13929475
Effects of Web retail service quality and product categories on consumer behavior: a research model and empirical exploration
This paper explores how Web retail service quality at the point of purchase influences consumers' perceptions of value and willingness to buy. In particular, this study highlights how Web retail service quality has different effects on perceived product quality, value, and willingness to buy according to product categories. We provide a research model on the basis of service quality, product categories on the Web, and marketing theories for consumers' purchase behavior. Consumer perceptions of Web retail service quality are collected from a sample of shoppers who actively search for products over the Internet. The results imply that functional Web retail service quality has a direct effect on willingness to buy and technical Web retail service quality influences consumer perceptions of product quality and value. Furthermore, product categories moderate the relationships among Web retail service quality, perceived product quality, perceived value, and willingness to buy. Implications for Internet marketing and future research directions are discussed.
206110402
Knowledge management strategy and its link to knowledge creation process
Abstract Knowledge has become to be considered as valuable strategic assets that can provide proprietary competitive advantages. It is more important for companies to distinguish themselves through knowledge management strategies. Without a constant creation of knowledge, a business is condemned to poor performance. However, it is still unclear how these strategies affect knowledge creation. Knowledge management strategies can be categorized as being either human or system oriented. This paper proposes a model to illustrate the link between the strategies and its creating process. The model is derived on the basis of samples from 58 Korean firms. The model depicts how companies should align the strategies with four knowledge creation modes such as socialization, externalization, combination, and internalization. It is found that human strategy is more likely to be effective for socialization while system strategy is more likely to be effective for combination. Furthermore, the survey result suggests that managers should adjust knowledge management strategies in view of the characteristics of their departments.
13147316
Using Gossip for Dynamic Resource Discovery
Resource discovery is the process of locating shared resources on a computer network. Previously studied examples include efficiently finding files with a given title on a file sharing system. New developments in the application of networked computers raise the issue of dynamic resource discovery, the process of locating shared resources that are always changing. An example application is peer-to-peer computing, where a user wishes to locate idle CPU time anywhere on the network. Peer-to-peer computing is an exciting new computing paradigm. There are vast amounts of idle CPU resources scattered through the globe. We envision a peer-to-peer system to harness those resources, where every member of the network can both share their own CPU and utilize others' CPUs. In a network of hundreds of thousands of computers, resource discovery will play an important role. To avoid debilitating amounts of excess network traffic it is imperative that an efficient resource discovery algorithm be chosen. This paper's contribution to this topic is the use of gossip to reduce network traffic without sacrificing effectiveness. This project has investigated piggybacking gossip messages on other communications to increase the intelligence of searching protocols. The overhead of piggybacking the small amount of data needed is very small, and a case study by simulation shows that it can reduce network traffic by 71-84 percent
17095732
Incremental evaluation of schema-directed XML publishing
When large XML documents published from a database are maintained externally, it is inefficient to repeatedly recompute them when the database is updated. Vastly preferable is incremental update, as common for views stored in a data warehouse. However, to support schema-directed publishing, there may be no simple query that defines the mapping from the database to the external document. To meet the need for efficient incremental update, this paper studies two approaches for incremental evaluation of ATGs [4], a formalism for schema-directed XML publishing. The reduction approach seeks to push as much work as possible to the underlying DBMS. It is based on a relational encoding of XML trees and a nontrivial translation of ATGs to SQL 99 queries with recursion. However, a weakness of this approach is that it relies on high-end DBMS features rather than the lowest common denominator. In contrast, the bud-cut approach pushes only simple queries to the DBNS and performs the bulk of the work in middleware. It capitalizes on the tree-structure of XML views to minimize unnecessary recomputations and leverages optimization techniques developed for XML publishing. While implementation of the reduction approach is not yet in the reach of commercial DBMS, we have implemented the bud-cut approach and experimentally evaluated its performance compared to recomputation.
16011778
A Uniform System for Publishing and Maintaining XML Data
XML has become the prime standard for data exchange on the Web. To exchange data residing in Databases, one needs to publish it in XML. Data publishing is often done with a predefined “schema.” The chapter proposes a new approach for schema-directed publishing of relational data in XML, based on the novel notion of attribute transformation grammars (ATGs). ATGs provide guidance on how to define views conforming to target schemas (DTDs), and automatically ensure schema conformance. The chapter also develops an incremental algorithm for maintaining XML views produced by ATGs, based on new incremental computation techniques that capitalize on the hierarchical structure of XML data and unique features of the ATGs. Taking real-life data from Gene Ontology (GO), this chapter also demonstrates how this system can efficiently publish the GO data in XML with respect to a predefined recursive DTD, and how it incrementally updates the target XML data in response to changes to the underlying GO database.
8402297
The Effects of Users' Motivation on their Perception to Trading Systems of Digital Content Accessories: Focusing on Trading Items in Online Games
As the market for digital content accessories grows, motivation for trading digital content accessories has significant effects on their fun, transaction cost, and intention to trade and use digital contents. However, few empirical studies have investigated users' perception of trading digital content accessories. The main purpose of this study is to construct and verify a research model identifying the relationships among the attributes of transaction, users' perceived fun and transaction cost, and the intention to trade and use digital contents, all of which are modulated by users' motivation. The research model was constructed based on transaction cost theory and motivational theory. An experiment in a real massive multiplayer online role playing game (MMORPG) environment was conducted and the results indicate that users' different motivations have effects on their perception to digital content accessories trading systems, intention to use those systems, and intention to use digital contents
38524318
Making Sense of Search Results by Automatic Web-page Classifications
This paper reports the development of a system for automatically organizing Internet web pages into meaningful categories. The aim of the system is to allow Internet users to find useful information in less time. The current problem with using the Internet is how to find the information that we need. With the explosive growth in the Internet, the information overload situation is getting worse. The proposed system automatically classifies web pages based on three types of information: (1) The system analyzes organizational information among web pages (inter-web-page relationship), such as an URL and links within a web page. (2) It analyzes the meta-web-page information such as data contained in META tags and formatting data of a web page. And (3), it analyzes web-page-content information such as keywords and phrases in the content of a web page. Our results show that combining all three types of information provides better accuracy.