| EVALUATION OF SHOPLIFTERS |
The 2001 National Retail Security Survey reports that losses from shoplifting have reached record levels. The study, conducted by the University of Florida, discovered that retail security managers attributed 30.6 percent of retail losses to the thefts of shoplifters.
Shoplifting costs U.S. retailers $10 billion annually. Employee theft and shoplifting combined account for the largest source of property crime committed annually in the United States. This percentage of loss is estimated to be over $32 billion. This study concludes "that the single largest category of larceny in the United States is the crime that occurs in retail stores." This figure is larger than motor vehicle theft, bank robbery and household burglary combined.
"Theft Talk" surveyed schools regarding student theft. "Theft Talk" questioned 13,213 youths and found 18% of 7th graders admitted to stealing within the last year. For 8th graders, the figure jumps to 26% who admit to stealing within the past year. And, independent studies show that youths between the ages of 14 and 17 that have been caught shoplifting have a 50% chance of re-offending within one year.
The most primitive assessment procedures in the field of shoplifting rely solely upon criminal history. This kind of information is readily available to law enforcement and justice officials. On the surface, it seems reasonable to assume that a person convicted of shoplifting has a higher probability than the average person of being again convicted of shoplifting. But, that is not necessarily the case. By itself, a shoplifting conviction does not necessarily increase the accuracy of predicting another shoplifting theft in the future.
Multiple regression analysis determines the best combination of predictor variables in a predictor equation. Multiple regression is a statistical procedure that combines predictor variables in an equation to predict a target variable like shoplifting. Predictor equations do not rely upon criminal history. Predictor equations are composed of predictor variables that have been demonstrated to contribute substantially to the prediction.
There are three types of predictor variables: demographics like age and education, criminal history like age at first arrest, number of times placed on probation and substance abuse-related arrests and criminogenic needs. Criminogenic needs are variables that are capable of change and that contribute to inappropriate behavior, negativistic attitudes and recidivism (Andres, Bonta & Hoge, 1990). These criminogenic variables include substance (alcohol and other drugs) abuse, antisocial thinking, impulsiveness, self-esteem, peer-pressure, vulnerability, entitlement attitudes and judgment. Gendreau (1994) notes that measurement of these dynamic variables is important for positive behavioral change.
With regard to the Shoplifting Inventory (SI), its criminogenic needs include: Shoplifting, Entitlement, Peer Pressure, Self-Esteem, Impulsiveness, Antisocial Thoughts and Substance (alcohol and other illicit drugs) Abuse. It is not by chance that these criminogenic needs represent the Shoplifting Inventory (SI) scales or measures.
References
Andrews, D., Bonta, J. & Hoge, R. (1990). Classification for effective rehabilitation: Rediscovering Psychology. Criminal Justice and Behavior 17, 19 – 52. This article outlines risk, responsivity and criminogenic needs classification.
Gendreau, P. (1994). "Principles of Effective Intervention." In Restructuring Intensive Supervision Programs: Applying "What Works." Lexington, KY: American Probation and Parole Association.