Srinivasan Ragothaman

The ISO 9000 international quality registration: An empirical analysis of implications for business firms

Abstract The purpose of this article is to explore managerial perceptions of ISO 9000 standards. Previous surveys found general agreement that ISO 9000 registration influenced supplier selection, improved customer satisfaction, and enhanced operating efficiency. The present survey of production managers in 212 U.S. locations gathered data related to the perceived impact of registration on their businesses. Data analysis suggests strong agreement with benefits provided by improved documentation, the use of ISO 9000 as a marketing tool and greater export potential as a result of implementing these standards. Respondents did not agree that ISO 9000 provides positive benefits in product development or reduces production time. Annual sales were included to determine if there is a difference in perceived impacts based on firm size. Managers of smaller firms held a stronger belief that ISO 9000 registration results in cost reduction and increases export potential than did large firm managers. Small firms with less well developed export connections may find ISO 9000 registration useful in helping to establish a reputation that will help make the necessary connections in the export markets. The improvements in documentation of products and process may highlight areas of potential production efficiencies and possible cost reductions.

Using rule induction for knowledge acquisition: An expert systems approach to evaluating material errors and irregularities

Abstract There has been a significant increase in the magnitude of material errors discovered in financial statements during the 1980s. Auditors, financial analysts, and regulators have shown considerable interest in evaluating and predicting these material errors. This paper describes the development and validation of a prototype expert system, ERRORXPERT, which evaluates material errors and potential fraud. This prototype system is designed to assist auditors at the planning stage in the design of subsequent substantive tests, when material errors and irregularities in the financial statements are probable. A commercial machine learning program was used for rule induction. A set of training examples comprising error and non-error firms was used to generate rules and a separate holdout sample was used to validate the expert system results. The performance of the expert system was also compared to that of a multiple discriminant analysis model using the same data. The results demonstrate that the expert system, ERRORXPERT, outperforms the discriminant model and is a powerful evaluation tool to classify firms into error and non-error categories. The size of the sample used in this study somewhat limits the generalizability of the specific rules.

Predicting Corporate Acquisitions: An Application of Uncertain Reasoning Using Rule Induction

Artificial Intelligence (AI)-based rule induction techniques such as IXL and ID3 are powerful tools that can be used to classify firms as acquisition candidates or not, based on financial and other data. The purpose of this paper is to develop an expert system that employs uncertainty representation and predicts acquisition targets. We outline in this paper, the features of IXL, a machine learning technique that we use to induce rules. We also discuss how uncertainty is handled by IXL and describe the use of confidence factors. Rules generated by IXL are incorporated into a prototype expert system, ACQTARGET, which evaluates corporate acquisitions. The use of confidence factors in ACQTARGET allows investors to specifically incorporate uncertainties into the decision making process. A set of training examples comprising 65 acquired and 65 non-acquired real world firms is used to generate the rules and a separate holdout sample containing 32 acquired and 32 non-acquired real world firms is used to validate the expert system results. The performance of the expert system is also compared with a conventional discriminant analysis model and a logit model using the same data. The results show that the expert system, ACQTARGET, performs as well as the statistical models and is a useful evaluation tool to classify firms into acquisition and non-acquisition target categories. This rule induction technique can be a valuable decision aid to help financial analysts and investors in their buy/sell decisions.