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XML Schema is used to define schema of XML documents that have become standards for data exchange in various Web-based information applications. The main problem of XML Schema is that it emphasizes syntax and format rather than semantics and knowledge representation. Hence, even though having the advantage of describing the structure and constraining the contents of XML documents, XML Schema lacks the computer-interpretability to support knowledge representation for existing information systems. The purpose of this study is to propose role-mapping annotations for XML Schema (RMAXS) to integrate Semantic Web with XML Schema, which allows the facilitation interoperability between adjoining layers of the Semantic Web stack.

The XML, XML Schema, ontology, and rule can be completely integrated into a multi-layered intelligent framework (MIF) for XML-based applications in the current web environment. This work presents a semantic-role-mapping intelligent system, called SRMIS, based on the MIF. SRMIS consists of XML-based document repository, search engine, inference engine and transformation engine, which provides different approaches to present the various metadata and knowledge representations.

The traditional Semantic Web stack has three gaps between adjoining layers. The first gap, between the XML and XML Schema layers can be bridged with an XMLSchema-instance mechanism. The third gap, between the ontology and rule layers can be connected by building rules on top of ontologies. This study proposes RMAXS to couple the second gap, between the XML schema and ontology layers. The proposed multi-layered intelligent framework (MIF) adopts these coupling technologies to facilitate interoperability between adjoining layers. Therefore, the XML, XML Schema, ontology, and rule can be completely integrated into the MIF for intelligent applications in the web environment.

To demonstrate the SRMIS applications, this work implements a prototype that helps researchers to find interested papers.

This work presents a semantic-role-mapping intelligent system, called SRMIS, based on the MIF. SRMIS consists of XML-based document repository, search engine, inference engine and transformation engine, which provides different approaches to present the various metadata and knowledge representations. The proposed SRMIS can be applied in various application domains.

This study aims to explore three critical factors, namely, specific assets investment (SAI), knowledge integration mechanism (KIM) and complementary capability (CC), the antecedents of market knowledge from on structure, process and strategy aspects. This study then tests their effects on the market knowledge-market performance linkage in an asymmetric commerce relationship.

This study identified the asymmetric business-to-business (B2B) channel relationship of travel service industry. A total of 248 responses were received from the two waves of data collection and the data was analyzed by the structural equation modeling method.

Based on the managerial theory related to transaction cost, knowledge-based view and resource-dependent, SAI, KIM and CC all affect market knowledge, and had an indirect effect on market performance; market knowledge significantly and positively affects market performance.

In addition to relationship marketing or social exchange theory, this study provides an integrated framework with different theoretical studies to supplement the explanation of relationship marketing theory in the non-significant relationship between trust and commitment and their outcomes.

This study provides answers for weaker firms how to enhance their market knowledge from their stronger partners.

No current studies have explored how service firms with weak bargaining power could enhance their market knowledge under an imbalanced B2B relationship. This supports the call for the possible factors as the key antecedents of market knowledge on the asymmetric B2B relationship.