Emergence of an agriculture innovation system in Rwanda: Stakeholders and policies as points of departure

National innovation system and the THM

A consensus in the literature and among policy circles has more or less emerged about what is meant by innovation, a national innovation system and the Triple Helix and about their relevance for economic growth and national competitiveness and societal well-being. Both the national innovation system model (NIS) and the THM emphasize the importance of interaction among the key actors for knowledge production and sharing, aside from a strong capacity in R&D. The ability to innovate is often related to collective action, coordination, the exchange of knowledge among diverse actors, the incentives and resources available to form partnerships and develop businesses, and the conditions that make it possible for firms and entrepreneurs to use innovation (Chaminade et al., 2018; Etzkowitz and Leydesdorff, 2000; Fagerberg and Srholec, 2008). Technological skills, innovative solutions, functional institutions and stakeholders’ capacity (financial and knowledge) are imperative for the needed systemic approach (Juma, 2015; Lundvall, 2010). Such an approach echoes the importance of joint efforts in policies and policymaking processes as a means for ensuring collective interest in the system and inclusivity. This ultimately defines the functioning and success of the system as policies and aligned instruments play an important role in decision-making for collaborations among actors and investments, leading to high innovation propensity (Mytelka, 2016).

The NIS literature engages directly with the concept of system as a kind of loose metaphor to describe broad relationships among the relevant stakeholders whose activities affect innovation (cf. Lundvall, 2010). In a series of empirical studies, scholars had shown that systems of innovation can be achieved at national or regional level (e.g., while a national system may be more visible in the Netherlands, the regional level prevails in Germany—see Cooke and Leydesdorff, 2006; Isaksen and Asheim, 2002; Leydesdorff and Fritsch, 2006). Moreover, one can analyze whether innovation systems are technology-specific or sector-based (Carlsson, 2006; Malerba, 2007; Pavitt, 1984). The core idea of the regional innovation system (RIS) or the sectoral innovation system (SIS) does not differ from the overall concept of the NIS, except in the level of operationalization (Cooke, 2002; Lundvall, 2005).

The THM is employed to understand the specific roles of three key stakeholders, university, industry and government, and the synergy between them (Etzkowitz and Leydesdorff, 2000). The model encourages closer relations among actors, with each not only playing its own role but also taking over each other’s roles, as well as creating hybrid organizations at their interfaces. An example is the science park, in which research results and knowledge developed in a university are transferred to private firms or commercialized in incubators by entrepreneurs with the financial support of governmental agencies. In this model, the traditional university transforms into the “entrepreneurial university” which becomes the main organizational actor. Universities in the THM keep their autonomy but develop reciprocal relations with the other actors (Etzkowitz, 2013; Leydesdorff and Etzkowitz, 1996). ¹ Using the THM, analysis can be more specific than using NIS as it embraces interaction among all organizations and institutions at the national level.

Despite some limitations and critique, the THM is being used as a research tool in several studies focusing on both developed countries (e.g., Sweden, Denmark, Netherlands, Finland, Israel) and developing countries (e.g., China, Latin America, South Africa, Kenya). It has become popularized even as a policy framework or concept by numerous national organizations (e.g., Vinnova in Sweden, Magnet in Israel) and supranational organizations (e.g., the European Union) (for more information, see Benner and Sandstrom, 2000; Göktepe, 2003; Jongwanich et al., 2014; Liu and Huang, 2018; Nordfors et al., 2003; Sutz, 2000; Tuunainen, 2002).

The THM has evolved from a descriptive framework and an analytical tool into a normative model used in many countries and regions to foster technological innovation and economic growth. Many national agencies and ministries in developing countries have tried to learn from the success of developed countries or from countries that have managed to catch up quickly (such as South Korea or China). They have relied on external experts and scholars to obtain the recipe for innovation policy. These experts often simplify the process of knowledge creation and innovation into public–private partnerships in different spatial and other contexts as the key for innovation policy frameworks in many countries (Jongwanich et al., 2014; Leydesdorff and Zawdie, 2010). However, it is still hard for the policymakers or policy analysts to learn from these frameworks and to use the underlying ideas rigorously.

Policymaking approaches and policy goals for innovation

Up to this point, we have discussed the emergence of systemic approaches (NIS, THM) for innovation as a scholarly field. In this section, we delve into a complementary discussion on policymaking approaches and how the choice of policymaking approach can lead to policy actions that influence innovation performance. We give a brief overview of policymaking approaches and how they are related to innovation policy goals. We discuss the literature related to policy transfer, policy learning and evidence-based policymaking. From this discussion, we suggest a simplified analytical tool (Table 1) that we apply to policies and policy instruments to identify key policy drivers and how they orient policy actions that support innovation in the Rwandan agriculture sector.

Policy transfer (whether voluntary or coercive or a combination of both), in particular, between developed and developing countries underlines the partition of countries into “donor/lending and borrowing” countries. It is often labeled as “lesson-drawing” or “lesson-learning,” and countries that look at successful experiences frequently expect that the policy lessons will generate similar success for them (Howlett, 2009; Stone, 2017). This misapprehension, however, ignores the importance of local capacities, competencies, resources, infrastructures and, particularly, local culture and needs. Policy transfer is rarely a perfect process of transmission (Meseguer, 2005).

Policy learning, by contrast, may result in a more coherent adaptation of ideas, policies and practices (Stone, 2017). However, there is no clear-cut distinction between policy transfer and policy learning. Depending on how the transfer is done, there might be a soft transition between the transfer and the learning, but in other cases there may be a direct transfer of policy such as often happens between developing countries (the Global South) and their donor countries (the Global North). Learning occurs in specific institutional contexts: that is, in systemic environments shaped inter alia by regulation, law, political culture and the “rules of the game” of economic institutions. These environments of course include policy institutions and actions. Policy learning, like policy transfer (emulation), may therefore fail to capture the holistic nature of problems and solutions. This may result in a lack of support for innovation development, which is the primary motivation for learning from best practices and success stories.

Direct policy transfer, in particular learning and implementing successful policy instruments from one context to another, can be a too complicated and risky option, as there is no detailed blueprint for making innovation happen at a given time in a given place for a given result. The formulation of innovation policies and development plans based on success stories is problematic due to the complexity of the innovation process (Clark, 2016; Stone, 2017). Innovation policy must build on the key characteristics of how innovation comes about: it is uncertain, cumulative and collective (Lazonick and Mazzucato, 2013). It has to take into account national factors, historical path-dependencies, local conditions, economic inequities, demographic challenges and informal economic activity (Fagerberg and Srholec, 2008; Muchie et al., 2003). This requires evidence to inform policy on these issues. Thus, evidence-based policymaking becomes a more efficient and strong approach.

Evidence-based policymaking and stakeholders’ engagement are among the effective approaches that are used in places where efficient policies are observed. Policy efficiency at both macro and micro levels solicits a systemic approach with the ability to set priorities and proper resource allocation (Chaminade and Lundvall, 2019; Howlett, 2010; Mytelka and Smith, 2002). Evidence-based policymaking emphasizes that the government must produce policies that are forward-looking and shaped by evidence rather than a response to short-term pressures; that tackle causes not the symptoms. This approach requires a pool of accurate pieces of evidence that will ensure the potential for policy success. Those pieces of evidence are obtained from diverse sources, with research-based evidence preferred in most cases—although the active engagement of actors in the process is also considered a means of capturing real problems in their actual context.

Howlett (2009) considers problem examination as a starting point in policy design for organizing thinking and analytical efforts in a more productive way that can lead to effective and efficient policies and policy instruments. The acquisition of evidence and real problem analysis are key challenging stages in the policymaking process. They are expected to be systematic processes that consider different dimensions in order to generate realistic and implementable policy tools in the context of operationalization. Efficient frameworks and avenues for consultation and experience/ideas sharing play an important role in the process. Based on the complexity of the innovation process, it is hard to rely on a single approach to provide policies and policy instruments that capture all policy demands for conditions to innovate. A balance in the use of these approaches is needed, depending on learning capabilities and the capacity to generate and use evidence. Undeniably, due to the dynamics of globalization, it is often suggested that a mix of policy transfer, policy learning and evidence-based policymaking is “on the rise” as an empirical phenomenon (Davis, 2009; Howlett, 2010).

However, navigating all the dynamics involved in this mix is challenging, and criticisms have been emerging with regard to evidence-based policymaking, which is considered an efficient policymaking approach in many places. Criticisms concern how the evidence is generated, its accuracy and objectivity, and how it provides answers to policy problems. There are arguments about the influence of personal and policy agendas in evidence production as well as uncertainty in the research process, which is considered the main source of trustworthy evidence. There is also concern that policymakers can manipulate evidence to make sense of their own narrative or political agenda (Greenhalgh et al., 2020; Hulst and Yanow, 2016). Thus, it may be wise to adopt any policymaking approach with caution and to engage in critical reflections that will allow a balanced view of the policy problems and the policy options to answer those problems.

In this paper, we build on the fundamental principles of the above policymaking approaches to understand how Rwandan agriculture policies and policy instruments are designed and how they provide an operational framework for innovation. As noted above, lessons are drawn from success stories in developed countries (Global North practices) and international development goals and programs (the global agenda) or are imposed by donors (donors’ requirements). Moreover, some lessons are learned within regions (from regional plans) or within a country at different levels (national, sub-regional, sectoral plans). As for evidence, it can be acquired through research, the analysis of stakeholders’ problems and the analysis of local conditions (Howlett, 2010; Stone, 2017). These sources of lessons and evidence are in principle the main policy drivers that provide the foundation of policy orientations. However, the influence of power and politics cannot be neglected in the policymaking process. On this basis, we designed a guide (Table 1) to organize policymaking approaches and their associated policy drivers. ² The guide helps in the exploration of how policies and policy instruments in the Rwandan agriculture sector support innovation activities for facilitating the emerging AIS. It helps to connect the policymaking approach, policy drivers and policy initiatives, and how stakeholders build on them to orient innovation activities that increase the innovation propensity in the sector.

OPEN IN VIEWER

Table 1.

Policymaking approaches and associated policy drivers.

Policymaking approach	Policy drivers
Policy transfer	Global North practices, global agendas, donors’ requirements (practices)
Policy learning	Global North practices, global agendas, donors’ requirements (practices), regional plans, sub-regional plans, national plans, sectoral & cross-sectoral plans
Evidence-based policymaking	Research evidence, stakeholders’ needs/problems, local conditions

Stakeholders and their roles in innovation

Stakeholders in the Rwandan agriculture sector are grouped into farmers, government, non-governmental organizations, the private sector and knowledge institutions. The farmers’ group is mainly composed of farmers’ federation and cooperatives as well as individual farmers, small-scale farmers and large-scale farmers. The small-scale category consists of farmers with less than 0.7 ha of farming land, while large-scale farmers have 1 ha or more (Ayalew Ali and Deininger, 2014; Rwirahira, 2009). The NGO category comprises both local and international bodies (including UN agencies and regional/transboundary organizations directly or indirectly engaged in the agriculture sector). Line ministries, aligned agencies and local administration entities are the main components of the government category. The private sector category is composed of agro-dealers and agribusiness entrepreneurs, including industries. Research and training institutions (i.e. higher education) make up the knowledge institutions group.

These stakeholder groups have a wide range of roles and functions to perform for the development of innovation in Rwanda’s agriculture sector. The government plays the central role of providing an operational environment through planning and policymaking. Knowledge institutions conduct research and technology transfer to provide needed skills and technology to address problems in the sector. The research dissemination and technology transfer roles are accomplished through interaction—still meager due to weak collaborations and a lack of joint activities. The interaction involves knowledge institutions as technology providers, public agencies and NGOs as facilitators and farmers as technology end-users. Innovation propensity is expected to increase through interaction and mutual learning among the stakeholders, particularly between knowledge institutions and technology end-users (farmers and industries). To translate all these efforts into economic significance, roles related to financing and commercialization are fulfilled by the private sector.

As noted above, interaction among stakeholders is still low and this was highlighted by all the interviewees (Figure 2). However, they recognized emerging efforts to enhance interaction through consultative meetings and workshops, although these means are not seen as satisfactory in light of the high expectations of research, technology and innovation as the main drivers for the transformation of the agriculture sector. A cooperative representative commented:

We are not consulted for technologies that are brought to us and sometimes we find them not useful based on our needs. And the same happens for different training that we attend; they are many times like normal classes and yet we want hands-on practices to increase yield in our farms.

OPEN IN VIEWER

Figure 2.

Status of stakeholder interactions in the Rwandan AIS.

The level and quality of interactions among stakeholders, investment and the consideration of critical issues in a specific context are key for increasing innovation propensity (cf. Lundvall, 2007b). These are likely to be observed if there are: a joint planning framework that allows what is in the collective interest to happen; participatory research approaches; active learning processes; and a clear perspective on the complexity of the system by considering all dimensions (Ngaboyisonga et al., 2014). Well-accomplished stakeholder roles are essential to these factors, and the adoption of engaging avenues for interaction can help to overcome the lack of cooperation in emerging innovation systems such as the Rwandan AIS (Dosso et al., 2018; Jiggins et al., 2016).

Institutional set-ups to facilitate the innovation process

The above discussion provides an overview of the actors involved in building the Rwandan AIS. However, as pointed out by Lundvall (2010), to stabilize and mature innovation systems need strong institutions to support actors (organizations) in performing their roles and functions in the innovation process. In our study, we noted that institutional frameworks were being set up to ensure proper coordination and collaboration. Specialized institutional structures, policies, law and regulatory frameworks are major institutional patterns that are emerging. Specialized public agencies and their regulatory frameworks have been established to facilitate research, technology transfer, innovation, capacity building and agribusiness (including export). Among the established agencies are the Rwanda Agriculture and Animal Resources Development Board, which deals mainly with research and extension activities in the agriculture sector. The National Agriculture Export Board was established to promote agribusiness, particularly export. In addition to these specialized agencies in agriculture, the National Industrial Research Development Agency was put in place to promote industrial activities in different sectors of the economy, including agriculture. All these institutional structures are aligned with different policies and policy instruments to support innovation activities in the agriculture sector. The National Agriculture Policy, the National Industrial Policy and the Strategic Plan for Agriculture Transformation are among the key policies that have been put in place (Table 2).

Moreover, farmers’ organizations (cooperatives and federation) have been established to facilitate technology transfer among farming communities. Capacity building schemes have also been developed, from formal education to farmers’ training. There are specialized agriculture universities, colleges and technical colleges. For example, 6 of 22 certificate courses offered as Technical Vocation Education and Training are in agriculture (WDA, 2018) and there are Higher Learning Institutions which specialize in agriculture (HEC, 2019).

In addition to institutional structures, there are regulations and regulatory frameworks that favor the adoption of new technologies and facilitate dynamics in markets from the local to international level. The interviewed stakeholders from the private sector appreciated the established subsidy schemes for the importation of technical equipment as an important regulatory mechanism for supporting product diversification and enhancing their innovation propensity. The same applies to the local certification and standardization framework which helps local industries to ensure the quality of products, particularly for agro-processing and export.

Although there was an appreciation of these efforts, the stakeholders also highlighted issues that were hampering the current institutional structure in facilitating innovation in the agriculture sector. These included a lack of budget to support innovation activities, limited interaction among organizations, a lack of consistent strategies to build internal capacities and a lack of policy feedback channels. Institutional coordination, trust among actors and institutional stability were other areas considered in need of improvement. As highlighted by a researcher at an international NGO, there is a need to match institutional strategies and policies with resources allocation:

Both the National Agriculture policy and the 4th strategic plan for the transformation of agriculture place a lot of emphasis on research and innovation (actually it’s the first pillar in PSTA4). In other words, government policies are supportive. The main challenge is that a very limited budget is made available for research and extension.

Policymaking approaches and policy instruments to promote innovation

Rwanda has put in place policies and policy instruments (Table 2) to support innovation for agriculture sector development and national socio-economic development in general. They provide key priorities and implementation guidance to increase innovation propensity in the agriculture system, and have been formulated using different policymaking approaches. Policy transfer and policy learning appear to be the most popular approaches in the Rwandan agriculture policy cycle, whereas evidence-based policymaking is less in evidence. Policy transfer is observed mainly in development plans influenced by global and continental agendas. Policy learning and evidence-based policymaking are observed in contextual priority-setting based on national realities or specific agro-ecological zones. Consultation with stakeholders is used as the main tool in the learning process and the acquisition of evidence.

For policy transfer and learning, global and regional development agendas are the main policy drivers. The Sustainable Development Goals of the United Nations, Agenda 2063, the Comprehensive African Agriculture Development Plan (CAADP) and the East African Vision 2050 are the main frames of reference and influence national priorities (African Union Commission, 2014, 2015; EAC, 2015; NEPAD, 2003; United Nations, 2015). These agendas are seen as motivations to set national development strategies targeted at global integration and harmonization with regional initiatives. Rwanda’s Vision 2020 and Vision 2050 are the main development strategies that provide orientation to other national policies and strategies. From these guiding strategies, there is a vertical transfer of development priorities from central government to specific sectors, including agriculture. The transfer of ideas and priorities appears to be state-driven, as highlighted by one of the policymakers interviewed: “We follow the guidelines from the national leadership.” However, consultations with stakeholders at workshops and meetings provide the main sources of evidence and interaction that inform policies. These consultations, though, are perceived by some stakeholders (particularly farmers, researchers and processors) as unsatisfactory because they follow a predefined agenda and the audience may not be well informed about the policy problems that need to be addressed.

OPEN IN VIEWER

Table 2.

Policy instruments and policymaking approaches to support innovation.

Main policy/policy instrument	Main approach	Major policy drivers	Key policy initiative/orientation
National development vision & strategies: Vision 2020 (2002, revised 2012), Vision 2050 (2020) and NST1 (2017)	Policy transfer and policy learning	Global agendas, donors’ requirements, and Global North practices	Promotion of knowledge-based economy, predefined development priorities, vision for Rwandan agriculture
National policies: National Agriculture Policy (2018) and National Industrial Policy (2011)	Policy transfer and policy learning	Regional plans, sub-regional plans, national plans and sectoral & cross-sectoral plans	Promotion of agri-technologies, establishment of research programs
Sector strategies: Strategic Plan for Agriculture Transformation IV (2018)	Policy transfer, policy learning and evidence-based policymaking	National priorities and needs and local conditions	Promotion of agriculture technologies, specialized research and technology transfer programs, market diversification
Local strategies: Crop Intensification Program and Land Use Consolidation Act (2008)	Policy transfer, policy learning and evidence-based policymaking	Donors’ requirements, national priorities and local conditions	Promotion of agri-technologies (improved seeds, processing, etc.), community-based technology transfer tools

Note: This table is based on authors’ analysis of policy documents (MINAGRI, 2018a, 2018b; MINECOFIN, 2012, 2017, 2020; MINICOM, 2011; USAID, 2014) and interviews with policymakers.

Given the process described above, the level of learning is still low because policy is formulated top-down, with the government leading. Farmers in particular claim that policies do not take into account their problems, reflecting the dominance of policy transfer in policy learning and evidence-based policymaking, as lessons learned are not put into context so that policies do not capture the practical reality faced by stakeholders. To enhance learning and the contextualization of lessons learned from the global and regional agendas, there is a need to enhance the active engagement of stakeholders and consider bottom-up interactions with research-based evidence.

However, although the policymaking process has shortcomings, the policies and policy instruments that are in place do provide an orientation toward what needs to be done to establish favorable conditions for innovation in the Rwandan agriculture sector. Major policy goals and actions emphasize enhancing research and technology transfer efforts as a means of addressing the issues identified. An example is Pillar 2 of the National Agriculture Policy (2018), which sets out a direction for the agriculture research agenda and policy actions for “technological upgrading and skills development” in the Rwandan agriculture sector, and identifies priority areas for research and technology transfer efforts. Accordingly, research programs and infrastructures have been developed to address seed improvement, disease and pest control, and genetic resources improvement in both animals and crops as major challenges in the sector.

Infrastructures like gene banks, seed centers and germplasm centers have been established to facilitate research and agricultural technology advancement. As means for community outreach and technology dissemination, technical tools for helping farmers have been developed and platforms for interaction and capacity building have been initiated. The Farmer’s Field School (FFS) is among the policy instruments initiated to facilitate technology transfer between researchers and farmers (Gahakwa et al., 2014). Policies indicate an interest in innovation platforms, FFS Master Trainers and Farmer Promoters as facilitators of technology transfer and innovation development (MINAGRI, 2018a). However, these are still at the early stage of adoption and face challenges of coordination, ownership and investment (Adam et al., 2018).