Six Sigma has been gaining momentum in industry; however, academics have conducted little research on this emerging phenomenon. Understanding Six Sigma first requires providing a conceptual definition and identifying an underlying theory. In this paper we use the grounded theory approach and the scant literature available to propose an initial definition and theory of Six Sigma. Our research argues that although the tools and techniques in Six Sigma are strikingly similar to prior approaches to quality management, it provides an organizational structure not previously seen. This emergent structure for quality management helps organizations more rigorously control process improvement activities, while at the same time creating a context that enables problem exploration between disparate organizational members. Although Six Sigma provides benefits over prior approaches to quality management, it also creates new challenges for researchers and practitioners. # 2007 Published by Elsevier B.V.

Several quality thought leaders have considered the role of knowledge in quality management practices. For example, Deming proposed The Deming System of Profound Knowledge TM that dealt explicitly with knowledge. However, various authors in the quality field diverge considerably when contemplating knowledge. We propose an integrated view of quality and knowledge using Nonaka's theory of knowledge creation. This integrated view helps illuminate how quality practices can lead to knowledge creation and retention. The knowledge perspective also provides insight into what it means to effectively deploy quality management practices. Previous empirical research noted the importance of effective deployment, but provided little insight into what effective deployment means. This research argues that quality management practices create knowledge, which leads to organizational performance. Taking a knowledge-based view (KBV) of the firm provides a deeper understanding of why some organizations are more successful at deploying quality management practices than others. #

Purpose -Recently, benchmarking has become a common approach to optimize production processes by comparing certain aspects of a company with its competitors. However, one of the biggest challenges is not only to define suitable benchmarking topics and partners, to gather and statistically evaluate characteristic data, but to derive concrete measures to interpret the results, i.e. to overcome the revealed weaknesses. The purpose of this paper is to present an already implemented and successfully used functional benchmarking methodology for production performance of small and medium batch size processes, that is currently extended by using a knowledge base for reasoning strategies to semi-automatically support the interpretation of the extracted statistical data. Design/methodology/approach -A comprehensive approach is presented to develop a new model for the evaluation of a small to medium-sized enterprise's production performance using an existing European database called BETT Benchmark. Findings -The knowledge-based concept enables sophisticated interpretation strategies to be used on an already existing base of real company data. The decisive point of the approach presented is to map production variables on room for improvement by taking varying parameters into account. Originality/value -The proposed tool is a valuable tool that takes advantage of a statistically firmed analysis of a substantial database and combines it with the comprehensive expertise of experienced specialists in the field of performance assessment.

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