abstract: Unethical behavior is a phenomenon that is unavoidable in the workplace. Ethical transgressors, when caught, often receive feedback regarding their actions. Though such moral feedback—feedback that is in response to an ethical transgression—may be aimed at curtailing future unethical behavior, I seek to demonstrate that under certain conditions, moral feedback may promote subsequent unethical behavior. Specifically, I propose that moral intensity and affective tone are two primary dimensions of moral feedback that work together to affect ethical transgressor moral disengagement and future behavior. The notion of moral disengagement, which occurs when self-regulatory systems are deactivated, may account for situations whereby individuals perform unethical acts without associated guilt. Despite the burgeoning literature on this theme, research has yet to examine whether feedback from one individual can influence another individual’s moral disengagement. This is surprising considering the idea of moral disengagement stems from social cognitive theory which emphasizes the role that external factors have in affecting behavior. With my dissertation, I draw from research primarily in social psychology to explore how moral feedback affects transgressor moral disengagement. To do so, I develop a typology of moral feedback and test how each moral feedback type affects transgressor future behavior through moral disengagement. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2018

The thesis consists of four conceptual articles focused on application of theories and findings of behavioral economics and behavioral ethics in the sphere of managerial science (What Comes to a Manager's Mind: Theory of Local Thinking; A Perspective on Consumers 3.0: They Are Not Better Decision-Makers Than Previous Generations; Professional Identity and Dishonest Behavior; Puppet Master: Possible Influence of Parasite Toxoplasma gondii on Managers and Employees). The thesis contains introductory unifying commentary that deals with the replication crisis in management science and then speculates on the possibilities of behavioral organization economics. Introductory commentary contains also a summary of the main ideas presented in the conceptual articles and complementary empirical studies listed in the Appendix.

Job performance has historically been divided into two subsets, that which is prescribed and that which is discretionary. Further, discretionary workplace behavior has typically been described as either helpful or ethical (i.e. organizational citizenship behavior) or harmful and unethical (i.e. workplace deviance behavior) with behavior that is both helpful and unethical rarely discussed. I term this lesser discussed type of discretionary workplace behavior unethical prosocial behavior and define it as discretionary actions that are intended to benefit a specific referent outside the self, either an individual or a group, that are illegal and/or morally inappropriate to larger society. In addition to defining unethical prosocial behavior, this paper places the behavior in an organizing framework of discretionary workplace behaviors and tests several hypotheses regarding unethical prosocial behavior. The hypotheses address three primary research questions. First, are there contextual conditions that make it more likely that a person will engage in unethical prosocial behavior? Second, does the nature of the relationship between the actor and the beneficiary make unethical prosocial behavior more or less likely? And third, are there individual characteristics that serve to either constrain or enhance the likelihood that and individual will engage in unethical prosocial behavior? A 2 x 2 experimental design was used to test these hypotheses. As expected, in-group (vs. out-group) salience increased the likelihood of UPB. Individuals in the in-group condition engaged in significantly greater UPBs than those in the out-group condition. Contrary to expectations, shared reward (vs. no reward) decreased the likelihood of UPB. Individuals who were due a reward engaged less in UPBs than those who were not due a reward. Possible explanations for this relationship (both methodological and theoretical) are explored. While the overall effect of reward structure on UPB was in the opposite direction from that which was expected, propensity to morally disengage had the anticipated effect on the relationship between rewards and UPB. Those high in propensity to morally disengage were more likely to engage in UPB when a shared reward was offered (vs. no reward). Due to the nature of the task and the data collected, it was possible to operationalize UPB as a continuous measure as well as a dichotomous event (UPB/no UPB). This lead to a supplemental analysis that shed additional light on the nature of the relationship between group salience and UPB. The analysis shows that not only do subjects tend to over report the scores for fellow in-group members, but they also tend to underreport scores for out-group members. Fruitful areas for future work on the nascent UPB construct are discussed.

With the arrival of automated vehicles (AVs) on our streets virtually around the corner, this thesis explores advances in automated driving technology with a focus on ethical decision making in dilemmatic traf- fic situations. In a total of five publications, we take a multi-facetted approach to analyse and address the core challenges related to auto- mated ethical decision making in AVs. In publications one through three, we conduct a series of immersive virtual reality studies to analyze human behavior in traffic dilemmas, explore mathematical approaches to model the decision making process, investigate how the assessment methodology can affect moral judgment, and discuss the implications of these studies for algorithmic decision making in the real-world. In publication number four, we provide a comprehensive summary of the status quo of AV technology and legislation with regard to automated ethical decision making. Here, we discuss when and why ethical deci- sion making systems become necessary in AVs, review existing guide- lines for the behavior of AVs in dilemma situations, and compile a set of 10 demands and open questions that need to be addressed in the pursuit of a framework for ethical decision making in AVs. Finally, the basis for automated ethical decision making in AVs will be provided by accurate assessments of the immediate environment of the car. The pri- mary technology used to provide the required information processing of camera and LiDAR images in AVs is machine learning, and in particular deep learning. In publication five, we propose a form of adaptive acti- vation functions, addressing a central element of deep neural networks, which could, for instance, lead to increased detection rates of relevant objects, and thus help to provide a more accurate assessment of the AVs environment. Overall, this thesis provides a structured and compre- hensive overview of the state of the art in ethical decision making for AVs. It includes important implications for the design of decision mak- ing algorithms in practice, and concisely outlines the central remaining challenges on the road to a safe, fair and successful introduction of fully automated vehicles into the market.