Ethical Dilemmas

JOURNAL OF MANAGERIAL ISSUES Vol. XXXII Number 3 Fall 2020

JOURNAL OF MANAGERIAL ISSUES VOL. XXXII NUMBER 3 Fall 2020

Advice-Taking in Ethical Dilemmas

Danny Franklin Assistant Professor

University of Wisconsin – La Crosse [email protected]

Amy J. Guerber

Assistant Professor of Management West Texas A&M University

[email protected]

Organizational decisions are rarely made in social isolation. When faced with a decision, people may rely on advice from others to help interpret the context, evaluate alternatives, and make a choice. Taking advice can help decision-makers improve their judgment (Dalal and Bonaccio, 2010), maintain interpersonal relationships in the organization (Phillips, 1999), comply with organizational norms like accepting help from others, and diffuse responsibility for adverse decision outcomes (Harvey and Fischer, 1997). Previous research has explored how characteristics of the decision, decision-makers, and advisors impact decision-makers’ openness to advice, but advice- taking has not been studied in the context of ethical decisions where the factors influencing openness to advice may differ from other types of decisions.

Ethical decisions involve deliberations of moral norms and standards, or potentially harmful consequences for stakeholders (Treviño, 1986). They often do not have an objectively correct solution and are inherently judgmental (as opposed to intellective) in nature. Individuals faced with ethical decisions make moral judgments about their options based on their own ethical values or the ethical norms and standards of those around them (Treviño, 1986). In ethical decision-making, taking advice could have both advantages and disadvantages. On one hand, advice might provide valuable insights about the ethical values and norms of others, and may increase the likelihood that a decision-maker’s choice will be accepted by others. On the other hand, advice might be a distraction from the decision-maker’s own moral compass and may decrease the chance that the decision-maker will feel good about the choice made. Taking advice about an ethical issue might increase the decision-maker’s accountability for the decision process but also reduce the decision-maker’s personal responsibility for the outcome of the decision.

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For the current study, a theoretical model is developed to predict openness to advice in an ethical decision context using individual and situational factors which are specifically relevant in ethical decision-making. The applicability of this model is compared to a more generic model of advice-taking which incorporates predictors previously found to influence openness to advice in non-ethical decision tasks. These models are referred to as the ethical decision advice-taking (EDAT) model and the generic advice-taking (GAT) model, respectively, throughout this paper. The results show that the ethical decision advice-taking model explains significant variance in individuals’ openness to advice about an ethical decision while the generic model does not. Furthermore, the results of this study show that individuals faced with ethical decisions are most open to taking advice when they have little concern for the ethical implications of the decision.

LITERATURE REVIEW

Advice-Taking

Advice-taking behaviors have been studied in numerous literatures including judgment and decision-making, communications, persuasion, and social/information networks (Rader et al., 2017). Within the organizational decision-making literature, dominant frameworks include Judge-Advisor Systems (JAS) and Hierarchical Decision- Making Teams (HDT). This literature often focuses on understanding the factors which influence decision-makers’ willingness to receive and utilize advice, and the accuracy or quality of their decisions. Previous research holds that advice-taking can be affected by (1) the characteristics of the decision, (2) characteristics and perceptions of advisors, and (3) the characteristics of decision-makers themselves (Gino and Schweitzer, 2008; Tost et al., 2012).

First, advice-taking is affected by certain characteristics of the decision. Research has found that people tend to be more receptive to advice when facing particularly difficult decisions or in situations that are uncertain or ambiguous in nature (Gino and Moore, 2007). Indeed, when people are unable to envision the possible outcomes of a decision, or unable to predict the probabilities of various outcomes, they may come to rely on advice to navigate the decision at hand (cf. Milliken, 1987). Recent research has found that decision-makers are more likely to take advice when decisions are of low urgency but high criticality as opposed to high urgency and low criticality (Johnson and Johnson, 2017). This suggests that decision-makers consider taking advice to be valuable when facing important decisions but also see gathering and evaluating advice as a time- consuming endeavor.

In addition to the difficulty of the task itself, the extent to which the decision task has an “objectively correct answer within a shared conceptual system” (Gino and Moore, 2007: 31) or involves “political, ethical, aesthetic or behavioral judgments for which there is no objective [answer]” (Laughlin, 1980: 128) – that is, the extent to which the task in question is intellective versus judgmental in nature – may affect advice-taking as well. A majority of early advice-taking studies focused on intellective decision tasks because such tasks allow the researcher to quantitatively measure the accuracy of a decision and the extent to which a decision-maker’s final choice is influenced by advice they received (Rader et al., 2017). More recently, researchers have begun exploring advice-taking in judgmental decision tasks (Van Swol, 2011; Yaniv et al., 2011).

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Intellective decisions involve matters of fact, and value of advice can be objectively evaluated in terms of accuracy. Judgmental decisions involve matters of taste or opinion, making the quality or value of advice subjective. One study found that decision-makers are more likely to take advice in intellective as opposed to judgmental decisions (Van Swol, 2011).

Second, advice-taking is affected by the characteristics and perceptions of advisors. Generally, decision-makers wish to take good advice while avoiding or ignoring bad advice, but because they cannot directly determine how good a particular piece of advice is, they rely on cues from the advisor to make inferences about the quality of the advice offered. Decision-makers’ perceptions of advisors’ expertise may be based on information about their credentials, background, and track-record. Many experimental studies manipulate the perceived expertise of advisors by providing decision-makers with information indicative of relevant expertise or by demonstrating the advisors track- record in related decision tasks. Perceptions of an advisor’s expertise can also be influenced by communication and interactions between the advisor and decision-maker. For example, research has found that advisors who use a higher construal level when discussing the problem at hand are perceived as having greater expertise than those who discuss the problem in low construal terms (Reyt et al., 2016). Research has also found that decision-makers are more likely to take advice from others they view as experts in the field (Borgatti and Cross, 2003). They may accept advice from people they view as more experienced and better informed, and discount advice from people they view as less knowledgeable (Soll and Larrick, 2009; Tost et al., 2012). People may also be inclined to accept advice from others they view as more confident than themselves, and from people they trust to make the right decision (Sniezek and Van Swol, 2001; Van Swol, 2011).

One’s similarity with advisors on dimensions like status, values, and personality can influence advice-taking as well (Gino et al., 2009). When decision-makers lack information needed to make an optimal decision, taking advice from cognitively diverse advisors who offer different perspectives is more likely to improve decision-making than taking advice from cognitively similar advisors. Nonetheless, research generally finds that decision-makers are more likely to trust advisors who they perceive as similar to themselves, and often discount or ignore advice that is distant from their own judgments (Rader et al., 2017). Homophily is thought to have tremendous implications for organizational interactions with wide-ranging implications. In the advice-taking literature, researchers have found that decision-makers are more likely to interact with and accept advice from similar advisors (Feld, 1984; McPherson et al., 2001), but this relationship also varies across different types of decisions. Homophily plays a larger role in predicting decision-makers’ willingness to accept advice in judgmental decisions than in intellective decisions. In judgmental decisions, a decision-maker’s perception that an advisor shares similar values increases the decision-maker’s trust in the advisor, which increases the decision-maker’s willingness to accept advice. In intellective decisions, perceived similarities in values do not relate to increased trust in an advisor. Instead, perceptions of the advisor’s confidence are positively related to trust and willingness to take advice in intellective decisions (Van Swol, 2011).

Third, certain characteristics of decision-makers also affect their advice-taking. Personal characteristics like ambiguity tolerance (i.e., one’s dispositional orientation towards “complex, unfamiliar and insoluble” stimuli; McLain, 2009), narcissism (i.e., a

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sense of self-admiration and belief in one’s superiority to others; Kausel et al., 2015), and power (i.e., one’s “capacity to influence others, stemming from… control over resources, rewards, or punishments;” See et al., 2011) may influence decision-makers’ openness to advice. When decision-makers are extremely averse to ambiguity, for instance, they may adopt an avoidance orientation (or a flight response) when faced with ambiguous decisions, skewing their advice-taking in these situations. Narcissistic decision-makers discount the competencies of others and take less advice than non- narcissists. Additionally, non-narcissists increase advice-taking when they expect to be held accountable for their decision process, but such accountability does not alter narcissists’ advice-taking (Kausel et al., 2015). High-power decision-makers have been found to be more confident in their own judgments and less willing to take advice than those with less power (See et al., 2011), although those who view their power as a responsibility are more likely to accept advice than those who view their power as an opportunity (De Wit et al., 2017).

Decision-makers’ internal states like confidence, anxiety, anger, and gratitude may also have predictable effects on advice-taking (Gino and Schweitzer, 2008). Anxiety has been found to decrease decision-makers’ self-confidence leading to increased advice- seeking and taking. Anxiety also reduces decision-makers’ ability to discern whether or not advice is good and whether or not an advisor has a conflict of interest (Gino et al., 2012). In a study of undergraduate students at Carnegie Mellon University, Gino and Schweitzer (2008) found that incidental anger (unrelated to the judgment task itself) caused people to be less receptive to advice from others, presumably because the negative emotion led to reduced trust in others while gratitude caused people to be more receptive to advice from others, eventually resulting in more accurate judgments in the experimental task (Gino and Schweitzer, 2008). More recent research suggests that it is the interaction between the valence (positive or negative) and the agency (self-focused or other-focused) of emotions that determines their impact on openness to advice (de Hooge et al., 2014). Both negative self-focused emotions (e.g., shame) and positive other-focused emotions (e.g., gratitude) led to increased openness to advice while positive self-focused emotions (e.g., pride) and negative other-focused emotions (e.g., anger) reduced openness to advice (de Hooge et al., 2014).

Decision-makers’ motivations in the decision-making context can also affect their advice-taking. People are thought to be motivated to take advice for two primary reasons – to improve the quality of their decision and to share responsibility for uncertain outcomes. First, people are thought to be motivated to improve their judgment and maximize the accuracy of decisions they face (Dalal and Bonaccio, 2010; Phillips, 1999; Sniezek and Buckley, 1995). Paying heed to knowledgeable advisors enables one to improve one’s understanding of the decision and make better choices. Second, people are also thought to be motivated to take advice to reduce the potential negative consequences of committing errors in risky situations (cf. Harvey and Fischer, 1997). The diffusion of responsibility that accompanies advice-taking insulates individual decision-makers from the organizational, social, relational, and psychological consequences associated with making the “wrong” decision (Harvey and Fischer, 1997). People may be inclined to take advice from other individuals to share responsibility for decision outcomes when these outcomes are uncertain and consequential (Harvey and Fischer, 1997; Yaniv, 2004).

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Taking advice can provide task-related and social benefits, and there are many reasons for decision-makers to take advice. Nonetheless, research has frequently found that decision-makers often avoid or underutilize advice even when the advice could have improved their decision outcomes (Rader et al., 2017). Thus, considerable research has explored reasons or motivations for taking advice as well as reasons for avoiding or ignoring advice. Gathering, evaluating, and using advice is time-consuming, and may create conflicts or social obligations for the decision-maker. Research indicates that it may be particularly difficult for decision-makers to evaluate the quality of advice in judgmental decision tasks, making the job of discerning good advice from bad more burdensome, and in turn reducing decision-makers’ overall propensity to take advice (Ecken and Pibernik, 2016). Taking advice and relinquishing one’s decision-making autonomy may be threatening to the self-concept or construed self-image (Rader et al., 2017). Decision-makers may worry that taking advice will reduce their freedom to make a decision that is consistent with their own values, beliefs, or identity (Ashford and Barton, 2007). They may also worry that taking advice will make them appear less competent or less confident in their own judgement (Rader et al., 2017).

Advice-Taking in Ethical Decision-Making

Although not explicitly studied within the advice-taking literature, several studies in the ethical decision-making literature provide insights about the influence others can have on the ethical decision-making process. One of the earliest considerations of the role of others on ethical decision-making within organizations was Trevino’s person- situation interactionist model. This model suggests that decision-makers who are field dependent or who exhibit a lower level of cognitive moral development (i.e., Conventional moral development stages 3 and 4) will be more open to influence when they are facing ethical issues (Treviño, 1986). Research has also explored the role of social influence in spreading and maintaining corruption within organizations (Ashforth and Anand, 2003; Bandura, 1999). Finally, the social constructionist model of ethical decision-making (Sonenshein, 2007) posits that ethical issues are recognized and defined through social interaction but moral judgments are made intuitively by individuals.

Within the ethical decision-making literature there are mixed signals as to whether seeking or accepting advice will lead to more or less ethical decisions. On the one hand, researchers have provided theory and research in support of ethical decision support systems such as ethics hotlines, ethics training, and reporting requirements for employees (Kaptein, 1999; Thorne et al., 2004; Lange, 2008). In one study of accounting professionals, seeking advice from a professional body about ethical issues was treated as a measure of ethical behavior in itself (McManus and Subramaniam, 2009). On the other hand, researchers have often implied that individuals who have a strong moral compass will not be influenced by others when making ethical decisions (Trevino, 1986). Empirical research suggests that individuals with a high internal locus of control make more ethical decisions than those with an external locus of control (Street and Street, 2006). Researchers from social psychology and organizational studies have often highlighted the corrupting effect that social influence can have on ethical decision- making in organizations (Ashforth and Anand, 2003; Brief et al., 2001; Vaughan, 1999).

Although ethical decisions are a particular type of decision, they are still decisions after all, thus it seems likely that good advice could help improve ethical decision-

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making. However, because ethical decisions are complex judgmental decisions, it may be difficult for decision-makers to distinguish good versus bad advice. Furthermore, while some ethical decision-makers may wish to use good advice in order to improve the quality of their decisions, others may use advice indiscriminately for social validation or to share responsibility for their decisions. In this study two models of advice-taking are developed and tested. The first is based on existing advice-taking research and is referred to as the General Advice-Taking (GAT) model. The second is based on factors specific to ethical decision contexts and is referred to as the Ethical Decision Advice- Taking (EDAT) model. Testing these two models provides insight into whether existing advice-taking research can be generalized to ethical decision contexts or whether more nuanced models are needed to understand advice-taking preferences in ethical decision- making.

THEORY AND HYPOTHESES

General Advice-Taking (GAT) Model

The GAT model, illustrated in Figure I, is a distillation of factors which have been consistently found to influence openness to advice in the advice-taking literature. This model predicts that openness to advice will be influenced by perceived decision characteristics and individual characteristics of the decision-maker. Based on previous research, the GAT model predicts that uncertainty and ambiguity tolerance influence openness to advice and that the relationship between uncertainty and openness to advice will vary as a function of decision-makers’ tolerance for ambiguity.

Uncertainty is a strong driving force in decision-making in that it provides an occasion for sensemaking (Sonenshein, 2007; Weick, 1995). Uncertainty has been defined in three major ways in the literature: the extent to which decision-makers are unable to predict probabilities of future events or states of the environment; the extent

Uncertainty

Openness to Advice AT

Unc. X AT

Figure I Generic Advice-Taking (GAT) Model

Note: Unc. = Uncertainty; AT = Ambiguity Tolerance

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to which they lack information regarding cause-effect relationships; and the extent to which they are unable to predict the outcomes of their decisions (Milliken, 1987). When people are faced with high levels of state, effect, or response uncertainty, they are thrust into a state of ignorance, which in turn prompts them to engage in “careful discovery” (Weick, 1995: 95), prompting advice-taking. As decision-makers’ perceptions of uncertainty increase, their confidence in their own ability to understand and respond to the decision task decreases, in turn increasing their openness to advice.

Some decision-makers are more comfortable with uncertainty and ambiguity than others, and this characteristic is also likely to influence advice-taking preferences such that ambiguity tolerance will relate negatively to openness to advice. Individuals who are more comfortable with ambiguity are more likely to be confident in their ability to handle the decision independently, whereas individuals who are less tolerant of ambiguity are likely to be less comfortable with the decision task and to look to outside sources for advice. Furthermore, ambiguity tolerance is also likely to moderate the relationship between uncertainty and openness to advice. Specifically, the relationship between uncertainty and openness to advice is likely to be strongest when ambiguity tolerance is low, and much weaker when ambiguity tolerance is high. Individuals who have a high tolerance for ambiguity may still recognize uncertainty in a decision situation but they will be less likely than others to alter their decision-making process and advice-taking preferences as a result of uncertainty. The predictions derived from the GAT models are summarized in the following hypotheses:

Hypothesis 1: Uncertainty is positively related to openness to advice in ethical

decision-making. Hypothesis 2: Ambiguity tolerance is negatively related to openness to advice in ethical

decision-making. Hypothesis 3: The positive relationship between uncertainty and openness to advice is

stronger (conversely, weaker) when ambiguity tolerance is low (high).

Ethical Decision Advice-Taking (EDAT) Model

Ethical decisions involve the application of moral norms or standards and potentially have negative impacts on stakeholders (Treviño, 1986). Such decisions present unique challenges to decision-makers who must evaluate competing stakeholder claims, and apply moral values and principles to judge between these claims, all the while faced with high levels of uncertainty and difficulty in decision-making (Chia and Lim, 2000; Waters et al., 1986). In the vocabulary of advice-taking research, ethical decisions are inherently judgmental – as opposed to intellective – decision tasks. In judgmental decision-making, evaluations of the quality and value of advice are subjective, and openness to advice is a function of decision-makers’ trust in their own judgment as well as their willingness to trust the judgment of an advisor. The EDAT model, illustrated in Figure II, suggests that factors which are uniquely relevant in ethical decision-making influence openness to advice in ethical decision situations.

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Moral recognition means that a decision-maker understands that a decision has ethical implications and requires a moral judgment, and has often been depicted as a necessary first step of the ethical decision process (Rest, 1986; Jones, 1991). Moral recognition could impact openness to advice-taking in two ways. First, moral recognition may increase decision-makers’ perceptions of the importance of the decision. Second, moral recognition may increase decision-makers’ concern for the self-concept and construed self-image implications of the decision. On one hand, increased perceptions of a decision’s importance should increase a decision-maker’s openness to advice. On the other hand, increased concern for one’s self-concept and construed self-image is likely to increase a decision-maker’s desire for autonomy, and reduce their openness to advice. Thus, the relationship between moral recognition and openness to advice is likely to vary depending on whether moral recognition leads to increased concern for the ethical implications or to increased concern for one’s self-concept and image. Ultimately, the relationship between moral recognition and openness to advice may vary depending on the characteristics of decision-makers.

One individual characteristic which is specifically relevant in ethical decision- making is dispositional moral disengagement. Dispositional moral disengagement is a general tendency of individuals to “disengage internalized moral standards” (Kish- Gephart et al., 2014) across situations. According to social cognitive theory, individuals develop standards of moral or ethical behavior through life experiences (Bandura, 1999). These moral standards serve a regulatory role and thus bring about ethical behavior when they are activated (Bandura, 1999). However, certain individual traits have been proposed to make people more likely to disengage their internal moral standards across a broad range of situations (Detert et al., 2008; Moore, 2008).

Dispositional moral disengagement may affect advice-taking preferences in two ways. First, individuals who are morally disengaged may not even recognize the moral or ethical content of situations they are faced with. Second, individuals who recognize the moral content of ethical decisions may use various mechanisms like moral justification, euphemistic labeling, and diffusion of responsibility to diminish their own perceptions of the importance of the ethical implications of the decision (Bandura, 1999). Thus, dispositional moral disengagement systematically affects one’s response to ethical situations and one’s receptivity to advice in these situations. Individuals with high

DMD

Openness to Advice

DMD X MR

Figure II Ethical Decision Advice-Taking (EDAT) Model

Note: MR = Moral Recognition; DMD = Dispositional Moral Disengagement.

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levels of dispositional moral disengagement are unlikely to be concerned about the ethical implications of a decision and unconcerned about the quality of their decision. Such individuals are likely to be happy to sacrifice decision-making autonomy in exchange for reducing their own effort and responsibility for the decision. These decision-makers are likely to be motivated to take advice in order to share responsibility rather than improve the quality of their decision. Thus, morally disengaged decision- makers may be open to a broad range of advice (as long as it reduces their own decision- making effort and responsibility) and have little concern for the quality of the advice.

Dispositional moral disengagement is also likely to moderate the relationship between moral recognition and openness to advice. Individuals who are low in dispositional moral disengagement are more sensitive to ethical issues and may be particularly motivated to make a morally correct choice. Since the moral correctness of a choice is largely a function of the social acceptability of that choice and/or the decision process used to arrive at it, these people may become more motivated to seek opinions and consult with experienced people around them as the perceived ethical implications of the decision increase. In contrast, individuals with high dispositional moral disengagement may have a very different approach when they perceive ethical implications of the decision. Disregarding the potential consequences of the decision for stakeholders, these people may worry primarily about their image when faced with an ethical issue. For these individuals increased moral recognition is likely to lead to an increased desire to appear confident and competent in their ability to make an ethical decision. Thus, individuals with high dispositional moral disengagement are likely to become less open to advice as moral recognition increases. The relationships predicted by the EDAT model are summarized in the following hypotheses:

Hypothesis 4: Dispositional moral disengagement is positively related to openness to

advice. Hypothesis 5: Moral recognition and dispositional moral disengagement interact such

that individuals with low (high) dispositional moral disengagement become more (less) open to advice as moral recognition increases.

METHOD

Procedure

Experimental vignette methods have been used extensively in the field of behavioral ethics as they enable researchers to study sensitive topics and achieve high levels of internal and external validity at the same time (Aguinis and Bradley, 2014). For this study, realistic and immersive scenarios were used to introduce participants to hypothetical decisions and to study advice-taking preferences. A two-wave scenario- based survey was used to examine the proposed models of advice-taking. In the first wave of the survey, participants were presented with a neutral job-choice scenario followed by measures of the variables of interest. This job choice scenario is a modified version of that administered by Dalal and Bonaccio (2010), where students must decide between five job offers to accept upon graduation. Data from the first wave provided some baseline information and was primarily used for the measurement of dispositional variables (i.e., ambiguity tolerance and dispositional moral disengagement). In the second wave of the survey, an ethical decision-making scenario involving the

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discontinuation of a need-based scholarship by a student organization was presented. Following the presentation of the scenario and advice snippets, independent and dependent variables were measured.

Sample

Undergraduate business students (N=155) at a large public university in the southern United States were recruited to participate in the study in exchange for course points. While the use of student samples has been broadly criticized in organizational research, it is appropriate to use student samples in certain situations, especially when studying the relationships between theoretically-relevant variables like ambiguity tolerance and dispositional moral disengagement on ethical decision-making (Randall and Gibson, 1990). Student participants were informed of their rights and were offered reasonable alternative opportunities to gain the course points offered for the study. Out of the 155 students who participated in the first wave, 134 students also participated in the second wave of the survey. Four responses were dropped due to large amounts of missing data, yielding an overall response rate of 83.9%. There were no significant differences in age, sex, or years of work experience between participants who responded to the second wave and those who dropped out after the first wave of the study.

Measures

Ambiguity Tolerance. Ambiguity tolerance was measured using 13 items from the MSTAT-II scale developed and refined by McLain (2009). Three sample items are “I try to avoid situations that are ambiguous,” “I find it hard to make a choice when the outcome is uncertain,” and “I generally prefer novelty over familiarity,” rated on five- point Likert scales from 1 = Strongly Disagree to 5 = Strongly Agree. Cronbach’s alpha for the measure was 0.85.

Dispositional Moral Disengagement. Dispositional moral disengagement was measured using eight items from Detert and colleagues’ (2008) 24-item scale that tapped into eight distinct moral disengagement mechanisms (Martin et al., 2014). These items were slightly modified to fit the decision-making context. Two sample items are “Some people have to be treated roughly because they lack feelings that can be hurt” and “Taking something without the owner’s permission is okay as long as you’re just borrowing it,” rated on five-point Likert scales anchored from 1 = Strongly Disagree to 5 = Strongly Agree. Alpha for the scale was 0.86.

Uncertainty. Uncertainty was measured using six items developed by Franklin et al. (2013), building on Milliken’s (1987) definition of the construct. Sample items are “The consequences of my decision are not clear” and “I cannot predict how my decision will play out,” rated on five-point Likert scales anchored from 1 = Strongly Disagree to 5 = Strongly Agree. Alpha for the scale was 0.83.

Moral Recognition. Moral recognition was measured using five items developed for the study from Butterfield et al.’s (2000) definition of the construct. Two sample items are “There is some party that is harmed no matter what decision I make” and “Welfare of some student might be negatively affected by my decision,” both rated on five-point Likert scales anchored from 1 = Strongly Disagree to 5 = Strongly Agree. Alpha for the measure was 0.92. A measure of perceived moral intensity was used to establish the nomological validity of the scale. Specifically, as per Jones’ (1991) issue-contingent

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model of ethical decision-making, there ought to be a moderately strong positive correlation between perceived issue characteristics (i.e., magnitude of consequences, social consensus, probability of effect, temporal immediacy, proximity and concentration of effect; Jones, 1991) and moral recognition. Perceived moral intensity was measured using six items developed from Jones’ (1991) definition. Two sample items are “There is very small likelihood that my decision will actually cause harm” and “My decision will not cause harm in the immediate future” (both reverse coded) rated on five-point Likert scales anchored from 1 = Strongly Disagree to 5 = Strongly Agree ( = 0.71). As expected, perceived moral intensity strongly correlated with moral recognition, r = 0.56, p < 0.01, lending evidence towards construct validity.

Openness to Recommendations. Following the presentation of recommendation-for and recommendation-against advice snippets, openness to recommendations was measured using two four-item scales developed by Dalal and Bonaccio (2010). Sample items are “How satisfied would you be with this interaction?” and “How useful would this interaction be for you?” rated on five-point Likert scales anchored from 1 = Not at all to 5 = Extremely. Cronbach’s alpha for the scale was 0.95. Using data from the first wave of the study, a principal axis exploratory factor analysis was performed with Varimax rotation on the eight items. As expected, one factor emerged, explaining 68.66% of variance in the items. A visual examination of the Scree plot also confirmed the one-factor solution. Factor loadings of individual items varied from 0.79 to 0.89, supporting the unidimensionality of the measure.

RESULTS AND DISCUSSION

The correlations between the measured variables are presented in Table 1.

Openness to recommendations was negatively correlated with moral recognition, and positively correlated with dispositional moral disengagement. Further, moral recognition and dispositional moral disengagement were negatively correlated with each other, indicating a rather complex relationship between these two variables and the dependent variable. Uncertainty and ambiguity tolerance were not significantly correlated with openness to recommendations. These correlations suggest that openness to advice in ethical decision-making relate significantly to factors in the EDAT model but not those in the GAT model.

Hypotheses were tested by regressing openness to recommendations on the centered main effect and interaction terms (Cohen et al., 2013). Hypothesis 1 predicted a positive main effect of uncertainty on openness to advice. Hypothesis 2 predicted that ambiguity tolerance would be negatively related to openness to advice, and Hypothesis 3 predicted that the strength of the relationship between uncertainty and openness to advice would be moderated by ambiguity tolerance. Results of this regression analysis are presented in Table 2. The main effect model (R2 = 0.02, F(2,127) = 1.40, p > 0.10) and the interaction model ( R2 = 0.01, Fchange(1,126) = 1.20, p > 0.10) failed to significantly explain variance in openness to recommendations. Although the coefficients of variables in this model were in the expected directions, none of them were statistically significant. As such, the GAT model and Hypotheses 1, 2, and 3 did not receive support in the ethical decision-making context.

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Table 1 Descriptive Statistics and Correlations

Variable M SD 1 2 3 4

1. Ambiguity Tolerance 3.26 0.54

2. DMD 1.82 0.70 -0.25**

3. Moral Recognition 4.23 0.66 0.14 -0.23**

4. Uncertainty 3.29 0.79 -0.07 0.00 0.43**

5. Openness to Recommendations

1.74 0.77 -0.14 0.32** -0.15 0.05

Note: N = 130. DMD = Dispositional Moral Disengagement. M = Mean. SD = Standard Deviation.

p < 0.1, * p < 0.05, ** p < 0.01

Table 2 Regression Results: General Advice-Taking (GAT) Model

Variables Main Effect Interaction

Uncertainty 0.04 0.02

Ambiguity Tolerance -0.14 -0.12

AT X Uncertainty -0.10

R 2 0.02 0.03

R 2 0.02 0.01

F change

1.40 1.20

Note: Standardized Beta coefficients are reported. p < 0.1, * p < 0.05, ** p < 0.01

Hypothesis 4 predicted that openness to advice would be positively related to

dispositional moral disengagement, and Hypothesis 5 predicted that the relationship between moral recognition and openness to advice would be positive for individuals with low dispositional moral disengagement and negative for those with high dispositional moral disengagement. As before, these hypotheses were tested by regressing openness to recommendations on the centered main effect and interaction terms. Results of this analysis are presented in Table 3. As predicted, the relationship between dispositional moral disengagement and openness to advice is positive and significant ( = 0.30, p < 0.01) lending support to Hypothesis 4. The interaction model ( R2 = 0.05, Fchange(1,126) = 6.81, p < 0.05) significantly explained variance in openness to recommendations,

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beyond that accounted for by the main effect model (R2 = 0.11, F(2,127) = 7.73, p < 0.01). Interactions were plotted to aid in the interpretation of results. As seen in Figure III, the relationship between moral recognition and openness to advice is positive for individuals with low dispositional moral disengagement and negative for those with high dispositional moral disengagement.

This study provides novel insights about the impact of situational and individual factors on decision-makers’ willingness to take advice when faced with ethical decisions. First, it is noteworthy that the EDAT model captures factors which influence openness to recommendations in ethical decision situations whereas the GAT model does not. Previous research has often focused on the impact of uncertainty and difficulty on decision-makers’ advice-taking behaviors (e.g., Gino and Moore, 2007; Lipshitz and Strauss, 1997), but these studies have not explicitly explored advice-taking in ethical situations. Results from this study demonstrating a relationship between factors specific to ethical decision-making and openness to recommendations suggest there may in fact be important differences between the drivers of advice-taking in ethical and non-ethical situations. Future work should focus on understanding the differences in advice-taking behaviors in ethical versus non-ethical decisions. What types of advice do people prefer in ethical decision-making? Do advice preferences change with an increase in moral intensity of the decision? Does advice from internal organizational stakeholders versus external stakeholders systematically affect the quality or acceptability of the final decision? If so, how can managers encourage advice-taking in ethical decision-making, and how might researchers help decision-makers recognize and use good advice when faced with ethical decisions? These lines of inquiry will help advance researchers’ understanding of interpersonal and social influences in ethical decision-making – an area that has been somewhat ignored in the behavioral ethics field (see Treviño et al., 2014).

Table 3 Regression Results: Ethical Decision Advice-Taking (EDAT) Model

Variables Main Effect Interaction

Moral Recognition -0.08 -0.07

DMD 0.30** 0.27**

DMD X Moral Recognition -0.22**

R 2 0.11** 0.15**

R 2 0.11** 0.05*

F change

7.73** 6.81*

Note: Standardized Beta coefficients are reported. DMD = Dispositional Moral Disengagement

p < 0.1, * p < 0.05, ** p < 0.01

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Figure III Interaction between Moral Recognition and DMD

Note: DMD = Dispositional Moral Disengagement

Next, it is also noteworthy that dispositional moral disengagement influences openness to advice and moderates the relationship between moral recognition and openness to recommendations. Organizations often implement ethical decision support systems in order to increase the quality and reliability of ethical decision outcomes within the organization (see Mathieson, 2007). Such support systems may be informal, relying on information and advice networks to ensure that organization members understand and follow relevant norms when facing ethical decisions. In other cases, ethical decision support systems may be formal, relying on codified policies and procedures to ensure that ethical issues are referred to the appropriate individuals and handled consistently. Informal ethical decision support systems are especially reliant on individuals’ willingness to seek and take advice regarding ethical issues, and even with formal ethical decision systems there is a risk that individuals may not recognize ethical issues or may choose to ignore such issues even when they are noticed. Results of this study suggest that those decision-makers who are least concerned about the ethical implications of their decisions may be the most likely to use such advice systems, thus ensuring that these systems provide high quality advice may improve ethical decision outcomes.

Findings further suggest that managers should consider individual differences which impact openness to advice when designing and implementing ethical decision support systems. Of course, the specific designs of such systems would depend on the goals of the organization. If the organization wants to ensure that ethical decisions are handled efficiently and consistently, finding ways to encourage individuals to seek and accept recommendations from knowledgeable advisers may be important. Many interesting research questions come to light. Can incentive systems be used to supersede individual differences and ensure employee engagement with ethical decision support

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systems? If the organization wants to override these individual differences and encourage creativity in ethical decision-making, should managers find ways to encourage moral dialogue that is perhaps not designed to lead to an immediate recommendation? Answers to these questions may be helpful to organizations seeking to implement ethical decision support systems.

The nature of the interaction between dispositional moral disengagement and moral recognition in influencing advice-taking is also interesting for several reasons. The slopes of the relationships demonstrate that individuals with high levels of dispositional moral disengagement become less open to recommendations as moral recognition becomes stronger, whereas individuals with low levels of dispositional moral disengagement become more open to recommendations as moral recognition becomes stronger. It is notable that overall, individuals with high levels of moral disengagement are more open to advice in ethical decisions than their counterparts with low levels of dispositional moral disengagement. While additional research is needed to fully understand this relationship, it may suggest that morally disengaged individuals are more content to take recommendations in order to reduce their personal responsibility for an ethical decision or to simply reduce their own effort and deliberation in making a choice. An interesting avenue for future research would be to examine groups consisting of one or more morally disengaged individuals. Since most organizational decisions are made in a group context, there is reason to believe that morally disengaged individuals may have disruptive influences on group ethical decision-making.

Overall, this study suggests that it should not be assumed that previous advice- taking research will generalize to ethical decision-making. Instead, advice-taking preferences and behaviors in ethical decisions are influenced by factors uniquely relevant to ethical decision situations. Additionally, concepts related to behavioral ethics and decision-making organizations such as self-serving bias, overconfidence bias, groupthink, peer pressure, and information processing may provide valuable insights into the processes by which decision-makers seek, evaluate, and use advice when faced with ethical decisions. This study provides novel information about factors that influence openness to advice in ethical decision-making as well as a clear foundation for additional research exploring advice-taking in ethical decision-making.

Limitations and Directions for Future Research

The motivation of this study was not to comprehensively answer all questions about advice-taking in ethical decision-making. Instead, the motivation was to test whether unique factors affect advice-taking in ethical, as opposed to non-ethical, decision- making. Findings suggest that unique factors do play a role in shaping advice-taking preferences in ethical decision-making. Despite its unique contributions to understanding advice-taking in ethical dilemmas, this study has certain limitations that need to be addressed. First, this study used a vignette to analyze responses to a hypothetical ethical dilemma. While experimental vignette methods are often used to study responses to ethical dilemmas in the field of behavioral ethics (see Kish-Gephart et al., 2014), this methodology is limited by its lack of realism (McGrath, 1984). Efforts were taken to make the decision scenarios as realistic as possible, but it is plausible that participants may respond differently to hypothetical decision tasks compared to real- world decisions. Also, ethical issues can vary across many dimensions, including the extent to which they are judgmental or intellective in nature. The use of just one ethical

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decision task in the current study limits its ability to discern the impact of other characteristics of ethical issues on advice-taking. Future research could explore how various characteristics of ethical decisions impact advice-taking. Additionally, although openness to advice is a relevant outcome, this study does not provide direct information about the extent to which decision-makers will ultimately be influenced by advice. Future research might use alternative methods (e.g., a natural experiment) and/or measures (e.g., advice-taking behavior) to study advice-taking in ethical decision-making.

Second, in the current study, advice was operationalized as recommendations for or against particular choice options. While this is in line with much of the previous advice-taking research, Bonaccio and Dalal (2006) emphasize that recommendations are but one of several types of advice that might be given. Other forms of advice include information about options, information or suggestions about how to go about making the decision (i.e., decision process support), and social support. Previous research suggests that supporting information is particularly important in judgmental decision tasks (Ecken and Pibernik, 2016; Tzioti et al., 2014). This suggests that decision-makers facing ethical issues might react more favorably to information about options than to simple, unsupported recommendations. Future research could explore differences in ethical decision-makers’ openness to various types of advice.

Third, while this study explores the impact of dispositional moral disengagement on openness to advice in ethical decision-making, it is likely that other decision-maker characteristics also impact openness to advice. Following the contours of research in advice-taking, research in the ethical decision-making context could explore additional decision-maker and advisor characteristics on advice-taking in ethical decision-making. Decision-maker characteristics which have been explored in the ethical decision-making literature such as locus of control, cognitive moral development, and Machiavellianism may be worth exploring. It is also possible that links may exist between openness to advice and demographic characteristics such as age, gender, tenure in an organization or profession, and education.

Future research could also explore the impact of advisor characteristics on openness to advice in ethical decision-making. Previous research has found that openness to advice can be impacted by the perceived expertise of the advisor as well as similarity between the advisor and the decision-maker. It seems likely that ethical decision-makers may be more open to advice from advisors who they believe share their own values. This may be particularly true among ethically-sensitive decision-makers who are concerned with making a decision with which they feel morally comfortable. Decision-makers with high dispositional moral disengagement may be more concerned with making decisions that will be accepted by other members of the organization and may prefer advice from someone in a position of authority or someone who is held in high esteem within the organization. Future research could explore the impact of these characteristics on openness to advice and could also seek to understand how ethical decision-makers evaluate the values or expertise of advisors in an ethical decision context. Additionally, since ethical decisions often affect stakeholders outside of the organization, it would be valuable to understand factors that influence decision-makers’ openness to advice from external parties.

Finally, future research should seek to understand if or when taking advice improves the quality of ethical decision-making. First, research should seek to understand the conditions under which ethical decision-makers actually use advice.

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While previous advice-taking studies have used objective decision scenarios in order to quantitatively measure the weight of advice, ethical decisions do not lend themselves to such straightforward measures of the extent to which decision-makers use advice. Thus, researchers will need to explore more creative and nuanced ways to examine the extent to which advice impacts ethical decisions. One option might be to ask the decision- maker to explain the thought process behind their decision after they have made a choice. This could provide insight into how much consideration decision-makers gave to advice and whether they ultimately acquiesced to the advice or not. Such a technique might even provide insight into whether the decision-maker would have preferred another type of advice or advice from additional sources as well. Next, research should explore the impact of advice on decision outcomes. Does advice help decision-makers recognize additional options? Does taking advice lead to more positive perceptions of the decision process and outcome from the perspective of the decision-maker or other audiences? Understanding the impact of advice on ethical decision outcomes will be foundational to the development of effective ethical decision support systems in organizations.

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