The purpose of this study is to investigate the role of loyalty in consumers’ selection of brand extensions in the presence of familiar competitors. The findings show that fit may not have a linear relationship with the choice of an extension when loyalty and brand familiarity are considered. Loyal consumers’ likelihood to choose high-fit and moderate-fit extensions is not much lower than their likelihood to choose products from familiar competitors. We also find an inverted-U-shaped relationship between choice behavior and degree of perceived fit for loyal and moderately loyal consumers. Moreover, brand concepts can make a brand more elastic and extendable, increasing loyal and moderately loyal consumers’ likelihood to choose moderate- and even low-fit extensions. However, disloyal consumers are highly unlikely to choose extensions over products from familiar competitors regardless of fit and types of similarity. Finally, the effect of similarity on consumers’ choice of extensions is fully mediated by loyalty and perceived risks.

The effects of feature frequency and similarity on object recognition have been examined through behavioral experiments, and a model of the formation of visual object representations and old/new recognition has been proposed. A number of experiments were conducted to test the hypothesis that frequency and similarity of object features affect the old/new responses to test stimuli in a later recognition task. In the first experiment, when the feature frequencies are controlled, there was a significant increase in the percentage of &ldquo / old&rdquo / responses for unstudied objects as the number of frequently repeated features (FRFs) on the object increased. In the second experiment, where all features had equal frequency, similarity of test objects did not affect old/new responses. An evaluation of the models on object recognition and categorization with respect to the experimental results showed that these models can only partially explain experimental results. A comprehensive model for the formation of visual object representations and old/new recognition, called CDZ-VIS, developed on the Convergence-Divergence Zone framework by Damasio (1989), has been proposed. According to this framework, co-occurring object features converge to upper layer units in the hierarchical representation which act as binding units. As more objects are displayed, frequent object features cause grouping of these binding units which converge to upper binding units. The performance of the CDZ-VIS model on the feature frequency and similarity experiments of the present study was shown to be closer to the performance of the human participants, compared to the performance of two models from the categorization literature.

通訊技術的演化與智慧型手機的普及，改變了人際溝通的方式與手機的應用情境，在此變動快速的行動運算時代，欲研究探討使用者的行為模式，必須建立一個包含硬體、軟體與使用者社群的實驗平台，以量化的數據補強質性的觀察，準此，本論文將以現有之平台為基礎，強化其功能與易用性，方便其他研究者觀察資料的概況，並擷取符合某些條件之資料，此外，我們採用3-gram之應用程式序列，作為行為模式(behavior pattern)之特徵定義，配合不同的應用程式被使用之頻率，在相似度比較上進行不同比重的加權，根據實驗結果，可大致對使用者進行初步的分類，亦可利用此指標，針對已分類過的使用者更進一步探討之間的歧異程度。 / The rapid evolution of information technology and prevalence of smart-phones have changed the way people communicate. To effectively observe and investigate user behavior in this new era of mobile computing, an experimental platform that consists of hardware devices, software applications and user groups is essential. In this thesis, we enhance and extend the functions of a user log collection and analysis system to facilitate quick overview of the recorded data and allow flexible query/extraction of desired data segments for further processing. In addition, we employ 3-gram app log sequence as the main feature to characterize user behavior. A similarity measure that takes into account the relative app usage frequency has been defined to compare and classify users and their usage patterns. Experimental results indicate that this measure can effectively distinguish users of different traits given enough time period of observation.