Institutionalization and Structuration: Studying the Links between Action and Institution

Institutional theory and structuration theory both contend that institutions and actions are inextricably linked and that institutionalization is best understood as a dynamic, ongoing process. Institutionalists, however, have pursued an empirical agenda that has largely ignored how institutions are created, altered, and reproduced, in part, because their models of institutionalization as a process are underdeveloped. Structuration theory, on the other hand, largely remains a process theory of such abstraction that it has generated few empirical studies. This paper discusses the similarities between the two theories, develops an argument for why a fusion of the two would enable institutional theory to significantly advance, develops a model of institutionalization as a structuration process, and proposes methodological guidelines for investigating the process empirically

Science and Technology Studies: Exploring the Knowledge Base

Science and Technology Studies (STS) is one of a number of new research fields to emerge over the last four or five decades. This paper attempts to identify its core academic contributions using the references that are most cited by the authors of chapters in a number of authoritative ‘handbooks’. The study then analyses the impact of these contributions by exploring the research fields, journals, and geographical location of the researchers that have cited these core contributions in their own work. Together, these two analyses reveal the various phases in the development of STS and the various aspects of convergence and divergence of the field as the quantitative studies of science and technology gradually separated from the main body of STS. The paper ends with some conclusions about the evolution of STS such as the role of ‘institution builders’ in developing new research fields and the structures required to hold them together.science studies, STS, knowledge base, handbooks, core contributions

How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures

In scientometric research, the use of co-occurrence data is very common. In many cases, a similarity measure is employed to normalize the data. However, there is no consensus among researchers on which similarity measure is most appropriate for normalization purposes. In this paper, we theoretically analyze the properties of similarity measures for co-occurrence data, focusing in particular on four well-known measures: the association strength, the cosine, the inclusion index, and the Jaccard index. We also study the behavior of these measures empirically. Our analysis reveals that there exist two fundamentally different types of similarity measures, namely set-theoretic measures and probabilistic measures. The association strength is a probabilistic measure, while the cosine, the inclusion index, and the Jaccard index are set-theoretic measures. Both our theoretical and our empirical results indicate that co-occurrence data can best be normalized using a probabilistic measure. This provides strong support for the use of the association strength in scientometric research

Innovatics – a new toolbox of skills for innovative production managers

We describe a metaphorical “toolbox” for innovatics – a new set of skills for managers who specialize in innovation management and in the study of innovations. We emphasize the importance of quantitative skills, multidisciplinary inspirations and heuristic methods for generatig innovative solutions. Knowledge of organizational behavior is essential to create in the workplace environment conducive to innovativeness