Gangadharbatla for their invaluable help during the data collection. Consumers learn about products from the experience of interacting with people, objects and the environment. However, an experience is more than simply the passive reception of external sensations or subjective mental interpretations of a situation. Rather, an experience is the result of an ongoing transaction that gains in quality, intensity, meaning, and value integrating both psychological and emotional conditions (Mathur, 1971). These conditions are ultimately accomplished via the generation of thoughts and/or sensations brought together creating the experience (Hirshman, 1984). A product purchase is in many ways not the purchase of a physical good itself but of an experience that the product affords (Pine II and Gilmore, 1998). Thus, the role of consumer learning about a product prior to the purchase is mainly to assess what consumption experience the product can offer and how well it can meet the expectations of the anticipated experience (Hoch and Deighton, 1989). Research has documented that consumers learn about products through indirect

This thesis is the result of two and half years of hard work whereby I have been supported by many people. It is pleasant that I have now the opportunity to express my gratitude for all of them. First of all, I am deeply indebted to Dr. Xigen Li, my thesis advisor, for his constant encouragement, advice and research support throughout my master's studies. He has always challenged me to dig beneath the surface of knowledge so that I am able to expand my thinking on that depth of knowledge. I am very fortunate to have Dr. Li as my advisor. I would also like to thank my committee members, Dr. Renita Coleman and Dr. Richard Alan Nelson. Dr. Coleman not only took effort in providing me with valuable comments on this thesis, but also shared me with her experience as a graduate student. Dr. Nelson always had more faith in me than I had in myself. With his kindness, wisdom and mentorship, he contributed immensely to shaping me as a person and a researcher as well. Last but not the least, I would like to give my special thanks to my parents, who

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Through a series of studies designed to explore important aspects of virtual experience, a new type of product affordances—virtual affordances—is proposed and tested empirically. In addition, the existing geometric and material product taxonomy is extended to include mechanical products within the classification structure. Utilizing these new concepts, 3-D product visualization is compared with traditional 2-D product representations and television advertising. The results largely support the proposition that 3-D product visualization is capable of influencing brand attitude and purchase intention for geometric and mechanical products within e-commerce environments. 2 The Role of Virtual Experience in Consumer Learning Consumers learn about products through both direct and indirect experience. While direct experience is solely derived from actual product contact, indirect experience can be generated from various sources such as word of mouth, brochures, and advertising. Interactive advertising in the form of 3-D product visualization simulates a new type of indirect experience—virtual experience. Li, Daugherty and Biocca (2001) examined the characteristics of a virtual experience

1.1 Examples.......................................... 1 1.2 Research novelty and relevance.............................. 3 2 Research framework 5

In CSCL research, collaboration through chat has primarily been studied in dyadic settings. In VMT’s larger groups it becomes harder to specify procedures for coding postings because the interactions are more complicated and ambiguous. This chapter discusses four issues that emerged during the development of a multidimensional coding procedure for smallgroup chat communication: (a) the unit of analysis and unit fragmentation, (b) the reconstruction of the response structure, (c) determining reliability without overestimation, and (d) the validity of constructs inspired by diverse theoretical-methodological stances. Threading, i.e., connections between analysis units, proved essential to handle unit fragmentation, to reconstruct the response structure and for reliability of coding. In addition, a risk for reliability overestimation is illustrated. Implications for reliability, validity and analysis methodology in CSCL are discussed. Keywords: Unit of analysis, response structure, reliability, validity, coding scheme, methodology Coding of communication processes (content analysis) to determine effects of computer-supported collaborative learning (CSCL) has become a common research

This paper discusses the growing trend of applying computational thinking and linguistic approaches to social science research, arguing that computational linguistics is a useful but underutilized approach that may potentially be able to make significantly contributions to research in a wide range of social science domains. The paper begins with an introduction to computational thinking and argues that this approach can be applied not only in the sciences but also in the social sciences. Next, the paper discusses the linguistic turn in the social sciences and provides an overview of research on manual content analysis. The following sections describe how automatic content analysis evolved from manual content analysis, and describe how a computational approach can support content analysis. The paper then describes principles and techniques for applying automatic content analysis. Next, the paper gives examples of domains where automatic content analysis is already being applied and domains where it could be applied in the future. Finally, the paper calls attention to the need for additional work in this area.

This paper describes progress on an ongoing project that integrates both communication theories and computer science algorithms to create a program that can detect the occurrence of sexual predation in an online social setting. Though there has been much work exploring social media in general, this particular aspect of online social interaction remains largely untapped. In particular, our study attempts to evaluate and categorize the strategies used by online sexual predators in their attempts to develop relationships with children using the Internet. Our software system, ChatCoder, is designed to decide which lines in the chat log contain predatory language. The labels we use are based on the communicative model for online predation that we have developed and are refining. This article describes the communicative model in detail, with specific descriptions of the choices we made as we refined the model. In previous work we developed phrase-matching and rule-based approaches to classify and label lines of chat logs. In the current work, we expand these techniques and use machine learning algorithms to classify posts. Our machine learning system leveraged

Small and medium-sized enterprises (SMEs) are a vital and growing part of any national economies. In common with most large businesses, SMEs have recognized the importance of knowledge management. Using survey data from 219 small and medium-sized enterprises in Austria and Switzerland including Liechtenstein, this paper investigates the use of knowledge processes and knowledge methods for SMEs. The objective of this paper is the identification of key knowledge processes in Austrian and Swiss Small and Medium-sized Enterprises. The basic research framework is the knowledge process model from Probst/Raub/Romhardt (1999) with its eight building blocks. Empirical studies conducted by the authors show that for SMEs only four knowledge processes of the building block approach are important: (1) knowledge identification, (2) knowledge acquisition, (3) knowledge distribution and (4) knowledge preservation. Based on the result of this first empirical study, a comparative study was conducted to gain more insight which knowledge methods support the four key knowledge processes in Austrian and Swiss SMEs. In this paper, the authors introduce a knowledge framework for the implementation of knowledge management in SMEs.

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