Building a semantics-assisted risk analysis (SARA) framework for vendor risk management

Recently, electronic procurement or eProcurement has gradually acquired wide acceptance in various industries as an effective, efficient, and cost-saving mechanism to search for and contact potential vendors over the Internet. However, it is also a common situation that purchasers do not have handy and reliable tools for the evaluation of the risk deriving from their choices of selecting seemingly promising but unfamiliar vendors, identified through the eProcurement mechanism. The purchasing corporations need to implement a systematic framework to identify, and assess the risks associated with their vendor choices, that is, the vendor risk, and even to memorize their collective experience on risk analysis, while they try to gain benefits from the practice of the eProcurement strategy.; Although there are several solutions available in the industry to manage the vendor risk confronting corporate purchasers in their practices of traditional procurement mechanism, they are not widely accepted among industries practicing the traditional procurement mechanism. Moreover, they are unfeasible to be implemented in the eProcurement mechanism. They rely heavily on self-assessment data provided by vendors or transaction records from purchasing departments, and there is a lack of a systematic approach to accumulate the collective experience of the corporation in vendor risk management.; This study proposes the establishment of the Vendor Risk Analysis (VRA) system to assist procurement officers in vendor risk analysis as a support to their decision of seeking promising vendors over the Internet. The VRA system adopts a Semantic-Assisted Risk Analysis (SARA) framework to implement an innovative approach in the implementation of risk assessment. The SARA framework deploys the collaboration of a knowledge-based Expert System and several emerging semantic technologies, including Information Extraction, a Community Template Repository, and a Semantic Platform for Information Indexing and Retrieval, to enhance the capability of the VRA system in the capability of acquiring sufficient risk evidence over the Internet to provide timely and reliable risk assessment support to vendor choice decisions.; The structure for the establishment of the semantic application identified in this study can be generalized as the common framework for developing an automatic information extractor to acquire Internet content as the support for making important business decisions. The structure is composed of three basic components: (1) an information collection method to identify specific information over the Internet through the deployment of semantic technology, (2) an ontology repository to associate the collected data and the specific data schema, and (3) a scheme to associate the data schema with the analytical methods which would be deployed to provide decision support.; Moreover, the risk cause taxonomy identified in this study lays out the theoretical grounds for the development of any software applications relating to the deployment of risk perceptions held by procurement professionals and practitioners.