, and is not conducive to the formation of error management climate. Development orientation of performance appraisal tends to reduce the punishment of error or failure on employee, which can promote the formation of error management climate.

Secondly, the research about the effect of error management climate focuses on organizational performance, organizational or employee learning, reducing error of adverse effects, secondary error prevention, promoting employee innovative behavior, and encouraging employees to exploration, trial and error, improving the quality of products and services and so on (Dyck, 2005).

The study of Gronewold (2013) in a professional service organization found that error management climate will affect employee’s voluntary error reporting intentions: high error management climate can bring higher willingness to report self false, with this relationship regulated by the type of error. Compared to the operational errors, the concept errors are more able to strengthen the relationship between error management climate and the willingness to report self false. At the same time, it is found that the error management climate can promote the generation of employee’s moral behavior, especially among the junior staff. With empirical study Dyck (2005) found that: the organization’s error management culture and organizational goals, objective economic performance is significantly related. At the same time, error management culture has a positive correlation with organizational performance, while error pressure is negatively related to organizational performance. Cigularov, Chen, & Rosecrance (2010) conducted a survey of 235 American construction associations to investigate the influence of the Contractor’s error management climate and the safety of the workers on the safety behavior and injury. The results show that the error management climate and security communication have significant positive effects on the reduction of workers’ injuries. Good error management climate and security communication are helpful to improve the safety of the construction industry. Cai Yuqiao’s (2009) investigation of 152 Taiwan business people from various industries has found that: forward error management culture has positive influence on organizational learning and organizational performance and organizational learning plays an intermediary role between error management culture and organizational performance. Wang (2000) ’s study of the 168 subjects from 50 companies found that the error mastery dimension of error management climate has significantly positive correlation with organizational performance; the error stress dimension and organizational performance was significantly negatively correlated. Zhu & Pei (2014) investigated 227 employees and found that error management culture has a significant positive impact on employee Innovative behavior, and psychological empowerment plays an intermediary role between the two and innovation efficacy can positively regulate the relationship between psychological empowerment and employee’s innovative behavior. Ma (2015) surveyed 562 employees of 105 companies and found that: open oriented error management climate can promote knowledge socialization and externalization; blame oriented error management climate can promote the combination of knowledge and internalization. Open oriented error management climate can promote employee’s ability of exploratory innovation; blame oriented error management climate can promote employee’s ability of utilization innovation.

6. Prospect

Although there has been a lot of research on error management climate at home and abroad, most of the scholars still focus on the theoretical research, which is rarely related to the empirical study of the error management climate. Based on this, the future research can consider how to apply the error management climate to the management practice, and explore how it interacts with the employee’s emotion and attitude. In addition, because most of the research on the error management climate is positive, the future direction can also take into account the negative error management climate.

Background

This Briefing Note (BN) presents a definition of error management. It explains the complex process of making mistakes, focuses on what can trigger the mistake process and proposes prevention and recovery strategies.

This BN will help familiarize the reader with the important topics of human errors and violations in order to provide guidance for productive solutions in error and violation management.

Introduction

With the high reliability of modern aircraft systems, human performance has become a key focus for flight safety. Various types of human error are often cited as contributing factors to incidents and accidents. Safety officers at airlines observe human errors and even rule violations when they monitor the safety performance of their airline through safety reports and flight data monitoring. Information or training alone cannot immunize a person or an organization against error. Improvement is only achieved through concrete improvements that make errors less probable and their consequences less severe. The primary perspective of this BN is at the organizational level. Its goal is to help personnel such as safety and training managers identify and apply the most effective systemic solutions for managing errors and violations in their organizations. While much of the material presented is also applicable at the individual level, the aim of this BN is to reduce the number and gravity of threats faced by pilots rather than to teach pilots new threat and error management techniques.

Defining Human Error and Violation

Errors and Violations

In everyday parlance, the term “error” is used in a very broad sense. For a more detailed discussion of the topic, we need more precise definitions. The classification used here is in line with James Reason’s definitions[1].

Errors are intentional (in)actions that fail to achieve their intended outcomes.

Errors can only be associated with actions with a clear intention to achieve a specific intended outcome. Therefore, uncontrolled movements, e.g. reflexes, are not considered errors. The error itself by definition is not intentional, but the original planned action has to be intentional. Furthermore, it is assumed in the above definition that the outcome is not determined by factors outside the control of the actor.

Violations are intentional (in)actions that break known rules, procedures or norms.

The fundamental difference between errors and violations is that violations are deliberate, whereas errors are not. In other words, committing a violation is a conscious decision, whereas an error can be made while a person is consciously trying to perform in an error-free manner. Cases of intentional sabotage and theoretical cases of unintentional violation (breaking a rule because the person is not aware of the rule) are outside the scope of this flight operations BN.

Therefore, it is important to realize that within the scope of this discussion that a person committing a violation does not intend the dramatic negative consequences that sometimes follow a violation — usually it is believed in good faith that the situation will remain under control despite the violation.

It is worth noting that many sources, even in the domain of aviation safety, use the term “error” in a wider sense, covering both errors as defined here and violations.

Errors can further be divided into the two following categories:

1. Slips and lapses are failures in the execution of the intended action.

   Slips are actions that do not go as planned, while lapses are memory failures. For example, operating the flap lever instead of the (intended) gear lever is a slip. Forgetting a checklist item is a lapse.

2. Mistakes are failures in the plan of action. Even if execution of the plan was correct, it would not be possible to achieve the intended outcome.

   Plans that lead to mistakes can be defective (not good for anything), inappropriate (good for another situation), clumsy (with side effects) or dangerous (with increased risks).

Figure 1: Summary of Errors and Violations

Performance Levels

Different error types are often associated with what are termed performance levels. At any point in time, a person usually performs several tasks simultaneously. For example, a pilot may be flying the aircraft manually (reading instruments, analysing the situation and giving inputs to flight controls), going through the checklist read by the pilot not flying (PNF) and remaining vigilant for any radio traffic. In order to be capable of such multi-tasking, despite limited attention resources, human cognition is able to perform familiar tasks with minimal attention and the most familiar tasks automatically.

This capability can be modeled with Rasmussen’s skill-based, rule-based, knowledge-based presentation of performance levels. Rasmussen’s model is briefly introduced below.

Applying learned routine skills in normal, well-known situations is skill-based performance.

In the hierarchy of performance levels, the next level is rule-based performance. In rule-based performance, the person is confronted with a situation where attention must be focused on making a decision or creating a solution. However, the situation is a well-known one, for which the person has been trained. Therefore, as soon as the situation has been identified, the person can easily apply a known solution and carry on with the original activity, often returning to the skill-based level. The name “rule-based” reflects the existence of learned solutions providing if-then “rules” that can be applied to the situation — not necessarily rules in the classical sense, i.e., regulations or norms.

Training and experience allow a person to construct a collection of rules, to know when to apply these rules and to know which cues to use to identify a situation correctly. For instance, at the time when windshear and microburst phenomena were still not well known within the aviation community, many flight crews found themselves in a surprising situation where it was difficult to understand what was happening, and without any effective solutions to apply. Sometimes the consequences were disastrous. Since these phenomena have become better known, crews have been trained to identify the situation rapidly and correctly and to apply the correct flying techniques.

The most attention-consuming performance level is the knowledge-based level. In a completely new situation, without the help of any existing solutions, the person is forced to face the task of trying to derive an on-the-spot solution based solely on knowledge of the system. When such a situation emerges in the context of a complex system and under time pressure, the analytical capacity of human cognition may be quickly surpassed, and the chances for a successful outcome are seriously compromised. Preventing crewmembers from getting into such testing situations is one of aviation’s guiding principles.

Errors and violations have different forms at different performance levels.

Slips and lapses typically emerge at the skill-based level. There are several known mechanisms behind slips and lapses. It is known, for example, that mental “programs” that are most commonly used may take over from very similar programs, which are less frequent or exceptional.

Violations at the skill-based level are routine violations: violations that have become part of the person’s automated routines, like routinely exceeding the speed limit slightly when driving.

Mistakes are results of conscious decision making, so they occur at rule-based and knowledge-based performance levels. In both cases, the two typical areas that can lead to problems are:

1. Identifying the situation correctly
2. Knowing the correct solution (rule) to apply.

At the knowledge-based level, the challenge is to process an overflowing quantity of information and to understand it in such a way as to be able to make both a correct diagnosis and appropriate decisions. In contrast, at the rule-based level the flow of information may be well within processing limits, but the partially unconscious process of situation diagnosis and the quality of previously learned solutions (rules) become critical.

Violations at the rule-based level are usually situational: the person performs the corner-cutting he or she judges necessary or useful to get the job done. Violations at the knowledge-based level are usually so-called exceptional violations, and sometimes are quite serious in their nature.

Figure 2: Performance Levels and Main Error and Violation Types (adapted from Rasmussen and Reason)

Consequences of Errors and Violations

Errors and violations together form the unreliable part of human performance. It is often stated that 70-90 percent of current aviation disasters are due to “human factors.” While the reality is somewhat more complex, it is true that current accidents usually contain important human performance elements. Errors and violations contribute to accidents both directly and by making the consequences of other problems more serious.

In a complex (at least a priori), high-risk system — such as commercial aviation — there are multiple layers of defenses against known types of accidents. Therefore, an accident involves several contributing factors, some usually being quite visible and others being more distant in time and place from the actual accident. It is important to realize, that in such a system, the consequences of an error typically depend more on factors other than the apparent gravity of the error itself. In other words, it is usually wrong to think that a big catastrophe must have been preceded by an equally serious error. More commonly it is the number of errors and the capability of the system to contain the errors that determine the outcomes.

As these examples portray, the very same error can have completely different consequences, depending on the factors involved.

Some error types tend to have more serious consequences than others:

• Slips are usually easy to detect quickly and do not have immediate serious consequences due to built-in system protections.
• Lapses may be more difficult to detect and therefore may also be more likely to have consequences.
• Mistakes are even more dangerous, because the person committing the mistake believes that he or she is doing the correct thing and thus carries on with the action often despite a growing number of signs that things are not going right.
• Violations are similar to mistakes but with an increased potential to deviate to an abnormal type of operation with an associated increase in risk. Many violations are tempting because often they bring benefits without any readily apparent drawbacks. The embedded dangers may not be obvious, and people have few chances to learn to appreciate them because violations are forbidden and thus a taboo subject. For example, the violator usually assumes the remainder of the system to be nominal (i.e., no other errors or violations). Ironically, Line Operations Safety Audit (Line Operations Safety Audit (LOSA)) data have shown that a violation almost doubles the chances of committing a further error or violation during the remainder of the flight.

One common false assumption is that errors and violations are limited to incidents and accidents. Recent data from flight operations monitoring programs (e.g., LOSA) indicate that errors and violations are quite common. According to a University of Texas LOSA database, in approximately 60% of the studied flights at least one error or violation was observed, the average being 1.5 errors per flight.

A quarter of the errors and violations were mismanaged or had consequences (an undesired aircraft state or an additional error). The study also indicated that a third of the errors were detected and corrected by the flight crew, 4% were detected but made worse, and more than 60% of errors remained undetected. These data underline the fact that errors are part of normal flight operations and, as such, usually are not immediately dangerous.

Overall, when an error has serious consequences in a highly safety-protected system, it usually tells more about the operational system than about the error itself. Safe systems such as aviation are supposed to be engineered to manage errors in different ways to avoid serious consequences.

Error Management

People in management positions often find it difficult to deal with human errors. Simple reactions such as asking people to be “more careful” very rarely bring improvement. The seemingly easy solution to add warnings in documentation usually turns out to have a very limited effect. Another natural reaction is to train people more, hoping errors will then be avoided. While various technical and non-technical skills can be improved by training and thereby have a positive impact on certain types of mistakes, training does very little to prevent slips and lapses.

Effective managers must accept the fact that errors cannot be completely prevented no matter how much people are trained and how many warnings are put in the operational documentation.

The first step in successful error management is to understand the nature of the errors that occur and the causal mechanisms behind them. This is problem identification.

Real solutions for the problems human errors cause often require systemic improvements in the operation. For example, a systemic change could involve improving working conditions, procedures and knowledge in order to reduce the likelihood of error and to improve error detection. Another way is to build more error tolerance into the system, i.e., limit the consequences of errors when they do occur.

Achieving such systemic solutions requires first adopting a global, organizational approach to error management rather than focusing only on the individuals committing the errors.

Even the best safety program cannot prevent all errors. Therefore, the best strategy to adopt is error management. This chapter focuses first on effective error management strategies in general, and then discusses the specifics of managing slips, lapses and mistakes.

Error Management Strategies

• Error Prevention aims at avoiding the error completely. It is possible only in some specific cases and, almost without exception, requires design-based solutions.
• Error Reduction aims at minimizing both the likelihood and the magnitude of the error.
• Error Detection aims at making errors apparent as fast and as clearly as possible, thereby enabling recovery. An error can be:
  • Detected by the person that committed the error (self-monitoring), or
  • Cued by the environment (e.g., detected by the system hardware and software), or
  • Detected by another person.
• Error Recovery aims at making it easy to rapidly recover the system to its safe state after an error has been committed.
• Error Tolerance aims at making the system better able to sustain itself despite error, i.e. minimizing the consequences of errors.

Managing Slips and Lapses

Slips and lapses are an unfortunate byproduct of the useful human capability to perform actions “automatically,” without full attention. The mechanisms causing slips and lapses function at an unconscious level. Therefore, even if slips and lapses can be reduced through good design of the working interfaces, procedures and environments, it is impossible to prevent all of them.

The last example further illustrates the fact that effective solutions usually require operational changes at the organizational level.

Due to the somewhat unpredictable nature of slips and lapses, the key management strategies are detection, recovery and tolerance. Fortunately, most slips and lapses are detected, usually by the person who made the error. Also, when a slip or lapse is detected, it is usually easy to recover.

Managing Mistakes

As stated, mistakes are deficient solutions or decisions, often caused by failed situational diagnosis or poor-quality learned solutions.

If crewmembers find themselves in a knowledge-based problem-solving situation, their chances of success depend on their basic knowledge of the key phenomena, and the use of skills promoted through crew resource management (Crew Resource Management) training, such as the ability to stay calm, communicate and cooperate. Because mistakes at the knowledge-based level are difficult to recover, instead of trying to develop related error management strategies the principle in aviation is simply to prevent crews from getting into such situations. The whole aviation system has been built accordingly.

Scientific data suggest that the probability of correctly recovering from a skill-based slip is double compared with a rule-based mistake and three times higher than for a knowledge-based mistake. The remainder of this chapter concentrates on rule-based mistakes.

The usable mistake-mitigation strategies are reduction, detection and recovery. Success in these will be mainly determined by three elements: knowledge, attention factors and strategic factors:

1. Knowledge is reflected both in how well situations are diagnosed and the quality of the chosen solutions. Adequate knowledge relies on training, experience and availability of updated situational information, such as weather and runway conditions.
2. Attention factors determine how easily the relevant information is available. In an ideal case, the attention of the crew is guided to the contextually most relevant and reliable source of information, and the presentation of the information is such that it enables the crew to rapidly achieve complete situational understanding.

   Information overload, distractions and noise should be avoided. When the available information corresponds to attention resources and information needs, diagnosis is easier and potential mistakes are more easily detected. Attention factors are particularly important in view of the biases and heuristics[2] that can distort the diagnostic process.

3. Strategic factors determine the difficulty of the situation in terms of multiple goals, some of which are often partly in conflict. Usually, some goals are obvious and official, while it is possible that others are hidden, personal or even unconscious. Strategic factors become most visible in decision-making situations.

It is clear that while some strategic factors originate from the flight crew, many of them are imposed by the organization and external agents. Obviously, the organization should try to ensure that serious goal conflicts are avoided or when they do arise that safety is not compromised.

A significant proportion of mistakes is caused by incorrect situation diagnosis, which is a particularly problematic task for human cognition. Such diagnosis is mainly due to the biases and heuristics used by human cognition in an attempt to process rapidly large amounts of information.

Violation Management

In simple terms, violation management consists of understanding the reasons for violations and then trying to eliminate these reasons. In an ideal situation, the organization facilitates learning from difficulties in the operations and fixing them before people need to “fill the gaps” by committing violations.

There are known factors that increase the probability of violations:

• Expectation that rules will have to be bent to get the work done
• Powerfulness, Feeling that skills and experience justify deviating from the standard procedures
• Opportunities for short cuts and other ways of doing things in a seemingly better way
• Poor planning and preparation, putting the person in situations where it is necessary to improvise and solve problems as they arise.

This set of factors is sometimes called the “lethal cocktail”.

Often the conditions that induce violations are created because the organization cannot adapt fast enough to new circumstances. The violator may be a very motivated person trying to do things “better” for the company. This explains why management pilots are often more likely to commit violations, especially in small companies where business pressures are strongly felt.

As with errors, it is important to look for the root causes of violations in an organization. Solutions focused at the root-cause level will be the most effective. It is also important to recognize that it is not always productive to punish a violator because the violation may be committed due to factors beyond his or her control.

However, this in no way is intended to undermine the importance of individual responsibility for one’s own actions. Dangerous and reckless behavior should never be tolerated. However, some routine or situational violations may have been imposed on the individual by deficient organization or planning, and any individual put in the same situation might find it difficult not to commit a violation.

Acceptance of a non-compliant way of doing the job may have become part of the local working culture, which also means that the whole group — including management — is responsible for the violation, not just the individual actually committing it.

The ultimate goal is to establish a working culture where violations are neither necessary nor an acceptable option. Like all cultural issues, this establishment can take considerable time and effort. Chances for success are greatly enhanced if the employees themselves are involved in setting the limits of what is acceptable in their own work. The limits must then be clearly communicated and imposed.

On a continuous basis, violation management can take four different forms:

1. Establish channels for people to communicate difficulties and to discuss solutions. This facilitates learning about problems and adjusting planning accordingly to avoid strains which could lead to violations.
2. Analyze existing violations and assess current violation potential. Try to understand the background of current violations. Use the above list of violation-inducing factors to assess the potential for future violations.
3. Try to ensure that management reduces violations through good leadership and planning.
4. Ensure that both management and employees are aware of their responsibilities and the key risks related to their work and understand how violations reduce vital safety margins.

Key Points

• Errors and violations are more common in flight operations than one would expect. They have the potential to affect safety, although usually the robustness of the aviation system is sufficient to compensate for errors and violations without significant consequences.
• The first step in error and violation management is to understand their true causal factors. This flight operations BN has aimed at providing basic information on the subject.
• Successful management of errors and violations requires continuous application of systemic improvements at the organizational level. Ultimately, violation-free operations should become a natural part of the corporate culture.

References

1. ^ James Reason (1990) Human Error, Cambridge University Press, Cambridge, UK
2. ^ Heuristics are simple mental rules of thumb that the human mind uses to solve problems and make decisions efficiently, especially when facing complex problems or incomplete information. These rules work well under most circumstances, but sometimes lead to systematic misjudgments.

Associated OGHFA Material

The following OGHFA material should be reviewed along with the above information:

Briefing Notes:

• Flight Preparation and Conducting Effective Briefings
• Threat Management Training
• Organizational Threat Management
• Managing Interruptions and Distractions
• Pilot-Controller Communications

Visuals:

• Managing Interruptions and Distractions
• Error Management

Situational Examples:

• Runway Overrun After Unstabilised Approach
• Threat and Error Management Preventing CFIT

Additional Reading Material / Websites References

• David D. Woods et al (1994) Behind Human Error: Cognitive Systems, Computers, and Hindsight, CSERIAC State-of-the-Art Report, Wright-Patterson Air Force Base, Ohio, US.
• Patrick Hudson, University of Leiden (2000) Non-Adherence to Procedures: Distinguishing Errors and Violations, presentation given to the 11th Airbus Human Factors Symposium, Melbourne, Australia.

Related Skybrary Articles

• Threat and Error Management (TEM)
• Maintenance Error Management System