Page 71 - Global Project Management Handbook

3-6 STATE OF THE ART OF GLOBAL PROJECT MANAGEMENT

However, it is necessary to build on this convergence. The reluctance of the qualitativists
to use statistical analysis must be overcome, and on the other hand, the materials collected
and their application must contribute to a theoretically defensible concept of science
(Callon et al., 1986b).
Built on the actor-network theory, and as a consequence of interaction between actor
networks, resulting structure of problems, and networks of problematization (Callon et al.,
1986a), the coword-analysis technique was first proposed to map the dynamics of sci-
ence. The most feasible way to understand the dynamics of science is to take the force of
science in present-day societies into account. Actor network is the theoretical foundation
for coword analysis to map the dynamics of science. Laboratories and the literature are
considered as two powerful tools for scientists to change the world. They build complex
worlds in laboratories and enforce them on paper (Latour, 1987). This implies that scien-
tists attach particular importance to texts. They use texts not only to publish their world
built in the laboratory but also as a way to build a world and enroll others. Even though
science cannot be reduced to texts alone, texts are still a prime source for studies on how
worlds are created and transformed in the laboratory. Therefore, instead of following the
actors to see how they change the world, following the texts is another way to map the
dynamics of science.
Based on the co-occurrence of pairs of words, coword analysis seeks to extract the
themes of science and detect the linkages among these themes directly from the subject
content of the texts. It does not rely on any a priori definition of themes in science. This
enables us to follow actors objectively and detect the dynamics of science without reduc-
ing them to the extremes of either internalism or externalism (Callon et al., 1986b).
Overall, coword analysis considers the dynamics of science as a result of actor strategies.
Changes in the content of a subject area are the combined effect of a large number of
individual strategies. This technique should allow us in principle to identify the actors
and explain the global dynamics (Callon et al., 1991).

Coword Analysis Method

Coword analysis is a content-analysis technique that uses patterns of co-occurrence of
pairs of items (i.e., words or noun phrases) in the corpus of texts to identify the rela-
tionships between ideas within the subject areas as presented in these texts. Indexes

based on the co-occurrence frequency of items, such as an inclusion index and a prox-
imity index, are used to measure the strength of relationships between items. Based on
these indexes, items are clustered into groups and displayed in network maps. Some
other indexes, such as those based on density and centrality, are employed to evaluate
the shape of each map, showing the degree to which each area is centrally structured
and the extent to which each area is central to the others. By comparing the network
maps for different time periods, the scientific dynamic can be detected. For about 25
years, this technique has been employed to map the dynamic development of several
research fields.
Many examples (Turner and Callon, 1986; Callon, 1986; Courtial and Law, 1989;
Law and Whittaker, 1992; Coulter et al., 1998) reveal that coword analysis is a promis-
ing method for discovering associations among research areas in science and for
revealing significant linkages that otherwise may be difficult to detect. It is a powerful
tool that makes it possible to trace the structure and evolution of a sociocognitive net-
work (Bauin, 1986). As such, it offers a significant approach to knowledge discovery.
The following paragraphs introduce the main metrics used in this study. A more
detailed presentation of the metrics employed in coword analysis can be found in He
(1999).