social sustainability, supplier selection, emerging markets, international sourcing, stakeholder theory,

Intangibles are becoming increasingly important to the scientific community as well as the business world. This is mainly due to a highly competitive business environment combined with exceptionally limited resources and the growing importance of knowledge as a commodity. The fluctuating differences between market and book values of companies indicate the extent of the intangibles' rising importance. By focusing on major publications since 1997, this paper critically analyzes current trends and differing views in this field. The publications are analyzed according to their content and methodologies. Review of the literature clearly shows that most publications in this area still lack a theoretical foundation. A large number of differing terms and definitions are present. Much of the literature analyzed here also fails to provide detailed suggestions for the management of intangibles, be they theory-based or empirically-derived. Discussion of these issues generally remains on a very abstract level. Research on intangibles is characterized by a large variety of views and interpretations -dominant schools of thought have yet to develop. This situation offers much opportunity for further research in this important field of management.

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PurposeThe purpose of this paper is to review and integrate the extensive literature base which examines judgment and decision‐making biases, to introduce this literature to the field of supply management, to create a valid, mutually exclusive, and exhaustive taxonomy of decision biases that can affect supply managers, and to provide guidance for future research and applications of this taxonomy.Design/methodology/approachThe authors use a qualitative cluster analysis, combined with a Q‐sort methodology, to develop a taxonomy of decision biases.FindingsA mutually exclusive, and exhaustive taxonomy of nine decision biases is developed through a qualitative cluster analysis. The Q‐sort methodology provides initial confirmation of the reliability and validity of the cluster analysis results. The findings, along with numerous examples provided in the text, suggest that supply management decisions are vulnerable to the described biases.Originality/valueThis paper provides a comprehensive review of the judgment and decision bias literature, and creates a logical and manageable taxonomy of biases which can impact supply management decision making. The introduction and organization of this vast extant literature base provides a contrasting perspective to much of the existing supply management research, which has incorporated the assumption of the rational agent, or what is known in the economics literature as homo economicus. In addition, the authors describe the use of qualitative cluster analysis and the Q‐sort methodology, techniques which have been used rarely if at all in within the field of supply chain management.