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Introduction

Items

Almost Daily

About Once a Week

4 to 12 Times a Year

1 to 3 Times a Year

Total

Retail Sector (N = 3,567) Misuse the discount privilege Take store merchandise Get paid for more hours than were worked Purposely underring a purchase Borrow or take money from employer without approval Be reimbursed for more money than spent on business

0.6 0.2 0.2 0.1 0.1

2.4 0.5 0.4 0.3 0.1

11 1.3 1.2 1.1 0.5

14.9 4.6 4 1.7 2

28.9 6.6 5.8 3.2 2.7

expenses Damage merchandise to buy it on discount

0.1 0

0.2 0.1

0.5 0.2

1.3 1

2.1 1.3

0.2 0.1 0.2 0.1

0.8 0.3 0.5 0.1

8.4 1.9 1.6 0.4

17.9 5.5 3.8 4.1

27.3 7.8 6.1 4.7

0.1

0

0.2

0.8

1.1

Involvement

Exhibit 1.3

Hollinger-Clark Property Deviance

Combined Phase I and Phase II Property Deviance Items and Percentage of Reported Involvement, by Sector

Total involved in property deviance

Hospital Sector (N = 4,111) Take hospital supplies (e.g., linens, bandages) Take or use medication intended for patients Get paid for more hours than were worked Take hospital equipment or tools Be reimbursed for more money than spent on business

expenses

35.1

Manufacturing Sector (N = 1,497) Take raw materials used in production Get paid for more hours than were worked Take company tools or equipment Be reimbursed for more money than spent on business

0.1 0.2 0

0.3 0.5 0.1

3.5 2.9 1.1

10.4 5.6 7.5

14.3 9.2 8.7

expenses Take finished products Take precious metals (e.g., platinum, gold)

0.1 0 0.1

0.6 0 0.1

1.4 0.4 0.5

5.6 2.7 1.1

7.7 3.1 1.8

Total involved in property deviance

33.3

Total involved in property deviance

28.4

Source: Adapted from Richard C. Hollinger and John P. Clark, Theft

by Employees (Lexington, KY: Lexington Books, 1983), p. 42.

In order to empirically test whether economics had an effect on the level of theft, the researchers also sorted the data by household income, under the theory that the lower the level of income, the greater the degree of thefts. However, they were unable to confirm such a statistical relationship. This would tend to indicate—at least in this study—that absolute income is not a predictor of employee theft. But they were able to confirm that there was a statistical relationship between a person’s “concern” over his or her financial situation and the level of theft.

Exhibit 1.4 provides a summary of the Hollinger and Clark research with respect to production deviance. Not surprisingly, the most common violations were taking too long for lunch or breaks, with more than half of the employees involved in this activity.37

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