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This chapter adopts a problem-solving perspective to analyze the competitive dynamics of innovation ecosystems. We argue that features such as uncertainty, complexity, and ambiguity, entail different knowledge requirements which explain the varying abilities of focal firms to coordinate the ecosystem and benefit from the activities of their suppliers, complementors, and users. We develop an analytical framework to interpret various instances of coupling patterns and identify four archetypical types of innovation ecosystems.

We develop an experimental setting where the assumptions and predictions of the garbage can model can be tested. A careful reconstruction of the original simulation model let us select parameters that leave room for potential variations in individual behavior. Our experimental design replicates these parameters and thereby facilitates comparison of human behavior with the original model. We find that the majority strategy of human subjects is consistent with the original model, but exhibits some behavioral diversity. Human subjects exhibit fluid diverse behaviors that improve coordination in the face of uncertainty, but hinder collective learning that can improve group performance.

In recent years, the concept of “reification” has virtually disappeared from debates in social theory, including critical social theory. The concept was at the center of the revitalization of Marxist theory in the early twentieth century generally known as Western Marxism. Georg Lukács in particular introduced the concept to express how the process described in Marx's critique of alienation and commodification could be grasped more effectively by combining it with Max Weber's theory of rationalization (see Agger, 1979; Stedman Jones et al., 1977).¹ In Lukács's use, the concept of reification captured the process by which advanced capitalist production, as opposed to earlier stages of capitalist development, assimilated processes of social, cultural, and political production and reproduction to the dynamic imperatives and logic of capitalist accumulation. It is not just interpersonal relations and forms of organization constituting the capitalist production process that are being refashioned along the lines of one specific definition of economic necessity. In addition, and more consequentially, the capitalist mode of production also assimilates to its specific requirements the ways in which human beings think the world. As a result, the continuous expansion and perfection of capitalist production and its control over the work environment impoverishes concrete social, political, and cultural forms of coexistence and cooperation, and it brings about an impoverishment of our ability to conceive of reality from a variety of social, political, and philosophical viewpoints.

This study employs multiple measures of schema acquisition and analyzes subjects' problem-solving error patterns in order to investigate schema acquisition by decision aid users. Results of both the error analysis and multiple schema acquisition measures indicate that: (1) problems of ordered complexity can effectively capture differences in schema acquisition of decision aid users; and (2) problem solvers rely on incorrect simple schemata to solve problems when they have not acquired the complex schemata necessary to solve a problem. The results also provide additional support for prior findings that problem-solving schemata are acquired in a linear order flowing from computationally simple problems to more complex problems, and that cognitive load interferes with the acquisition of schemata from decision aids.

For Weberian Marxists, the social theories of Max Weber and Karl Marx are complementary contributions to the analysis of modern capitalist society. Combining Weber's theory of rationalization with Marx's critique of commodity fetishism to develop his own critique of reification, Georg Lukács contended that the combination of Marx's and Weber's social theories is essential to envisioning socially transformative modes of praxis in advanced capitalist society. By comparing Lukács's theory of reification with Habermas's theory of communicative action as two theories in the tradition of Weberian Marxism, I show how the prevailing mode of “doing theory” has shifted from Marx's critique of economic determinism to Weber's idea of the inner logic of social value spheres. Today, Weberian Marxism can make an important contribution to theoretical sociology by reconstituting itself as a framework for critically examining prevailing societal definitions of the rationalization imperatives specific to purposive-rational social value spheres (the economy, the administrative state, etc.). In a second step, Weberian Marxists would explore how these value spheres relate to each other and to value spheres that are open to the type of communicative rationalization characteristic of the lifeworld level of social organization.

In this chapter, we consider how neuroscience methods can enhance the study of team processes, as well as facilitate the development of teams. We overview exciting new neuroscience technology that can be applied to the assessment of teams in real time. While research that has already used this technology to study team engagement and workload is summarized, we also consider other team-based concepts to which it might be applied, such as groupthink and shared mental models. We further suggest that emotional contagion and neurological mirroring concepts can come together to help us form a better understanding of emotions and their effects in teams. We conclude the chapter with a consideration of how neurological methods can potentially help develop team processes and provide insights for both members and team leaders.

A current vision of education in America today is that all students be science literate. To accomplish this, educators and teachers need to be aware of the challenges involved in promoting science literacy: science literacy encompasses a wide range of knowledge, including construction of knowledge, use of that knowledge, and recall of critical facts necessary to apply scientific information in the world today. In addition, teachers and educators need a knowledge of the issues of “inclusion” since students of diverse abilities, including those with disabilities and others at risk for school failure, are being educated, as much as possible, in general education classrooms taught by content experts.

A bridge to span the gap between the challenges of science literacy for all students and the complexities of student diversity is Content Enhancement – instruction that responds to the needs of students of diverse abilities while maintaining content integrity by focusing on the critical information that all students need to know. In Content Enhancement, the teacher helps students learn by organizing information, providing explicit instruction when necessary, and assuring that students are active partners with the teacher and other students in the construction of knowledge. Graphic organizers and instructional sequences have been developed to help teachers organize information at the course, unit and lesson levels; learn to answer large, difficult questions with ideas that can be generalized to other settings; explore and manipulate knowledge by developing analogies and comparisons; and respond to assessments.