Knowledge for Development

Innovation Systems in Agriculture and Rural Development

Author: Tesfaye Beshah, Post Doctoral Fellow, International Livestock Research Institute

Date: 30/06/2009

Introduction:

Much has been written on innovation systems (IS), especially in industrialized economies, and recently in developing countries contexts (Muchie et al., 2003; Hall 2005; Spielman et al., 2006; World Bank 2007). However, with few exceptions (e.g., Hall 2005; Hall et al., 2007; World Bank 2007), literature on IS does not adequately explain how system thinking enhances innovation or how IS can be initiated and facilitated. Another gap is the fact that “innovation” itself is promoted rather than its embeddedness within a system that in turn operates within certain institutional and policy contexts. Even though there is consensus on the importance of innovation for economic development, the systemic mechanism through which it can be enhanced is not given equal attention. These and other grey areas limit the promotion of the concept of IS, and in a worst case raises suspicion on its value addition for research and development.


 

2. Innovation system and how it functions

2.1 What is innovation system?

The World Bank (2007) defines innovation system as a network of organizations focused on bringing new processes and new forms of organization into social and economic use, together with the institutions and policies that affect their behaviour and performance. This is a general understanding of the contemporary concept of innovation that sees innovation not as mere technologies or products but as the process through which knowledge is generated, crafted from various sources and put into use. Thus, innovation may address new creations of social and economic significance, improvements in technical and managerial issues, institutional and policy aspects (Smits, 2002; Hall et al., 2004).

In spite of many encouraging developments in the promotion of the IS perspective in many parts of the world, there are still grey areas in its application. The major problem occurs when innovation is divorced from system concepts that can demonstrate its architecture for operationalization. This misunderstanding is not only dominant among the public organizations, but also among the private sector, non-governmental organizations, and international organizations. With few exceptions, innovation, innovation systems and systems concepts are not adequately treated in university curricula and training programmes of several intermediate training centers. Had there been adequate space for these organizations to contribute to addressing this gap, much could have been achieved in promoting the idea. System thinking is a good mirror to help us rethink about our science and development paradigms.

An innovation system is a designed social system facilitated by human agency. Following the system thinking of the 1980s, after the work of Checkland and his associates, a system is a mutually agreed definition or delineation of entities performing specific functions. What makes it a system is some degree of ‘organizedness’ that defines its structure (Checkland, 1993, Senge et al., 1994). This structure owes its essential characteristics and thereby its functions to the patterns of organization (Capra, 1997; 2002). These patterns of organization are created through a configuration of relationships among components of a system. In a nutshell, the overall design includes aspects such as the roles and expectations of different actors, incentives structure to change habits and practices, patterns of interaction in communication within the nodes, and decision-making processes.

In agriculture and rural development, the IS could, for example, consist of research, extension, farmers, NGOs, private sector, parastatals, and cooperatives, farmers, and community based organizations. Specific IS, for instance, in dairy or fodder, could be defined by patterns of organization relevant to dairy or fodder, as each configuration is unique. However, this does not mean that there is no room for sharing generic principles on how to establish a comparable system in another domain within its own context (Tesfaye, 2008). As the recent definition of the World Bank indicates, IS are embodied in a wider institutional and policy context to bring about behavioural changes and improve performance. These developments do not only refer to individual organizations within the network, but also to that of the system which is characterized by patterns of organization akin to actors involved. Taking this point even further, what a full-fledged IS depicts is the innovation capacity [1] at system level rather than isolated capacities of component organizations (Hall, 2005). Therefore, the challenge is to achieve a genuine paradigm shift in research and development through increased understanding and application of IS thinking for agriculture and rural development. This should be based on the architecture on which it is crafted i.e., the link between structure and pattern (see above), which are often implicit in IS literature.

A system is partly influenced by the external environment and partly driven internally. The resultant change in the transformation process is, however, determined by the internal dynamics of the system – the process - in which the structure and patterns are linked (Capra, 2002). Hence, application of IS thinking requires understanding of which actors to bring on board if the intention is the creation of IS for a particular purpose, and what process to adopt to facilitate the system. Note that the process is creating patterns of organization of that system. Some of these patterns are installed at the beginning when the system is defined, while others emerge in the learning process. This in turn requires inductive learning through a flexible approach in both time and other resources. The ultimate goal is of course, ensuring changes in the innovation capacity of the system (Hall et al., 2007) and self-reliance.

Patterns of organization in a given IS are maintained and develop through communication loops at different nodes ensuring the flow of information within and between the system and its environment. Moreover, these communication loops help to produce and reproduce the meaning of the system which leads to a set of rules and values that shape the behaviour of the system actors and patterns of interaction with the environment. This network-like communication tends to operate as self-generating mechanisms (Capra, 2002) that ensure continuity of that system. Hence, learning and thereby innovation takes place through this continuous communication loop in which actors within an IS are engaged. What needs to be emphasized is that IS are organically “built” networks of organizations. This organic link is ensured as long as there is continuous communication and learning. Poor or no communication leads to an erosion of the organic link within the network and maybe even a failure of the system, and innovation itself.

As the ultimate goal is a holistic system that involves all potential actors, it needs to operate as a learning system. This goal is facilitated by a soft system methodology that suits the action research framework (Salomon and Engel, 1997; Wilson and Morren, 1990; Checkland and Scholes, 1990).

2.2 Developments in system thinking, action research and IS

In the early 1980s research on system thinking led to two main perspectives: hard system and soft system. Owing to the bio-physical roots of early system thinking, the overall conceptualization later framed what is considered now as hard system that is posited to be systemic and constructs models to represent the world to optimize it. On the contrary, the soft system thinking creates the process of inquiry as a system, epistemologically. The aim of the soft system methodology is not to generate knowledge that enables us to predict about the nature of world reality (ontology), rather to enhance understanding of the reality through a purposeful action which involves negotiation, consensus and accommodation (Checkland and Scholes, 1990; Bawden, 1995; Roling, 1997; Salomon and Engel, 1997).

Soft system methodology [2], which gives due recognition to the hard system methodology is very appropriate for IS. It is compatible with the key features of IS such as complexity and involvement of networks of actors – organizations - which have different values, habits, and practices, which vary in their spatial positions and face differential access to resources, knowledge and power.

Turning to action research, its marked development also goes back to the first half of the twentieth century when Kurt Lewin (1946) published his work on action research (Melrose, 2001). Action research is an approach rather than a methodology as it integrates methodology from both qualitative and quantitative roots. Simply defined, action research is about undertaking action and studying that action as it takes place (Bargal, 2008). Use of action research helps to improve the scope of learning unlike that of action learning in the family of participatory approaches (Pretty, 1995) that does not give adequate room for research.

With few exceptions, (Checkland and Scholes, 1990; Checkland, 1993; Salomon and Engel, 1997), similarities of soft system methodology and action research framework are not explicit in most literature on the subjects. From the ontological and epistemological points of view, soft system methodology and action research are one and the same. Therefore, IS can be readily operationalized through action research that is widely known, using soft system methodology as a guide of the inquiry process (Tesfaye, 2008).

2.3 How to initiate IS in agriculture and rural development

Innovation requires systemic view as it involves various dimensions that are contributed by different actors. It also involves institutional and policy, technological artefacts, economic issues, and managerial aspects. However, the scope of a system, with respect to sub-systems and environment within which it operates varies from situation to situation. Even though various systems are related to one another, trying to bring all actors from the very beginning may not be possible nor desirable in a designed system like IS.

In view of this, IS facilitators need to understand the overall context of particular IS. For example, in fodder, a range of actors who can contribute to the fodder sector need to be invited for participation in the fodder IS. What is even very important is that fodder or for that matter any technical option is not a stand alone component, but embedded in a wider institutional and policy, socio-economic, technical and political environment in which several actors participate (Hall et al., 2007). This common-sense observation makes a strong case for IS perspective to organize and manage wider developmental issues. Innovation system facilitates the context within which technological changes could be enhanced. This requires involvement of relevant actors as deemed necessary rather than requiring involvement of all actors at once. This approach minimizes occurrence of second-generation problems such as no market for produce, no credit for processing products, restrictive policies and institutions, etc., that can be internalized through involvement of wider actors.

In the real-life situation all actors who are relevant for actors’ configuration in fodder IS may not see their roles and perhaps have the required incentive to join the initiative from the very beginning (Personal experience [3] in FIP-II project, India). However, unlike in the bio-physical system where missing one component impairs the functioning of that system, in the designed system such as IS, one may start from some key actors to build the IS as a network that grows until all potential actors are brought on board. However, when the initial actors have less power or resources, the process could be slow, but it will get there, as long as there is adequate facilitation.

The IS framework can also be used to organize actors around non-farm activities within rural development programmes, gender sensitive initiatives, and any other human activity for that matter. The basic issues are identification of relevant actors around a common goal and facilitation of the learning process through action research. As indicated above, actors who do not have much in common can hardly communicate and thereby exchange information and resources for innovation. Hence, creating the conditions for networking when there is potential contribution is inevitable (cf. action research).

Even though the journey of initiating and facilitating IS is far from easy and there is no blue-print, one may use different concepts, tools and techniques to grapple with the complex situation (Hall et al, 2007) [4]. Box 1 provides some initial outlines.

Box 1: Some useful tips to initiate and facilitate IS

1. Getting started

  • Understanding of micro and macro environments of intended area of operation, region and country. The focus is on policy and institutional landscape, socio-economic, political and bio-physical environments. This can be achieved partly through secondary data.
  • Density and organizational history of key organizations (commonly known as stakeholders analysis)
  • Organizing awareness creation workshops to engage with potential partners

2. Identification of champion organizations to initiate the network (who are interested, and would align themselves with the purpose of the initiatives)

3. Identification of starter problems or entry point. This may change in the course of interactions among actors and learning, but at least one common issue or problem is required as a learning tool at the beginning.

4. Socio-economic baseline: Information from analysis of these data is to be used as a learning tool to monitor impacts. Changes in the action research process will be tracked through monitoring and learning mechanisms to be developed according to the nature of patterns of organization of a given system. This can also be used to draw a plausible casual link in the course of the process.

5. In depth diagnosis of the identified innovation system

  • Actors (organizations) and their domain of operations
  • Habits and practices of organizations
  • Patterns of interaction among organizations
  • Institutional and policy environments that influences functions of the actors.

6. Planning action research around the starter issue or problem and implementation.

7. Design and implement monitoring and learning system

8. Periodic reflection on learning outcomes based on monitoring and learning system. Monitoring focuses on habits and practices of the network, learning at individual and organizational levels, patterns of interactions within the network and with the environment in which it is embedded.

9. Redefine actors and actions as required, including interactions with policy-makers through various means.

10. Consolidate lessons and apply the experiences in another domain or scale out within the same domain.

Note that the entire facilitation is guided by the IS concept which is well adapted to the specific domain of operation that needs to be enriched through learning from actions; according to the principles of action research and soft systems methodology. It should be noted that some of the above activities are overlapping and also carried out in a reiterative manner rather than as stand-alone one-off linear activities, as rapport has to be developed with stakeholders on some issues.

3. IS and pro-poor initiatives

Pro-poor initiatives are key policy directions among international and public organizations. However, options to make them more responsive are very limited. Often the poor are marginalized and left behind in innovation processes due to lack of conducive enabling environments. What has the IS perspective to offer to pro-poor initiatives?

Creation of an enabling environment for rural poor, for instance, requires mobilization of knowledge and other resources through networks of organizations to improve their option in farm and wider rural economies. This task is less efficiently carried out if it continues to be deployed by individual organizations or even through narrow partnership as shown by poor performance of these initiatives during the last sixty years. This is an area to which international donors should pay attention and consider a new approach such as IS in poverty reduction.

Efforts to bring relevant actors together through IS design would obviously face challenges to accommodate the values of affluent members of the community who have more capacity to take advantage of early opportunities, and that of poor men and women farmers who require more empowerment to negotiate for their interests. This makes the power issue in the management of social network very explicit, which is a challenge for the facilitators of IS (Kristjanson et al., 2009).

As innovation results from interactions of various actors and factors, IS are useful mechanisms to address poverty. There is a high chance of convergence of multiple drivers of innovation (e.g., access to information, markets, finance, collective actions, and institutional changes) through networks of actors initiated in the IS. If pro-poor initiatives are facilitated through IS, interactions of these drivers would positively contribute to poverty reduction.

IS should have capacity to generate information, manage conflicts, build trust, create access to technical inputs and other resources with conscious attention to the poor, all of which are important aspects of poverty reduction. Without such explicit endeavours, the cause of the poor people would always end up with lip-service rather than appropriate responses.

The ultimate service of IS to pro-poor initiatives is strengthening innovation capacity of the poor enhancing their adaptive strategy for sustainable livelihoods (World Bank, 2007). Given the growing complexity of production processes, coupled with declining availability of physical resources such as land and scarcity of water, increasing demand for knowledge is inevitable in order to sustain livelihoods of people. Hence, promotion of IS has strategic purposes in a broad-based development.

4. Some precautions in use of IS perspectives

The innovation system approach is not a panacea. The IS perspective is useful when an issue or problem involves multiple actors who have complementary contributions and mutual benefits from the outcomes. As the concept is still evolving and has not attracted adequate attention from leading organizations and actors, misconceptions exist at various levels. In this regard, it is necessary to address two issues based on the complex nature of IS.

Does IS provide quick solutions [5]? IS perspective can give rapid feedback, but not necessarily a quick solution. These phenomena are explained by the very fact that IS involve multiple actors and connect them through communication networks that facilitate innovation. As most or all desired actors would be within the network, IS can provide rapid feedback. However, inasmuch as IS deal with multiple actors, reaching win-win solutions, and even defining the problem, solutions are likely to take a longer time. However, solutions of IS should not only be measured with the final product or material to be generated. The improved capacity of actors and the entire system that is achieved through the process of learning and use of this experience for the future should not be overlooked. In view of this, order of the day is material-focused development and capacity rather than multi-dimensional capacity, with a knowledge focus. A shift of paradigm is also required in this regard among international donors and all research and development communities.

With respect to the role of science and scientists in IS, there is a world-wide network of agricultural and allied sciences that is financed by the international public fund, not to mention the science and technology activities that are run by nation states using tax payers’ money; grants and loans through bilateral and multilateral arrangements. If IS thinking has any value adding, it is to the extent that it creates a legitimate context for increased demand for cutting-edge science and also in generating such knowledge. Increased innovation capacity of the system means that various actors in the system would shift towards knowledge intensive options of production and processing of food, fiber, and services which opens more space for science and scientists. Hence, IS are not only the grounds for social scientists and practitioners who adopted systems thinking. It is rather how to bring those, actors, ranging from scientists to policy makers to end users under one platform for learning. The essence is, therefore, to examine the IS in detail and create a wider context within which there would be more demand for science based knowledge and its efficient utilization.

5. Conclusions

The key motivation of this paper is the gap between the importance accorded to innovation for economic development and the practice of IS on the ground. In view of this, the paper, using system theory, provided the architecture of IS by specifying how the structure is formed and functions. The basic engine in the function of a system is its patterns of organization. Such patterns start from some basic operational elements and procedures that define its characteristics. Over time, these may change as its functions change through learning. Patterns of organization include roles of different actors, incentives, patterns of interactions and decision-making processes, making the strength of the system being determined by its patterns of organization. Communication loops among the nodes of the system maintain and stimulate the learning of the system.

Hence, it is through the communication process that the meaning of the system is produced and reproduced in the network to enhance innovation within the system. Due to similarities of soft system methodology and action research, IS can be operationalized through action research using soft system methodology as a guide. Hence, IS can be organized for any human agency. In this connection some hints on how to initiate and facilitate IS were provided using insights from field experiences.

As IS can handle complex phenomena, it is very suitable to facilitate pro-poor initiatives. Hence, international organizations and donors need to give more attention to IS in their endeavours to promote a broad-based development.

Finally it was noted that IS is not a panacea. Even though it may not necessarily provide a quick solution, it can, however, provide rapid feedback and non-material capacities. In addition, IS is inclusive and its greatest value is inasmuch as it creates more demand for knowledge intensive initiatives where science and scientists will have immense contribution by learning with other actors.

Footnotes

  1. According to Hall et al. (2007) innovation capacity refers to skills and knowledge held by individuals and organizations, institutions, patterns of interaction and policies developed, which enhances the knowledge processes – ranging from its generation to utilization.
  2. Literature on IS does not make distinction between hard and soft systems which to me seems to cause miscommunication between technical scientists and those who promote IS. The former ones tend to fall back to FSR’s (farming systems research) view of system thinking that is essentially a hard system.
  3. Since January 2008, I am involved in Fodder Innovation Project in India as a Post Doctoral Fellow, ILRI.
  4. Empirical results from application of a conceptual framework in IS in Fodder Innovation Project in India and Nigeria are expected towards end of this year. For progresses so far, see www.fodderinnovation.org
  5. Some practitioners even try to equate it with the pace of transfer of technology.

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