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Decision support systems for farm management: a theoretical framework from the sociology of science and technology.

Emma Jakku, Peter Thorburn and Clare Gambley

Tropical Landscapes Program, CSIRO Sustainable Ecosystems, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia
QLD 4067 Email, and


This paper identifies some key elements of a theoretical framework based on concepts from the sociology of science and technology in order to examine the social dimensions of the development of decision support systems (DSSs) for farm management. In particular, this paper introduces three sociological concepts that are useful for analysing new and complex technologies: interpretive flexibility, technological frames and boundary objects. Each of these concepts provides an interesting perspective on the social factors that influence the design and implementation of DSSs. This paper highlights the importance of the relationship between researchers and stakeholders and the complexity of the socio-technical system within which DSSs for farm management are developed.

Media summary

Theories from the sociology of science and technology can extend our understanding of the social context of the development of DSSs for farm management.

Key words

Interpretive flexibility, technological frames, boundary objects, diffusion, participatory action research


The application of DSSs to farm management involves a range of opportunities and challenges. McCown (2002a, p. 180) captures the fundamental appeal of DSSs, which is based on the search for technology that can make “agricultural systems science more accessible and useful for guiding management of production systems.” The challenge is that the rate of adoption of these DSSs has disappointed the researchers responsible for developing them (McCown, 2002a). There is a need to increase our understanding of these new and complex innovations, especially if we want to find the most effective mode of delivery of these DSSs. This paper proposes that a theoretical framework based on insights from the sociology of science and technology has the potential to further our understanding of the challenges associated with developing DSSs for improved management of farming systems, which we will subsequently refer to as farm management. The paper begins with some background on DSSs and then briefly reviews the literature on diffusion and participatory action research (PAR). The paper then introduces the sociology of science and technology and identifies three concepts from this literature that offer some interesting perspectives on technological innovation. The paper concludes by identifying how the sociology of science and technology can enhance our understanding of DSSs for farm management.

Decision support systems for farm management

Adelman (1992, p. 2) defines DSSs as “interactive computer programs that utilize analytic methods…for developing models to help decision makers formulate alternatives, analyze their impacts, and interpret and select appropriate options for implementation.” McCown (2002b, p. 19) notes that the idealised concept of DSSs is “easy-to-use software on a computer readily accessible to a manager to provide interactive assistance in the manager’s decision process.” However, he notes that the application of DSSs is much more complicated. McCown (2002a) develops a socio-technical conceptual framework to examine this complexity and identifies the literature on diffusion and PAR as providing some important background to the challenge of applying DSSs to farm management. The next sections briefly review this literature.

Diffusion and adoption of innovations

Rogers (1995, p. 35) defines diffusion as “the process by which an innovation is communicated through certain channels over time among members of a social system.” The identification of factors that determine the rate of adoption is a key theme within the literature. Much of the literature on diffusion is dedicated to investigating how these factors either enable or constrain the adoption of innovations. Diffusion research has been criticised for its pro-innovation bias and its tendency to ‘blame the individual’ for non-adoption, by focusing on individual characteristics of decision-makers (Rogers, 1995). Diffusion research has also been criticised on methodological grounds, such as whether respondents can accurately recall the time that they decided to adopt an innovation (Rogers, 1995). Finally, diffusion research has received criticism for neglecting the socio-economic impacts of innovations (Fliegel & Korsching, 2001). Therefore, although diffusion research can provide some insights into technological change, it is important to be aware of its limitations. The next section focuses on PAR, which has the potential to complement diffusion research.

Theory and practice of participatory action research

PAR has received an increasing level of attention as a means of enhancing the relevance and impact of research. Parkes and Panelli (2001, p. 87) note that PAR involves “forms of inquiry where researchers and the researched population form collaborative relations in order to identify and address mutually conceived issues or problems through cycles of action and research.” Table 1 illustrates the relationship between researchers and stakeholders in different modes of research. PAR should be characterised by collaborative or collegiate relationships between researchers and stakeholders (Cornwall & Jewkes, 1995). The trend towards the increased use of PAR has influenced the development of DSSs. One example of this trend is the FARMSCAPE project, which used PAR to investigate “whether farmers could value simulation as a decision support tool for managing their farming systems…” (Carberry et al., 2002, p. 141). Their central assumption was that “science can not research management of agricultural systems without meaningful participation of systems managers” (Carberry et al., 2002, p. 144).

Table 1: Typology of participation

Mode of participation

Involvement of local/researched people

Relationship of research to people


Token representatives are chosen but there is no real local input or power sharing.



People are contracted into the projects of researchers to take part in the enquiries or experiments, but researchers decide the agenda and direct the actions.



Local opinions are sought before interventions are made, but researchers analyse and decide on the best course of action.



Local people work together with researchers to determine priorities but the responsibility for designing, initiating and managing the research process remains with the researchers.



Local people and researchers work together as colleagues with different skills and knowledge to offer, in order to create action plans based on mutual learning, where local people have control over the research process.


Collective action

Local people set their own agenda and mobilise to carry it out in the absence of outside initiators and with or without outside facilitators.


Sources: Modified from Biggs (1989, p. 3), Cornwall and Jewkes (1995, p. 1669) and Parkes and Panelli (2001, p. 88).

Cornwall and Jewkes (1995) provide an overview of the challenges associated with PAR. For instance, PAR is a time consuming process. Not everyone in a local community will be willing or able to participate and local interest will rise and fall throughout the process. The ‘local community’ is rarely a well-defined, homogenous or integrated entity. There is the danger that researchers can raise false hopes about the research outcomes or that the research can have unintended negative consequences. Researchers may find it difficult to reconcile the process of PAR with the demands of their funding agencies for particular kinds of outputs and outcomes. Conventional researchers may regard PAR as lacking in rigour and reliability. Nevertheless, Cornwall and Jewkes (1995) argue that PAR is worth aspiring to. Ultimately, PAR is based on an attitude that recognises the importance of “respecting and understanding the people with and for whom researchers work” (Cornwall & Jewkes, 1995, p. 1674). Therefore, PAR raises some interesting questions about the relationship between expert and local knowledge and the implications of different perceptions of and attitudes towards technological innovations. The literature on the sociology of science and technology can provide some valuable insights into these issues.

Sociology of science and technology

The sociology of science and the sociology of technology are sub-disciplines of the sociology of knowledge. Social constructionism is a common theme that unites much of the work in this area. Berger and Luckmann (1967) develop a social constructionist framework for understanding knowledge systems as products of human activity. The sociology of science and technology provides a range of useful conceptual tools that can extend our understanding of the socio-technical processes involved in developing complex technologies, such as DSSs. The concepts of interpretive flexibility, technological frames and boundary objects are particularly useful as a framework for analysing the design and implementation of technological innovations.

Interpretive flexibility

The concept of interpretive flexibility captures the simple idea that any object can mean different things to different people. When applied to the issue of technological change, interpretive flexibility describes the way in which a specific technology can be interpreted in multiple and diverse ways by different social groups. Pinch and Bijker (1987, p. 28) develop a “multidirectional” model to examine the history of the development of the bicycle. They trace the variation in the early designs of the bicycle and explore how these different designs were based on the needs and priorities of different social groups. For instance, young men who valued speed and saw bicycling primarily as a sport favoured high-wheeled designs, whereas women and older men placed more emphasis on safety and favoured low-wheeled designs. Variations in bicycle design remain today. For instance, mountain bikes, racing bikes and road bikes are designed to cater for different kinds of users who ride bikes for different reasons. Interpretive flexibility therefore highlights the way in which the design and implementation of technologies is not solely a technical issue, since there are a range of social factors that influence the choices that are made in this process (Williams & Edge, 1996, p. 260).

Technological frames

Orlikowski and Gash (1994, p. 178) explain that technological frames “are the understandings that members of a social group come to have of a particular technology”, which includes the “local understanding of specific uses” of that technology. Thus, the theory of technological frames builds on the concept of interpretive flexibility to examine the way in which the basic assumptions, beliefs and expectations that people hold about a specific technology influence the design and use of that technology. Orlikowski and Gash (1994, p. 183-184) identify three important dimensions of technological frames: Nature of technology, which refers to people’s perceptions and understanding of the technology; Technology strategy, which refers to people’s views of why their organisation acquired and implemented the technology; and Technology in use, which refers to people’s understanding of how the technology will be used and the likely or actual conditions and consequences associated with such use. These three dimensions of technological frames provide a useful platform for analysing different social group’s perceptions of the design and implementation of new technologies. Therefore, technological frames capture how people interpret the meaning and value of a particular technology, their views on whether it should be implemented and if so, why it should be implemented and how it can be used to create a change in behaviour and practice.

Boundary objects

The concept of boundary objects adds another dimension to the issue of technological innovations. Star and Griesemer (1989) developed the concept of boundary objects in their study of a museum of vertebrate zoology. They define boundary objects as “objects which are plastic enough to adapt to local needs and constraints of the several parties employing them, yet robust enough to maintain a common identity across sites” (Star & Griesemer, 1989, p. 393). Harvey and Chrisman (1998) examine how GIS technology can act as a boundary object. This is an interesting case study, since the challenge of designing and implementing DSSs appears similar to those faced in the development of GIS technology. Harvey and Chrisman (1998, p. 1693) use the concept of boundary objects to understand how GIS technology “exists as part of an intricate web of social relations”, through which the diverse interest of scientists, policy specialists, various institutions and concerned citizens are linked. Therefore, by providing a common ‘talking point’, the GIS technology that they studied became a boundary object, since it facilitated cooperation between different social groups. Therefore, by highlighting the ways in which cooperation between multiple groups can still occur despite the fact that different social groups can hold diverse perceptions of a particular technology, the concept of a boundary object addresses the challenge of how to manage interpretive flexibility and differences in technological frames.

Discussion and conclusions

McCown (2002a, 2002b) develops a socio-technical conceptual framework to examine the ongoing ‘problem of implementation’ of information systems. This paper has suggested ways in which the sociology of science and technology can add another dimension to our understanding of how social factors influence the design and use of DSSs. To successfully implement new and complex technologies, we need to understand the complexity of the socio-technical system that DSS design and implementation occurs within. The concepts of interpretive flexibility, technological frames and boundary objects provide different perspectives on the socially constructed nature of technologies such as agricultural DSSs. When combined, these concepts offer a theoretical framework that encourages critical reflection on the way in which DSSs might be more effectively developed in partnership with relevant stakeholders, which could in turn improve the impact of these new technologies. The concepts of interpretive flexibility and technological frames increase our understanding of the way in which different people will perceive and interact with DSSs in different ways. The theory on boundary objects highlights the way in which a technology can help develop cooperative relationships between diverse social groups. For instance, DSSs designed to improve farm management can act as a talking point between scientists, farmers and other relevant stakeholders. The cooperative development of such technologies can improve working relationships between these groups and foster co-learning, providing a better understanding of farm management for both the scientists and farmers involved in developing the technology. Thus, the idea that a DSS can act as a boundary object and encourage dialogue and collaboration between multiple social groups provides a new way of thinking about the intangible benefits that are associated with such technologies. These concepts have not previously been applied to understanding agricultural DSSs. Further research is therefore needed to empirically test this framework in terms of how it contributes to our understanding of the challenges and opportunities for developing DSSs for farm management. However, current research within the sociology of science and technology has demonstrated the socially-situated character of technological innovations. In doing so, the sociology of science and technology can provide a more in-depth understanding of the knowledge, needs and priorities of relevant stakeholders and the implications of different interaction styles between researchers and stakeholders. Therefore, the insights from the sociology of science and technology can reveal the way in which the social context of technology development influences the effectiveness and impact of these technologies, which could make a worthwhile contribution to enhancing the value and relevance of DSSs for farm management.


This study was supported by funds from the Australian sugar industry and Australian Government through Sugar Research and Development Corporation, which are gratefully acknowledged.


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