Job Perceptions of Citizenship Behavior and Deviance: Musings from Behind the Bar

The purpose of this research was to examine bartender workplace behavior. This study begins with a review of the literature pertaining to the job of bartending, and positive work behavior (citizenship) and negative (deviant) workplace behavior. Data was collected by semi-structured interview. The bartenders expressed instances of both behaviors and showed support for a newly termed citizenship behavior, norm avoidance.

A study of the relationship between employee virtuality and technology deviance as mediated by leadership and employee perceptions

Recent studies found that organizations have been investing significant capital in developing teams and employees in geographic areas where labor and resources are considerably cheaper. Furthermore, organizations are moving core operational activities such as research and development and back-office processes to globally distributed teams. ^ However, several factors that are inherent to these virtual teams can have a negative impact on employee perceptions and engagement; specifically, the physical and temporal differences between employees and their supervisors, the lack of meaningful social interaction intrinsic to working relationships, and cultural biases that can be fostered when close, daily interactions is not there to help bridge the dissimilarity. ^ When strategies are not in place to mitigate these deficiencies, it can cause virtual employees to disengage emotionally and intellectually from the organization, or lead them to feel justified in working against the best interest of the company. ^ Past research indicates that although deviant behavior in the workplace is not new, transgressions committed by employees have been increasing significantly every year. Beyond the focus of why employees are motivated to act against the organization, to what extent do the recent changes to the organization’s structure influence this type of behavior through their actions at the macro (organizational) and micro level (leadership). ^ In addition, there is a related phenomenon that has aided the transformation of the workplace—namely, the ubiquity of technology. In the context of workplace deviance, established research has documented an increasing trend of employees utilizing company technology as a medium and amplifier when harming the organization. It is important to understand whether technology has facilitated or hindered workplace deviance by virtue of the technology itself (as a means), and as part of the new employee roles created by the evolving technology (i.e., virtual employees). Therefore, it is important to identify how individual attitudes and behaviors can be affected by an employee’s degree of virtuality. ^ This study will add to the understanding of how social interaction and physical proximity, leadership and other perception factors contribute to the changes organizations are experiencing as their structure evolves and adapts to compete in the new global environment. ^

A Study of the Relationship between Employee Virtuality and Technology Deviance as Mediated by Leadership and Employee Perceptions

Recent studies found that organizations have been investing significant capital in developing teams and employees in geographic areas where labor and resources are considerably cheaper. Furthermore, organizations are moving core operational activities such as research and development and back-office processes to globally distributed teams. However, several factors that are inherent to these virtual teams can have a negative impact on employee perceptions and engagement; specifically, the physical and temporal differences between employees and their supervisors, the lack of meaningful social interaction intrinsic to working relationships, and cultural biases that can be fostered when close, daily interactions is not there to help bridge the dissimilarity. When strategies are not in place to mitigate these deficiencies, it can cause virtual employees to disengage emotionally and intellectually from the organization, or lead them to feel justified in working against the best interest of the company. Past research indicates that although deviant behavior in the workplace is not new, transgressions committed by employees have been increasing significantly every year. Beyond the focus of why employees are motivated to act against the organization, to what extent do the recent changes to the organization’s structure influence this type of behavior through their actions at the macro (organizational) and micro level (leadership). In addition, there is a related phenomenon that has aided the transformation of the workplace – namely, the ubiquity of technology. In the context of workplace deviance, established research has documented an increasing trend of employees utilizing company technology as a medium and amplifier when harming the organization. It is important to understand whether technology has facilitated or hindered workplace deviance by virtue of the technology itself (as a means), and as part of the new employee roles created by the evolving technology (i.e, virtual employees). Therefore, it is important to identify how individual attitudes and behaviors can be affected by an employee’s degree of virtuality. This study will add to the understanding of how social interaction and physical proximity, leadership and other perception factors contribute to the changes organizations are experiencing as their structure evolves and adapts to compete in the new global environment.

Gauging Employee Theft and Other Unacceptable Behaviors in Food Service Operations

Unacceptable employee behavior ultimately results in higher prices for consumers. Members of the Indiana Hospitality and Restaurant Association were surveyed about the practices being used to safeguard their assets and control employee deviance in food service. They were also asked to estimate the losses that result from employee theft. This information was used to investigate whether certain policies and procedures were more effective than others in limiting their losses.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Don't Get Mad, Get Even: How Employees Abused by Their Supervisor Retaliate Against the Organization and Undermine Their Spouses

My study investigated the effects of abusive supervision on work and family outcomes including supervisor-directed and organization-directed deviance and spousal undermining. Using a moderated-mediation model, the relationship of abusive supervision on outcome variables was proposed to be mediated by moral courage and moderated by leader-member exchange (a-path) and work and family role quality (b-path). Two separate studies were conducted using a sample (N=200) recruited through Amazon’s Mechanical Turk and through relatives of students at a large US public southeastern university (N=150 dyads). Results confirm the effects of abusive supervision on work and family outcomes while analyses of contextual and conditional factors are mixed. Confirmatory factor analyses, factor loadings, and model fit statistics are provided and implications for research and practice are discussed.

The Prison System and the Media: How “Orange Is The New Black” Engages with the Prison as a Normalizing Agent

The purpose of this project is to ascertain the ways in which Orange is the New Black uses its platform to either complicate or reify narratives about the prison system, prisoners and their relationship to the state. This research uses the works of Giorgio Agamben, Colin Dayan, Michelle Alexander and Lisa Guenther to situate the ways the state uses the prison and social narratives about the prison to extend its control on certain populations beyond prison walls through police presence, parole, the war on drugs and prison fees. From that basis, this work argues that while Orange does challenge some narratives about race and sexuality, because of its reliance on “bad choices” as a humanizing trope and its reliance on certain racialized stereotypes for entertainment, the show ultimately does more to reify existing narratives that support state interests.

Don't get mad, get even: How employees abused by their supervisor retaliate against the organization and undermine their spouses

My study investigated the effects of abusive supervision on work and family outcomes including supervisor-directed and organization-directed deviance and spousal undermining. Using a moderated-mediation model, the relationship of abusive supervision on outcome variables was proposed to be mediated by moral courage and moderated by leader-member exchange (a-path) and work and family role quality (b-path). Two separate studies were conducted using a sample (N=200) recruited through Amazon’s Mechanical Turk and through relatives of students at a large US public southeastern university (N=150 dyads). Results confirm the effects of abusive supervision on work and family outcomes while analyses of contextual and conditional factors are mixed. Confirmatory factor analyses, factor loadings, and model fit statistics are provided and implications for research and practice are discussed.^

Development of Safety Performance Functions for SafetyAnalyst Applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency’s safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.