In an increasingly volatile and complex market environment, adaptability becomes essential to success. Basic to every manufacturing strategy is the identification of the technological means of meeting the firm's competitive priorities. But what should guide the decision-making process regarding which capabilities to develop, given rapid change and uncertain outcomes? Current manufacturing strategy models fall short of explaining how firms adapt to technological change and what is the source of that change. To meet this need, we can turn to evolutionary economics. The model presented in this paper holds that technologically embodied trade-offs change the practices of technology users, creating momentum along existent trajectories. The paper reports evidence to support the model, gathered through a series of interviews with technology users, suppliers, and service providers. The findings indicate that manufacturing strategy forms a critical link not only in firms' ability to adapt to change in their environments, but also in their ability to knowingly shape their futures.

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In the early 1990s, community indicators gained currency as a principal means of turning visions of sustainability into action. In the intervening years, indicator projects have been launched by communities the world over to guide and measure progress towards sustainability, but their effectiveness in serving this purpose has also been questioned. These critiques have focused attention on how information is organized within indicator systems in addition to the content and quality of the information itself. This case study draws on the work of Sustainable Seattle, an early pioneer in developing community indicators through participatory processes, to create a next-generation sustainability indicators system, the BSustainable Information Commons. The study aims to make the framework's design explicit according to its purposes by reflexively analyzing the design in relation to the theory and practice of framework development. The framework's most ambitious goal is to stimulate "information flows" that will lead to collective understandings of emerging sustainability patterns.

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