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Constituents in the judicial process such as jurors and lawyers who often play a critical role in the aftermath of an alleged financial reporting fraud have largely been ignored in the accounting literature. Literature in psychology suggests that both laypeople and highly trained professionals frequently over-attribute causality of an observed behavior to the disposition of the person performing that behavior. In doing so, these individuals underestimate the power of situations and fail to recognize important environmental factors that lead to a particular behavior. Within the context of fraudulent financial reporting, there is little understanding of how jurors and lawyers initially perceive and react to fraudulent behavior. Consequently, it is possible jurors and lawyers who are asked to evaluate the causality of a suspected fraudulent event, are inaccurate in their assessment of the causality of that event. This study addresses the question of whether or not the various constituents in the judicial process are biased in their attributions when evaluating causal factors related to financial reporting decisions. More specifically, it focuses on how individuals outside the profession of accounting, laymen jurors and corporate lawyers, make attributions when observing decisions related to fraudulent financial reporting, and whether or not these attributions differ from those made by corporate accountants. Further, after identifying differences in attributions, this study attempts to determine the causes of these differences; and whether recent changes in business culture have been effective in curbing financial reporting fraud. The late 1990s and early 2000s saw a proliferation of high profile financial reporting frauds, and as a result, numerous changes have been made within the regulatory environment governing financial reporting. Many of these changes targeted overall business culture and a commitment to ethical financial reporting. By studying the attributions of corporate accountants we learn about their perceptions of the current environment and better understand their willingness to report something in a manner that would constitute financial reporting fraud. Evidence demonstrates that laymen, corporate lawyers, and corporate accountants differ in their attributions and that laymen are typically more biased when observing individuals and their financial reporting decisions. Laymen are also shown to lack awareness of recent changes in the financial reporting environment, have unrealistic expectations of the likelihood accountants are willing to intentionally misreport something, and are not as good at identifying appropriate and inappropriate financial reporting behaviors. Results also suggest recent changes in business culture and governance around financial reporting have been effective in convincing corporate accountants that environmental factors should not lead to, and are not a viable excuse for, fraudulent financial reporting. / Ph. D.

Given access to detailed tracking data, the problem of attribution modelling has recently gained attention in both academia and the industry. Being able to determine the influence of each marketing channel in driving conversions can help advertisers to allocate their marketing budgets accordingly and ultimately increase their customer base and achieve a higher Return On Investment (ROI). However, Last-Touch Attribution (LTA), the current industry standard to approach the problem, has been criticized for oversimplification.  In this degree project, two data-driven attribution models are therefore compared to the LTA model on real data from an insurance company, with the objective to optimize for customer base growth and ROI. Raw attributions for each channel are obtained after training the models to predict conversion or non-conversion. By using a linear function to obtain a Customer Lifetime Value (CLV) estimate, the attributions are then adjusted to the ROI of each channel and finally validated through an attribution based budget allocation and historical marketing data replay. The experimental results demonstrate that all models reach approximately 82% accuracy on balanced data, just below the calculated theoretical maximum. While current research consistently argues for more complex data-driven Multi-Touch Attribution (MTA) models, this project provides a nuance to this field of research in showing that the LTA model may, in fact, be suitable in some cases. A new approach to develop specialized models based on correlations between conversion and contextual variables, then shows that attribution models for mobile users specifically yield higher accuracy. The sum of such unnormalized attributions function as indicators for the conversion strength of contextual variables and can further assist decision making. / Givet tillgång till detaljerad spårningsinformation har attributionsmodellering nyligen fått uppmärksamhet i både akademin och näringslivet. Att kunna förstå påverkan varje marknadsföringskanal har på att driva konverteringar, kan underlätta för annonsörer att fördela marknadsföringsbudgetar och i slutändan öka antalet kunder samt uppnå en högre avkastning på investeringen. Last-Touch-Attribution (LTA), den nuvarande branschstandarden för att angripa problemet, har emellertid kritiserats för att vara överförenklande. I det här examensarbetet jämförs därför två datadrivna attributions-modeller med LTA på verklig data från ett försäkringsbolag med målet att optimera för kundbastillväxt och avkastning. Råa attributioner för varje kanal erhålls efter att modellerna tränats på att prediktera konvertering eller icke-konvertering. Genom att estimera kundens livstidsvärde med en linjär funktion, justeras attributionerna sedan med avkastningen på investering för varje kanal och valideras slutligen genom en attributionsbaserad budgetallokering och uppspelning av historisk marknadsföringsdata. De experimentella resultaten visar att alla modeller når ungefär 82% träffsäkerhet på balanserad data, strax under det beräknade teoretiska maximivärdet. Medan aktuell forskning konsekvent argumenterar för mer komplexa datadrivna multi-touch-modeller, ger det här projektet en nyans till forskningsfältet genom att visa att LTA i vissa fall kan vara lämplig. Ett nytt tillvägagångssätt för att utveckla specialiserade modeller baserade på korrelationer mellan konvertering och kontextuella variabler, visar sedan att attributionsmodeller för enbart mobilanvändare ger högre träffsäkerhet. Summan av sådana onormaliserade attributioner fungerar som indikatorer på konverteringsstyrkan för kontextuella variabler och kan ytterligare underlätta beslutsfattandet.

Authorship attribution of source code is the task of deciding who wrote a program, given its source code. Applications include software forensics, plagiarism detection, and determining software ownership. A number of methods for the authorship attribution of source code have been presented in the past. A review of those existing methods is presented, while focusing on the two state-of-the-art methods: SCAP and Burrows. The primary goal was to develop a new method for authorship attribution of source code that is even more effective than the current state-of-the-art methods. Toward that end, a comparative study of the methods was performed in order to determine their relative effectiveness and establish a baseline. A suitable set of test data was also established in a manner intended to support the vision of a universal data set suitable for standard use in authorship attribution experiments. A data set was chosen consisting of 7,231 open-source and textbook programs written in C++ and Java by thirty unique authors. The baseline study showed both the Burrows and SCAP methods were indeed state-of-the-art. The Burrows method correctly attributed 89% of all documents, while the SCAP method correctly attributed 95%. The Burrows method inherently anonymizes the data by stripping all comments and string literals, while the SCAP method does not. So the methods were also compared using anonymized data. The SCAP method correctly attributed 91% of the anonymized documents, compared to 89% by Burrows. The Burrows method was improved in two ways: the set of features used to represent programs was updated and the similarity metric was updated. As a result, the improved method successfully attributed nearly 94% of all documents, compared to 89% attributed in the baseline. The SCAP method was also improved in two ways: the technique used to anonymize documents was changed and the amount of information retained in the source code author profiles was determined differently. As a result, the improved method successfully attributed 97% of anonymized documents and 98% of non-anonymized documents, compared to 91% and 95% that were attributed in the baseline, respectively. The two improved methods were used to create an ensemble method based on the Bayes optimal classifier. The ensemble method successfully attributed nearly 99% of all documents in the data set.

published_or_final_version / Education / Doctoral / Doctor of Philosophy

Theory of mind, the ability to attribute mental states to oneself and others, has traditionally been investigated in humans and nonhuman primates. However, non-primate species, such as domestic dogs, may also be potential candidates for such a faculty. Domestic dogs (Canis familiaris) evolved from a social-living, wolf-like ancestor, and were the first species to be domesticated, with likely selection for sensitivity to human cues and human-like cognitive abilities. Dogs typically spend their lives in the rich social environment of human families, and thus dogs are naturally enculturated. The combination of these factors make dogs an excellent candidate for having a functional theory of mind. Yet perhaps surprisingly, prior research on theory of mind in dogs is limited, with inconclusive and contradictory results. The research described in this thesis is a systematic investigation of dogs' potential to demonstrate a functional theory of mind in their interactions with humans. Four experiments are presented, based on the Knower-Guesser paradigm (Povinelli et al., 1990), in which a knowledgeable and an ignorant human informant indicated the location of hidden food to the dog. In Experiment 1, one informant was absent (Guesser) and one present (Knower) during the food-hiding, and the dogs chose the Knower. However, when both informants were present, the dogs chose the informant that did the baiting, but this preference was less than when the Guesser was absent. In Experiments 2 and 3, a third experimenter hid the food while the informants covered their cheeks (Knower) or eyes (Guesser) with their hands, or were attentive (Knower) or inattentive (Guesser) to the food-hiding. In both cases, the dogs showed a significant preference for the Knower. In Experiment 4, the dogs showed no preference between the informants when they had equal perceptual access to the baiting, and were unsuccessful at selecting any container when the informants did not provide communicative cues. Overall, the present research provides the most definitive evidence yet that domestic dogs may be able to attribute differential states of knowledge to human observers, and thus may possess a functional theory of mind.

Most dispute resolution is between employers and employees, family or friends, neighbors, and other groups who have continued contact after they leave the courtroom, mediator's office, or agree to contract terms. Because of such ongoing relationships, a vital component of any kind of dispute resolution is how conflicting parties feel about each other after the process is over. Although previous conflict resolution research focuses primarily on the perceived fairness of the third-party, process or outcome, my dissertation centers around how the two parties engaged in the process perceive each other and their relations. Specifically, I ask how intermediaries' intervention in a resolution process affects disputing individuals' perceptions of fairness of one another, general positive regard toward one another, and predictions for positive future interactions with one another.I explore the relationship between third party intervention and such relationship outcomes using two experimental methods, vignettes and laboratory research. In each experiment I vary the level of third party intervention (high, low, absent), while holding dispute resolution outcomes constant, and then measure disputants' perceptions of one another. I also test three potential intervening mechanisms for the relationship between intervention and perceptions - procedural fairness, situational attributions, and salience of conflict.Results indicate that third party intervention does affect perceptions disputants' have of one another and that such results vary based on the method used. In the vignettes, the method typical of research in third party intervention, intervention is negatively related to perceptions of the other party. However, the opposite is true in the laboratory experiment. The results from the laboratory suggest that third party intervention is positively related to perceptions of the other party and that both the increased likelihood of situational attributions and decreased salience of conflict with high third party intervention partially explain this relationship.Implications of these results, and potential areas of future research, are discussed.

Despite the existence of nineteen universities in Lebanon, student motivation and achievement have not received attention in relation to attribution theory by Lebanese researchers. In the present study, attribution theory is used as a conceptual framework for investigating the motivation of undergraduate business computing students at a Mediterranean university based on their academic achievement in an introductory computer programming course. While numerous studies have used attribution theory as a framework to study student motivation based on hypothetical scenarios or laboratory tasks, this study investigated forty-five male and female business computing students who completed a computer programming course that lasted for a thirteen-week semester. Instead of focusing on either success or failure, the study explored five strata of achievement outcomes. Semi-structured interviews were conducted to obtain students' perceptions. The participants made 11 causal attributions for their achievement outcomes. Only two of those 11 causes appeared in the original attribution theory model (Weiner et al. 1971, p.96), but they were amongst those least cited in this study. This study also shows that of the 11 causes, 'lack of study' and 'appropriate learning strategy' were the leading ones. The latter was cited by all high achievers. While there was total agreement on some of the underlying causal properties of some causal attributions, other causal attributions were perceived differently in the causal space. In addition, there was strong evidence that globality is a fourth dimension in this achievement context. Furthermore, the two dimensions of the Expectancy-Value motivation model (Amone 2005, p.4) do not seem to relate to attribution theory dimensions in this study, especially for low achievers. Finally, it was possible to identify some attribution styles that lead to either success or failure, thus supporting the predictive power of attribution theory.

En speciallärare bör ha goda insikter i motivationens betydelse för att kunna hjälpa elever i matematiksvårigheter. Laborativ matematik föreslås som ett sätt att motivera elever. I min aktion undersöks om SUM-elevernas (elever med speciella undervisningsbehov i matematik) motivation i matematik påverkas av ett laborativt undervisningssätt. Enkäter och intervjuer används i min studie för att bedöma vilka effekter laborativ matematik har för eleverna. De mäts i termerna av elevernas effekter av attribueringar och grad av inre motivation med utgångspunkt i Medbestämmandeteorin, Attributionsteorin och Målorienteringsteorin. En effekt av aktionsstudien är, att de börjar inse att de har talang. Det handlar om hur mycket de anstränger sig i matematik och inte bristen på förmåga. En annan effekt är att eleverna anser att matematiken är roligare, eftersom de får arbeta praktiskt och i mindre grupp. Man kan uppenbarligen påverka elever med en aktionsstudie, men det är inte säkert att den blir bestående. Det är viktigt att elever lyckas och inte misslyckas om och om igen, för då tappar de sin motivation.

By the end of 2016 surveillance and reconnaissance satellites will have been monitoring Arctic-wide sea ice conditions for decades. Situated at the boundary between atmosphere and ocean, Arctic sea ice retreat has been one of the most conspicuous indication of climate change, especially in the two most recent decades. The 2001 annual minimum extent of Arctic sea ice marks the last year above the 1981 -- 2012 long-term average extent. Ever since then only lower than average Arctic sea ice has been observed at the end of each summer's melt season. For more than a century climate scientists have postulated that the darkening of the Arctic due to retreating sea ice and therefore more exposed open ocean would be the consequence of global warming. In the first decade of the 2000s the human influence on that warming in the Arctic was indeed detected in observations and attributed to increasing atmospheric greenhouse-gas concentrations. In this study we direct our attention to a potential offsetting effect from other anthropogenic (OANT) forcing agents, mainly aerosols, that has potentially out masked a fraction of greenhouse-gas induced warming by a combined cooling effect. We acknowledge that multiple sources of uncertainty exist in our method, in particular in the observed records of Arctic sea ice and corresponding simulations from climate models. No formal detection and attribution (DA) analysis has yet been carried out to try to detect the combined cooling effect from aerosols in observations of Arctic sea ice extent. We use three publicly available observational data sets of Arctic sea ice and climate simulations from eight models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). In our detection and attribution study observations are regressed on model-derived climate response pattern, or fingerprints, under all known historical (ALL), greenhouse-gas only (GHG) and known natural-only (NAT) forcing factors using an optimal fingerprinting method. We estimate regression coefficients (scaling factors) for each forcing group that scale the fingerprints to best match the observed record. From the scaled ALL, GHG and NAT fingerprints we calculate the relative contribution of the observed sea ice decline attributable to OANT forcing agent. Based on our DA results we show that the simulated climate response patterns to changes in GHG, OANT and NAT forcing are detected in the observed records of September Arctic sea ice extent for the 1953 to 2012 period. / Graduate