Accepted Manuscript Beware the Dark Side: Cultural Preferences for Lying Online
Kent Marett, Joey F. George, Carmen C. Lewis, Manjul Gupta, Gabriel Giordano PII:
S0747-5632(17)30392-8
DOI:
10.1016/j.chb.2017.06.021
Reference:
CHB 5031
To appear in:
Computers in Human Behavior
Received Date:
20 January 2017
Revised Date:
07 April 2017
Accepted Date:
13 June 2017
Please cite this article as: Kent Marett, Joey F. George, Carmen C. Lewis, Manjul Gupta, Gabriel Giordano, Beware the Dark Side: Cultural Preferences for Lying Online, Computers in Human Behavior (2017), doi: 10.1016/j.chb.2017.06.021
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Beware the Dark Side: Cultural Preferences for Lying Online AUTHORS: Kent Marett † Department of Management & Information Systems College of Business Mississippi State University Mississippi State, MS 39762 US
[email protected] Joey F. George Department of Information Systems College of Business Iowa State University Ames, IA 50011 USA
[email protected] Carmen C. Lewis Department of Quantitative Methods and Information Systems Sorrell College of Business Troy University-Dothan Dothan, AL 36303 USA
[email protected] Manjul Gupta Department of Information Systems and Business Analytics College of Business Florida International University Miami, FL 33199 USA
[email protected] Gabriel Giordano Department of Management Information Systems College of Business Ohio University Athens, OH 45701 USA
[email protected] † contact author
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Beware the Dark Side: Cultural Preferences for Lying Online ABSTRACT: Deceptive communication is a part of everyday life, regardless of one’s geographical location or method of communication. Very little research has examined the role of espoused cultural values in the preferences that individuals hold when considering to deceive others. These preferences include the relationship and the sex of the target of the deception and the modality used for committing the deception. This study features a survey of Internet users from four countries that differ in cultural values. Results indicate that more lying occurs online no matter the country, but preferences for lying differ between nationalities. KEYWORDS: computer-mediate communication, deception, cultural dimensions, communication modalities, gender
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Beware the Dark Side: Cultural Preferences for Lying Online 1. Introduction Even though lying is discouraged within most societies, it is actually a common part of daily communication (DePaulo, Kirkendol, Kashy, Wyer, & Epstein, 1996; Hancock, ThomSantelli, & Ritchie, 2004). And although most the research relating to lying behavior has been conducted in a North American context, there is evidence that lying is a universal form of communication (see for example Aune & Waters (1994); Choi, Park, & Oh (2011); Fu, Lee, Cameron, & Xu (2001); Mealy, Stephan, & Urrutla (2007)). Much of the research on lying and deception has focused on simulating face-to-face, real time, dyadic interaction, but today much of our communication takes place in computer-mediated modes, such as email, text messaging, and videoconferencing via such tools as Skype and FaceTime. Although we know relatively less about deception in a computer-mediated environment, we do know that deception regularly takes place across many different modes of communication (George & Robb, 2008). There are approximately 2.8 billion users of the Internet worldwide (Lynley, 2015) and the online population is continually growing more diverse. In 2015, India surpassed the United States as the second-largest online population, trailing only China (Russell, 2015). It would be naïve to think that all of the worldwide Internet users were communicating honestly with each other all of the time. In fact, there is some evidence that people lie more online than they do face-to-face (Cornwall & Lundgren, 2001; Lewis & George, 2008; Whitty, 2002). There are many ways in which deceptive behavior would be more attractive in computer-mediated modes, especially when those modes have limited visual components. Text-based modes would allow for deception about age, gender, and other physical characteristics. Both text-based and audio-only modes would allow for deception about where one lived, where one worked, one’s income and personal interests. While such deceptions are common (and even expected) in some online situations, such as online dating (Toma, Hancock, & Ellison, 2008), it may be a slippery slope from deceiving others about relatively trivial issues to deceiving them about more serious matters. This is where the pull of the “dark side” of computing comes into play: If success at
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trivial deception online comes easily, then the temptation exists to attempt online deception when the stakes are higher. The temptation to deceive online is not the same for everyone. We know that within a group, some people refuse to lie (George & Carlson, 2010). We also know that there are variations across groups and cultures – for example, people from collectivist societies are more likely to lie during business negotiations than are people from individualistic societies (Triandis et al., 2001). Thus, the temptation to deceive via computer-mediated modes of communication may be stronger for some groups than for others. We know little, however, about the tendencies to deceive online between cultures and societies. Given that tendencies to deceive online are not well understood, and given that we know little about these tendencies across cultures and societies, the research reported in this paper is designed to address the following research questions: 1) Do people lie more online than in person (face-to-face)? 2) What are they most likely to lie about face-to-face and online? 3) And, are there differences in how people from different cultural groups lie, whether online or face-toface? The rest of the paper is organized as follows: We start with a review of relevant theory and literature. This is followed by the presentation and justification of our hypotheses. We then present details of our research methods and our findings. We end with a discussion of our results, including implications for practice and research. 2. Theory & Literature Review While deception is common across different modes of communication, its prevalence no doubt varies across modes. Online modes of communication, especially those that are textbased, would appear to be havens for deception, given that they hide aspects of the deceiver that would show particular lies to be obviously untrue (e.g., statements about age, gender, and physical appearance). Several established theories dealing with media differences help explain why some modes of communication are more tempting for liars than others. First, media richness theory (MRT) illustrates how the inherent properties of a medium influence effective communication between two or more parties (Daft & Lengel, 1986; Daft, Lengel, & Trevino, 1987). Face-to-face communication is considered to be the richest mode of communication, in that it allows instant mutual feedback, the transmission of verbal and nonverbal cues, the 3
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availability of natural language and emotion, and discussion that is exactly tailored to the other communicator. By comparison, communicating by text messaging, by e-mail, or even by video conferencing software like Skype is considered less rich (Rao & Lim, 2000; Tung & Turban, 1998). MRT predicts that much of the nonverbal communication that reliably points to deception is filtered out in the lean computer-mediated environment, which might be appealing to a deceiver. A second media theory, media synchronicity theory or MST (Dennis, Fuller, & Valacich, 2008), considers the synchronicity afforded by a medium, i.e., the use of the medium for communicators with a common focus to work together in a coordinated timing pattern. Face-toface communication is considered a highly synchronous communication mode because it allows for an expected temporal pattern (a regular give and take of communication), while computermediated modalities like e-mail are more asynchronous, with communication tending to exhibit a less regular timing pattern. Where deception is concerned, asynchronous communication should aid online deceivers in developing a more believable message based on the opportunity to craft and rehearse a message before sending it. By the same token, a lack of synchronicity should aid receivers in appraising a questionable message before responding. Phishers, for example, are able to benefit from the rehearsability afforded by online communication, and in an effort to discourage receivers from thoroughly appraising the message, often attempt to instill a sense of urgency in receivers of phishing messages (Wright & Marett, 2010). However, while these two theories start to reveal important differences about the attractiveness of different media for liars, guidance provided by the concepts of deindividuation and social presence theory may be more conclusive. Deindividuation concerns a rise in uninhibited behavior an individual exhibits should the individual supplant his or her sense of identity with the antinormative behaviors belonging to a larger group he or she identifies with and is involved with (Diener, 1979; Zimbardo, 1969). Simply put, the individual undergoes decreased awareness of his or her internal standards and loses the capacity to regulate his or her own actions, leading to an assortment of antinormative behaviors. Deindividuated communication, for instance, can include an increase in profanity, threatening language, and of interest here, deception (Lewis & George, 2008; Marett & George, 2013). We expect deindividuated behavior to be present in online settings and that it can lead to deceptive communication. Social Presence Theory (Short, Williams, & Christie, 1976) offers an 4
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explanation for the potential for deindividuation in online contexts. Social presence was originally defined as whether “another person is perceived as present or absent” when communicating, but it has been reconceived to acknowledge that the other communicator is actively engaging and evaluating transmitted messages (Biocca, Harms, & Burgoon, 2003). Perceptions of low social presence would mean no regard is paid to the active evaluation of the other person. The theory explains that perceptions of social presence are mediated by the communication modality used by the two parties, which is increasingly technology-based. While it may seem that media high in richness naturally conveys the most social presence, instead it is a question of fit between the most appropriate technology for meeting the goals of the communicator (Rice, 1993). Table 1 summarizes the differences in face-to-face and CMC extending to this study. Table 1: Summary of Key Differences in Face-to-Face and Computer-Mediated Communication Face-to-Face Communication Speed of Communication Availability of Communication Cues Level of Social Presence and Personalization
Instant feedback Verbal and nonverbal cues High level of personalization and social presence
Computer-Mediated Communication Slower, often asynchronous feedback Limited set of cues – often only textbased Deindividualized communication due to low social presence
Goals like “touching base” and exchanging information may not require much in terms of social presence, but successfully completing more complex goals like negotiation, decision making, and “getting to know one another” require a higher level. Following from Social Presence Theory, the medium either accommodates or inhibits cues that promote social presence. When communicators desire to complete complex communicative tasks, the media limitations that prevent the transmission of social cues can ultimately lead them to be less psychologically engaged with the other person, and therefore less concerned with maintaining good appearances and normative behavior (Xu, Cenfetelli, & Aquino, 2012). Thus, deindividuated behavior like deception seems to be more likely when the medium being used fails to convey a sufficient level 5
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of social presence for the task at hand, as is the case with complex tasks utilizing computermediated communication. Thus, we predict: H1: Individuals are more likely to lie using computer-mediated communication than to lie faceto-face. Explanations of how various cultures differ in deceptive behavior largely draw on Hofstede’s Theory of Cultural Differences (Hofstede, 1980). According to Hofstede’s theory, there are five dimensions of espoused cultural values: individualism/collectivism, power distance, uncertainty avoidance, masculinity/femininity, and long/short-term orientation. Individualism/collectivism refers to the degree to which individuals are affiliated with groups. While individualism is characterized by loose group ties, collectivism is illustrated by individuals being integrated into strong, cohesive groups. Individuals in collectivist societies are motivated by group interests, regardless of whether the group is the family, the tribe, or the clan (Hofstede, 1984). Power distance is the extent to which less powerful individuals accept and expect an unequal distribution of power. Surprisingly, an unequal power distance culture is authorized by its followers as much or more than its leaders, with superiors not necessarily abusing power. Uncertainty avoidance describes the extent to which individuals feel comfortable in uncertain and ambiguous situations. High uncertainty avoidance cultures are characterized by resistance to change and risk. Typical of these societies are strict rules, policies, and laws, adopted to satisfy deep emotional needs for predictability and moderation of unexpected events. Masculinity/femininity relates the extent to which a culture values and exhibits masculine or feminine characteristics. While masculine cultures are characterized as assertive and competitive, placing a strong emphasis on performance, feminine cultures display more modest and caring values, demonstrated through the desire to improve quality of life for its members. Naturally, there is a smaller gap between the values of men and women in feminine countries than in masculine countries. The final dimension, long-term orientation, establishes the degree to which individuals value saving, persistence, and planning behaviors. Short-term orientation, in contrast, is identified with past and present values like personal stability, respect for tradition, and reciprocation of favors and gifts. People from different cultural groups often differ in how they view deception and in how they deceive others. For example, Chinese study participants perceived deception more 6
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favorably than Americans for modest behaviors, such as falsely distributing credit rightly due to an individual to the larger collective (Fu, Heyman, & Lee, 2011). Russians lied more often than Americans if it helped underperforming in-group members (Bessarabova, 2014). Also, Irish males were found to be more deceptive than American males in their online dating activities (Hamilton & Kirwan, 2013). Differences in how groups perceive deception should be reflected in their communication behavior. A recent meta-analysis of studies of the effects of cultural values on communication revealed distinct differences across cultural groups, using four of Hofstede’s dimensions of culture (Merkin, Taras, & Steel, 2014). The authors found a relationship between cultural values and deceptive communication for only one of the four dimensions, individualism-collectivism. Individualism was found to be negatively related to a propensity to use deception, while collectivism was found to be positively related. These findings reflect those of earlier studies, that collectivists were more likely to lie in business negotiations than were individualists (Li, Triandis, & Yu, 2006), and that collectivists were more likely to use blatant, self-serving and altruistic lies in order to have sex, than were individualists (Phan, 2013). The relationship between deceptive communication and Hofstede’s other cultural dimensions has not received as much attention as the relationship between deception and individualism-collectivism. One exception is a study that looked at the differences between Euro-Americans and Ecuadorians (Mealy, Stephan, & Carolina Urrutia, 2007). Ecuadorians scored higher on uncertainty avoidance and power distance than Euro-Americans, and they perceived lying as less acceptable. The authors explained their findings as “Lies create uncertainty and imperil cultures that favor hierarchical social structures, so it should not be surprising that Ecuadorians so strongly disapprove of lying (p. 698).” Relatively little research has investigated the relationship between cultural values and deception. The studies that have been conducted have found differences in how different cultural groups perceive deception, and some of those differences can be explained by looking at the role of specific cultural dimensions from Hofstede. However, there is not enough theoretical or empirical work to predict how different scores on each dimension would precisely predict deceptive behavior, but we can craft the following hypothesis: H2: Espoused cultural values will affect deceptive behavior. 7
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In additional to espoused cultural values affecting deceptive behavior in general, is it also possible that their influences on online deception and face-to-face deception are different? Few studies have attempted to examine the impact of cultural differences on lying behavior in online computer-mediated communication (CMC). One study investigated the relationship between differences in Korean and American culture, and deceptive behavior for both face-to-face and online communication (Lewis & George, 2008). The results showed that Koreans were more likely to lie in general than Americans. Further, individuals from both groups demonstrated greater deceptive behavior while communicating face-to-face than in an online environment. Additionally, individuals with espoused masculine cultural values (i.e., characterized by assertive and achievement-oriented behavior) were found to exhibit more deceptive behavior than those with espoused feminine cultural values (i.e., characterized by modest and nurturing behavior). None of the other cultural dimensions were found to be significantly related to deceptive behavior. A second study investigated the relationship between espoused cultural values of Chinese and American college students and their preferred media choice for deception (Furner & George, 2012). The findings indicated that both groups overwhelmingly preferred face-to-face over online communication for deception; however, the espoused cultural values of individuals were found to influence their choice of CMC-based media for lying. Individuals with high scores on collectivism favored text-based media (e.g., email) for lying, while those with high scores on power distance favored audio-based media for lying (e.g., voice-over-IP). On the other hand, individuals with espoused masculine cultural values preferred to lie using visual media (e.g., FtF). Apart from the two studies reviewed above, the research stream pertaining to the intersection of online communication, culture, and deception remains in an embryonic state; however, there is some research indicating that people from different cultures are likely to alter their behavior depending on the mode of communication. For example, St. Amant (2002) contended that people from high-context cultures (i.e., cultures in which communication relies heavily on contextual and non-verbal cues) are likely to get “uncomfortable, frustrated, or reserved” when the communication medium lacks the capability to transmit the symbols required to establish the identity of the other person (p.201). Thus, individuals from high-context 8
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cultures, which in general tend to be highly collectivist, are likely to demonstrate different communication behavior than individuals from low-context cultures (i.e., cultures in which communication is more direct and considered highly individualistic) while communicating online (Gudykunst et al., 1996; Hall & Hall, 1976; St. Amant, 2002). These studies yield some interesting insights. First, they suggest that espoused cultural values of individuals can be linked to their deceptive behavior (Lewis & George, 2008). Second, cultural dimensions are likely to impact the preferred choice of CMC-based media for lying (Furner & George, 2012). Finally, individuals from some cultures may adjust their behavior depending on the extent to which the medium they are using for online communication is capable of transmitting different symbols or cues. While St. Amant (2002) did not specifically talk about deceptive behavior, based on his work and related insights (Furner & George, 2012; Lewis & George, 2008), we propose that cultural dimensions are likely to influence deceptive behavior differently during face-to-face and online communication. Thus, we hypothesize: H3: Dimensions of culture will affect online deceptive behavior differently from how they affect face-to-face deceptive behavior. There is an ongoing debate about who lies more, men or women. Some studies have found that men lie more (Dreber & Johannesson, 2008), while others have found no differences (Childs, 2012). While these and related studies have focused on lying behavior in general, at least one study has investigated differences in lying between genders when online. Whitty (2002) found that men lied more than women in chat rooms. On that basis, we predict: H4: Males are more likely to lie when communicating online than females when communicating online. When engaged in deceptive activities online, are men more likely to lie to women or to other men? The answer is not clear. On the one hand, a negotiation study found that women were thought to be more easily misled, thus negotiators deceived women more often than they deceived men (Kray, Kennedy, & Van Zant, 2014). Additionally, a dating study found that men did more self-presenting than women, when anticipating a future interaction with a prospective date, and 9
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this effect was enhanced when the exchange was to be over email as opposed to face-to-face (Guadagno, Okdie, & Kruse, 2012). Both of these studies imply that men would lie more to women than to other men. However, other literature found that women pay attention to different indicators of deception than do men (Sato & Nihei, 2009) and that in fact women are better able to detect deception than are men (Burgoon, Blair, Buller, & Tilley, 2006). If women are indeed better deception detectors, then it would not be wise to lie to them. However, behavior is not always based on the best information, and most men may not realize how adept women are at deception detection. Therefore, we predict: H5: Individuals are more likely to lie to females than to males when communicating online. Past research has consistently found that people are more likely to lie to strangers than they are to people they know (Ennis, Vrij, & Chance, 2008; Van Swol, Malhotra, & Braun, 2012). Individuals tend to feel more discomfort when lying to close friends than to strangers, and they generally think that it is more acceptable to lie to strangers than to friends (Levine, 2014). Therefore, we hypothesize that: H6: Individuals are more likely to lie to strangers than to family members when communicating online. 3. Research Method Subjects were recruited from four countries (France, India, South Korea, and the United States) using both Amazon Mechanical Turk and Qualtrics Survey Paneling. The surveys were translated from English into the native language of each country. Subjects were all 18 years or older, and because they were contacted via the Internet, they were deemed to be appropriate to the context of lying online. A total of 461 responses were received through the survey effort; however, 96 of the responses were dropped due to being incomplete or through failing an attention check item embedded within the survey. The remaining 365 responses were composed of 100 French, 46 Indians, 122 South Koreans, and 97 Americans. In order to test the hypotheses, a 2 x 2 x 2 factorial design was used, mixing communication media (online vs. face-to-face), the gender of the recipient (male vs. female), and 10
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the relationship of the recipient (family member vs. stranger). The four countries were selected for their presumed differences on the Hofstede cultural dimensions (Srite & Karahanna, 2006). Although the Hofstede measures have been utilized repeatedly in information systems research (e.g., Hovav & D’Arcy (2012); Lowry, Zhang, Zhou, & Fu, (2010)), because the context and sample differs from that of previous studies, we re-assessed the validity of those measures here. Table 2 displays the results of the confirmatory factor analysis conducted using SPSS 23.0. Three of the items in the Uncertainty Avoidance measure and one item in the Long Term Orientation measure were determined to be problematic, and by dropping them, the reliabilities of the remaining measures were improved. Apart from Long Term Orientation, all Cronbach’s Alpha results were satisfactory (> 0.7) (Straub, Boudreau, & Gefen, 2004). Table 2: Confirmatory Factor Analysis for Cultural Dimensions Collectivism α = 0.82 COLL1 COLL2 COLL3 COLL4 COLL5 COLL6 POWDIST1 POWDIST2 POWDIST3 POWDIST4 POWDIST5 POWDIST6 POWDIST7 UNCERTAIN1 UNCERTAIN2 UNCERTAIN3 MASC1 MASC2 MASC3 MASC4 MASC5 LONGTERM1 LONGTERM2
0.79 0.80 0.91 0.91 0.85 0.76 0.01 0.04 0.07 0.16 0.09 0.12 0.01 0.04 0.06 0.02 0.07 0.17 0.01 0.02 0.26 0.07 0.08
Power Distance α = 0.88 0.09 0.03 0.07 0.05 0.11 0.32 0.84 0.78 0.81 0.82 0.74 0.77 0.80 0.01 0.05 0.06 0.24 0.01 0.22 0.14 0.39 0.01 0.01
Uncertainty Avoidance α = 0.81 0.01 0.01 0.03 0.01 0.14 0.17 0.15 0.23 0.14 0.01 0.44 0.27 0.11 0.93 0.92 0.92 0.13 0.21 0.06 0.01 0.07 0.05 0.05
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Masculinity α = 0.86 0.31 0.28 0.06 0.14 0.28 0.29 0.19 0.01 0.05 0.10 0.25 0.07 0.06 0.04 0.01 0.03 0.78 0.87 0.80 0.87 0.87 0.07 0.07
Long Term Orientation α = 0.65 0.04 0.06 0.10 0.03 0.11 0.20 0.01 0.08 0.10 0.01 0.08 0.27 0.04 0.02 0.02 0.04 0.02 0.06 0.04 0.03 0.10 0.94 0.90
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Table 3 below displays the traditional cultural dimension levels provided by Hofstede with the cultural responses from individuals from each country that we collected through the survey. A one-way ANOVA indicated a significant difference among the four countries across all five cultural dimensions, suggesting that a heterogeneous sample of espoused cultures had been collected. Table 3: Values for the four countries on Hofstede’s five cultural dimensions Power distance
Individualism Masculinity Uncertainty avoidance 71 43 86 48 56 40 18 39 85
France 68 India 77 South 60 Korea US 40 91 Source: geert-hofstede.com Power distance
Collectivism
France 2.55 2.70 India 3.51 3.77 South 2.45 2.83 Korea US 2.55 2.48 F 40.88*** 59.17*** Scale from 1 (low) to 5 high (high). * significant at the .05 level (2-tailed) ** significant at the .01 level (2-tailed) *** significant at the .001 level (2-tailed)
62
46
Long-term orientation 63 61 100 29
Masculinity Uncertainty avoidance 2.68 2.31 1.67 2.34 1.99 2.29
Long-term orientation 1.55 1.60 1.49
3.05 69.66***
1.56 3.50*
2.47 4.55**
Subjects were asked how often they lied about eight specific topics when using online or face-to-face communication (Cornwall & Lundgren, 2001; Whitty, 2002). The questions used a 5-point Likert scale, as follows: 1 = never, 2 = a little, 3 = sometimes, 4 = most of the time, and 5 = always. The relationship between the respondent and the potential target for deception and the sex of the target were both manipulated within the items themselves (e.g., “When communicating with a female family member…”). The topics were: age, gender, where the
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individual lived, education, job, income, personal interests, and physical appearance. Thus, the questions took the following form: When communicating with [another person], have you lied about [topic]… … when communicating face-to-face? … when communicating via computer? The dependent variable used for much of the subsequent data analysis was a tally of the dummy-coded “Yes” responses to each of the eight topics. We refer to the sum total of the tally as the “lying index.” This is equivalent to the “total misrepresentation score” used in similar research (Cornwall & Lundgren, 2001). The lying index score ranged from a minimum of zero (no lying about any of the topics) to eight (every topic has been lied about). Table 4 provides a summary of the six hypotheses that were tested, the measures from the instrument appropriated for the test, and the statistical test that was utilized in each case. Table 4. Summary of Hypotheses and Statistical Tests. Hypothesis
Key Measures
Statistical Tests
H1
Lying Index Score
T-tests
Lying Index Score, Cultural Dimensions, Nationality Lying Index Score, Modality, Cultural Dimensions
Linear Regression, ANOVA, Bonferroni comparisons Regression
Lying Index Score, Sex of Respondent
ANOVA
Lying Index Score, Sex of Respondent
ANOVA
Lying Index Score, Sex of Respondent
ANOVA
H2 H3
H4 H5 H6
Individuals are more likely to lie using computer-mediated communication than to lie face-to-face. Espoused cultural values will affect deceptive behavior. Dimensions of culture will affect online deceptive behavior differently from how they affect face-to-face deceptive behavior. Males are more likely to lie when communicating online than females when communicating online. Individuals are more likely to lie to females than to males when communicating online. Individuals are more likely to lie to strangers than to family members when communicating online.
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4. Results Table 5 displays the descriptive statistics for each topic separated by communication modality. For all but one topic, more lies are reportedly told by the respondents when using CMC than when communicating face-to-face. Income was the exception, and it was the topic most commonly lied about face-to-face. Using two-tailed t-tests, we statistically examined the computed the T-values. Three of the topics are lied about significantly more when communicating via computer, and the overall lying index for CMC was significantly larger than for face-to-face, supporting Hypothesis 1. Table 5: Descriptive statistics for deception items and indices Item/Index
Face-to-Face Online (CMC) Mean S.D. Mean S.D. Age 0.14 0.32 0.21 0.39 Gender 0.05 0.21 0.13 0.29 Where you live 0.19 0.35 0.22 0.38 Education 0.13 0.31 0.16 0.34 Job 0.16 0.33 0.19 0.37 Income 0.21 0.39 0.19 0.39 Interests 0.17 0.37 0.17 0.37 Physical appearance 0.10 0.26 0.17 0.35 Lying index 1.12 1.97 1.40 2.24 NOTE: Values represent the mean number of topics lied about. Overall sample (n=365; df=364) ** significant at the .01 level (2-tailed) *** significant at the .001 level (2-tailed)
t-value 3.62*** 3.49*** 1.13 1.46 1.10 -0.78 0.42 3.07** 3.30***
Hypothesis 2 focused on the differing amounts of deception due to espoused cultural values. To test the hypothesis, we analyzed the overall lie index for all respondents (regardless of their country) using linear regression modeling. The results indicated that only power distance (β=0.19; p
