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Thesis (M.A.)--Miami University, Dept. of Psychology, 2007. / Title from first page of PDF document. Includes bibliographical references (p. 21-24).

In this thesis we examine the question whether it is possible to model approach and avoidance behaviour with probabilistic machine learning. The results from this project will primarily aid in our collective understanding of human existence. Secondly, it will extend the knowledge with regards to probabilistic machine learning in the Neuroscience domain. We aid this through building a Variational Recurrent Neural Network (VRNN) that is trained on Electroencephalography (EEG)-data from participants that is subjected to odours with varying pleasantness. The pleasantness of the odours is used to divide the participants into two classes based on their self reported experience. This data is used to train the VRNN. The performance of the VRNN is evaluated by how well we are able to reconstruct the original data from a low dimensional latent representation. In this task the model performs on a similar level as related works. We further investigate how changes in the latent space effects reconstructed data. Despite being disentangled, the latent variables are hard to interpret. Furthermore we try to classify and cluster the latent space as either approach or avoidance behaviour with a Support Vector Machine and Uniform Manifold Approximation. The classification results are only slightly better than random, indicating that the learned latent space is not suitable for the task This is most likely due to the patterns that make up approach and avoidance behaviour is seen as noise by the VRNN. This leads to the patterns not being accurately modelled. This is shown by the evidence that frontal α -asymmetry that exists in the data is not reconstructed by the model. The conclusion is therefore that a VRNN is less suitable for modelling underlying behaviour from raw EEG data due to the low signal to noise ratio. We instead suggests to focus on specific frequency ranges in specific regions when applying machine learning in this domain. / Den här uppsatsen behandlar frågan huruvida det är möjligt att modellera närmande och frånstötande beteendemönster med hjälp av maskininlärning. Resultaten från detta projekt ämnar huvudsakligen att främja vidare förståelse av den mänskliga existensen. Vidare ämnar den även att utvidga förståelsen av hur probabilistisk maskininlärning kan användas för att utforska dylika hänseenden. Vi genomför detta genom att bygga en Variational Recurrent Neural Network-modell (VRNN) som tränas på data från experiment där personer utsätts för olika lukter samtidigt som deras Elektroencefalografi (EEG) spelas in. Deltagarna delas in i två klasser beroende på deras självrapporterade upplevelse av luktens njutbarhet. Maskininlärningsmodellen utvärderas genom att vi analyserar hur väl den lyckas rekonstruera datan. Detta lyckas den väl med. Vidare så undersöker vi hur förändringar i modellens latenta rum påverkar rekonstrueringen av datan. Resultaten från det experimentet är ej tydliga. Vidare så försöker vi klassificera och klustra det latenta rummet med avseende på närmande och frånstötande beteende med hjälp av en Support Vector Machine och Uniform Manifold Approximation. Resultaten från dessa experiment är att vi inte lyckas klassificera eller klustra det latenta rummet med avseende på närmande och frånstötande beteende bättre än slumpen. Vi argumenterar för att detta beror på att de underliggande mönster som skapar dessa beteenden ses som brus av VRNN-modellen och därmed inte modelleras. Detta visas genom att frontal α-asymmetri som existerar i datan ej rekonstrueras av modellen. Slutsaten blir därmed att en VRNN är mindre passande att använda vid modellering av underliggande beteenden av obehandlad EEG data. Detta på grund av det låga signal till brus-förhållandet i EEG-datan. Vi föreslår att istället fokusera på specifika frekvensområden i specifika hjärnregioner när maskininlärning appliceras på EEG.

The main purpose of this thesis was to investigate the fit between four achievement goals, personal goal attributes and self-regulation strategies, and the generalisation of goal-strategy patterns to (1) different life domains (academic and physical activity settings), (2) two cultures (individualistic/the UK and collectivistic/Romania) and (3) over time, in two contexts (academic and sport university settings) in the UK. Additionally, differences between high level English and Romanian athletes in self-construals (individualism versus collectivism), achievement goals and self-regulation processes was investigated in one study. Method. The participants in the four studies of this thesis were: English university students (N = 591; study 1), English university athletes and exercise participants (N = 294 and N = 288, respectively; study 2), English and Romanian elite/sub-elite athletes (N = 91, N = 109 respectively; study 3a), Romanian university students involved in sport at elite and sub-elite levels (N = 196; study 3b), and English university student-athletes (N= 295; study 4). Three main questionnaires were used: the Achievement Goals Questionnaire (AGQ; Elliot & McGregor, 2001) (studies 1, 3b, and 4) and the Achievement Goals Questionnaire for Sport (AGQ-S; Conroy, Elliot & Hofer, 2003) (studies 2, 3ab and 4) measured four achievement goals in academic and sport settings, respectively (mastery-approach, mastery-avoidance, performance-approach and performance-avoidance goals); the third questionnaire, the Goal Systems Assessment Battery (GSAB; Karoly & Ruehlman, 1995) (all studies) required participants to state their most important personal goal, and measured two goal attributes (efficacy and value) and five self-regulation strategies used during goal pursuit (planning, self-monitoring, social comparison, self-reward and self-criticism). The fourth questionnaire, was the Self-Construal Scale-Revised (SCS-R; Hardin, 2006) which measured individualistic and collectivistic self-definitions in study 3a. Studies 1, 2 and 3a and 3b employed a correlational design, structural equation modelling analyses, and multivariate and univariate analyses of covariance (study 3a only), while study 4 employed a longitudinal design, latent growth curve analyses and structural equation modelling. Studies 1 and 2 Results. The goal-strategy models identified in education (study 1), sport and exercise (study 2) in the UK were very similar to each other, and consisted of both positive and negative paths (see figure A overleaf). Furthermore, in study 1, the total sample was divided into two samples according to the difficulty and specificity of personal goals: students in sample 1 (N = 325) set easy and vague goals, while students in sample 2 (N = 266) set difficult and specific goals. The model found in the total sample was tested again simultaneous in these two samples in order to ascertain the potential moderation effects of goal difficulty and specificity. As the model was invariant across groups it was concluded that personal goal difficulty/specificity was not a moderator of achievement goal relations with self-regulation processes. Finally, in study 2 Map relations with planning/self-monitoring was fully and partially mediated by goal efficacy and value in the sport and exercise domains, respectively. Study 3a and 3b Results. In study 3a, Romanian athletes had higher collectivistic self-construals than English athletes, while the two groups were similar in individualism. After controlling for collectivism, Romanian athletes, regardless of sport type (individual or team sport) had higher scores than English athletes on Pap and Pav goals, social comparison and self-motivation strategies (self-reward and self-criticism); and Romanian team sport athletes had higher scores on Map and planning/self-monitoring than their English counterparts. In study 3b the goal-strategy models identified in moderately competitive academic and physical activity settings in an individualistic West European culture (UK) were tested in highly competitive academic and elite sport settings in a collectivistic East European culture (Romania). The academic and sport domain models identified in Romania were similar to each other, and to those found in the UK. The following differences in model paths were noted in Romania: in the academic domain, four paths were not significant (Map and Mav to efficacy, efficacy to self-reward, and social comparison to self-criticism); and a new negative path was identified, from Map to social comparison; in the sport domain, five paths were not significant (Mav to efficacy, Pap to efficacy and social comparison, efficacy to reward and social comparison to self-criticism) and three new paths emerged, two positive paths, Pav to social comparison, and efficacy to planning/self-monitoring, and one negative path from efficacy to criticism. The positive path from Pav to social comparison (found in highly competitive sport settings) represents the most notable difference between the UK and Romanian models. Study 4 Results. The goal-strategy models identified in academic and sport contexts in studies 1 and 2 (described earlier) emerged again in these settings in study 4 (minus the path from efficacy to reward in both settings, and efficacy to criticism in academia) at three measurement times (start, middle and end of academic year/competitive season). Therefore, the model was stable over time. Unconditional growth curve analyses showed that, during one year, achievement goals and self-regulation processes followed different patterns of change: Map and Pav goals declined, while Pap and Mav goals were stable in education, and all goals declined in sport settings; goal commitment (a composite measure of goal efficacy and value) declined and planning/self-monitoring remained stable (in both settings); social comparison and self-motivation (a composite measure of self-reward and self-criticism) increased in education, while in sport the former was stable and the latter declined . Finally, associative growth curve models showed that in both domains: 1) temporal changes in Map were positively related to changes in goal commitment and planning/monitoring, and changes in the latter were associated with changes in self-motivation; 2) changes in Pap, social comparison and self-motivation were positively related; and 3) Mav changes were not related to changes in SR processes. Conclusion. This thesis advocates a conceptualisation of achievement goals as a dynamic, cyclical interplay between situated reasons, standards and self-regulated action; 2) an exploration of goal standards dimensions beyond the mastery-performance focus with the reason-standard complex; and 3) an expanded achievement motivation and self-regulation model, including the why (achievement goals), the what (personal goals/goal setting), and the how (self-regulated action), where the focus of enquiry is sifted from the correlates to the mechanisms of achievement goal effects.

Background: Today’s marketers are focusing on creating more than just a transaction place for consumers seeking to purchase products in physical stores, such as a pleasant in store experience. The reason for this is due to the increased competition that present retailers are experiencing. The implementation of sensory marketing in stores has been proven to be useful in order to influence the behaviors of consumers. To do so, sensory cues have been applied as a mean to trigger the emotions of the people visiting the stores. Scholars have stressed the importance of identifying in what manner different sensory cues affect the behavior of consumers. Moreover, there is a need to further research how a visual sensory cue could influence the approach behavior of consumers and enhance their desire to touch products.   Purpose: The purpose of this thesis is to expand the knowledge of how a certain visual sensory cue in a retail atmosphere influences the consumers’ approach behavior and the desire to touch. Additionally, in order to attain valuable insights, two research questions have been designed.   Method: A mixed research methodology has been applied for this study, where the triangulation of using observations, follow-up interviews and in-depth interviews has acted as the source to fulfill the objective of this thesis. The conducted observations account for the quantitative data that have been collected, whereas the follow-up and in-depth interviews generated rich qualitative data. The main methodological focus of this study is to ensure the ability to interpret the findings. Therefore, in order to identify how visual cues influence consumers’ approach behavior and the desire to touch, an inductive approach has been used together with open questions to generate fruitful conversations and theory development. In order to obtain the required data a convenience sampling procedure was employed.   Conclusion: The empirical findings suggest that visual stimuli in the store environment can influence approach behavior of consumers. However, to what extent the visual sensory cue affected the approach behavior and the desire to touch among the participants of this study could not be accounted for. The empirical findings demonstrate that color and smell in the store environment had a positive effect on the emotions of the participants. This further influenced the approach behavior, as well as the desire to touch products.