13 Transcending the Loading Dock Paradigm—Rethinking …
253
Despite a variety of usage contexts, transfer can be defined as a “transmission” of information or objects between a sender and a receiver, some of which
operate in specific contexts. In application-oriented research, transfer is conventionally equated with the transfer of research results to potential users. In this context,
transfer becomes an instrument that appears in the context of innovation and diffusion
research (Schröder et al. 2011).
In applied science, aspects of T&I have been the focus of numerous empirical
studies on the diffusion of innovations since the 1920s and 1930s. Since then,
mainly application-related disciplines, such as engineering and technical sciences,
medicine and geography have addressed questions relating to T&I research. The
aims of research activities include the systematic analysis of transfer conditions and
modelling approaches (Gräsel et al. 2006: 479).
From the perspective of research on T&I, different approaches have been
developed. Of particular note here are actor-centred approaches, which operate
with a typology of persons (groups) in the diffusion process. According to these
approaches, innovations by persons or groups of people are adapted at different
speeds (Hägerstrand 1952; Rogers 1995). Another approach, based on the findings
of the network theory, considers actors as objects in a superordinate social network
whose connections are of central importance (see, for example, Granovetter 1973).
A third model that has been widely adapted in German innovation policy (Blümel
2016) is the linear model of technology push or science push (based on Bush (1945)).
According to this model, innovations go through a gradual evolution that ranges from
basic research, through applied research, to product development and innovation.
This model is also based on unidirectional knowledge transfer, which understands
“society” as the addressee of scientific results.
The principle of unidirectional transfer was dominant in the past (between the
1960s and the 1990s), but increasingly came under criticism. Cash et al. (2006) used
the metaphor of the “loading dock” of science transfer to describe its deficiencies.
According to this term, scientists perform their research activities in a house (with an
adjacent loading dock) that symbolises academia. At the end of the research cycle,
the results are eventually stored as readymade “information packages” or “products”
on a dock and made available to potential end users: “You take it out there, and you
leave it on the dock and you say, there it is. And then you walk away and go back
inside” (ibid. 484). This approach is based on the premise that the information that
reaches the recipient triggers appropriate action, or that research results are adapted
from the practical side.
In the field of science communication, this phenomenon is also known as the
“information deficit model”, which attributes public scepticism to science to a lack
of understanding, resulting from a lack of information. In science-based consultancy,
an artificial separation of scientific information from policymaking was promoted by
its clients (Weith 2011) and thus manifested the inherent logic of the loading dock
metaphor.
The loading dock approach underlines the notion of a purely knowledgedriven science which, as the sole knowledge producer, remained separate from the
application-relevant areas of knowledge (“policy knowledge”). It not only leaves
253
Despite a variety of usage contexts, transfer can be defined as a “transmission” of information or objects between a sender and a receiver, some of which
operate in specific contexts. In application-oriented research, transfer is conventionally equated with the transfer of research results to potential users. In this context,
transfer becomes an instrument that appears in the context of innovation and diffusion
research (Schröder et al. 2011).
In applied science, aspects of T&I have been the focus of numerous empirical
studies on the diffusion of innovations since the 1920s and 1930s. Since then,
mainly application-related disciplines, such as engineering and technical sciences,
medicine and geography have addressed questions relating to T&I research. The
aims of research activities include the systematic analysis of transfer conditions and
modelling approaches (Gräsel et al. 2006: 479).
From the perspective of research on T&I, different approaches have been
developed. Of particular note here are actor-centred approaches, which operate
with a typology of persons (groups) in the diffusion process. According to these
approaches, innovations by persons or groups of people are adapted at different
speeds (Hägerstrand 1952; Rogers 1995). Another approach, based on the findings
of the network theory, considers actors as objects in a superordinate social network
whose connections are of central importance (see, for example, Granovetter 1973).
A third model that has been widely adapted in German innovation policy (Blümel
2016) is the linear model of technology push or science push (based on Bush (1945)).
According to this model, innovations go through a gradual evolution that ranges from
basic research, through applied research, to product development and innovation.
This model is also based on unidirectional knowledge transfer, which understands
“society” as the addressee of scientific results.
The principle of unidirectional transfer was dominant in the past (between the
1960s and the 1990s), but increasingly came under criticism. Cash et al. (2006) used
the metaphor of the “loading dock” of science transfer to describe its deficiencies.
According to this term, scientists perform their research activities in a house (with an
adjacent loading dock) that symbolises academia. At the end of the research cycle,
the results are eventually stored as readymade “information packages” or “products”
on a dock and made available to potential end users: “You take it out there, and you
leave it on the dock and you say, there it is. And then you walk away and go back
inside” (ibid. 484). This approach is based on the premise that the information that
reaches the recipient triggers appropriate action, or that research results are adapted
from the practical side.
In the field of science communication, this phenomenon is also known as the
“information deficit model”, which attributes public scepticism to science to a lack
of understanding, resulting from a lack of information. In science-based consultancy,
an artificial separation of scientific information from policymaking was promoted by
its clients (Weith 2011) and thus manifested the inherent logic of the loading dock
metaphor.
The loading dock approach underlines the notion of a purely knowledgedriven science which, as the sole knowledge producer, remained separate from the
application-relevant areas of knowledge (“policy knowledge”). It not only leaves