In the last few years we have witnessed a surge of business-to-consumer and business-to-business commerce operated on the Internet. However, most current electronic commerce systems are little more than electronic catalogues that allow a user to purchase a product under predetermined and inflexible terms and conditions. We believe that in the next few years we will see a new generation of electronic commerce systems emerge, based on automated negotiation. In this paper, we identify the main parameters on which any automated negotiation depends. To show the applicability of our classification framework, we use it to categorise a representative sample of some of the most prominent negotiation models that exist in the literature.

Software agents help automate a variety of tasks including those involved in buying and selling products over the Internet. This paper surveys several of these agentmediated electronic commerce systems by describing their roles in the context of a Consumer Buying Behavior (CBB) model. The CBB model we present augments traditional marketing models with concepts from Software Agents research to accommodate electronic markets. 1.

Software agents help automate a variety of tasks including those involved in buying and selling products over the Internet. This paper surveys several of these agentmediated electronic commerce systems by describing their roles in the context of a Consumer Buying Behavior (CBB) model. The CBB model we present augments traditional marketing models with concepts from Software Agents research to accommodate electronic markets. We then discuss the variety of Artificial Intelligence techniques that support agent mediation and conclude with future

The potential for the efficient and effective organization of market processes by using interactive media is hardly used. Intelligent software agents represent one of most interesting the innovative technologies under economical criteria. This article shows how supplier can use software agents for the individualization and automation of their marketing instruments applied. The use of methods from artificial intelligence enables agents to learn. Thus the automatic optimization of the marketing instruments becomes possible to satisfy massive individualized needs of the demander. Moreover it is outlined, which effect the supplier's use of software agent has on the buying behavior of the demander. Interaction effects are considerated, which develop, if demander likewise use software agents for the support of their purchase process. This article shows that software agents increase the effectiveness and efficiency of market processes on several levels of the Consumer Buying Behavior Model. Keywords: Intelligent Software Agents, Marketing, eCommerce, Virtual Market Place BRT Keywords: CB, GA, GE, HB

Abstract—This paper presents an approach based on the adoption of a distributed cognition framework and a non parametric multicriteria evaluation methodology (DEA) designed specifically to compare e-commerce websites from the consumer/user viewpoint. In particular, the framework considers a website relative efficiency as a measure of its quality and usability. A website is modelled as a black box capable to provide the consumer/user with a set of functionalities. When the consumer/user interacts with the website to perform a task, he/she is involved in a cognitive activity, sustaining a cognitive cost to search, interpret and process information, and experiencing a sense of satisfaction. The degree of ambiguity and uncertainty he/she perceives and the needed search time determine the effort size – and, henceforth, the cognitive cost amount – he/she has to sustain to perform his/her task. On the contrary, task performing and result achievement induce a sense of gratification, satisfaction and usefulness. In total, 9 variables are measured, classified in a set of 3 website macro-dimensions (user experience, site navigability and structure). The framework is implemented to compare 40 websites of businesses performing electronic commerce in the information technology market. A questionnaire to collect subjective judgements for the websites in the sample was purposely designed and administered to 85 university students enrolled in computer science and information systems engineering undergraduate courses.

O’Guinn for their valuable comments, Carina Holmberg for contribution to an earlier draft of this paper, and the Bank of Sweden Tercentenary Foundation for funding this project. Also, in reference to the topic of study, the author would like to express her appreciation to the Association for Consumer Research, their conferences and newsletters, which have made her feel part of a family of consumer researchers at times when there have been relatively few consumer researchers in Sweden. EXECUTIVE SUMMARY The family metaphor is in this paper used to describe the development of consumer behavior as a field of study and to illustrate how consumer behavior researchers act and interact, in the past and presently. We are born or married into a family, just as we as researchers are thrust or introduced into a family of researchers, by choosing a particular research orientation when starting Ph.D. studies or when working on joint research projects. Even though the importance of the family as an institution varies across cultures, it appears to play a major role in most of our lives. The legal system of heritage is based on the family notion and kinship and we are reminded and related to the past in terms of testaments and the heritage of family heirlooms. This is also the case in research families where new research is related to previous research. By studying family roots, we will better understand family history, just as the genealogy of consumer behavior will increase our understanding of its development and sources of inspiration. It will help us comprehend today’s situation and who our family members are, but also make us reflect upon the future development of consumer behavior as a field of study. The purpose of this paper is to encourage the dynamic development of consumer behavior and to make the relations to our research “family ” (or families) to a topic for discussion and reflection.

Discrete choice methods model a decision-maker’s choice among a set of mutually exclusive and collectively exhaustive alternatives. They are used in a variety of disciplines (transportation, economics, psychology, public policy, etc.) in order to inform policy and marketing decisions and to better understand and test hypotheses of behavior. This dissertation is concerned with the enhancement of discrete choice methods. The workhorses of discrete choice are the multinomial and nested logit models. These models rely on simplistic assumptions, and there has been much debate regarding their validity. Behavioral researchers have emphasized the importance of amorphous influences on behavior such as context, knowledge, and attitudes. Cognitive scientists have uncovered anomalies that appear to violate the microeconomic underpinnings that are the basis of discrete choice analysis. To address these criticisms, researchers have for some time been working on enhancing discrete choice models. While there have been numerous advances, typically these extensions are examined and applied in isolation. In this dissertation, we present, empirically demonstrate, and test a generalized methodological framework that integrates the extensions of discrete choice.

Abstract. In contrast to customers of bricks and mortar stores, users of online selling environments are not supported by human sales experts. In such situations recommender applications help to identify the products and/or services that fit the user’s wishes and needs. In order to successfully apply recommendation technologies we have to develop an in-depth understanding of decision strategies of users. These decision strategies are explained in different models of human decision making. In this paper we provide an overview of selected models and discuss their importance for recommender system development. Furthermore, we provide an outlook on future research issues.