Thesis (Ph. D.)--Michigan State University. Dept. of Accounting and Information Systems, 2008. / Title from PDF t.p. (viewed on July 23, 2009) Includes bibliographical references (p. 74-77). Also issued in print.

Decision making for fast-moving consumer goods involves a choice between numerous similar alternatives. Under such demanding circumstances, a decision is made for one product. The decision is dependent on the interaction between the environment and the mind of the consumer, both of which are filled with information that can influence the outcome. The aim of this dissertation is to explore how the mind and the environment guides attention towards considered and chosen products in consumer decision making at the point-of-purchase. Consumers are equipped with several effort reduction strategies to simplify complex decision making. The selection of strategies can be conscious or automatic and driven by information in the environment or the mind of the decision maker. The selected decision strategy reduces the set of options to one alternative in an iterative process of comparisons that are fast and rely on perceptual cues to quickly exclude irrelevant products. This thesis uses eye-tracking to explore this rapid processing that lacks conscious access or control. The purpose is to explore how product packaging and placement (as in-store factors), and recognition, preferences, and choice task (as out-of-store factors) influence the decision-making process through visual attention. The results of the 10 experiments in the five papers that comprise this thesis shed new light on the role of visual attention in the interaction between the environment and the mind, and its influence on the consumer. It is said that consumers choose with their eyes, which means that unseen is unsold. The results of this thesis show that it is just as important to be comprehended as it is to be seen. In split-second decision making, the ability to recognize and comprehend a product can significantly impact preferences. Comprehension stretches beyond perception as consumers infer value from memory structures that influence attention. Hence, the eye truly sees what the mind is prepared to comprehend.

Die Dynamik des Erdsystems im Anthropozän wird durch eine zunehmende Verschränkung von Prozessen auf physikalischer und ökologischer sowie auf sozioökonomischer Ebene bestimmt. Wenn Modelle als Entscheidungshilfen in diesem Umfeld nützlich sein sollen, müssen sie diese komplexen Rückkopplungen ebenso berücksichtigen wie die inhärent emergenten und heterogenen Qualitäten gesellschaftlicher Dynamik. Diese Arbeit schlägt vor, den Menschen als begrenzten rationalen Entscheidungsträger zu modellieren, die (soziales) Lernen nutzen, um Entscheidungsheuristiken zu erwerben, die in einer gegebenen Umgebung gut funktionieren. Dies wird in einem Wirtschaftsmodell mit zwei Sektoren veranschaulicht, in dem ein Sektor eine fossile Ressource für die wirtschaftliche Produktion verwendet und die Haushalte ihre Investitionsentscheidungen in der zuvor beschriebenen Weise treffen. In der Modellökonomie können individuelle Entscheidungsfindung und soziale Dynamik die CO 2 Emissionen nicht auf ein Niveau begrenzen, das eine globale Erwärmung über 1,5◦C verhindert. Eine Kombination aus kollektivem Handeln und koordinierter öffentlicher Politik allerdings kann. Eine Folgestudie analysiert das soziale Lernen der individuellen Sparquoten in einer Ein-Sektor-Wirtschaft. Hier nähert sich die aggregierte Sparquote der eines intertemporär optimierenden allwissenden Sozialen Planers an, wenn die soziale Interaktionsrate ausreichend niedrig ist. Gleichzeitig führt eine abnehmende Interaktionsrate einem plötzlichen Übergangs von einer unimodalen zu einer stark bimodalen Verteilung des Vermögens unter den Haushalten. Schließlich schlägt diese Arbeit eine Kombination verschiedener Methoden vor, die zur Ableitung analytischer Näherungen für solche vernetzten heterogenen Agentenmodelle verwendet werden können, bei denen Interaktionen zwischen Agenten sowohl auf individueller als auch auf aggregierter Ebene auftreten. / The trajectory of the Earth system in the Anthropocene is governed by an increasing entanglement of processes on a physical and ecological as well as on a socio-economic level. If models are to be useful as decision support tools in this environment, they ought acknowledge these complex feedback loops as well as the inherently emergent and heterogeneous qualities of societal dynamics. This thesis improves the capability of social-ecological and socio-economic models to picture emergent social phenomena and uses and extends techniques from dynamical systems theory and statistical physics for their analysis. It proposes to model humans as bounded rational decision makers that use (social) learning to acquire decision heuristics that function well in a given environment. This is illustrated in a two sector economic model in which one sector uses a fossil resource for economic production and households make their investment decisions in the previously described way. In the model economy individual decision making and social dynamics can not limit CO 2 emissions to a level that prevents global warming above 1.5 ◦ C. However, a combination of collective action and coordinated public policy actually can. A follow up study analyzes social learning of individual savings rates in a one sector investment economy. Here, the aggregate savings rate in the economy approaches that of an intertemporarily optimizing omniscient social planner if the social interaction rate is sufficiently low. Sumultaneously, a decreasing interaction rate leads to emergent inequality in the model in the form of a sudden transition from a unimodal to a strongly bimodal distribution of wealth among households. Finally, this thesis proposes a combination of different moment closure techniques that can be used to derive analytic approximations for such networked heterogeneous agent models where interactions between agents occur on an individual as well as on an aggregated level.