Empirical Findings On Persuasiveness Of Recommender Systems For Customer Decision Support In Electronic Commerce

More and more companies are making online presence by opening online stores and providing customers with company and products information but the overwhelming amount of information also creates information overload for the customers. Customers feel frustrated when given too many choices while companies face the problem of turning browsers into actual buyers. Online recommender systems have been adopted to facilitate customer product search and provide personalized recommendation in the market place. The study will compare the persuasiveness of different online recommender systems and the factors influencing customer preferences. Review of the literature does show that online recommender systems provide customers with more choices, less effort, and better accuracy. Recommender systems using different technologies have been compared for their accuracy and effectiveness. Studies have also compared online recommender systems with human recommendations 4 and recommendations from expert systems. The focus of the comparison in this study is on the recommender systems using different methods to solicit product preference and develop recommendation message. Different from the technology adoption and acceptance models, the persuasive theory used in the study is a new perspective to look at the end user issues in information systems. This study will also evaluate the impact of product complexity and product involvement on recommendation persuasiveness. The goal of the research is to explore whether there are differences in the persuasiveness of recommendation given by different recommender systems as well as the underlying reasons for the differences. Results of this research may help online store designers and ecommerce participants in selecting online recommender systems so as to improve their products target and advertisement efficiency and effectiveness

Intelligent agents, markets and competition

Strategisch onderzoek naar de ontwikkelingen op de markt voor intelligent agents. Intelligent Agents kunnen enorme invloed krijgen in de business-to-consumer Internethandel. Veel hangt daarbij af van hoe aanbieders hun producten aanbieden op het Internet. In de reisbranche zijn de mogelijkheden voor productori�ntatie en -aankoop op de websites van reisaanbieders nog beperkt. Op boekensites is meer informatie voorhanden. Hier hebben agents slechts een beperkte functie, omdat onderscheid tussen boekaanbieders enkel op prijs is te maken.

A Hybrid Simulation Framework of Consumer-to-Consumer Ecommerce Space

In the past decade, ecommerce transformed the business models of many organizations. Information Technology leveled the playing field for new participants, who were capable of causing disruptive changes in every industry. Web 2.0 or Social Web further redefined ways users enlist for services. It is now easy to be influenced to make choices of services based on recommendations of friends and popularity amongst peers. This research proposes a simulation framework to investigate how actions of stakeholders at this level of complexity affect system performance as well as the dynamics that exist between different models using concepts from the fields of operations engineering, engineering management, and multi-model simulation. Viewing this complex model from a systems perspective calls for the integration of different levels of behaviors. Complex interactions exist among stakeholders, the environment and available technology. The presence of continuous and discrete behaviors coupled with stochastic and deterministic behaviors present challenges for using standalone simulation tools to simulate the business model. We propose a framework that takes into account dynamic system complexity and risk from a hybrid paradigm. The SCOR model is employed to map the business processes and it is implemented using agent based simulation and system dynamics. By combining system dynamics at the strategy level with agent based models of consumer behaviors, an accurate yet efficient representation of the business model that makes for sound basis of decision making can be achieved to maximize stakeholders\u27 utility

Fault Management For Service-Oriented Systems

Service Oriented Architectures (SOAs) enable the automatic creation of business applications from independently developed and deployed Web services. As Web services are inherently unreliable, how to deliver reliable Web services composition over unreliable Web services is a significant and challenging problem. The process requires monitoring the system\u27s behavior, determining when and why faults occur, and then applying fault prevention/recovery mechanisms to minimize the impact and/or recover from these faults. However, it is hard to apply a non-distributed management approach to SOA, since a manager needs to communicate with the different components through authentications. In SOA, a business process can terminate successfully if all services finish their work correctly through providing alternative plans in case of fault. However, the business process itself may encounter different faults because the fault may occur anywhere at any time due to SOA specifications. In this work, we propose new fault management technique (FLEX) and we identify several improvements over existing techniques. First, existing techniques rely mainly on static information while FLEX is based on dynamic information. Second, existing frameworks use a limited number of attributes; while we use all possible attributes by identify them as either required or optional. Third, FLEX reduces the comparison cost (time and space) by filtering out services at each level needed for evaluation. In general, FLEX is divided into two phases: Phase I, computes service reliability and utility, while in Phase II, runtime planning and evaluation. In Phase I, we assess the fault likelihood of the service using a combination of techniques (e.g., Hidden Marcov Model, Reputation, and Clustering). In Phase II, we build a recovery plan to execute in case of fault(s) and we calculate the overall system reliability based on the fault occurrence likelihoods assessed for all the services that are part of the current composition. FLEX is novel because it relies on key activities of the autonomic control loop (i.e., collect, analyze, decide, plan, and execute) to support dynamic management based on the changes of user requirements and QoS level. Our technique dynamically evaluates the performance of Web services based on their previous history and user requirements, assess the likelihood of fault occurrence, and uses the result to create (multiple) recovery plans. Moreover, we define a method to assess the overall system reliability by evaluating the performance of individual recovery plans, when invoked together. The Experiment results show that our technique improves the service selection quality by selecting the services with the highest score and improves the overall system performance in comparison with existing works. In the future, we plan to investigate techniques for monitoring service oriented systems and assess the online negotiation possibilities for combining different services to create high performance systems

Federal Register

Daily publication of the U.S. Office of the Federal Register contains rules and regulations, proposed legislation and rule changes, and other notices, including "Presidential proclamations and Executive Orders, Federal agency documents having general applicability and legal effect, documents required to be published by act of Congress, and other Federal agency documents of public interest" (p. ii). Table of Contents starts on page iii

Bowdoin Orient v.130, no.1-22 (1998-1999)

https://digitalcommons.bowdoin.edu/bowdoinorient-1990s/1011/thumbnail.jp

Bowdoin Orient v.126, no.1-23 (1997-1998)

https://digitalcommons.bowdoin.edu/bowdoinorient-1990s/1010/thumbnail.jp