This article examines how knowledge management (KM) affects innovation performance within biotechnology firms. This is an industry in which small- and medium-sized biotech enterprises live together with the biotech divisions of large pharmaceutical firms. We conceptualize KM as a set of practices and dynamic capabilities, and hypothesize that KM dynamic capabilities act as a mediating variable between KM practices and innovation performance. We use structural equation modelling to test the hypotheses on a data set from the biotechnology industry. The results support our conceptualization and demonstrate its utility in explaining differences in innovation performance across firms. Findings have important implications regarding KM and innovation in high-tech small- and medium-sized enterprises.

Although knowledge management has been investigated in the context of decision support and expert systems for over a decade, interest in and attention to this topic have exploded recently. But integration of knowledge process design with knowledge system design is strangely missing from the knowledge management literature and practice. The research described in this chapter focuses on knowledge management and system design from three integrated perspectives: 1) reengineering process innovation, 2) expert systems knowledge acquisition and representation, and 3) information systems analysis and design. Through careful analysis and discussion, we integrate these three perspectives in a systematic manner, beginning with analysis and design of the enterprise process of interest, progressively moving into knowledge capture and formalization, and then system design and implementation. Thus, we develop an integrated approach that covers the gamut of design considerations from the enterprise process in the large, through alternative classes of knowledge in the middle, and on to specific systems in the detail. We show how this integrated methodology is more complete than existing developmental approaches and illustrate the use and utility of the approach through a specific enterprise example, which addresses many factors widely considered important in the knowledge management environment. Using the integrated methodology that we develop and illustrate in this article, the reader can see how to identify, select, compose and integrate the many component applications and technologies required for effective knowledge system and process design.

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Studies conducted in recent years have shown that outcome feedback in dynamic decision-making tasks does not lead to improved performance. This has led researchers to examine alternatives to outcome feedback for improving decision makers' performance in such tasks. This study examines the feasibility of improving performance in dynamic tasks by providing cognitive feedback or feedforward. We report a laboratory experiment in which subjects managed a set of simulated software development projects. Results indicate that subjects provided with cognitive feedback performed best, followed by those provided with feedforward. Subjects provided with outcome feedback performed poorly. We discuss the implications of the results for decision support in dynamic tasks.dynamic decision making, decision support systems, cognitive feedback, feedforward, outcome feedback, software project management

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