Employee Theft

Employee theft refers to the wrongful taking of money, goods, or property by an organization member. The target is most commonly the organization itself, but the definition would also encompass stealing from coworkers or customers. The psychological literature on employee theft focuses on money and physical goods, although the definition would also encompass intellectual property.

Theft is one example of a broader phenomenon, commonly known as counterproductive work behavior (CWB). Counterproductive work behavior includes any intentional behavior by an organization member that is viewed by the organization as contrary to its legitimate interests. Theft, sabotage, misuse of time and resources, unsafe behavior, drug and alcohol use at work, physical violence, and sexual harassment are all examples of CWB. After a long history of examining each of these separately, recent research documents a consistent pattern of positive correlations among CWB. Thus there is value in examining common antecedents and common interventions; for example, tests designed to predict theft have been found to also predict a range of CWB.

Measurement of Employee Theft

Perhaps the most critical feature of employee theft is that it is difficult to detect. It is clearly undertaken by employees with the intent of going undetected and thus stands in contrast with most other organizational phenomena of interest to the industrial/organizational psychologist. This problem of detection has widespread implications for research and practice. One issue is that it makes it difficult to even document the extent of the problem. The proportion of employees caught stealing is generally very small. For example, a common strategy for test validation is to test applicants, put them on the job, measure the behavioral outcome of interest, and then examine the relationship between test scores and outcomes. When this is done with theft as the outcome of interest, rates of detected theft over the first year of employment among typical populations (e.g., entry-level retail workers) are in the 1% to 3% range. Although there is general agreement that some theft goes undetected, there is no agreement as to the proportion. Published estimates of the extent and cost of the employee theft problem reflect untested assumptions about the rate of undetected theft.

A second implication of the difficulty-of-detection problem is that it makes research on employee theft hard to interpret. For example, in trying to document psychological characteristics of employee thieves, one faces the question of whether detected thieves constitute a random sample of all thieves, or whether those caught are different in important ways from those who steal and are not caught. Organizations using selection systems, for example, hope to screen out individuals prone to theft, not merely those prone to get caught while stealing. Another research implication is that the statistical tools used to examine the relationship between psychological variables and employee theft (e.g., the correlation coefficient) cannot be interpreted in the normal manner when a variable under study is highly skewed. The maximum value of a correlation drops as the proportion caught/not caught stealing departs from 50%. At a 98%-to-2% split, the maximum possible correlation is .39, rather than the expected 1.0, and thus correlations with theft need to be interpreted relative to this maximum value.

There are two common alternatives to reliance on detected theft in studying employee theft. The first is the use of self-report. Such measures are approximations to the true state of affairs, as respondents may perceive themselves to be at risk in admitting theft, even in situations in which anonymity is assured. Some settings are more conducive to accurate responding than others: An anonymous survey conducted by a university-based researcher is likely to be viewed differently than a survey conducted by one’s current employer. A useful recent development is the use of techniques for ensuring anonymity, known as randomized response techniques.

The second alternative to detected theft measures is the use of aggregate measures, such as store-level sales, inventory valuation, or unaccounted losses (commonly known as shrinkage). Using time-series designs, monthly financial measures are tracked as a theft intervention is implemented. Such designs require the inference that change is caused by theft reduction, and thus care must be taken to ensure that the theft intervention is not confounded with other changes.

Antecedents of Employee Theft

Antecedents of employee theft can be grouped into two main categories: person and situation antecedents. Although these categories reflect different perspectives, they are not necessarily in opposition. That is, situational characteristics, such as strong norms regarding theft or tight surveillance of employees, will probably affect the likelihood of theft. At the same time, regardless of the strength of any situation, employees will differ in their beliefs about the consequences of theft, the desirability of those consequences, the existence of norms about theft, and motivation to comply with perceived norms. So, within the same situation, individual differences will cause some employees to be more prone to steal than others. Therefore, to fully understand what causes theft, the optimal approach is one recognizing the interaction between person and situation variables. Keeping this in mind, it is still useful to understand the person and situation variables that covary with theft. The most widely cited research findings relating to the two broad categories are outlined below.

Person Antecedents

The most common within-person approach to prediction of theft is that of measuring individual differences in integrity. Integrity is best conceptualized as a compound trait mostly reflecting the Big Five personality traits of conscientiousness, agreeableness, and emotional stability. Integrity is typically measured via commercially marketed self-report instruments called integrity tests that contain items dealing either with admissions of theft and attitudes toward theft, or more personality-like constructs such as dependability, conscientiousness, social conformity, thrill seeking, trouble with authority, and hostility. A long line of criterion-related validity evidence, including extensive meta-analyses, supports the use of integrity tests for predicting theft.

Various demographic factors have also been shown to covary with theft. For instance, employees who are young; new to their jobs; work part-time; have low-paying, low-status positions; or abuse drugs or alcohol are more likely to steal. It is difficult to interpret such demographic factors, though. For instance, are younger employees more likely to steal because of their youth, or because they may hold less satisfying jobs?

Situation Antecedents

The most commonly cited situational antecedents of theft are organizational justice, organizational culture and norms, and control systems. In terms of organizational justice, there is considerable evidence demonstrating that employees are more likely to steal when there is inequitable distribution of rewards or punishments, formal procedures are unfair, or interpersonal treatment is poor. Concerning organizational culture and norms, research has shown that things such as strong company codes of ethics, average honesty level in the organization or work group, punitiveness of an organization toward theft, and informal understandings about acceptability of theft among work-group members are related to the occurrence of theft. Finally, concerning control systems (physical or procedural entities within the workplace, meant specifically to diminish theft occurrence through providing alternatives to, increasing the risk of, or increasing penalties for theft), despite the intuitive appeal of their relationship with theft, there is little empirical evidence for their effectiveness. As the opportunity to steal is reduced, though, some effect on the occurrence of theft should be expected.

Employee Theft Interventions

Given that employee theft is caused by person and situation variables, it follows that two ways to reduce theft are to change the persons or change the situation.

Person-Oriented Interventions

The first way to attempt to reduce theft by changing the employees is to change the types of persons that are hired. That is, selection systems can be designed to select applicants with traits that covary with reduced likelihood of theft. Given the relationship between integrity test scores and theft, an organization wishing to reduce theft could hire employees based on their integrity test scores. This would create a workforce predisposed to integrity and would likely result in an organizational culture and norms of integrity.

The second way to attempt to reduce theft by changing the employees is through training and development. Ethics programs are probably the most common form of such training. Ethics programs are designed to create organizational cultures that sensitize employees to behaviors considered inappropriate (such as theft) and to discourage employees from engaging in them. The content of ethics programs generally varies, but training programs designed to help employees understand ethical issues are common. There is very little empirical evidence that ethics programs reduce the incidence of theft, but preliminary evidence has been supportive.

Situation-Oriented Interventions

Another way in which to reduce the likelihood of theft is to change the situation in ways known to covary with the incidence of theft. Person-oriented ethics training, as discussed above, is commonly accompanied by situation-oriented features, such as formal codes of ethics, ethics committees, disciplinary practices, violation-reporting mechanisms, and ethics officers. These ethics programs are one form of control system; other types of control systems aimed at theft reduction include security systems (e.g., audits, surveillance); environmental design; posting signs reporting the amount missing or stolen in the past week; rewarding whistleblowers; and providing employees the opportunity to take merchandise that is dated or partially damaged or cannot be sold. There is little empirical evidence of the effectiveness of such control systems. Finally, because employee perceptions of injustice affect the likelihood of theft, interventions aimed to decrease injustice perceptions may have some effect on theft. Organizational justice perceptions can be broken down into three areas: distributive, procedural, and interpersonal justice. If distributive justice is suspected to be a cause of theft, the organization may address whether the allocation of rewards and punishments is equitable. If procedural justice is a concern, the organization may consider if changing the unfair procedure would have an effect on theft. If interpersonal justice is a cause of theft, attempting to create more positive interactions with employees may be an effective theft intervention.

References:

  1. Greenberg, J. (1990). Employee theft as a reaction to underpayment inequity: The hidden cost of pay cuts. Journal of Applied Psychology, 75, 561-568.
  2. Hollinger, R. C., & Clark, J. P. (1983). Theft by employees. Lexington, MA: D. C. Heath. Theory of Action 803
  3. Murphy, K. R. (1993). Honesty in the workplace. Belmont, CA: Brooks/Cole.
  4. Sackett, P. R., & DeVore, C. J. (2001). Counterproductive behaviors at work. In N. Anderson, D. Ones, H. Sinangil, & C.Viswesvaran (Eds.), International handbook of work psychology. Thousand Oaks, CA: Sage.
  5. Sackett, P. R., & Wanek, J. E. (1996). New developments in the use of measures of honesty, integrity, conscientiousness, dependability, trustworthiness, and reliability for personnel selection. Personnel Psychology, 47, 787-829.

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