Sensational Offending: An Application of Sensation Seeking to White-Collar and Conventional Crimes

Abstract

A recent trend in the study of crime is to investigate the role of individual differences in predicting offending, particularly in studying the differences between white-collar and conventional offenders. To further this line of inquiry, the current study assessed the role of the psychological trait of sensation seeking on individualistic white-collar crime and conventional crime, and also whether this relationship varied based upon the individual’s level of self-control. Results from a sample of undergraduate students revealed that there are more similarities than differences between these two offense types. Specifically, those with higher degrees of the unsocialized aspect of sensation seeking were more likely to report intentions to engage in both offense forms. Study implications and limitations are presented.

Keywords

personality factors low self-control sensation seeking white-collar crime

Introduction

Criminology has seen an increased interest in the role of individual differences in predicting criminal behavior, including white-collar crime (Blickle, Schlegel, Fassbender, & Klein, 2006; N. L. Piquero, Exum, & Simpson, 2005; Schoepfer, Piquero, & Langton, 2014). This has arisen from research that investigates whether white-collar offenders differ from the more commonly studied street offenders. In general, studies find that some individual differences, such as low self-control (Gottfredson & Hirschi, 1990), are common among both street offenders and some white-collar offenders (Schoepfer et al., 2014). However, scholars have also identified some personality traits that distinguish white-collar from street offenders such as desire for control (Burger & Cooper, 1979; N. L. Piquero, Schoepfer, & Langton, 2010).

One trait that, to our knowledge, is yet to be applied to white-collar offending samples is the psychological trait of sensation seeking (Zuckerman, 1979). This personality characteristic is “defined by the seeking of varied, novel, complex, and intense sensations and experiences, and the willingness to take physical, social, legal, and financial risks for the sake of such experience” (Zuckerman, 1994, p. 27). Although past research has found sensation seeking to be related to antisocial behavior in general (Knust & Stewart, 2002; Zuckerman, 2007), the degree to which it applies to individuals engaging in acts such as embezzlement or fraud is yet to be investigated. We seek to fill this gap for several reasons. First, many of the acts subsumed under the white-collar crime perspective could involve the experience of complex and new sensations and certainly require undertaking legal, social, and financial risks. Thus, this investigation will further our theoretical understanding of white-collar criminals, and determine whether they share this trait with conventional, street offenders. Furthermore, the literature suggests sensation seeking and low self-control (Gottfredson & Hirschi, 1990) are related (Knust & Stewart, 2002), so the joint roles of these individual differences on offending will also be assessed. This study’s findings are meant to have not only theoretical implications but policy implications as well. Specifically, if sensation seeking is found to be related to white-collar offenses, then employers can take steps to identify and train employees who may be at a higher risk for engaging in such offenses than others (see Bechtoldt, Welk, Hartig, & Zapf, 2007). Prior to presenting the results of this study, a discussion of the literature will first be presented, including a description of the sensation-seeking trait, why it is believed to be related to low self-control, and closing with this study’s hypotheses.

Literature Review

Before discussing the role of individual differences in white-collar crime, it is important to offer our definition of this offense type as the literature offers many classifications. This study defines white-collar crime as “illegal or unethical acts that violate fiduciary responsibility or public trust, committed by an individual or an organization, usually during the course of legitimate occupational activity, by persons of high or respectable social status for personal or organizational gain” (Helmkamp, Ball, & Townsend, 1996, p. 351). It is important to keep in mind that white-collar crime can be organized into two categories of offenses: individualistic white-collar crime and corporate white-collar crime (Friedrichs, 2002; N. L. Piquero, Carmichael, & Piquero, 2008). The former indicates offenses committed by an individual that benefit that individual whereas corporate crime (also referred to as organizational white-collar crime) tends to benefit the organization more directly than the individuals committing it. The current study focuses on individualistic white-collar crime though both are deserving of empirical attention.

Individual Differences and White-Collar Crime

Much of the recent research into white-collar crime has focused on the role of individual differences in predicting these offenses and differentiating white-collar from street offenders. Gottfredson and Hirschi’s (1990) concept of low self-control has been used a great deal in both types of these studies. The scholars argue that those with low self-control will be more likely to commit crime and other analogous acts, when given the opportunity, than those with higher self-control. Furthermore, low self-control individuals are said to be risk takers, shortsighted, impulsive, nonverbal, insensitive, and have a preference for physical tasks. Gottfredson and Hirschi argue that low self-control is able to explain all types of crime, including white-collar crime. However, the characteristics used to epitomize those with low self-control do not seem to fit all white-collar offenders as many would need to have a long-term perspective and not give into their impulsive desires to achieve their employed roles. Given this possible contradiction, it is not a surprise that many white-collar crime scholars have applied this particular individual difference to white-collar crimes (Holtfreter, Reisig, Piquero, & Piquero, 2010; Langton, Piquero, & Hollinger, 2006; Seipel & Eifler, 2010; Simpson & Piquero, 2002). As a whole, these studies reported mixed results. Specifically, low self-control has been found to predict individualistic white-collar crimes such as embezzlement (Langton et al., 2006) and fraud (Holtfreter et al., 2010) but has not been found to be associated with corporate crime (Simpson & Piquero, 2002).

These results suggest both similarities and differences between white-collar and street offending. Specifically, individualistic white-collar crime has been found to be predicted by factors similar to street offending whereas corporate offending has not. The current study aims to focus more on the possible similarities between individualistic white-collar crime and street crime by applying the personality trait of sensation seeking to three different offenses: shoplifting, embezzlement, and credit card fraud. As will be discussed, there are both theoretical and empirical reasons to expect this trait to predict these offenses.

Sensation Seeking

The central concept of interest to this study is sensation seeking, a biosocial theory that was originally developed by Zuckerman (1979). Sensation seeking is a psychological characteristic that involves not only seeking new, intense, and complicated experiences and sensations but also accepting the legal, physical, financial, and social risks associated with these experiences (Zuckerman, 1994). It is typically measured with four subscales: Thrill and Adventure Seeking, Experience Seeking, Disinhibition, and Boredom Susceptibility (Knust & Stewart, 2002; Zuckerman, 1974). The first subtrait includes behaviors such as skydiving whereby the individual seeks adventure, or sensation, through socialized but risky and exciting activities. Experience Seeking includes pursuing “sensations through the mind, senses, and a nonconforming lifestyle” (Knust & Stewart, 2002, p. 587) to be excited. Criminologists would be more familiar with the concept of disinhibition, which refers to acts such as substance use and partying. The last subtrait of Boredom Susceptibility refers to a distaste for monotonous situations. Sensation seeking as a whole is a component of an individual’s personality and these four characteristics represent different modes of sensation seeking. In other words, one may be higher on one (i.e., adventure seeking) than on another (i.e., disinhibition).

Although this characteristic has not been used broadly in the field of criminology, it has been used in the psychological research of risk-taking behaviors, including deviance and crime (Knust & Stewart, 2002; Zuckerman, 2007). A notable study was conducted by Steinberg and his colleagues (2008) who examined age differences in impulsivity and sensation seeking through the use of a diverse sample of 10- to 30-year-olds. The results suggested a dual systems model where individuals are more vulnerable to risky behaviors during their teenage years as a result of an increased drive for sensation seeking and an underdeveloped self-regulation system. However, although this explanation provides a logical biosocial explanation for juvenile delinquency and other analogous behaviors, it does not account for adult criminal behavior. Its measures of risky behavior were also limited to non-illegal behaviors.

DeAndrea, Carpenter, Shulman, and Levine (2009) conducted an experiment to investigate the effects of sensation seeking on another act that breaches trust—cheating behavior. The experiment involved the undergraduate participants and an unknown confederate taking a trivia quiz when the trivia master left the room. The answers were in a folder on the desk and the confederate suggested the participant cheat by looking at the answers. The results indicated that high-sensation seekers were more likely to cheat than low-sensation seekers. Although this experiment was unable to measure white-collar offending, cheating on a quiz could be argued to be similar as it does involve a type of fraudulent behavior to achieve personal gain, two aspects shared within the broad definition of white-collar crime. Furthermore, as other research examining sensation seeking’s ability to predict criminal and delinquent behavior has focused on traditional images of criminality such as street crime and substance use, this research provides an opening link to white-collar crime.

Furthermore, the definition of sensation seeking stresses individuals seeking new, intense, and complex experiences that have the possibility of legal and financial risks. Those qualities could fit a business man adding false charges to his expense account to make some extra money just to see if he can get away with it. These factors may also describe a retail employee stealing money from the cash drawer, or an individual committing an elaborate Ponzi scheme that requires complex planning and intense pressure. The white-collar offenses included in the current study include embezzlement and credit card fraud. Both of these offenses certainly carry with them the possibility of risk. For instance, employees stealing money from their employer are risking not only legal complications but also most certainly their employment status and future prospects if they were caught. In addition, stealing a roommate’s credit card presents not only a legal punishment but also an interpersonal cost if caught.

These offenses could also be construed as acts entailing new, complex, and intense experiences. For example, the credit card fraud scenario used in this study involves an individual claiming to be her roommate, a fraudulent behavior that many may perceive to be a high-pressure event. Likewise, this study’s embezzlement scenario of an employee stealing money from an employer could also be seen in a similar light. As such, the empirical validity of sensation seeking on white-collar crime appears to be an open empirical question.

Some may have noticed that some of sensation seeking’s subtraits are similar to low self-control. Recall that sensation seeking is argued to have four subtraits: Thrill and Adventure Seeking, Experience Seeking, Disinhibition, and Boredom Susceptibility. Prior research has categorized these subtraits into two groups—socialized sensation seeking (SSS) and unsocialized sensation seeking (USS; Knust & Stewart, 2002). Thrill and Adventure Seeking has been reported to compose the SSS category whereas the remaining three are categorized under the unsocialized group (Goma, 1995). This latter grouping has been found to be correlated to impulsivity (Knust & Stewart, 2002). As impulsivity is one of the characteristics of low self-control (Gottfredson & Hirschi, 1990), perhaps an individual’s self-control correlates with his or her level of USS. Thus, it is believed that the interaction of these characteristics will lead to an increased likelihood of committing both individualistic white-collar crime and street crime relative to those who do not have either of these characteristics.

Hypotheses

The discussion above brought us to draw several hypotheses from the prior literature. These are as follows:

Hypothesis 1: Those scoring higher on the USS trait will be more likely to report intentions to engage in embezzlement, shoplifting, and credit card fraud than those scoring lower. SSS will not have an effect on intentions to offend.

Hypothesis 2: Low self-control will be positively correlated with USS but not SSS.

Hypothesis 3: The interaction of low self-control and USS will increase the likelihood of reporting intentions to engage in embezzlement, credit card fraud, and shoplifting, relative to the effects of either of these characteristics independently.

Method

Sampling

The data used to investigate the relationship of sensation seeking and low self-control on offending are from a vignette study, a method common in the study of white-collar crime (Piquero, Schoepfer, & Langtron, 2010; Simpson & Piquero, 2002; Simpson, Paternoster, & Piquero, 1998). Upon receiving approval from the university’s institutional review board (IRB) in the spring of 2014, 10 lower level and general education social science undergraduate classes at a midsize university in a large southern state were asked to participate in a voluntary survey. The total number of surveys collected was 298 for a response rate of 54%. Three different vignettes were included in the survey, describing one minor property crime and two white-collar crimes. These vignettes described an individual engaging in minor shoplifting, participating in credit card fraud of US$30, and engaging in embezzlement of US$250. These particular scenarios were chosen as they seem to be realistic for our sample of young adults and they have successfully been used in prior studies (Holtfreter et al., 2010; Schoepfer et al., 2014). After reading each scenario, the respondents indicated the likelihood they would participate in the crime. The participants next responded to several personality scales, including the Brief Sensation Seeking Scale (BSSS; Hoyle, Stephenson, Palmgreen, Lorch, & Donohew, 2002) and the Grasmick, Tittle, Bursik, and Arneklev (1993) Low Self-Control Scale. Finally, several demographic variables were included as well.

Measurement

Dependent variables

After each vignette, the respondents indicated the chance that they would behave as the individual in the scenario did. The dependent variables denote the respondent’s reported intentions to engage in shoplifting, credit card fraud, and embezzlement. The response scale ranged from “0” indicating not at all to “10” indicating a great deal.

Independent variables

Our two independent variables of interest were the personality traits of self-control and sensation seeking. To compare our results with those of other white-collar crime studies (Piquero, Schoepfer, & Langton, 2010; Schoepfer et al., 2014), Grasmick et al.’s (1993) 24-item attitudinal scale was used to measure the respondents’ self-control. The scale responses ranged from “1” indicating strongly disagree to “4” indicating strongly agree. Those who scored higher on the scale had lower self-control relative to those scoring lower. The scale was found to have good internal consistency (α = .81; Cronbach, 1951).

Our sensation seeking measure comes from the BSSS (Hoyle et al., 2002). The BSSS contained eight items and were scored on a Likert-type scale where responses ranged from “1” (strongly disagree) to “5” (strongly agree). Those who scored higher on this scale have relatively more sensation seeking than those who score lower. The BSSS was found to have good internal consistency (α = .74; Cronbach, 1951). The BSSS also measures the four subtraits of sensation seeking with two items pertaining to each subtrait: Experience Seeking, Boredom Susceptibility, Thrill and Adventure Seeking, and Disinhibition. As Experience Seeking, Boredom Susceptibility, and Disinhibition are said to compose USS, and Thrill and Adventure Seeking is said to be the SSS, two other scales were created representing this division. The internal consistency scores for both the USS and SSS were found to be adequate (α = .66, α = .64, respectively).

Control variables

To account for the respondents’ demographics, four control variables were included in this study. The respondent’s sex was coded dichotomously, where “0” indicated female and “1” indicated male. Age was coded continuously. Race was also controlled for where “1” indicated White and “0” indicated non-White. Finally, we also controlled for those in a committed relationship. Those who were single, separated, or divorced were coded as “0,” and those who were in a relationship or married were coded as “1.”

Analyses

The analyses were conducted in a series of related steps. The bivariate correlations of all variables were examined first to better understand the relations between the variables and also to check for multicollinearity. We next estimated a series of left-censored Tobit regressions for each outcome (Tobin, 1958). This estimation method was chosen as it not only retains the original response distribution but also accounts for the offending intentions measures’ skewed distributions. First, we looked at the separate effects of the control variables on willingness to engage in embezzlement, credit card fraud, and shoplifting. Next, we examined the effect of the control variables and sensation seeking on intentions to offend. This included two separate analyses. The first estimated the effects of the full BSSS on offending intentions. The second analysis separated the BSSS into the USS and SSS to differentiate the effects of unsocialized and socialized sensation seeking on offending intentions. The next set of analyses examined the separate effects of the USS, SSS, and low self-control scales on intentions to offend. Finally, we examined a full model to assess the effects of the independent and interactive effects of sensation seeking and low self-control on offending intentions. After first standardizing the two variables, an interaction was created between USS and the low self-control measure. This interaction variable was included in the final model.

Results

Descriptive Statistics

Table 1 presents the descriptive statistics for the variables in the current analyses.¹ The mean score for intentions to engage in embezzlement was 1.21 whereas the mean score for credit card fraud intentions was 1.40. The mean score for intentions to engage in shoplifting was 2.01. The average score on the Grasmick et al. (1993) Low Self-Control Scale was 50.67, and the average sensation seeking score was 25.12. The average USS score was 18.86 whereas the mean SSS score was 6.21. Forty-four percent of the sample was male, and the average age was a little over 22 years. Half of the sample (50%) was White, and 32% of the sample reported they were either married or in a relationship.

Table 1.

Descriptive Statistics.

Variable	M	SD	Range	n
Embezzlement intentions	1.21	—	0-10	284
Credit card fraud intentions	1.40	—	0-10	283
Shoplifting Intentions	2.01	—	0-10	284
Personality traits
Low Self-control	50.67	9.65	28-76	275
Sensation seeking	25.12	6.18	8-40	283
Unsocialized sensation seeking	18.86	4.58	6-30	284
Socialized sensation seeking	6.21	2.47	2-10	284
Controls
Male	0.44	—	0-1	277
Age	22.32	4.03	18-37	276
White	0.50	—	0-1	286
Relationship	0.32	—	0-1	286

Bivariate Correlations

The bivariate correlations between the variables of interest are depicted in Table 2. Of special interest is the significant and positive moderate correlation between sensation seeking and low self-control (r = .44). There is also a positive and significant correlation between the willingness to engage in embezzlement and credit card fraud (r = .38). There is also a positive and significant relationship between willingness to engage in credit card fraud and shoplifting (r = .25). The relationship between intentions to engage in shoplifting and embezzlement is also positive and significant (.44). Low self-control has a positive and significant correlation with each of the dependent variables whereas sensation seeking has a significant and positive correlation only with shoplifting (r = .25). The only scenario where any of the sensation-seeking subtraits were significantly correlated with was shoplifting (.30). Hypothesis 2 was partially supported; low self-control was positively and significantly correlated with both USS (.44) and SSS (.31).

Table 2.

Bivariate Correlations Between All Variables.

Variable	1	2	3	4	5	6	7	8	9	10	11
Embezzlement	1.00
Credit card fraud	.38*	1.00
Shoplifting	.44*	.25*	1.00
Low self-control	.23*	.20*	.33*	1.00
Sensation seeking	.05	.08	.25*	.44*	1.00
Unsocialized sensation seeking	.09	.11	.30*	.44*	.94*	1.00
Socialized sensation seeking	−.05	.00	.07	.31*	.77*	.50*	1.00
Male	.07	.12	−.01	.11	.12*	.05	.19*	1.00
Age	−.18*	.03	−.13*	−.19*	−.00	−.02	.02	.09	1.00
White	−.17*	−.09	−.11	−.12*	−.05	.05	.05	.02	−.10	1.00
Relationship	−.13*	−.06	−.05	−.11	−.00	.01	−.01	−.12	.32*	.10	1.00

p < .05.

Effects of Control Variables on Intentions to Offend

Table 3 presents the results of the effects of the control variables on intentions to engage in embezzlement, credit card fraud, and shoplifting. As seen in the first model, males were marginally more likely to report intentions to engage in embezzlement than females (B = 0.96). Younger respondents (B = −0.22) and non-White respondents (B = −1.53) were significantly more likely to report embezzlement intentions than those who were older and White. Model 2 indicates none of the control variables were significant in predicting intentions to engage in credit card fraud. Model 3 demonstrates that younger respondents were more likely to report intentions to engage in shoplifting than those who were older (B = 0.22).

Table 3.

Tobit Regressions Predicting Intentions to Offend: Control Variables.

	Embezzlement		Credit card fraud		Shoplifting
Variable	Coefficient	SE	Coefficient	SE	Coefficient	SE
Male	0.96^†	.54	0.75	.65	−0.07	.69
Age	−0.22**	.07	0.04	.08	−0.22*	.09
White	−1.53**	.53	−0.71	.64	−1.04	.68
Relationship	−0.61	.60	−0.16	.72	0.21	.76
Constant	4.70**	1.57	−1.90	1.80	5.21*	2.00
Pseudo R²	.031		.004		.009
n	274		273		274

†

p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed).

Effects of Sensation Seeking on Intentions to Offend

The next set of models presented in Table 4 estimated the effects of sensation seeking along with the control variables on the offending scenarios. Younger (B = −0.21) and non-White (B = −1.58) respondents were significantly more likely to report intentions to engage in embezzlement than those who were older and White (Model 1). Males were also marginally more likely to report intentions to engage in embezzlement than females (B = 0.90). The next model demonstrates none of the included variables were significant in predicting intentions to engage in credit card fraud. The final model indicates those with higher levels of sensation seeking were significantly more likely to engage in shoplifting than those with lower sensation seeking (B = 0.26). Furthermore, younger respondents (B = −0.20) were significantly more likely to report shoplifting intentions, and non-White respondents (B = −1.27) were marginally more likely to report shoplifting intentions than their counterparts.

Table 4.

Tobit Regressions Predicting Intentions to Offend: Sensation Seeking.

	Embezzlement		Credit card fraud		Shoplifting
Variable	Coefficient	SE	Coefficient	SE	Coefficient	SE
Sensation seeking	0.05	.04	0.05	.05	0.26***	.06
Male	0.90^†	.54	0.66	.65	−0.46	.66
Age	−0.21**	.07	0.06	.08	−0.20*	.09
White	−1.58**	.53	−0.76	.63	−1.27^†	.65
Relationship	−0.67	.60	−0.24	.72	0.10	.73
Constant	3.32^†	1.90	−3.43	2.24	−1.36	2.35
Pseudo R²	.032		.005		.030
n	272		271		272

†

p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed).

Next, the sensation seeking scale was separated into its two components, and the effects of both unsocialized and socialized sensation seeking were assessed on intentions to offend. These results are presented in Table 5. As can be seen in Model 1, individuals with higher degrees of USS were significantly more likely to report embezzlement intentions than those with lower degrees (B = 0.20). Those with higher degrees of SSS were significantly less likely to report such intentions (B = −0.32). Furthermore, males (B = 1.16), younger respondents (B = −0.20), and non-White respondents (B = −1.58) were more likely to report intentions to engage in embezzlement than their counterparts.

Table 5.

Tobit Regressions Predicting Intentions to Offend: Unsocialized and Socialized Sensation Seeking.

	Embezzlement		Credit card fraud		Shoplifting
Variable	Coefficient	SE	Coefficient	SE	Coefficient	SE
Unsocialized sensation seeking	0.20**	.07	0.16^†	.08	0.45***	.08
Socialized sensation seeking	−0.32*	.13	−0.19	.15	−0.18	.15
Male	1.16*	.54	0.80	.65	−0.21	.65
Age	−0.20**	.07	0.06	.08	−0.18*	.09
White	−1.58**	.53	−0.73	.63	−1.23^†	.63
Relationship	−0.67	.59	−0.27	.71	0.09	.71
Constant	2.33	1.89	−3.98	2.24	−2.55	2.33
Pseudo R²	.043		.009		.039
n	272		271		272

†

p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed).

Model 2 indicates that USS was a marginal, positive predictor of intentions to engage in credit card fraud (B = 0.16). In Model 3, USS is a significant, positive predictor of reporting shoplifting intentions (B = 0.45). Age is a significant, negative predictor (B = −0.18) whereas non-White respondents were marginally more likely to report intentions to engage in shoplifting (B = −1.23).

Effects of Sensation Seeking and Low Self-Control on Intentions to Offend

Table 6 presents the results of the Tobit regressions predicting the effects of USS, SSS, and low self-control on intentions to engage in embezzlement, credit card fraud, and shoplifting. The first model shows USS (B = 0.14) and low self-control (B = 0.07) were both significant and positive predictors of intentions to engage in embezzlement. Those with higher degrees of USS were less likely to report intentions (B = −0.31), and male respondents were marginally more likely to report such intentions than females (B = 1.03). Younger (B = −0.15) and non-White respondents (B = −1.39) were significantly more likely to report intentions to engage in embezzlement.

Table 6.

Tobit Regressions Predicting Intentions to Offend: Unsocialized Sensation Seeking, Socialized Sensation Seeking, and Low Self-Control.

	Embezzlement		Credit card fraud		Shoplifting
Variable	Coefficient	SE	Coefficient	SE	Coefficient	SE
Unsocialized sensation seeking	0.14*	.07	0.09	.08	0.35***	.09
Socialized sensation seeking	−0.31*	.13	−0.20	.15	−0.19	.15
Low self-control	0.07*	.03	0.07^†	.04	0.11**	.04
Male	1.03^†	.54	0.70	.65	−0.69	.64
Age	−0.15*	.07	0.09	.08	−0.13	.08
White	−1.39**	.53	−0.87	.63	−1.07^†	.63
Relationship	−0.50	.58	−0.15	.70	0.20	.69
Constant	−1.11	2.32	−6.80*	2.74	−7.12*	2.78
Pseudo R²	.047		.015		.051
n	262		261		262

†

p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed).

The second model indicates low self-control was a marginal predictor of intentions to engage in credit card fraud (B = 0.07), and no other variables were significant in this model. The third model demonstrates USS (B = 0.35) and low self-control (B = 0.11) were both positive, significant predictors of intentions to engage in shoplifting. Non-White respondents were marginally more likely to report such intentions (B = −1.07).

The next set of Tobit regressions estimated the impact of the interaction between USS and low self-control on the three offending scenarios. These results are seen in Table 7. The first model indicates that although each of the three individual differences was a significant predictor of intentions to engage in embezzlement, the interaction variable was not a significant predictor. Specifically, USS (B = 0.14) and low self-control (B = 0.07) were both positive, significant predictors whereas SSS was a negative, significant predictor (B = −0.31). Males (B = 1.03) were marginally more likely to report embezzlement intentions whereas younger and non-White respondents were significantly more likely to report such intentions (B = −0.15; B = −1.39; respectively).

Table 7.

Tobit Regressions Predicting Intentions to Offend: Unsocialized Sensation Seeking and Low Self-Control Interaction.

	Embezzlement		Credit card fraud		Shoplifting
Variable	Coefficient	SE	Coefficient	SE	Coefficient	SE
Unsocialized sensation seeking	0.14*	.07	0.11	.09	0.37***	.09
Socialized sensation seeking	−0.31*	.13	−0.21	.15	−0.19	.15
Low self-control	0.07*	.03	0.07^†	.04	0.11**	.04
Interaction between USS and low self-control	−0.00	.26	−0.25	.33	−0.25	.33
Male	1.03^†	.54	0.69	.65	−0.70	.65
Age	−0.15*	.07	0.08	.08	−0.14	.09
White	−1.39**	.53	−0.85	.63	−1.06^†	.63
Relationship	−0.50	.59	−0.17	.70	0.18	.69
Constant	−1.11	2.32	−6.89*	2.75	−7.29*	2.81
Pseudo R²	.047		.015		.052
n	262		261		262

†

p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed).

Model 2 presents the results for intentions to engage in credit card fraud. Low self-control emerged as a marginal predictor (B = 0.07). However, the interaction variable was not significant. The third and final model indicates that those individuals with high degrees of USS (B = 0.37) and those with lower self-control (B = 0.11) were significantly more likely to report intentions to engage in shoplifting than their counterparts. Non-Whites were marginally more likely to report such intentions (B = −1.06). Similar to the prior two models, the interaction variable between USS and low self-control did not emerge as a significant predictor of intentions to offend.

Discussion and Conclusion

There has been increased attention recently to the similarities and differences between white-collar and street offenders (Blickle et al., 2006; N. L. Piquero, Schoepfer, & Langton, 2005; Schoepfer et al., 2014). One line of this research has focused particularly on the role of individual differences in distinguishing these two offending groups. For instance, Schoepfer and her colleagues (2014) recently found that desire for control predicted corporate white-collar crime, low self-control predicted street offending, and these two variables interacted to predict individualistic white-collar crime. The current study sought to further this branch of inquiry by investigating how sensation seeking (Zuckerman, 1979), a psychological trait that has been found to be associated with general deviance and antisocial behavior (Knust & Stewart, 2002; Steinberg et al., 2008), predicts two individualistic white-collar offenses and one street offense. Furthermore, as one component of this trait, unsocialized sensation seeking (USS), has been found to be correlated with impulsivity, the interaction of USS and low self-control (Gottfredson & Hirschi, 1990) was also assessed.

Using a scenario-based design, the results offered mixed support for our hypotheses. Our first hypothesis, that USS would be a positive predictor of intentions to engage in shoplifting, embezzlement, and credit card fraud but socialized sensation seeking (SSS) would not, was supported. Specifically, USS was found to have a positive, significant effect on both embezzlement and shoplifting and a positive, marginally significant effect on credit card fraud. Interestingly, the other component of sensation seeking, the socialized aspect, was found to have a protective effect on embezzlement. In other words, those with higher levels of SSS were less likely to report intentions to engage in embezzlement. This suggests that those who seek adventure and sensation from risky but prosocial activities are less likely to embezzle from their employees. This relationship though did not hold for the other two offending scenarios.

The second hypothesis, that low self-control (Gottfredson & Hirschi, 1990) would be positively correlated with USS but not SSS, was only partially supported. Low self-control was found to be positively correlated with both subtraits of sensation seeking, though the correlation between USS and low self-control (.44) was slightly larger than that between SSS and low self-control (.31). Thus, even though the unsocialized component of sensation seeking contains the element of impulsivity, low self-control and the prosocial component of sensation seeking are positively related. This is perhaps not too surprising given that both involve a risk-taking component. Those with lower self-control are more apt to engage in risky behaviors, regardless of whether those acts are prosocial or not. Perhaps it is their overlap, engaging in risky but prosocial behaviors, that is driving the positive relationship between SSS and low self-control.

The final hypothesis predicted that the interaction between low self-control and USS would increase the respondent’s intentions to engage in each of the three scenarios while controlling for the independent effects of both low self-control and USS. This hypothesis was not supported. In each of the three offending scenarios, the interaction variable was not significant in predicting any of the outcomes, though with the exception of credit card fraud, both USS and low self-control were found to independently predict intentions to offend. These results suggest that despite the fact that both these traits share a preference for risk taking, they do not interact with one another in such a way that increases the prevalence of antisocial behavior over the independent effects of each.

In sum, these findings serve to extend our knowledge on the role of individual differences in predicting both street and individualistic white-collar offending. Specifically, we found that there are more similarities than differences in the relationship between sensation seeking and each of these offenses. USS was found to increase the likelihood of all three of the measured offenses, particularly for embezzlement and shoplifting. Thus, it appears the drive to seek new, novel experiences and a nonconforming lifestyle leads individuals to be willing to engage in offenses that benefit them, whether that be through stealing from their employer or stealing from a store. These effects still remained upon the introduction of low self-control (Gottfredson & Hirschi, 1990), a consistent predictor of antisocial behavior (Pratt & Cullen, 2000). This demonstrates not only that USS is an important predictor of both individualistic white-collar and street crime but also that it operates independently of low self-control.

One interesting difference that did emerge was that SSS was found to be protective of embezzlement. In other words, those who were more likely to pursue exciting, prosocial activities were less likely to report embezzlement intentions. However, this result did not hold for either credit card fraud or shoplifting. It was hypothesized that SSS would have a null effect on offending, so this result was unexpected.

These findings should be considered in accordance with the study’s limitations. First, the sample was composed of a convenience sample of undergraduate students taking social science courses, limiting its generalizability. Nonetheless, this study was exploratory as sensation seeking had not yet been applied to the study of white-collar crime. It is also common to use student samples to assess how individual differences affect offending behavior (Payne & Chappell, 2008). A goal for future research would be to use different sampling strategies to assess the generalizability of these findings.

Another limitation includes that the vignette method utilized here only measures intentions to offend, instead of actual offending. That said, the large majority of the respondents found the scenarios to be realistic (between 89% and 95%), and prior research has also reported a strong correlation between actual behavior and reported intentions (Green, 1988; Kim & Hunter, 1993). Similarly, as one reviewer pointed out, the scenarios may involve several other variables, such as the need for money to buy food or pay for college registration that may affect the results of this study. Although this is a factor to be considered, it is important to note that other studies have used similar scenarios in their study of individual differences across offending types (Holtfreter et al., 2010; Schoepfer et al., 2014). An additional limitation is that this study only measured intentions to engage in two forms of individualistic white-collar crime and one form of street crime. This excluded a wide variety of other crimes, including corporate crime, leaving it an open question of how much sensation seeking applies to organizational white-collar crime. Future research should extend this line of inquiry and investigate the effects of sensation seeking on other forms of white-collar crime, such as corporate fraud, for example.

Finally, although the self-control measure utilized in this study was selected to compare results with other studies that have assessed the role of self-control on white-collar offending (Piquero, Schoepfer, & Langton, 2010; Schoepfer et al., 2014), the measure itself has been questioned regarding its validity (A. R. Piquero, MacIntosh, & Hickman, 2000). Extensions of this research should thus utilize other measures of self-control, such as behavioral measures, to evaluate the robustness of these results (see Simpson & Piquero, 2002).

Despite these limitations, this study extended our theoretical understanding of individualistic white-collar offenders by indicating they are more similar than different from conventional offenders, at least with respect to sensation seeking and low self-control. Regardless of the location of the offense (i.e., on the street or in a workplace) or the victim (a stranger as opposed to an employer or friend), individuals with greater USS and those with lower self-control are more likely to engage in acts that benefit themselves than their counterparts.

These findings’ implications extend into the policy arena as well. First, this study offers further empirical support for programs that serve to increase adolescents’ self-control (A. R. Piquero, Jennings, & Farrington, 2010). Recall that USS and low self-control have the trait of impulsivity in common. Thus, efforts to teach individuals restraint and the ability to control their impulses may serve to decrease not only conventional crime but individualistic white-collar crime as well. In addition, as Bechtoldt and her colleagues (2007) pointed out, employers can also screen current and prospective employees for these tendencies. Upon identifying those with lower self-control or heightened USS, specialized training can be geared toward these employees to prevent individualistic white-collar offenses from happening within the workplace.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Jessica M. Craig is an assistant professor of criminal justice at the University of North Texas. Her research interests include criminological theory, life course criminology, and white-collar offending. Some of her recent work can be seen in Criminal Behaviour and Mental Health, Crime & Delinquency, and Journal of Criminal Justice.

Nicole Leeper Piquero is the Robert Holmes professor of Criminology and associate provost at the University of Texas at Dallas. She received her PhD in Criminology and Criminal Justice from the University of Maryland. Her research focus includes the study of white-collar and corporate crimes, criminological theory, as well as gender and crime. She currently serves as the First vice president (2015-2016) for the Academy of Criminal Justice Sciences (ACJS) and has also served as secretary (2008-2010), as a trustee-at-large (2010-2013), and as second vice president (2015-2016). She was the recipient of the 2008 National White Collar Crime Research Consortium Young Career Award and the 2011 Outstanding Publication Award, has been recognized as an “academic star” (in 2007 and 2011), and was recognized as Teacher of the Year (2005-2006) from the University of Florida’s College of Arts and Sciences. She also has served and as editor of the Journal of Drug Issues from 2009-2012.

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